Metabolomics and 16S rRNA sequencing of human colorectal cancers and adjacent mucosa

Alteration of ascending colon mucosal microbiota in patients after cholecystectomy

BACKGROUND

Cholecystectomy is a successful treatment option for gallstones, although the incidence of colorectal cancer (CRC) has notably increased in post-cholecystectomy (PC) patients. However, it remains uncertain whether the altered mucosal microbiota in the ascending colon is related.

AIM

To investigate the potential correlation between gut microbiota and the surgical procedure of cholecystectomy.

METHODS

In total, 30 PC patients and 28 healthy controls underwent colonoscopies to collect mucosal biopsy samples. PC patients were divided based on their clinical features. Then, 16S-rRNA gene sequencing was used to analyze the amplicon, alpha diversity, beta diversity, and composition of the bacterial communities. Additionally, the Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) database, sourced from the Kyoto Encyclopedia of Genes and Genomes, was used to predict the functional capabilities of the bacteria.

RESULTS

PC patients were comparable with healthy controls. However, PC patients older than 60 years had a distinct composition compared to those under 60 years old. Bacteroidetes richness was considerably higher at the phylum level in PC patients. Bacteroides, Parabacteroides, and Bilophila were more abundant in the PC group than in the control group. Furthermore, PC patients exhibited greater enrichment in metabolic pathways, specifically those related to lipopolysaccharide biosynthesis and vancomycin group antibiotic production, than controls.

CONCLUSION

This study indicated that the mucosal microbiota in PC patients was altered, perhaps offering new perspectives on the treatment possibilities for CRC and diarrhea following cholecystectomy.

The microbiome compositional and functional differences between rectal mucosa and feces

In recent years, most studies on the gut microbiome have primarily focused on feces samples, leaving the microbial communities in the intestinal mucosa relatively unexplored. To address this gap, our study employed shotgun metagenomics to analyze the microbial compositions in normal rectal mucosa and matched feces from 20 patients with colonic polyps. Our findings revealed a pronounced distinction of the microbial communities between these two sample sets. Compared with feces, the mucosal microbiome contains fewer genera, with Burkholderia being the most discriminating genus between feces and mucosa, highlighting its significant influence on the mucosa. Furthermore, based on the microbial classification and KEGG Orthology (KO) annotation results, we explored the association between rectal mucosal microbiota and factors such as age, gender, BMI, and polyp risk level. Notably, we identified novel biomarkers for these phenotypes, such as Clostridium ramosum and Enterobacter cloacae in age. The mucosal microbiota showed an enrichment of KO pathways related to sugar transport and short chain fatty acid metabolism. Our comprehensive approach not only bridges the knowledge gap regarding the microbial community in the rectal mucosa but also underscores the complexity and specificity of microbial interactions within the human gut, particularly in the Chinese population.

IMPORTANCE

This study presents a system-level map of the differences between feces and rectal mucosal microbial communities in samples with colorectal cancer risk. It reveals the unique microecological characteristics of rectal mucosa and its potential influence on health. Additionally, it provides novel insights into the role of the gut microbiome in the pathogenesis of colorectal cancer and paves the way for the development of new prevention and treatment strategies.

Tumour-associated and non-tumour-associated bacteria co-abundance groups in colorectal cancer

BACKGROUND & AIMS

Gut microbiota is closely related to the occurrence and development of colorectal cancer (CRC). However, the differences in bacterial co-abundance groups (CAGs) between tumor tissue (TT) and normal tissue (NT), as well as their associations with clinical features, are needed to be clarified.

METHODS

Bacterial 16 S rRNA sequencing was performed by using TT samples and NT samples of 251 patients with colorectal cancer. Microbial diversity, taxonomic characteristics, microbial composition, and functional pathways were compared between TT and NT. Hierarchical clustering was used to construct CAGs.

RESULTS

Four CAGs were grouped in the hierarchical cluster analysis. CAG 2, which was mainly comprised of pathogenic bacteria, was significantly enriched in TT samples (2.27% in TT vs. 0.78% in NT, p < 0.0001). CAG 4, which was mainly comprised of non-pathogenic bacteria, was significantly enriched in NT samples (0.62% in TT vs. 0.79% in NT, p = 0.0004). In addition, CAG 2 was also significantly associated with tumor microsatellite instability (13.2% in unstable vs. 2.0% in stable, p = 0.016), and CAG 4 was positively correlated with the level of CA199 (r = 0.17, p = 0.009).

CONCLUSIONS

Our research will deepen our understanding of the interactions among multiple bacteria and offer insights into the potential mechanism of NT to TT transition.

Altered mucosal bacteria and metabolomics in patients with Peutz-Jeghers syndrome

BACKGROUND

Peutz-Jeghers syndrome (PJS) is a rare genetic disorder characterized by the development of pigmented spots, gastrointestinal polyps and increased susceptibility to cancers. Currently, most studies have investigated intestinal microbiota through fecal microbiota, and there are few reports about mucosa-associated microbiota. It remains valuable to search for the key intestinal microbiota or abnormal metabolic pathways linked to PJS.

AIM

This study aimed to assess the structure and composition of mucosa-associated microbiota in patients with PJS and to explore the potential influence of intestinal microbiota disorders and metabolite changes on PJS.

METHODS

The bacterial composition was analyzed in 13 PJS patients and 12 controls using 16S rRNA gene sequencing (Illumina MiSeq) for bacteria. Differential analyses of the intestinal microbiota were performed from the phylum to species level. Liquid chromatography-tandem mass spectrometry (LC‒MS) was used to detect the differentially abundant metabolites of PJS patients and controls to identify different metabolites and metabolic biomarkers of small intestinal mucosa samples.

RESULTS

High-throughput sequencing confirmed the special characteristics and biodiversity of the mucosa microflora in patients with PJS. They had lower bacterial biodiversity than controls. The abundance of intestinal mucosal microflora was significantly lower than that of fecal microflora. In addition, lipid metabolism, amino acid metabolism, carbohydrate metabolism, nucleotide metabolism and other pathways were significantly different from those of controls, which were associated with the development of the enteric nervous system, intestinal inflammation and development of tumors.

CONCLUSION

This is the first report on the mucosa-associated microbiota and metabolite profile of subjects with PJS, which may be meaningful to provide a structural basis for further research on intestinal microecology in PJS.

