Altered microbiota of rectal mucosa in rectal cancer patients

Abstract

BACKGROUND

With advances in sequencing techniques, microbiota dysbiosis and pathogenic microbes that accelerate colorectal cancer progression have been identified and widely reported. However, few studies have focused on the microbiota taxa of rectal mucus in rectal cancer (RC) patients. Here, we analyzed the composition and characteristics of the rectal mucosa microbiota of RC patients from Wenzhou city, China, and compared the results with those of healthy controls.

AIM

To explore the changes in the characteristics of the rectal mucosal flora associated with RC, and identify biomarkers of microbe taxa for RC.

METHODS

Rectal mucosa samples from a Chinese cohort of 72 recently diagnosed RC patients and 71 healthy controls were obtained. A validation cohort, which included 22 RC patients and 60 healthy controls, was also established. Changes in the rectal mucosal flora were observed by cultivation, 16S ribosomal DNA gene sequencing analysis and quantitative polymerase chain reaction analysis.

RESULTS

The 16S ribosomal DNA results demonstrated that RC patients presented increased bacterial community richness and alpha diversity as well as an altered rectal mucosal microbiota, with depletion of Proteobacteria and Thermi and enrichment of Bacteroidetes and Fusobacteria in cancerous mucosal tissues (CM) and enrichment of Firmicutes and Cyanobacteria in adjacent noncancerous mucosal tissues (AM). The culture results showed that the mean loads of Escherichia coli, Bifidobacterium, Enterococcus, and Lactobacillus were significantly reduced in RC patients. The ratios of Prevotella to Ruminococcus [areas under the receiver operating curve: 0.795 in AM vs normal control mucosa (NM), 0.77 in CM vs NM] and of Prevotella stercorea to Propionibacterium acnes (areas under the receiver operating curve: 0.808 in AM vs NM, 0.843 in CM vs NM) exhibited excellent abilities to differentiate between healthy controls and RC patients.

CONCLUSION

RC patients have an altered rectal mucosal microbiota, and the ratio of Prevotella to Ruminococcus or the ratio of Prevotella stercorea to Propionibacterium acnes may serve as a marker for RC diagnosis.

Key Words: Rectal cancer; Mucosal-associated microbiota; Gut microbiota; Genomics; Predictive biomarkers

Core Tip: In this study, we focused on the rectal mucosal microbiota, which is associated with the occurrence and development of rectal cancer (RC). Although the gut microbiota is commonly studied in patients with colorectal cancer, but few studies have focused on RC, especially the microbiota of the rectal mucus. Our research revealed that RC patients had an altered rectal mucosal microbiota; characterized by enrichment of Bacteroidetes, Fusobacteria and Firmicutes; and depletion of Proteobacteria and Thermi. The Prevotella/Ruminococcus ratio and the Prevotella stercorea/Propionibacterium acnes in the rectal mucosal microbiota may serve as a marker for RC diagnosis.

INTRODUCTION

Colorectal cancer (CRC) ranks third in terms of incidence and third in terms of mortality worldwide, and rectal cancer (RC) is responsible for more than one-third of CRC-related deaths[1]. The incidence of RC has increased in recent years, especially among young adults[2-4]. In China, CRC is also characterized by high morbidity and mortality rates, especially in high-income provinces[5]. The factors associated with the development of CRC include inflammatory bowel disease, smoking, red and processed meat consumption, excessive alcohol consumption and diabetes[6]. All of these factors are closely related to the gut microbiota. Dysbiosis, or alteration of the microbiota, has been shown to be associated with the occurrence and development of CRC[7,8]. Several carcinogenic bacteria, such as Fusobacterium nucleatum and enterotoxigenic Bacteroides fragilis, have been verified to be present in CRC[9-12]. Peptostreptococcus anaerobius, which is enriched in CRC patients, has been reported to promote colorectal carcinogenesis[13,14]. In contrast, beneficial genera, including Bifidobacterium and Lactobacillus, have been reported to be depleted in CRC patients[15].

