Alteration of the abundance of Parvimonas micra in the gut along the adenoma-carcinoma sequence

Parvimonas micra can translocate from the subgingival sulcus of the human oral cavity to colorectal adenocarcinoma

Oral and intestinal samples from a cohort of 93 colorectal cancer (CRC) patients and 30 healthy controls (non-CRC) were collected for microbiome analysis. Saliva (28 non-CRC and 94 CRC), feces (30 non-CRC and 97 CRC), subgingival fluid (20 CRC), and tumor tissue samples (20 CRC) were used for 16S metabarcoding and/or RNA sequencing (RNAseq) approaches. A differential analysis of the abundance, performed with the ANCOM-BC package, adjusting the P-values by the Holm-Bonferroni method, revealed that Parvimonas was significantly over-represented in feces from CRC patients (P-value < 0.001) compared to healthy controls. A total of 11 Parvimonas micra isolates were obtained from the oral cavity and adenocarcinoma of CRC patients. Genome analysis identified a pair of isolates from the same patient that shared 99.2% identity, demonstrating that P. micra can translocate from the subgingival cavity to the gut. The data suggest that P. micra could migrate in a synergistic consortium with other periodontal bacteria. Metatranscriptomics confirmed that oral bacteria were more active in tumor than in non-neoplastic tissues. We suggest that P. micra could be considered as a CRC biomarker detected in non-invasive samples such as feces.

The multispecies microbial cluster of Fusobacterium, Parvimonas, Bacteroides and Faecalibacterium as a precision biomarker for colorectal cancer diagnosis

The incidence of colorectal cancer (CRC) has increased worldwide, and early diagnosis is crucial to reduce mortality rates. Therefore, new noninvasive biomarkers for CRC are required. Recent studies have revealed an imbalance in the oral and gut microbiomes of patients with CRC, as well as impaired gut vascular barrier function. In the present study, the microbiomes of saliva, crevicular fluid, feces, and non-neoplastic and tumor intestinal tissue samples of 93 CRC patients and 30 healthy individuals without digestive disorders (non-CRC) were analyzed by 16S rRNA metabarcoding procedures. The data revealed that Parvimonas, Fusobacterium, and Bacteroides fragilis were significantly over-represented in stool samples of CRC patients, whereas Faecalibacterium and Blautia were significantly over-abundant in the non-CRC group. Moreover, the tumor samples were enriched in well-known periodontal anaerobes, including Fusobacterium, Parvimonas, Peptostreptococcus, Porphyromonas, and Prevotella. Co-occurrence patterns of these oral microorganisms were observed in the subgingival pocket and in the tumor tissues of CRC patients, where they also correlated with other gut microbes, such as Hungatella. This study provides new evidence that oral pathobionts, normally located in subgingival pockets, can migrate to the colon and probably aggregate with aerobic bacteria, forming synergistic consortia. Furthermore, we suggest that the group composed of Fusobacterium, Parvimonas, Bacteroides, and Faecalibacterium could be used to design an excellent noninvasive fecal test for the early diagnosis of CRC. The combination of these four genera would significantly improve the reliability of a discriminatory test with respect to others that use a single species as a unique CRC biomarker.

An independent evaluation in a CRC patient cohort of microbiome 16S rRNA sequence analysis methods: OTU clustering, DADA2, and Deblur