Signs of aging in midlife: physical function and sex differences in microbiota

Microbiota composition has been linked to physical activity, health measures, and biological age, but a shared profile has yet to be shown. The aim of this study was to examine the associations between microbiota composition and measures of function, such as a composite measure of physical capacity, and biological age in midlife, prior to onset of age-related diseases. Seventy healthy midlife individuals (age 44.58 ± 0.18) were examined cross-sectionally, and their gut-microbiota profile was characterized from stool samples using 16SrRNA gene sequencing. Biological age was measured using the Klemera-Doubal method and a composition of blood and physiological biomarkers. Physical capacity was calculated based on sex-standardized functional tests. We demonstrate that the women had significantly richer microbiota, p = 0.025; however, microbiota diversity was not linked with chronological age, biological age, or physical capacity for either women or men. Men had slightly greater β-diversity; however, β-diversity was positively associated with biological age and with physical capacity for women only (p = 0.01 and p = 0.04; respectively). For women, an increase in abundance of Roseburia faecis and Collinsella aerofaciens, as well as genus Ruminococcus and Dorea, was significantly associated with higher biological age and lower physical capacity; an increase in abundance of Akkermansia muciniphila and genera Bacteroides and Alistipes was associated with younger biological age and increased physical capacity. Differentially abundant taxa were also associated with non-communicable diseases. These findings suggest that microbiota composition is a potential mechanism linking physical capacity and health status; personalized probiotics may serve as a new means to support health-promoting interventions in midlife. Investigating additional factors underlying this link may facilitate the development of a more accurate method to estimate the rate of aging.

Identification of host gene-microbiome associations in colorectal cancer patients using mendelian randomization

BACKGROUND

There are many studies indicating that alterations in the abundance of certain gut microbiota are associated with colorectal cancer (CRC). However, a causal relationship has not been identified due to confounding factors such as lifestyle, environmental, and possible reverse causal associations between the two. Furthermore, certain host gene mutations can also contribute to the development of CRC. However, the association between genes and gut microbes in patients with CRC has not been extensively studied.

METHODS

We conducted a two-sample Mendelian randomization (MR) study to reveal the causal relationship between gut microbiota and CRC. We obtained SNPs associated with gut microbiome abundance as instrumental variables (IVs) from a large-scale, multi-ethnic GWAS study, and extracted CRC-related datasets from an East Asian Population genetic consortia GWAS (AGWAS) study and FinnGen consortium, respectively. We analyzed a total of 166 bacterial features at four taxonomic levels, including order, family, genus, and species. The inverse-variance-weighted (IVW), weighted median, MR-Egger, and simple median methods were applied to the MR analysis, and the robustness of the results were tested using a series of sensitivity analyses. We extracted IVs of gut microbiota with direct causal association with CRC for SNP annotation to identify the genes in which these genetic variants were located to reveal the possible host gene-microbiome associations in CRC patients.

RESULTS

The findings from our MR analysis based on CRC-associated GWAS datasets from AGWAS revealed causal relationships between 6 bacterial taxa and CRC at a locus-wide significance level (P < 1 × 10-5). The IVW method found that family Porphyromonadaceae, genera Anaerotruncus, Intestinibacter, Slackia, and Ruminococcaceae UCG004, and species Eubacterium coprostanoligenes group were positively associated with CRC risk, which was generally consistent with the results of other complementary analyses. The results of a meta-analysis of the MR estimates from the AGWAS and the FinnGen datasets showed that family Porphyromonadaceae and genera Slackia, Anaerotruncus, and Intestinibacter replicated the same causal association. Sensitivity analysis of all causal associations did not indicate significant heterogeneity, horizontal pleiotropy, or reverse causal associations. We annotated the SNPs at a locus-wide significance level of the above intestinal flora and identified 24 host genes that may be related to pathogenic intestinal microflora in CRC patients.

CONCLUSION

This study supported the causal relationship of gut microbiota on CRC and revealed a possible correlation between genes and pathogenic microbiota in CRC. These findings suggested that the study of the gut microbiome and its further multi-omics analysis was important for the prevention and treatment of CRC.

Elucidating colorectal cancer-associated bacteria through profiling of minimally perturbed tissue-associated microbiota

Sequencing-based interrogation of gut microbiota is a valuable approach for detecting microbes associated with colorectal cancer (CRC); however, such studies are often confounded by the effect of bowel preparation. In this study, we evaluated the viability of identifying CRC-associated mucosal bacteria through centimeter-scale profiling of the microbiota in tumors and adjacent noncancerous tissue from eleven patients who underwent colonic resection without preoperative bowel preparation. High-throughput 16S rRNA gene sequencing revealed that differences between on- and off-tumor microbiota varied considerably among patients. For some patients, phylotypes affiliated with genera previously implicated in colorectal carcinogenesis, as well as genera with less well-understood roles in CRC, were enriched in tumor tissue, whereas for other patients, on- and off-tumor microbiota were very similar. Notably, the enrichment of phylotypes in tumor-associated mucosa was highly localized and no longer apparent even a few centimeters away from the tumor. Through short-term liquid culturing and metagenomics, we further generated more than one-hundred metagenome-assembled genomes, several representing bacteria that were enriched in on-tumor samples. This is one of the first studies to analyze largely unperturbed mucosal microbiota in tissue samples from the resected colons of unprepped CRC patients. Future studies with larger cohorts are expected to clarify the causes and consequences of the observed variability in the emergence of tumor-localized microbiota among patients.

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.

Mucosal Microbiota from Colorectal Cancer, Adenoma and Normal Epithelium Reveals the Imprint of Fusobacterium nucleatum in Cancerogenesis

An increasing amount of evidence suggests the emerging role of the gut microbiota in the development of colorectal cancer (CRC). This study aimed to elucidate the architecture of microbial communities within normal and neoplastic colonic mucosa.

METHODS

Microbiota were analyzed by NGS and by an ensemble of metagenomics analysis tools in a total of 69 tissues from 9 patients with synchronous colorectal neoplasia and adenomas (27 specimens: 9 from normal tissues, 9 adenomas, and 9 tumours), 16 patients with only colonic adenomas (32 specimens: 16 from normal tissues and 16 adenomas), and from healthy subjects (10 specimens of normal mucosa).

RESULTS

Weak differences were observed in alpha and beta metrics among the synchronous tissues from CRC and controls. Through pairwise differential abundance analyses of sample groups, an increasing trend of Rikenellaceae, Pseudomonas and Fusobacterium, and decreasing trends of Staphylococcus, Actinobacillus and Gemmiger were observed in CRC, while Staphylococcus and Bifidobacterium were decreased in patients with only adenomas. At RT-qPCR analysis, Fusobacterium nucleatum was significantly enriched in all the tissues of subjects with synchronous colorectal neoplasia.

CONCLUSION

Our findings provide a comprehensive view of the human mucosa-associated gut microbiota, emphasizing global microbial diversity mostly in synchronous lesions and proving the constant presence of Fusobacterium nucleatum, with its ability to drive carcinogenesis.