The mucosal microbiota is closely related to the functional mucosal barrier and the balance of the mucosal immune system. Imbalances in the mucosal microbiota have been described in human distal CRC[16]. The mucosal microbiota is more stable than the intestinal microflora, as the composition of the fecal microbiota is affected by many factors, such as diet and drugs. Furthermore, the luminal and mucosal microbiota differ[17,18], and the major components of the luminal and mucosal microbiota have distinct functions, which calls into question the importance of the local microbiota[19]. Considering their accuracy and reliability, mucosal samples are more accurate for analyses of the microbiota than are fecal samples[18,20]. To date, few studies have investigated the relationship between the mucosal microbiota and RC. Hence, in the present study, we analyzed the rectal mucosal microbiota of RC patients and healthy controls in Wenzhou, China, to reveal the changes in the characteristics of the rectal mucosal flora associated with RC.

MATERIALS AND METHODS

Participants and sample collection

The RC mucosa (CM), adjacent noncancerous mucosa (AM) and normal control mucosa (NM) were intraoperatively harvested in triplicate intraoperatively from a cohort of patients in Wenzhou, China, including 72 CM and AM (age: 64.38 ± 11.41 years, 52 males and 20 females) and 71 NM (age: 49.90 ± 11.26 years, 47 males and 24 females) (Table 1). A validation cohort, which included 22 RC patients and 60 healthy controls, was included in the study. One of the samples was placed in the transport medium. None of these patients had taken antibiotics/probiotics within the last 2 months or used nonsteroidal anti-inflammatory drugs regularly. Individuals who had complications such as acute/chronic intestinal obstruction, chronic bowel disorders, and other foci of infections or food allergies/dietary restrictions were excluded from the study. Additional exclusion criteria for CRC patients included chemotherapy or radiation treatments before surgery. Any patients or healthy individuals with incomplete data will not be included in the study. Despite rigorous screening and selection criteria, it is important to acknowledge that unmeasured or undetected exposure risks including dietary habits or undiagnosed inflammatory conditions, may still exist and could influence the study outcomes. While every effort was made to minimize confounding through careful participant selection and exclusion criteria, the possibility of residual confounding due to these unmeasured exposures cannot be entirely ruled out. The samples were transported to the laboratory within 30 min after collection by the study participants. All the study protocols were reviewed and approved by The First Affiliated Hospital of Wenzhou Medical University (2020-127), and informed consent was provided by each patient following the protocol approved by the Institutional Review Board.

Table 1 Clinical characteristics of rectal cancer and healthy subjects, mean ± SD or n (%).

	RC, n = 72	Control, n = 71	P value
Age, year	64.38 ± 11.34	50.10 ± 11.44	< 0.05
Male	52 (72.2)	47 (66.2)	0.435
Female	20 (27.8)	24 (33.8)
BMI, kg/m2	22.41 ± 3.10	22.95 ± 2.24	0.230
TNM stage
I	21 (29.2)
II	15 (20.8)
III	33 (45.8)
IV	3 (4.2)

RC: Rectal cancer; BMI: Body mass index; TNM: Tumor-node-metastasis.

Cultivation of bacteria associated with the rectal mucosa

TPY medium (Hopebio Co., Ltd., Qingdao, China), MRS medium (Hopebio Co., Ltd., Qingdao, China), eosin and methylene blue (EMB) medium (Hopebio Co., Ltd., Qingdao, China) and Pfizer Enterococcus Selective medium (Hopebio Co., Ltd., Qingdao, China) were used to detect Bifidobacterium, Lactobacillus, Escherichia coli and Enterococcus, respectively. The media were preincubated in a 37 °C anaerobic chamber for at least 24 hours. The samples were weighed and milled, and suitable dilutions were generated in the corresponding TPY medium. A 50 μL sample with an appropriate dilution was spread on a wide range of selective plates in duplicate. Colonies were counted after 48 h of culture at 37 °C in aerobic (EMB) and anaerobic (other agars) environments, and colony counts were normalized to the mean colony count. The results are presented as colony-forming units/g (colony number × dilution)/ weight of sample in grams. The anaerobic environment was provided by AnaeroPack-Rectangular Jar (Mitsubishi Gas Chemical, Japan) and AnaeroPack-Anaero (Mitsubishi Gas Chemical, Japan).