16S rRNA is the universal gene of microbes, and it is often used as a target gene to obtain profiles of microbial communities via next-generation sequencing (NGS) technology. Traditionally, sequences are clustered into operational taxonomic units (OTUs) at a 97% threshold based on the taxonomic standard using 16S rRNA, and methods for the reduction of sequencing errors are bypassed, which may lead to false classification units. Several denoising algorithms have been published to solve this problem, such as DADA2 and Deblur, which can correct sequencing errors at single-nucleotide resolution by generating amplicon sequence variants (ASVs). As high-resolution ASVs are becoming more popular than OTUs and only one analysis method is usually selected in a particular study, there is a need for a thorough comparison of OTU clustering and denoising pipelines. In this study, three of the most widely used 16S rRNA methods (two denoising algorithms, DADA2 and Deblur, along with de novo OTU clustering) were thoroughly compared using 16S rRNA amplification sequencing data generated from 358 clinical stool samples from the Colorectal Cancer (CRC) Screening Cohort. Our findings indicated that all approaches led to similar taxonomic profiles (with P > 0.05 in PERMNAOVA and P <0.001 in the Mantel test), although the number of ASVs/OTUs and the alpha-diversity indices varied considerably. Despite considerable differences in disease-related markers identified, disease-related analysis showed that all methods could result in similar conclusions. Fusobacterium, Streptococcus, Peptostreptococcus, Parvimonas, Gemella, and Haemophilus were identified by all three methods as enriched in the CRC group, while Roseburia, Faecalibacterium, Butyricicoccus, and Blautia were identified by all three methods as enriched in the healthy group. In addition, disease-diagnostic models generated using machine learning algorithms based on the data from these different methods all achieved good diagnostic efficiency (AUC: 0.87-0.89), with the model based on DADA2 producing the highest AUC (0.8944 and 0.8907 in the training set and test set, respectively). However, there was no significant difference in performance between the models (P >0.05). In conclusion, this study demonstrates that DADA2, Deblur, and de novo OTU clustering display similar power levels in taxa assignment and can produce similar conclusions in the case of the CRC cohort.

Bacterial pathogens in pediatric appendicitis: a comprehensive retrospective study

Background

Appendicitis is a frequent condition, with peak incidences in the second decade of life. Its pathogenesis is under debate, but bacterial infections are crucial, and antibiotic treatment remains essential. Rare bacteria are accused of causing complications, and various calculated antibiotics are propagated, yet there is no comprehensive microbiological analysis of pediatric appendicitis. Here we review different pre-analytic pathways, identify rare and common bacterial pathogens and their antibiotic resistances, correlate clinical courses, and evaluate standard calculated antibiotics in a large pediatric cohort.

Method

We reviewed 579 patient records and microbiological results of intraoperative swabs in standard Amies agar media or fluid samples after appendectomies for appendicitis between May 2011 and April 2019. Bacteria were cultured and identified via VITEK 2 or MALDI-TOF MS. Minimal inhibitory concentrations were reevaluated according to EUCAST 2022. Results were correlated to clinical courses.

Results

Of 579 analyzed patients, in 372 patients we got 1330 bacterial growths with resistograms. 1259 times, bacteria could be identified to species level. 102 different bacteria could be cultivated. 49% of catarrhal and 52% of phlegmonous appendices resulted in bacterial growth. In gangrenous appendicitis, only 38% remained sterile, while this number reduced to 4% after perforation. Many fluid samples remained sterile even when unsterile swabs had been taken simultaneously. 40 common enteral genera were responsible for 76.5% of bacterial identifications in 96.8% of patients. However, 69 rare bacteria were found in 187 patients without specifically elevated risk for complications.

Conclusion

Amies agar gel swabs performed superior to fluid samples and should be a standard in appendectomies. Even catarrhal appendices were only sterile in 51%, which is interesting in view of a possible viral cause. According to our resistograms, the best in vitro antibiotic was imipenem with 88.4% susceptible strains, followed by piperacillin-tazobactam, cefuroxime with metronidazole, and ampicillin-sulbactam to which only 21.6% of bacteria were susceptible. Bacterial growths and higher resistances correlate to an elevated risk of complications. Rare bacteria are found in many patients, but there is no specific consequence regarding antibiotic susceptibility, clinical course, or complications. Prospective, comprehensive studies are needed to further elicit pediatric appendicitis microbiology and antibiotic treatment.