Methods and biomarkers for early detection, prediction, and diagnosis of colorectal cancer

Colorectal cancer (CRC) is one of the most common digestive diseases worldwide. It has steadily ascended to the top three cancers in terms of incidence and mortality. The primary cause is the inability to diagnose it at an early stage. Therefore, early detection and diagnosis are essential for colorectal cancer prevention. Although there are now various methods for CRC early detection, in addition to recent developments in surgical and multimodal therapy, the poor prognosis and late detection of CRC still remain significant. Thus, it is important to investigate novel technologies and biomarkers to improve the sensitization and specification of CRC diagnosis. Here, we present some common methods and biomarkers for early detection and diagnosis of CRC, we hope this review will encourage the adoption of screening programs and the clinical use of these potential molecules as biomarkers for CRC early detection and prognosis.

Multi-omics insights into the interplay between gut microbiota and colorectal cancer in the "microworld" age

Colorectal cancer (CRC) is a multifactorial heterogeneous disease largely due to both genetic predisposition and environmental factors including the gut microbiota, a dynamic microbial ecosystem inhabiting the gastrointestinal tract. Elucidation of the molecular mechanisms by which the gut microbiota interacts with the host may contribute to the pathogenesis, diagnosis, and promotion of CRC. However, deciphering the influence of genetic variants and interactions with the gut microbial ecosystem is rather challenging. Despite recent advancements in single omics analysis, the application of multi-omics approaches to integrate multiple layers of information in the microbiome and host to introduce effective prevention, diagnosis, and treatment strategies is still in its infancy. Here, we integrate host- and microbe-based multi-omics studies, respectively, to provide a strategy to explore potential causal relationships between gut microbiota and colorectal cancer. Specifically, we summarize the recent multi-omics studies such as metagenomics combined with metabolomics and metagenomics combined with genomics. Meanwhile, the sample size and sample types commonly used in multi-omics research, as well as the methods of data analysis, were also generalized. We highlight multiple layers of information from multi-omics that need to be verified by different types of models. Together, this review provides new insights into the clinical diagnosis and treatment of colorectal cancer patients.

Compartmentalization of the host microbiome: how tumor microbiota shapes checkpoint immunotherapy outcome and offers therapeutic prospects

The host microbiome is polymorphic, compartmentalized, and composed of distinctive tissue microbiomes. While research in the field of cancer immunotherapy has provided an improved understanding of the interaction with the gastrointestinal microbiome, the significance of the tumor-associated microbiome has only recently been grasped. This article provides a state-of-the-art review about the tumor-associated microbiome and sheds light on how local tumor microbiota shapes anticancer immunity and influences checkpoint immunotherapy outcome. The direct route of interaction between cancer cells, immune cells, and microbiota in the tumor microenvironment is emphasized and advocates a focus on the tumor-associated microbiome in addition to the spatially separated gut compartment. Since the mechanisms underlying checkpoint immunotherapy modulation by tumor-associated microbiota remain largely elusive, future research should dissect the pathways involved and outline strategies to therapeutically modulate microbes and their products within the tumor microenvironment. A more detailed knowledge about the mechanisms governing the composition and functional quality of the tumor microbiome will improve cancer immunotherapy and advance precision medicine for solid tumors.

Integrated Microbiome and Metabolome Analysis Reveals Correlations Between Gut Microbiota Components and Metabolic Profiles in Mice with Methotrexate-Induced Hepatoxicity

Purpose

We designed this study to investigate the potential correlations between gut microbiota compositions and hepatic metabolomic disorders in mice with methotrexate (MTX)-induced hepatoxicity.

Methods

We used MTX to induce hepatoxicity in healthy Kunming mice, and we determined plasma ALT and AST levels and assessed the liver tissue histopathology. We applied an integrated gas chromatography-mass spectrometry (GC-MS) and 16S ribosomal RNA (rRNA) gene sequencing approach to evaluate the effects of MTX on the gut microbiota and hepatic metabolic profiles of mice. We uncovered correlations between the gut microbiota and hepatic metabolomic profiles by calculating the Spearman correlation coefficient.

Results

MTX caused ALT and AST level elevations and hepatoxicity in our mouse model. MTX disrupted amino acid metabolic pathways (including biosyntheses of valine, leucine, and isoleucine; and arginine; and, metabolism of alanine, aspartate, and glutamate; histidine; beta-alanine; and glycine, serine, and threonine); biosyntheses of aminoacyl-tRNA; and pantothenate, and CoA; and, metabolic pathways of energy, glutathione, and porphyrin; and chlorophyll. In addition, MTX increased the abundances of Staphylococcus, Enterococcus, Collinsella, Streptococcus, and Aerococcus, but decreased the amounts of Lactobacillus, Ruminococcus, norank_f_Muribaculaceae, unclassified_f_Lachnospiraceae, norank_f_Lachnospiraceae, A2, Eubacterium_xylanophilum_group, Phascolarctobacterium, Bifidobacterium, and Faecalibaculum. Our correlation analyses showed that different flora abundance changes including those of Phascolarctobacterium, Faecalibaculum, norank_f_Muribaculaceae, Streptococcus, Enterococcus, Staphylococcus, and Collinsella were associated with liver injury.

Conclusion

We present evidence supporting the notion that MTX causes hepatoxicity by altering the gut microbiota and hepatic metabolite profiles, our findings provide new venues for the management of MTX-induced hepatoxicity.

Exploring Gut Microenvironment in Colorectal Patient with Dual-Omics Platform: A Comparison with Adenomatous Polyp or Occult Blood

The gut mucosa is actively absorptive and functions as the physical barrier to separate the gut ecosystem from host. Gut microbiota-utilized or food-derived metabolites are closely relevant to the homeostasis of the gut epithelial cells. Recent studies widely suggested the carcinogenic impact of gut dysbiosis or altered metabolites on the development of colorectal cancer (CRC). In this study, liquid chromatography coupled-mass spectrometry and long-read sequencing was applied to identify gut metabolites and microbiomes with statistically discriminative abundance in CRC patients (n = 20) as compared to those of a healthy group (n = 60) ofenrolled participants diagnosed with adenomatous polyp (n = 67) or occult blood (n = 40). In total, alteration in the relative abundance of 90 operational taxonomic units (OTUs) and 45 metabolites were identified between recruited CRC patients and healthy participants. Among the candidates, the gradual increases in nine OTUs or eight metabolites were identified in healthy participants, patients diagnosed with occult blood and adenomatous polyp, and CRC patients. The random forest regression model constructed with five OTUs or four metabolites achieved a distinct classification potential to differentially discriminate the presence of CRC (area under the ROC curve (AUC) = 0.998 or 0.975) from the diagnosis of adenomatous polyp (AUC = 0.831 or 0.777), respectively. These results provide the validity of CRC-associated markers, including microbial communities and metabolomic profiles across healthy and related populations toward the early screening or diagnosis of CRC.