DNA extraction, 16S ribosomal DNA sequencing and analysis

DNA was extracted via the MicroElute Genomic DNA Kit D3096 (Omega Bio-Tek, United States) per the manufacturer’s instructions. 16S ribosomal DNA (16S rDNA) gene amplification and library construction were performed according to Illumina recommendations[21]. The V4 hypervariable region of the 16S rDNA gene was amplified from genomic DNA with the primers 515-F (5-GTGCCAGCMGCCGCGGTAA-3) and 806-R (5-GGACTACHVGGGTWTCTAAT-3)[22]. The amplicons were normalized, pooled and sequenced on an Illumina HiSeq 4000 sequencer (2 × 150 bp paired end). We sequenced 288 samples, and a total of 34850344 read pairs were generated (mean: 121008 read pairs per sample). Sequence read processing was performed via QIIME2[23] and included additional quality trimming and demultiplexing[24]. Operational taxonomic unit picking via Vsearch v1.11.1 included dereplication, clustering, and detection of chimeras. Taxonomic assignment of individual datasets via SILVA128. Alpha diversity, including the ACE, Chao, Shannon and Simpson indices, was calculated with QIIME2. Beta diversity was performed with QIIME2 with a matrix of (weighted and unweighted) UniFrac distances. QLEfSe uses linear discriminant analysis to estimate the size of the effect of each component (species) abundance on the differences and to identify communities or species that had significant differences in the classification of the samples. The Kruskal test from R 4.1.2 was used to identify the species that were significantly different between the different groups.

Quantitative polymerase chain reaction analysis.

Real-time polymerase chain reaction (PCR) amplification and detection were performed via an ABI 7300 Real-Time PCR System (Applied Biosystems), and target gene expression was analyzed via the 2^–ΔΔCt method. We used Power SYBR Green PCR Master Mix (Applied Biosystems), which included 0.2 μM 16S rDNA primers 515-F (5’- GTGCCAGCMGCCGCGGTAA-3’) and 806-R (5’-GGACTACHVGGGTWTCTAAT-3’), the Prevotella stercorea (P. stercorea) primers F (5’-TTCACAGCAGGCATCTAACGTG-3’) and R (5’-TGGCTGGTTCAGACTCTCGT-3’), and Propionibacterium acnes (P. acnes) primers F (5’-CGGATCGCTGTGTTGTCCTA-3’) and R (5’-CCCCCGAGTAACAGGGTTG-3’). The cycling conditions included an initial incubation at 50 °C for 2 minutes; denaturation at 95 °C for 10 minutes; 40 cycles of 95 °C for 15 seconds and 56 °C for 1 minute; and a dissociation curve step of 95 °C for 15 seconds, 60 °C for 30 seconds, and 95 °C for 15 seconds.

RESULTS

Quantification of bacteria in rectal mucosal samples

The quantification results revealed that both the total number of bacteria in the CM and AM of RC patients was lower than that in the NM of healthy controls. In RC patients, the number of bacteria cultured from CM was significantly greater than that cultured from AM. The results are expressed as the mean ± SD (log10 colony-forming units/g): (1) Escherichia coli 9.10 ± 0.67 (NM), 5.86 ± 0.71 (AM), 6.39 ± 0.89 (CM) (P < 0.001) (Figure 1A); (2) Enterococcus 8.26 ± 0.50 (NM), 5.65 ± 0.83 (AM), 6.25 ± 0.86 (CM) (P < 0.05) (Figure 1B); (3) Bifidobacterium 8.24 ± 0.70 (NM), 5.98 ± 0.70 (AM), 6.63 ± 0.94 (CM) (P < 0.001) (Figure 1C); and (4) Lactobacillus 8.28 ± 0.56 (NM), 5.92 ± 0.88 (AM), 6.42 ± 0.82 (CM) (P < 0.001) (Figure 1D).

Figure 1 Culture results of mucosal samples between groups. A: Escherichia coli; B: Enterococcus; C: Bifidobacterium; D: Lactobacillus. The data are presented as the mean ± SD and were analyzed via the Kruskal-Wallis test. ^aP < 0.05, ^cP < 0.001. AM: Adjacent noncancerous mucosa; CM: Rectal cancer mucosa; NM: Normal control mucosa; CFU: Colony-forming unit.