Genetic heterogeneity of colorectal cancer and the microbiome

In 2020, the International Agency for Research on Cancer and the World Health Organization's GLOBOCAN database ranked colorectal cancer (CRC) as the third most common cancer in the world. Most cases of CRC (> 95%) are sporadic and develop from colorectal polyps that can progress to intramucosal carcinoma and CRC. Increasing evidence is accumulating that the gut microbiota can play a key role in the initiation and progression of CRC, as well as in the treatment of CRC, acting as an important metabolic and immunological regulator. Factors that may determine the microbiota role in CRC carcinogenesis include inflammation, changes in intestinal stem cell function, impact of bacterial metabolites on gut mucosa, accumulation of genetic mutations and other factors. In this review, I discuss the major mechanisms of the development of sporadic CRC, provide detailed characteristics of the bacteria that are most often associated with CRC, and analyze the role of the microbiome and microbial metabolites in inflammation initiation, activation of proliferative activity in intestinal epithelial and stem cells, and the development of genetic and epigenetic changes in CRC. I consider long-term studies in this direction to be very important, as they open up new opportunities for the treatment and prevention of CRC.

Leveraging Scheme for Cross-Study Microbiome Machine Learning Prediction and Feature Evaluations

The microbiota has proved to be one of the critical factors for many diseases, and researchers have been using microbiome data for disease prediction. However, models trained on one independent microbiome study may not be easily applicable to other independent studies due to the high level of variability in microbiome data. In this study, we developed a method for improving the generalizability and interpretability of machine learning models for predicting three different diseases (colorectal cancer, Crohn's disease, and immunotherapy response) using nine independent microbiome datasets. Our method involves combining a smaller dataset with a larger dataset, and we found that using at least 25% of the target samples in the source data resulted in improved model performance. We determined random forest as our top model and employed feature selection to identify common and important taxa for disease prediction across the different studies. Our results suggest that this leveraging scheme is a promising approach for improving the accuracy and interpretability of machine learning models for predicting diseases based on microbiome data.

Parvimonas micra activates the Ras/ERK/c-Fos pathway by upregulating miR-218-5p to promote colorectal cancer progression

BACKGROUND

Colorectal cancer (CRC) is the third most common cancer in the world, and a strong relationship exists between CRC and gut microbiota, which affects the occurrence, development, and metastasis of cancer. Bioinformatics-based analyses revealed that the abundance of Parvimonas micra (P. micra) in the feces of patients with cancer is significantly higher than that in healthy people. Therefore, an important relationship may exist between P. micra and CRC.

METHODS

We first confirmed that P. micra can promote the proliferation of cell lines through cell experiments and mouse models. Then we selected the signaling pathways and content of exosomes to promote the development of CRC by transcriptomics and microRNA sequencing. Finally, we confirmed that P. micra promoted CRC development through miR-218-5p/Ras/ERK/c-Fos pathway through the in vivo and in vitro experiments.

RESULTS

First, it was confirmed by in vitro and in vivo experiments that P. micra can promote the development of CRC. Transcriptome analysis after the coincubation of bacteria and cells revealed that P. micra promoted cell proliferation by activating the Ras/ERK/c-Fos pathway. Furthermore, microRNA sequencing analysis of the cells and exosomes showed that miR-218-5p and protein tyrosine phosphatase receptor R (PTPRR) were the key factors involved in activating the Ras/ERK/c-Fos pathway, and the miR-218-5p inhibitor was used to confirm the role of microRNA in xenograft mice.

CONCLUSION

This experiment confirmed that P. micra promoted the development of CRC by upregulating miR-218-5p expression in cells and exosomes, inhibiting PTPRR expression, and ultimately activating the Ras/ERK/c-Fos signaling pathway.

Tumour Colonisation of Parvimonas micra Is Associated with Decreased Survival in Colorectal Cancer Patients

Increasing evidence suggests that the gut microbiota may impact colorectal cancer (CRC) development and progression. In this study, the tumour colonisation of two CRC-associated bacteria, Parvimonas micra and Fusobacterium nucleatum, was studied in relation to patient survival in a cohort of 257 CRC patients. Colonisation of P. micra and F. nucleatum was analysed in fresh frozen tumour tissue (n = 112) and in faeces (n = 250) by qPCR. When analysing tumour tissues, both P. micra and F. nucleatum were found to be associated with decreased five-year cancer-specific survival, an association that remained significant in multivariable analysis for P. micra. Furthermore, we found significant associations of high levels of P. micra and F. nucleatum with tumour molecular characteristics, i.e., tumours mutated in BRAF^V600E, and tumours of the MSI subtype. The analysis of faecal samples showed weaker associations with prognosis and tumour molecular characteristics. In conclusion, our findings support a novel association of tumour colonisation of P. micra with decreased patient survival. A better understanding of the role of the gut microbiota in CRC might contribute to the advancement of prognostic tools and new targets for therapy.