The Tissue-Associated Microbiota in Colorectal Cancer: A Systematic Review

Simple Summary

Growing evidence shows a close relationship between the microbiome and colorectal cancer, but most studies analyze fecal samples. However, solid information on the microbial community that is present locally in the intestinal tumor tissues is lacking. Therefore, the aim of this systematic review was to compile evidence on the relationship between tissue-associated microbiota and colorectal cancer. Among 5080 screened publications, 39 were eligible and included in the analysis. Despite the heterogeneity in methodologies and reporting between studies, 12 groups of bacteria with strong positive and 18 groups of bacteria with strong negative associations with colorectal cancer were identified. Such knowledge may ultimately be used in novel strategies that aim to prevent, detect, and treat colorectal cancer in the upcoming years.

Abstract

The intestinal microbiome is associated with colorectal cancer. Although the mucosal microbiota better represents an individual’s local microbiome, studies on the colorectal cancer microbiota mainly reflect knowledge obtained from fecal samples. This systematic review aimed to summarize the current evidence on the relationship between the mucosal-associated bacterial microbiota and colorectal cancer. Searches were conducted in PubMed and Web of Science databases for publications comparing the mucosal microbiome of colorectal cancer patients with that of healthy controls, or with that of non-cancerous mucosal tissues. The primary outcomes were differences in microbial diversity and taxonomy. The Newcastle-Ottawa Scale was used to assess the quality of the included studies. Of the 5080 studies identified, 39 were eligible and included in the systematic review. No consistent results were identified for the α- and β-diversity, due to high heterogeneity in reporting and to differences in metrics and statistical approaches, limiting study comparability. Qualitative synthesis of microbial taxonomy identified 12 taxa with strong positive and 18 taxa with strong negative associations with colorectal cancer. Fusobacterium, Campylobacter, Parvimonas, Peptostreptococcus, Streptococcus, and Granulicatella were defined as enriched in colorectal cancer. Despite the methodological limitations of the studies, consistent evidence on bacterial taxa associated with colorectal cancer was identified. Prospective studies in large and well-characterized patient populations will be crucial to validate these findings.

Intestinal toxicity of micro- and nano-particles of foodborne titanium dioxide in juvenile mice: Disorders of gut microbiota-host co-metabolites and intestinal barrier damage

The wide use of TiO₂ particles in food and the high exposure risk to children have prompted research into the health risks of TiO₂. We used the microbiome and targeted metabolomics to explore the potential mechanism of intestinal toxicity of foodborne TiO₂ micro-/nanoparticles after oral exposure for 28 days in juvenile mice. Results showed that the gut microbiota-including the abundance of Bacteroides, Bifidobacterium, Lactobacillus, and Prevotella-changed dynamically during exposure. The organic inflammatory response was activated, and lipopolysaccharide levels increased. Intestinal toxicity manifested as increased mucosal permeability, impaired intestinal barrier, immune damage, and pathological changes. The expression of antimicrobial peptides, occludin, and ZO-1 significantly reduced, while that of JNK2 and Src/pSrc increased. Compared with micro-TiO₂ particles, the nano-TiO₂ particles had strong toxicity. Fecal microbiota transplant confirmed the key role of gut microbiota in intestinal toxicity. The levels of gut microbiota-host co-metabolites, including pyroglutamic acid, L-glutamic acid, phenylacetic acid, and 3-hydroxyphenylacetic acid, changed significantly. Significant changes were observed in the glutathione and propanoate metabolic pathways. There was a significant correlation between the changes in gut microbiota, metabolites, and intestinal cytokine levels. These, together with the intestinal barrier damage signaling pathway, constitute the network mechanism of the intestinal toxicity of TiO₂ particles.

Metagenomics analysis of cultured mucosal bacteria from colorectal cancer and adjacent normal mucosal tissues

Introduction. Colorectal cancer (CRC) is one of the most common cancers worldwide. Multiple risk factors are involved in CRC development, including age, genetics, lifestyle, diet and environment. Of these, the role of the gut microbiota in cancer biology is increasingly recognized.Hypothesis/Gap Statement. Micro-organisms have been widely detected in stool samples, but few mucosal samples have been detected and sequenced in depth.Aim. Analysis of cultured mucosal bacteria from colorectal cancer and adjacent normal mucosal tissues with metagenomics sequencing.Methodology. Twenty-eight paired tumour and non-tumour tissues from 14 patients undergoing surgery for CRC were analysed. We removed the influence of eukaryotic cells via culture. The composition of mucosal microbiota in intestinal mucosa were detected and analysed with metagenomic sequencing.Results. Compared with non-cultured mucosal sample, 80 % bacteria species could be detected after culture. Moreover, after culture, additional 30 % bacteria could be detected, compared with non-cultured samples. Since after culture it was difficult to estimate the original abundance of microbiome, we focused on the identification of the CRC tissue-specific species. There were 298 bacterial species, which could only be cultured and detected in CRC tissues. Myroides odoratimimus and Cellulophaga baltica could be isolated from all the tumour samples of 14 CRC patients, suggesting that these species may be related to tumour occurrence and development. Further functional analysis indicated that bacteria from CRC tissues showed more active functions, including basic metabolism, signal transduction and survival activities.Conclusion. We used a new method based on culture to implement information on prokaryotic taxa, and related functions, which samples were from colorectal tissues. This method is suitable for removing eukaryotic contamination and detecting micro-organisms from other tissues.

Impact of Helicobacter pylori infection on fluid duodenal microbial community structure and microbial metabolic pathways

Background

The bioactivities of commensal duodenal microbiota greatly influence the biofunction of hosts. We investigated the role of Helicobacter pylori infection in extra-gastroduodenal diseases by determining the impact of H. pylori infection on the duodenal microbiota. We sequenced 16 S rRNA genes in samples aspirated from the descending duodenum of 47 (male, 20; female, 27) individuals who were screened for gastric cancer. Samples were analysed using 16 S rRNA gene amplicon sequencing, and the LEFSe and Kyoto Encyclopaedia of Genes and Genomes methods were used to determine whether the duodenal microflora and microbial biofunctions were affected using H. pylori infection.

Results

Thirteen and 34 participants tested positive and negative for H. pylori, respectively. We identified 1,404 bacterial operational taxonomic units from 23 phyla and 253 genera. H. pylori infection changed the relative mean abundance of three phyla (Proteobacteria, Actinobacteria, and TM7) and ten genera (Neisseria, Rothia, TM7-3, Leptotrichia, Lachnospiraceae, Megasphaera, F16, Moryella, Filifactor, and Paludibacter). Microbiota features were significantly influenced in H. pylori-positive participants by 12 taxa mostly classified as Gammaproteobacteria. Microbial functional annotation revealed that H. pylori significantly affected 12 microbial metabolic pathways.