Mucosal microbiota of RC patients significantly differs from that of normal controls

The rectal mucosal microbiota was analyzed via 16S rDNA gene sequencing in a cohort comprising 72 RC patients and 71 healthy controls. The characteristics of the rectal mucosal microbiota were analyzed via QIIME and R software. The results revealed a significant difference in the composition of the rectal mucosal microbiota between RC patients and healthy controls (NM), as well as within RC patients (CM vs AM, P < 0.05). The data are presented as the mean ± SD (Table 2). To assess differences in the numbers of different species across the three groups, species richness was calculated based on operational taxonomic unit richness. The results demonstrated that both AM and CM resulted in significantly higher species detection rates at the analyzed levels than did NM (Figure 2). The α diversity of the mucosal bacterial community was assessed via the Shannon and Chao indices. Compared with healthy controls, RC patients presented increased richness and α diversity. Furthermore, CM presented greater richness but lower diversity than did AM (Figure 3A-D). In addition to the α diversity indices, the β diversity indices revealed distinct differences in bacterial compositions among the three groups, as evidenced by the unweighted UniFrac PCoA results (Figure 3E).

Figure 2 Numbers of each population at each level. A: Phylum; B: Class; C: Order; D: Family; E: Genus; F: Species. The data were analyzed via the Kruskal-Wallis test. ^aP < 0.05, ^bP < 0.01. AM: Adjacent noncancerous mucosa; CM: Rectal cancer mucosa; NM: Normal control mucosa.

Figure 3 Diversity indices between groups. A: Ace; B: Chao; C: Simpson; D: Shannon; E: Principal coordinates analysis. ^aP < 0.05, ^bP < 0.01. AM: Adjacent noncancerous mucosa; CM: Rectal cancer mucosa; NM: Normal control mucosa; NS: Not significant.

Table 2 Number of microbial communities at different level, mean ± SD.

Group	Phylum	Class	Order	Family	Genus	Species
AM	18.9 ± 3.0	37.7 ± 9.5	69.3 ± 21.8	123.1 ± 37.0	212.3 ± 58.5	2316.9 ± 587.4
CM	17.8 ± 2.2	33.0 ± 5.3	57.2 ± 13.2	102.8 ± 21.8	194.3 ± 44.8	2725.6 ± 840.2
NM	13.0 ± 2.5	23.6 ± 4.7	39.4 ± 7.5	74.9 ± 12.3	131.7 ± 21.7	1039.9 ± 243.0

AM: Adjacent noncancerous mucosa; CM: Rectal cancer mucosa; NM: Normal control mucosa.

Composition of the mucosal microbiota at different taxonomic levels

The major phyla detected throughout the study were Bacteroidetes, Firmicutes and Proteobacteria (Figure 4A). The linear discriminative analysis effect size (LEfSe) was applied. The discovery of bacterial biomarkers was conducted at all the analyzed taxonomic levels. At the phylum level, while Proteobacteria, Actinobacteria, Verrucomicrobia and Thermi were depleted in RC patients, the CM enriched Bacteroidetes and Fusobacteria, and the AM enriched Firmicutes, Cyanobacteria, Tenericutes, Lentisphaerae and Synergistetes (Figure 4B). At the class level, with decreasing Gammaproteobacteria abundance, the abundances of Actinobacteria, Verrucomicrobiac, Bctaprotcobactcria, Dcinococci and Alphaproteobacteria increased in the RC group, whereas the abundances of Bacteroidia, Clostridia, Fusobacteriia, Bacilli, 4C0d_2, Mollicutes, Lentisphaeria and Synergistia increased in the RC group (Figure 4C). At the order level, the relative abundance of Pseudomonadales decreased under CM and AM, whereas the relative abundances of Bacteroidales and Clostridiales increased under CM and AM (Figure 4D), respectively. At the family level, Bacteroidaceae, Prevotellaceae, Ruminococcaceae, S24_7, Fusobacteriaceae, Gemellaceae, Peptostreptococcaceae and Bamesiellaceae were significantly enriched in the RC group (Figure 4E), whereas Lachnospiraceae, Pseudomonadaceae, Enterobacteriaceae, Bifidobacteriaceae and Verrucomicrobiaceae were enriched in the NM group. At the genus level, Pseudomonas, Ruminococcus, Bifidobacterium, Proteus, Veillonella and Akkermansia increased in the NM group, whereas Bacteroides, Prevotella, Fusobacterium, Gemella, Faecalibacterium, Peptostreptococcus, Parvimonas and Coprococcus were enriched in the RC group (Figure 4F). As in the previous quantification results, Bifidobacterium, Enterococcus and Lactobacillus presented high relative abundances in the NM samples (Figure 4G-I).