Multi-Omics Approaches in Colorectal Cancer Screening and Diagnosis, Recent Updates and Future Perspectives

Colorectal cancer (CRC) is common Cancer as well as the third leading cause of mortality around the world; its exact molecular mechanism remains elusive. Although CRC risk is significantly correlated with genetic factors, the pathophysiology of CRC is also influenced by external and internal exposures and their interactions with genetic factors. The field of CRC research has recently benefited from significant advances through Omics technologies for screening biomarkers, including genes, transcripts, proteins, metabolites, microbiome, and lipidome unbiasedly. A promising application of omics technologies could enable new biomarkers to be found for the screening and diagnosis of CRC. Single-omics technologies cannot fully understand the molecular mechanisms of CRC. Therefore, this review article aims to summarize the multi-omics studies of Colorectal cancer, including genomics, transcriptomics, proteomics, microbiomics, metabolomics, and lipidomics that may shed new light on the discovery of novel biomarkers. It can contribute to identifying and validating new CRC biomarkers and better understanding colorectal carcinogenesis. Discovering biomarkers through multi-omics technologies could be difficult but valuable for disease genotyping and phenotyping. That can provide a better knowledge of CRC prognosis, diagnosis, and treatments.

Faecal microbiome-based machine learning for multi-class disease diagnosis

Systemic characterisation of the human faecal microbiome provides the opportunity to develop non-invasive approaches in the diagnosis of a major human disease. However, shared microbial signatures across different diseases make accurate diagnosis challenging in single-disease models. Herein, we present a machine-learning multi-class model using faecal metagenomic dataset of 2,320 individuals with nine well-characterised phenotypes, including colorectal cancer, colorectal adenomas, Crohn's disease, ulcerative colitis, irritable bowel syndrome, obesity, cardiovascular disease, post-acute COVID-19 syndrome and healthy individuals. Our processed data covers 325 microbial species derived from 14.3 terabytes of sequence. The trained model achieves an area under the receiver operating characteristic curve (AUROC) of 0.90 to 0.99 (Interquartile range, IQR, 0.91-0.94) in predicting different diseases in the independent test set, with a sensitivity of 0.81 to 0.95 (IQR, 0.87-0.93) at a specificity of 0.76 to 0.98 (IQR 0.83-0.95). Metagenomic analysis from public datasets of 1,597 samples across different populations observes comparable predictions with AUROC of 0.69 to 0.91 (IQR 0.79-0.87). Correlation of the top 50 microbial species with disease phenotypes identifies 363 significant associations (FDR < 0.05). This microbiome-based multi-disease model has potential clinical application in disease diagnostics and treatment response monitoring and warrants further exploration.

Parvimonas micra is associated with tumour immune profiles in molecular subtypes of colorectal cancer

The importance of the tumour microbiome in different aspects of colorectal cancer (CRC) has been increasingly recognised, but many questions remain. The aim of this study was to explore the effect of specific CRC associated microbes on the tumour immune response, which has a considerable prognostic value in CRC. We applied specific qPCR to detect Parvimonas micra and Fusobacterium nucleatum in tumour tissues from an immunologically well-characterised cohort of 69 CRC patients. This cohort included detailed analyses of immune profiles based on flow cytometry and transcriptomics in tumour tissue and blood, along with comprehensive analyses of molecular subtypes. P. micra and F. nucleatum were detected in 24% and 64% of tumour tissues, respectively. We found a significant association of P. micra with high-grade tumours and tumours of CMS1 subtype. F. nucleatum was significantly associated with right-sided tumours, microsatellite instability, and CMS1 tumours. The immunological analyses revealed significant associations of P. micra with activated CD69⁺ T lymphocytes and increased antigen-presenting HLA-DR⁺ B lymphocytes. P. micra was also positively associated with M1 and M2 macrophage traits. The impact of P. micra tumour colonisation on the immune response was further assessed using transcriptomics in validation of our findings. No associations were found between F. nucleatum and immune profiles in this study. Our findings support novel associations between P. micra and the immune response in CRC. A better understanding of these interactions might help to identify important predictive and prognostic tools as well as new targets for therapy.