Conclusions

H. pylori disrupted normal bacterial communities in the duodenum and changed the biofunctions of commensal microbiota primarily by upregulating specific metabolic pathways. Such upregulation may be involved in the onset of diseases associated with H. pylori infection.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12866-022-02437-w.

Examining the Interaction of the Gut Microbiome with Host Metabolism and Cardiometabolic Health in Metabolic Syndrome

(1) Background: The microbiota-host cross-talk has been previously investigated, while its role in health is not yet clear. This study aimed to unravel the network of microbial-host interactions and correlate it with cardiometabolic risk factors. (2) Methods: A total of 47 adults with overweight/obesity and metabolic syndrome from the METADIET study were included in this cross-sectional analysis. Microbiota composition (151 genera) was assessed by 16S rRNA sequencing, fecal (m = 203) and plasma (m = 373) metabolites were profiled. An unsupervised sparse generalized canonical correlation analysis was used to construct a network of microbiota-metabolite interactions. A multi-omics score was derived for each cluster of the network and associated with cardiometabolic risk factors. (3) Results: Five multi-omics clusters were identified. Thirty-one fecal metabolites formed these clusters and were correlated with plasma sphingomyelins, lysophospholipids and medium to long-chain acylcarnitines. Seven genera from Ruminococcaceae and a member from the Desulfovibrionaceae family were correlated with fecal and plasma metabolites. Positive correlations were found between the multi-omics scores from two clusters with cholesterol and triglycerides levels. (4) Conclusions: We identified a correlated network between specific microbial genera and fecal/plasma metabolites in an adult population with metabolic syndrome, suggesting an interplay between gut microbiota and host lipid metabolism on cardiometabolic health.

New Advances in Tissue Metabolomics: A Review

Metabolomics offers a hypothesis-generating approach for biomarker discovery in clinical medicine while also providing better understanding of the underlying mechanisms of chronic diseases. Clinical metabolomic studies largely rely on human biofluids (e.g., plasma, urine) as a more convenient specimen type for investigation. However, biofluids are non-organ specific reflecting complex biochemical processes throughout the body, which may complicate biochemical interpretations. For these reasons, tissue metabolomic studies enable deeper insights into aberrant metabolism occurring at the direct site of disease pathogenesis. This review highlights new advances in metabolomics for ex vivo analysis, as well as in situ imaging of tissue specimens, including diverse tissue types from animal models and human participants. Moreover, we discuss key pre-analytical and post-analytical challenges in tissue metabolomics for robust biomarker discovery with a focus on new methodological advances introduced over the past six years, including innovative clinical applications for improved screening, diagnostic testing, and therapeutic interventions for cancer.

The Application of High-Throughput Technologies for the Study of Microbiome and Cancer

Human gut microbiome research, especially gut microbiome, has been developing at a considerable pace over the last decades, driven by a rapid technological advancement. The emergence of high-throughput technologies, such as genomics, transcriptomics, and others, has afforded the generation of large volumes of data, and in relation to specific pathologies such as different cancer types. The current review identifies high-throughput technologies as they have been implemented in the study of microbiome and cancer. Four main thematic areas have emerged: the characterization of microbial diversity and composition, microbial functional analyses, biomarker prediction, and, lastly, potential therapeutic applications. The majority of studies identified focus on the microbiome diversity characterization, which is reaching technological maturity, while the remaining three thematic areas could be described as emerging.

Cancer-Preventive Role of Bone Marrow-Derived Mesenchymal Stem Cells on Colitis-Associated Colorectal Cancer: Roles of Gut Microbiota Involved

BACKGROUND

Mesenchymal stem cells (MSCs) treatment showed promising results in inflammatory bowel disease in both rodent models and patients. Nevertheless, previous studies conducted conflicting results on preclinical tumor models treated with MSCs concerning their influence on tumor initiation and progression. This study is designed to demonstrate the role of bone marrow-derived MSCs and the potential mechanism in the colitis-associated colon cancer (CAC) model.

METHODS

Bone marrow-derived MSCs were isolated from green fluorescent protein-transgenic mice, cultured, and identified by flow cytometry. Azoxymethane and dextran sulfate sodium were administrated to establish the CAC mouse model, and MSCs were infused intraperitoneally once per week. The mice were weighed weekly, and colon length, tumor number, and average tumor size were assessed after the mice were killed. MSC localization was detected by immunofluorescence staining; tumor cell proliferation and apoptosis were measured by immunohistochemistry staining of Ki-67 and terminal deoxynucleotidyl transferase deoxyuridine triphosphate nick end labeling assay, respectively. The colonic tumor tissues were isolated for RNA-seq, and fecal samples were collected for 16S ribosomal RNA sequencing of the microbiome.

RESULTS

After injection intraperitoneally, MSCs migrated to the intestine and inhibited the initiation of colitis-associated colorectal cancer. This inhibition effect was marked by less weight loss, longer colon length, and reduced tumor numbers. Moreover, MSCs reduced tumor cell proliferation and induced tumor cell apoptosis. Furthermore, MSCs could inhibit chronic inflammation assessed by RNA-sequencing and promote gut microbiome normalization detected by 16S ribosomal RNA sequencing.

CONCLUSION

The results proved that MSCs could migrate to the colon, inhibit chronic inflammation, and regulate gut microbiome dysbiosis to suppress the development of CAC.

Comprehensive Volatilome and Metabolome Signatures of Colorectal Cancer in Urine: A Systematic Review and Meta-Analysis

To increase compliance with colorectal cancer screening programs and to reduce the recommended screening age, cheaper and easy non-invasiveness alternatives to the fecal immunochemical test should be provided. Following the PRISMA procedure of studies that evaluated the metabolome and volatilome signatures of colorectal cancer in human urine samples, an exhaustive search in PubMed, Web of Science, and Scopus found 28 studies that met the required criteria. There were no restrictions on the query for the type of study, leading to not only colorectal cancer samples versus control comparison but also polyps versus control and prospective studies of surgical effects, CRC staging and comparisons of CRC with other cancers. With this systematic review, we identified up to 244 compounds in urine samples (3 shared compounds between the volatilome and metabolome), and 10 of them were relevant in more than three articles. In the meta-analysis, nine studies met the criteria for inclusion, and the results combining the case-control and the pre-/post-surgery groups, eleven compounds were found to be relevant. Four upregulated metabolites were identified, 3-hydroxybutyric acid, L-dopa, L-histidinol, and N1, N12-diacetylspermine and seven downregulated compounds were identified, pyruvic acid, hydroquinone, tartaric acid, and hippuric acid as metabolites and butyraldehyde, ether, and 1,1,6-trimethyl-1,2-dihydronaphthalene as volatiles.