Figure 4 LEfSe analysis across different taxonomic levels. A: Bacterial composition in each group; B: Phylum; C: Class; D: Order; E: Family; F: Genus; G: Relative abundance of Bifidobacterium; H: Relative abundance of Enterococcus; I: Relative abundance of Lactobacillus. ^aP < 0.05, ^bP < 0.01. AM: Adjacent noncancerous mucosa; CM: Rectal cancer mucosa; NM: Normal control mucosa; NS: Not significant.

Potential biomarkers for RC

To identify reliable indicators for distinguishing RC patients from healthy individuals, analyses were conducted on bacteria that were significantly enriched and depleted in RC patients at the genus and species levels. The ratio of Prevotella to Ruminococcus and the ratio of P. stercorea to P. acnes were calculated with data from our cohort and with validated datasets obtained from a validation cohort that included 22 RC patients and 60 healthy controls. The findings revealed that RC patients presented significantly greater ratios of Prevotella to Ruminococcus and P. stercorea to P. acnes than healthy controls did, regardless of sex (P < 0.01) (Figure 5A-F). For both sexes combined, the ratio of Prevotella to Ruminococcus yielded areas under the receiver operating curve (AUROC) of 0.795 (AM-NM, P < 0.01) (Figure 5G) and 0.77 (CM-NM, P < 0.01) (Figure 5J), respectively. In contrast, the ratio of P. stercorea to P. acnes was superior in distinguishing RC patients from healthy controls, with AUROC values of 0.808 (AM-NM, P < 0.01) (Figure 5G) and 0.843 (CM-NM, P < 0.01) (Figure 5J), respectively. When analyzed by sex, the Prevotella to Ruminococcus ratio in females resulted in AUROC values of 0.902 (AM-NM, P < 0.001) (Figure 5H) and 0.877 (CM-NM, P < 0.01) (Figure 5K), whereas in males, the values were 0.750 (AM-NM, P< 0.01) (Figure 5I) and 0.723 (CM-NM, P < 0.01) (Figure 5L). In the validation cohort, RC patients also presented significantly greater ratios of Prevotella to Ruminococcus (Supplementary Figure 1A), and the ratios presented AUROC values of 0.856 (AM-NM, P < 0.01) (Supplementary Figure 1B) and 0.754 (CM-NM, P < 0.01) (Supplementary Figure 1C). The ratio of P. stercorea to P. acnes yielded AUROC values of 0.814 (AM-NM, P < 0.01) (Figure 5H) and 0.868 (CM-NM, P < 0.01) (Figure 5K) in female subjects, whereas it was 0.798 (AM-NM, P < 0.01) (Figure 5I) and 0.823 (CM-NM, P < 0.01) (Figure 5L) in male subjects. When patients were stratified based on tumor stage, RC patients presented significantly greater ratios of Prevotella to Ruminococcus and P. stercorea to P. acnes than healthy controls, regardless of tumor stage (Supplementary Figure 2A-D). To assess the clinical applicability of the P. stercorea to P. acnes ratio without sequencing, we performed quantitative PCR assays using specific primers targeting these bacteria on rectal mucosal samples from a cohort including 24 RC patients and 24 healthy controls. Consistent with the sequencing data, the ratios obtained from the quantitative PCR assays were significantly greater in RC patients than in the controls (CM-NM, P < 0.001) (Supplementary Figure 1D).