Parvimonas micra promotes colorectal tumorigenesis and is associated with prognosis of colorectal cancer patients

Large-scale fecal shotgun metagenomic sequencing revealed the high abundance of Parvimonas micra in colorectal cancer (CRC) patients. We investigated the role and clinical significance of P. micra in colorectal tumorigenesis. The abundance of P. micra was examined in 309 fecal samples and 165 colon biopsy tissues of CRC patients and healthy subjects. P. micra was significantly enriched in fecal samples from 128 CRC patients compared to 181 healthy subjects (P < 0.0001); and in colon tissue biopsies from 52 CRC patients compared to 61 healthy subjects (P < 0.0001). Multivariate analysis showed that P. micra is an independent risk factor of poor survival in CRC patients (Hazard Ratio: 1.93). P. micra strain was isolated from feces of a CRC patient. Apc^min/+ mice gavaged with P. micra showed significantly higher tumor burden and tumor load (both P < 0.01). Consistently, gavage of P. micra significantly promoted colonocyte proliferation in conventional mice, which was further confirmed by germ-free mice. P. micra colonization up-regulated genes involved in cell proliferation, stemness, angiogenesis and invasiveness/metastasis; and enhanced Th17 cells infiltration and expression of Th17 cells-secreted cytokines (Il-17, Il-22, and Il-23) in the colon of Apc^min/+, conventional and germ-free mice. P. micra-conditioned medium significantly promoted the differentiation of CD4⁺ T cells to Th17 cells (IL-17⁺CD4⁺ phenotype) and enhanced the oncogenic Wnt signaling pathway. In conclusion, P. micra promoted colorectal tumorigenesis in mice by inducing colonocyte proliferation and altering Th17 immune response. P. micra may act as a prognostic biomarker for poor survival of CRC patients.

Detection of Streptococcus gallolyticus and Four Other CRC-Associated Bacteria in Patient Stools Reveals a Potential “Driver” Role for Enterotoxigenic Bacteroides fragilis

Purpose

Streptococcus gallolyticus subspecies gallolyticus (SGG) is an opportunistic pathogen causing invasive infections in the elderly often associated with colon neoplasia. The prevalence of SGG in the stools of patients with normal colonoscopy (control) was compared with patients with colorectal adenomas (CRA) or with carcinomas (CRC) from stages I to IV. The presence of the pks island encoding colibactin as well as other CRC-associated bacteria such as toxicogenic Bacteroides fragilis, Fusobacterium nucleatum, and Parvimonas micra was also investigated.

Patients and Methods

Fecal samples collected in France between 2011 and 2016 from patients with normal colonoscopy (n = 25), adenoma (n = 23), or colorectal cancer at different stages (n = 81) were tested by PCR for the presence of SGG, B. fragilis, F. nucleatum, P. micra, and the pks island. Relative quantification of SGG, F. nucleatum, and P. micra in stools was performed by qPCR.

Results

SGG prevalence was significantly increased in the CRC group. Our results also revealed i) a strong and significant increase of toxinogenic B. fragilis in patients with early-stage adenoma and of pks island at late-stage CRC and ii) increased levels of F. nucleatum and P. micra in the stools of CRC patients. Furthermore, the simultaneous detection of these five bacterial markers was only found in CRC patients.

Conclusions

Our results indicate that the prevalence or relative levels of CRC-associated bacteria vary during CRC development. Among them, B. fragilis (bft+) was singled out as the sole pathobiont detected at the early adenoma stage.