Temozolomide-Induced Changes in Gut Microbial Composition in a Mouse Model of Brain Glioma

Background

Gut microbiota is associated with the progression of brain tumors. However, the alterations in gut microbiota observed during glioma growth and temozolomide (TMZ) therapy remain poorly understood.

Methods

C57BL/6 male mice were implanted with GL261 glioma cells. TMZ/sodium carboxymethyl cellulose (SCC) was administered through gavage for five consecutive days (from 8 to 12 days after implantation). Fecal samples were collected before (T0) and on days 7 (T1), 14 (T2), and 28 (T3) after implantation. The gut microbiota was analyzed using 16S ribosomal DNA sequencing followed by absolute and relative quantitation analyses.

Results

Nineteen genera were altered during glioma progression with the most dramatic changes in Firmicutes and Bacteroidetes phyla. During glioma growth, Lactobacillus abundance decreased in the early stage (T1) and then gradually increased (T2, T3); Intestinimonas abundance exhibited a persistent increase; Anaerotruncus showed a transient increase (T2) and then a subsequent decrease (T3). Similar longitudinal changes in Intestinimonas and Anaerotruncus abundance were observed in TMZ-treated mice, but the decrease of Anaerotruncus at T3 in the TMZ-treated group was less than that in the vehicle-treated group. No significant change in Lactobacillus was observed after TMZ treatment. Additionally, compared to vehicle control, TMZ treatment led to an enrichment in Akkermansia and Bifidobacterium.

Conclusion

Glioma development and progression altered the composition of gut microbiota. Induction of Akkermansia and Bifidobacterium as well as the prevention of the reduction in Anaerotruncus may contribute to the anti-tumor effect of TMZ. This study helps to reveal the association between levels of specific microbial species in the gut and the anti-tumor effect of TMZ.

Targeting Dietary and Microbial Tryptophan-Indole Metabolism as Therapeutic Approaches to Colon Cancer

Tryptophan metabolism, via the kynurenine (Kyn) pathway, and microbial transformation of tryptophan to indolic compounds are fundamental for host health; both of which are altered in colon carcinogenesis. Alterations in tryptophan metabolism begin early in colon carcinogenesis as an adaptive mechanism for the tumor to escape immune surveillance and metastasize. The microbial community is a key part of the tumor microenvironment and influences cancer initiation, promotion and treatment response. A growing awareness of the impact of the microbiome on tryptophan (Trp) metabolism in the context of carcinogenesis has prompted this review. We first compare the different metabolic pathways of Trp under normal cellular physiology to colon carcinogenesis, in both the host cells and the microbiome. Second, we review how the microbiome, specifically indoles, influence host tryptophan pathways under normal and oncogenic metabolism. We conclude by proposing several dietary, microbial and drug therapeutic modalities that can be utilized in combination to abrogate tumorigenesis.

The colorectal cancer-associated faecal microbiome of developing countries resembles that of developed countries

BACKGROUND

The incidence of colorectal cancer (CRC) is increasing in developing countries, yet limited research on the CRC- associated microbiota has been conducted in these areas, in part due to scarce resources, facilities, and the difficulty of fresh or frozen stool storage/transport. Here, we aimed (1) to establish a broad representation of diverse developing countries (Argentina, Chile, India, and Vietnam); (2) to validate a 'resource-light' sample-collection protocol translatable in these settings using guaiac faecal occult blood test (gFOBT) cards stored and, importantly, shipped internationally at room temperature; (3) to perform initial profiling of the collective CRC-associated microbiome of these developing countries; and (4) to compare this quantitatively with established CRC biomarkers from developed countries.

METHODS

We assessed the effect of international storage and transport at room temperature by replicating gFOBT from five UK volunteers, storing two in the UK, and sending replicates to institutes in the four countries. Next, to determine the effect of prolonged UK storage, DNA extraction replicates for a subset of samples were performed up to 252 days apart. To profile the CRC-associated microbiome of developing countries, gFOBT were collected from 41 treatment-naïve CRC patients and 40 non-CRC controls from across the four institutes, and V4 16S rRNA gene sequencing was performed. Finally, we constructed a random forest (RF) model that was trained and tested against existing datasets from developed countries.

RESULTS

The microbiome was stably assayed when samples were stored/transported at room temperature and after prolonged UK storage. Large-scale microbiome structure was separated by country and continent, with a smaller effect from CRC. Importantly, the RF model performed similarly to models trained using external datasets and identified similar taxa of importance (Parvimonas, Peptostreptococcus, Fusobacterium, Alistipes, and Escherichia).

CONCLUSIONS

This study demonstrates that gFOBT, stored and transported at room temperature, represents a suitable method of faecal sample collection for amplicon-based microbiome biomarkers in developing countries and suggests a CRC-faecal microbiome association that is consistent between developed and developing countries.

Comparative assessment of gut microbial composition and function in patients with Graves' disease and Graves' orbitopathy

BACKGROUND

A previous study indicated that gut microbiota changed notably in Graves' orbitopathy (GO) patients as compared to controls. However, the characteristics of intestinal bacteria in Graves' disease (GD) and GO are unclear.

OBJECTIVE

The present study aimed to identify specific intestinal bacteria of GD and GO, respectively.

METHODS

The gut microbial communities of the fecal samples of 30 GD patients without GO, 33 GO subjects, and 32 healthy subjects were analyzed and compared by 16S rRNA gene sequencing.

RESULTS

At the phylum level, the proportion of Deinococcus-Thermus and Chloroflexi was decreased significantly in GO patients as compared to GD. At the genus level, the proportion of Subdoligranulum and Bilophila was increased while that of Blautia, Anaerostipes, Dorea, Butyricicoccus, Romboutsia, Fusicatenibacter, unidentified_ Lachnospiraceae, unidentified_Clostridiales, Collineslla, Intestinibacter, and Phascolarctobacterium was decreased in the GO group as compared to the GD group. Random forest analysis was used for the identification of specific intestinal microbiota, and Deinococcus-Thermus, Cyanobacteria and Chloroflexi were ranked in the top ten according to their contributions to sample classification. Moreover, compared to the control, there were multiple gut bacterial enrichment metabolic pathways in GO and GD patients, including nucleotide metabolism, enzyme family, and energy metabolism. Compared to GO, the only enrichment metabolic pathway found in GD was the viral protein family.

CONCLUSIONS

This study highlighted the significant differences in the intestinal microbiota and predictive functions of GD with GO, thereby providing new insights into the role of the gut bacteria that might contribute to the development of GO in GD patients.

Tissue metabolic profiling reveals major metabolic alteration in colorectal cancer

Metabolic reprogramming is a hallmark of cancer, which is still far from being fully understood in colorectal cancer. In order to characterize the metabolic changes in colorectal cancer, we performed metabolomics analysis of paired colon tissues from colorectal cancer patients by using a liquid chromatography-mass spectrometry (LC-MS)-based method. Bioinformation analysis was used to define important metabolites and metabolic pathways, as well as the prognosis significance and expression levels of the key molecules. The results indicated that the metabolite phenotype in cancerous colon tissues was obviously different from their normal counterpart, and we identified a series of important metabolic changes in colorectal cancer, including decreased trends of glucose, citrate, serotonin, 5-hydroxytryptophol and 5-hydroxyindoleacetate, as well as increased trends of glutamate, glutathione, creatine, proline, lactate, fructose 1,6-bisphosphate, succinate, tryptophan, kynurenine and long chain acyl-carnitines. These metabolites are mainly implicated in energy metabolism, amino acid metabolism, glutathione metabolism and fatty acid metabolism. In addition, we found that the expression levels of several key molecules in these pathways were closely correlated with the prognosis of colorectal cancer patients. This study characterizes the metabolic profile in colorectal cancer tissues and provides more insightful understanding of the metabolic reprogramming of colorectal cancer.

Low-concentration of dichloroacetonitrile (DCAN) in drinking water perturbs the health-associated gut microbiome and metabolic profile in rats

Dichloroacetonitrile (DCAN) is one of the emerging nitrogenous disinfection by-products (DBPs) in drinking water. However, its potential toxicological effects remain poorly understood, especially at a low concentration found in the environment. In the present study, we investigated whether the consumption of low-concentration DCAN through drinking water would produce significant effects in male SD rats, with particular focus on their physiological traits and changes in their gut microbiome and metabolite profiles. After a 4-weeks DCAN intervention, significant changes were observed in the body weight, blood indices, and histology in DCAN-treated (100 μg/L) group. Proteobacteria was relatively less abundant in 20 and 100 μg/L DCAN-treated groups compared with that in the control group at phylum level. At genus level, Parasutterella and Anaerotruncus were significantly less abundant in both 20 and 100 μg/L DCAN-treated groups than that in the control group. Furthermore, the gut microbiota-related metabolites were dramatically perturbed after DCAN consumption. In the 20 and 100 μg/L DCAN-treated groups, there were 48 and 95 altered metabolites, respectively, and were found to be involved in sphingolipid signaling pathway, fatty acid biosynthesis, and cGMP-PKG signaling pathway. In summary, we demonstrated that consumption of low-concentration DCAN through drinking water could impair host health and induce gut microbiota dysbiosis and gut microflora-related metabolic disorders in male SD rats. Our findings highlight the potential toxicity of low-concentration DBPs and provide new insight into potential causal relationship between low concentration DBPs found in the drinking water and the host health.

Omics technologies for improved diagnosis and treatment of colorectal cancer: Technical advancement and major perspectives

Colorectal cancer (CRC) ranks third among the most commonly occurring cancers worldwide, and it causes half a million deaths annually. Alongside mechanistic study for CRC detection and treatment by conventional techniques, new technologies have been developed to study CRC. These technologies include genomics, transcriptomics, proteomics, and metabolomics which elucidate DNA markers, RNA transcripts, protein and, metabolites produced inside the colon and rectum part of the gut. All these approaches form the omics arena, which presents a remarkable opportunity for the discovery of novel prognostic, diagnostic and therapeutic biomarkers and also delineate the underlying mechanism of CRC causation, which may further help in devising treatment strategies. This review also mentions the latest developments in metagenomics and culturomics as emerging evidence suggests that metagenomics of gut microbiota has profound implications in the causation, prognosis, and treatment of CRC. A majority of bacteria cannot be studied as they remain unculturable, so culturomics has also been strengthened to develop culture conditions suitable for the growth of unculturable bacteria and identify unknown bacteria. The overall purpose of this review is to succinctly evaluate the application of omics technologies in colorectal cancer research for improving the diagnosis and treatment strategies.

Profiling of polar urine metabolite extracts from Chinese colorectal cancer patients to screen for potential diagnostic and adverse-effect biomarkers

Background: Metabolomics has demonstrated its potential in the early diagnosis, drug safety evaluation and personalized toxicology research of various cancers. Objectives: We aim to screen for potential diagnostic and capecitabine-related adverse effect (CRAE) biomarkers from urinary endogenous metabolites in Chinese colorectal cancer (CRC) patients. Methods: The metabolic profiles of 139 CRC patients and 50 non-neoplastic controls were analyzed using ultra-high-performance liquid chromatography combined with quadrupole time-of-flight mass spectrometry. Results: There were 41 metabolites identified between the CRC patients and the non-neoplastic controls, and 19 metabolites were identified between CRC patients with and without CRAE. Based on these identified metabolites, bioinformatic analysis and prediction model construction were completed. Most of these differential metabolites have important roles in cell proliferation and differentiation and the immune system. Based on binary logistic regression, a CRC prediction model, composed of 3-methylhistidine, N-heptanoylglycine, N1,N12-diacetylspermine and hippurate, was established, with an area under curve (AUC) of 0.980 (95% CI: 0.953-1.000; sensitivity: 94.3%; specificity: 92.0%) in the training set, and an AUC of 0.968 (95% CI: 0.933-1.000; sensitivity: 89.9%; specificity: 92.0%) in the testing set. In addition, methionine and 4-pyridoxic acid can be combined to predict hand foot syndrome, with an AUC of 0.884; ubiquinone-1 and 4-pyridoxic acid can be combined to predict anemia, with an AUC of 0.889; and 5-acetamidovalerate and 3,4-methylenesebacic acid can be combined to predict neutropenia, with an AUC of 0.882. Conclusion: The profiling of urine polar metabolites has great potential in the early detection of CRC and the prediction of CRAE.

The Dual Role of Serotonin in Colorectal Cancer

Serotonin (5-HT) has complex effects on the central nervous system (CNS), neuroendocrine mechanisms, immunological reactions, intestinal microbiome, and cancer. It has been associated with more severe signs and symptoms of colitis, as well as promoting colorectal cancer (CRC) cells toward expansion. However, recent findings revealed that impairments in 5-HT synthesis lead to high levels of DNA damage in colonocytes, which is linked with inflammatory reactions promoting the development of CRC. Here, we review the diverse roles of 5-HT in intestinal homeostasis and in CRC and discuss how improved understanding of the modulation of the 5-HT pathway could be helpful for the design of novel anticancer therapies.