The airway microbiota of non-small cell lung cancer patients and its relationship to tumor stage and EGFR gene mutation

BACKGROUND

Accumulating studies have suggested the airway microbiota in lung cancer patients is significantly different from that of healthy controls. However, little is known about the relationship between airway microbiota and important clinical parameters of lung cancer. In this study, we aimed to explore the association between sputum microbiota and lung cancer stage, lymph node metastasis, intrathoracic metastasis, and epidermal growth factor receptor (EGFR) gene mutation.

METHODS

The microbiota of sputum samples from 85 newly-diagnosed NSCLC patients were sequenced via 16S rRNA sequencing of the V3-V4 region. Sequencing reads were filtered using QIIME2 and clustered against UPARSE.

RESULTS

Alpha- and β-diversity was significantly different between patients in stages I to II (early stage, ES) and patients in stages III to IV (advanced stage, AS). Linear discriminant analysis Effect Size (LEfSe) identified that genera Granulicatella and Actinobacillus were significantly enriched in ES, and the genus Actinomyces was significantly enriched in AS. PICRUSt2 identified that the NAD salvage pathway was significantly enriched in AS, which was positively associated with Granulicatella. Patients with intrathoracic metastasis were associated with increased genus Peptostreptococcus and incomplete reductive TCA cycle, which was associated with increased Peptostreptococcus. Genera Parvimonas, Pseudomona and L-valine biosynthesis were positively associated with lymph node metastasis. L-valine biosynthesis was related with increased Pseudomona. Finally, the genus Parvimonas was significantly enriched in adenocarcinoma patients with EGFR mutation.

CONCLUSION

The taxonomy structure differed between different lung cancer stages. The tumor stage, intrathoracic metastasis, lymph node metastasis, and EGFR mutation were associated with alteration of specific airway genera and metabolic function of sputum microbiota.

GMrepo v2: a curated human gut microbiome database with special focus on disease markers and cross-dataset comparison

GMrepo (data repository for Gut Microbiota) is a database of curated and consistently annotated human gut metagenomes. Its main purposes are to increase the reusability and accessibility of human gut metagenomic data, and enable cross-project and phenotype comparisons. To achieve these goals, we performed manual curation on the meta-data and organized the datasets in a phenotype-centric manner. GMrepo v2 contains 353 projects and 71,642 runs/samples, which are significantly increased from the previous version. Among these runs/samples, 45,111 and 26,531 were obtained by 16S rRNA amplicon and whole-genome metagenomics sequencing, respectively. We also increased the number of phenotypes from 92 to 133. In addition, we introduced disease-marker identification and cross-project/phenotype comparison. We first identified disease markers between two phenotypes (e.g. health versus diseases) on a per-project basis for selected projects. We then compared the identified markers for each phenotype pair across datasets to facilitate the identification of consistent microbial markers across datasets. Finally, we provided a marker-centric view to allow users to check if a marker has different trends in different diseases. So far, GMrepo includes 592 marker taxa (350 species and 242 genera) for 47 phenotype pairs, identified from 83 selected projects. GMrepo v2 is freely available at: https://gmrepo.humangut.info.

Recent advancements in the exploitation of the gut microbiome in the diagnosis and treatment of colorectal cancer

Over the last few decades it has been established that the complex interaction between the host and the multitude of organisms that compose the intestinal microbiota plays an important role in human metabolic health and disease. Whilst there is no defined consensus on the composition of a healthy microbiome due to confounding factors such as ethnicity, geographical locations, age and sex, there are undoubtably populations of microbes that are consistently dysregulated in gut diseases including colorectal cancer (CRC). In this review, we discuss the most recent advances in the application of the gut microbiota, not just bacteria, and derived microbial compounds in the diagnosis of CRC and the potential to exploit microbes as novel agents in the management and treatment of CRC. We highlight examples of the microbiota, and their derivatives, that have the potential to become standalone diagnostic tools or be used in combination with current screening techniques to improve sensitivity and specificity for earlier CRC diagnoses and provide a perspective on their potential as biotherapeutics with translatability to clinical trials.