TIAM2S Mediates Serotonin Homeostasis and Provokes a Pro-Inflammatory Immune Microenvironment Permissive for Colorectal Tumorigenesis

The short isoform of human TIAM2 has been shown to promote proliferation and invasion in various cancer cells. However, the roles of TIAM2S in immune cells in relation to tumor development have not been investigated. To characterize the effects of TIAM2S, we generated TIAM2S-overexpressing mouse lines and found that aged TIAM2S-transgenic (TIAM2S-TG) developed significantly higher occurrence of lymphocytic infiltration and tumorigenesis in various organs, including colon. In addition, TIAM2S-TG is more sensitized to AOM-induced colon tumor development, suggesting a priming effect toward tumorigenesis. In the light of our recent findings that TIAM2S functions as a novel regulator of cellular serotonin level, we found that serotonin, in addition to Cox2, is a unique inflammation marker presented in the colonic lesion sites in the aged TG animals. Furthermore, our results demonstrated that ectopic TIAM2S altered immunity via the expansion of T lymphocytes; this was especially pronounced in CD8⁺ T cells in combination with CXCL13/BCA-1 pro-inflammatory chemokine in the serum of TIAM2S-TG mice. Consequently, T lymphocytes and B cells were recruited to the lesion sites and stimulated IL-23/IL17A expression to form the tertiary lymphoid organs. Collectively, our research suggests that TIAM2S provokes a pro-inflammatory immune microenvironment permissive to colorectal tumorigenesis through the serotonin-induced immunomodulatory effects.

Decreased Triacylglycerol Content and Elevated Contents of Cell Membrane Lipids in Colorectal Cancer Tissue: A Lipidomic Study

Recent evidence suggests that lipid composition in cancer tissues may undergo multiple alterations. However, no comprehensive analysis of various lipid groups in colorectal cancer (CRC) tissue has been conducted thus far. To address the problem in question, we determined the contents of triacylglycerols (TG), an energetic substrate, various lipids necessary for cell membrane formation, among them phospholipids (phosphatidylcholine, phosphatidylethanolamine), sphingolipids (sphingomyelin) and cholesterol (free, esterified and total), and fatty acids included in complex lipids. ¹H-nuclear magnetic resonance (¹H-NMR) and gas chromatography-mass spectrometry (GC-MS) were used to analyze the lipid composition of colon cancer tissue and normal large intestinal mucosa from 25 patients. Compared with normal tissue, cancer tissues had significantly lower TG content, along with elevated levels of phospholipids, sphingomyelin, and cholesterol. Moreover, the content of oleic acid, the main component of TG, was decreased in cancer tissues, whereas the levels of saturated fatty acids and polyunsaturated fatty acids (PUFAs), which are principal components of polar lipids, were elevated. These lipidome rearrangements were associated with the overexpression of genes associated with fatty acid oxidation, and the synthesis of phospholipids and cholesterol. These findings suggest that reprogramming of lipid metabolism might occur in CRC tissue, with a shift towards increased utilization of TG for energy production and enhanced synthesis of membrane lipids, necessary for the rapid proliferation of cancer cells.

A gas chromatography-mass spectrometry (GC-MS) metabolomic approach in human colorectal cancer (CRC): the emerging role of monosaccharides and amino acids

Background

Colorectal cancer (CRC) has been confirmed to be the third most commonly diagnosed cancer in males and the second in females. We investigated the blood plasma metabolome in CRC patients and in healthy adults to elucidate the role of monosaccharides, amino acids, and their respective metabolic pathways as prognostic factors in patients with CRC.

Methods

Fifteen patients with CRC and nine healthy adults were enrolled in the study and their blood plasma samples analyzed by gas chromatography-mass spectrometry (GC-MS). Univariate Student's t-test, multivariate principal component analysis (PCA) and partial least square-discriminant analysis (PLS-DA) were conducted on MetaboAnalyst 4.0. The analysis of metabolic profiles was carried out by the web-based extension Metabolite Sets Enrichment Analysis (MSEA).

Results

Overall, 125 metabolites were identified in plasma samples by GC-MS. In CRC patient samples, nine metabolites, including D-mannose and fructose, were significantly more abundant than in controls; conversely, eleven amino derivatives were less abundant, including methionine, valine, lysine, and proline. Methionine was significantly less abundant in died patients compared with survivors. The most significantly altered metabolic pathways in CRC patients are those involving monosaccharides (primarily the catabolic pathway of fructose and D-mannose), and amino acids (primarily methionine, valine, leucine, and isoleucine).

Conclusions

The abundance of D-mannose in CRC patient samples contributes to inhibiting the growth of cancer cells, while the abundance of fructose may be consistent either with low consumption of fructose by aerobic glycolysis within cancer cells or with a high bioavailability of fructose from diet. The reduction in methionine concentration may be related to increased activity of the threonine and methionine catabolic pathways, confirmed by high levels of α-hydroxybutyrate.

Metabonomic Variation of Exopolysaccharide from Rhizopus nigricans on AOM/DSS-Induced Colorectal Cancer in Mice

BACKGROUND

Colorectal cancer (CRC), which occurs at the junction of the rectum and sigmoid colon, is a common malignancy associated with poor prognosis and high mortality worldwide. The exopolysaccharide (EPS1-1), isolated from the fermentation broth of Rhizopus nigricans (R. nigricans), has been reported to possess anti-CRC properties. However, the metabolic alterations caused by azoxymethane (AOM) and dextran sulfate sodium (DSS) are still unknown.

METHODS

In the present study, a mice colon cancer model was established by treatment with AOM/DSS. LC-MS/MS-based metabolomics studies were performed to analyze metabolic alterations at the tissue level. Partial least squares discriminant analysis (PLS-DA) was used to identify differentially expressed metabolites.

RESULTS

Nineteen distinct metabolites were identified that were associated with disruptions in the following pathways: biosynthesis of unsaturated fatty acids, pyrimidine metabolism, phenylalanine metabolism, fatty acid metabolism, folate biosynthesis, and inositol phosphate metabolism. Furthermore, six significantly altered metabolites were involved in these six pathways. Compared with the Model group, the expression of cytosine, deoxyuridine, 20-hydroxy-leukotriene E4, and L-homocysteic acid was lower, whereas that of 2-dehydro-3-deoxy-6-phospho-D-gluconic acid and hematoporphyrin was higher in the EPS1-1 group.

CONCLUSION

The results of multivariate statistical analysis demonstrate a promising application of the above metabolites by EPS1-1 in CRC therapy. Deeper understanding of the related mechanism warrants further investigation.