Figure 5 Differences in ratios between rectal cancer patients and healthy controls. A: Prevotella/Ruminococcus ratio in both sexes; B: Prevotella/Ruminococcus ratio in females; C: Prevotella/Ruminococcus ratio in males; D: Prevotella stercorea (P. stercorea)/Propionibacterium acnes (P. acnes) ratio in both sexes; E: P. stercorea/P. acnes ratio in females; F: P. stercorea/P. acnes ratio in males; G: Receiver operating curve (ROC) curves of two ratios in both sexes between the adjacent noncancerous mucosa (AM) and normal control mucosa (NM); H: ROC curves of two ratios in females between the AM and NM; I: ROC curves of two ratios in males between the AM and NM; J: ROC curves of two ratios in both sexes between the rectal cancer mucosa (CM) and NM; K: ROC curves of two ratios in females between the CM and NM; L: ROC curves of two ratios in males between the CM and NM. ^bP < 0.01. AM: Adjacent noncancerous mucosa; CM: Rectal cancer mucosa; NM: Normal control mucosa; NS: Not significant.

DISCUSSION

The human gastrointestinal tract harbors a vast community of approximately 10¹⁴ bacteria, and there is increasing appreciation that the trillions of microbes that live in our intestines play vital roles in health and disease, while a small number of bacteria, such as AKK, may attach to or colonize the intestinal mucosal membrane, forming the mucosal microbiota[25]. One hypothesis is that CRC can be initiated by some bacteria called “drivers” and promoted by others called “passengers”[26]. The driver bacteria are presumed to adhere to the mucosa and perform a tumorigenic function[13], such as promoting tumor formation, and passengers, including those who promote the growth of pro-tumor bacteria or opportunistic bacteria, subsequently replace the dominant driver. In addition to the microbes themselves, microbiome-derived oncometabolites are closely related to CRC. For example, formate is a metabolite produced by the CRC-associated bacterium Fusobacterium nucleatum that promotes CRC development[27], whereas SCFAs derived from probiotics can inhibit intestinal tumor development[28]. It seems likely that there is a certain correlation between the local microenvironment of the tumor and the microbiota. In this study, we found that the mucosal microbiome of RC patients had increased richness and diversity, which is consistent with previously published findings[29,30] but different from the findings of several previous studies[31,32]. Such inconsistencies might result from heterogeneous samples; the tumor microenvironment may provide a rich assortment of amino acids, sugars, phospholipids, and membrane proteins as tumor cells degrade the extracellular matrix and cannibalize the surrounding necrotic intestinal tissue to fuel their metabolism[33], whereas the microbiota is better able to multiply in the mucus layer.

Fecal samples can be easily and noninvasively obtained, but the sampling of mucosa-associated flora via endoscopic biopsy of intestinal tissues is an invasive procedure that is more difficult to perform than the collection of fecal samples, especially from healthy donors. Therefore, most studies addressing the relationship between the microbiota and CRC via fecal samples[7,34,35], such as Mira-Pascual et al[20], have pointed to inconsistencies between fecal and tumor-associated microbiota in CRC patients; to a lesser extent, few studies have investigated tumoral mucosal tissues and paired normal mucosal tissues[16,36,37]. Lin et al’s findings[17] suggest that in healthy individuals, the mucosa-associated microbiome and fecal-associated microbiome are highly differentiated, which might be attributed to their environments supporting localized niche groups of microbes. Bacteria are not uniformly distributed throughout the lumen, and differences in the local microenvironment lead to changes in both the identity and abundance of taxa[38,39]. In addition, developmental and biological differences in the proximal and distal colon may reflect different susceptibilities to neoplastic transformation[40]. Additionally, microbial compositions differ between proximal and distal cancerous colonic mucosa, with higher abundances of Prevotella, Pyramido-bacterium, Selenomonas and Peptostreptoccus in proximal tumors, whereas the relative abundances of Fusobacterium, Escherichia-Shigella and Leptotrichia are increased in distal colorectal tumors[41]. Notably, our findings showed that RC patients had a lower abundance of Akkermansia muciniphila (A. muciniphila), which is consistent with the findings of Wang et al[42], this is likely an epiphenomenon for poor outcomes, as A. muciniphila can suppress colorectal tumorigenesis[43]; however, excessively thick mucus at the tumor site may benefit A. muciniphila reproduction. In healthy subjects, the dominant phyla in our research were Firmicutes, Bacteroidetes, Proteobacteria and Fusobacteria, whereas in the study by Ringel et al[19], the dominant phyla in the fecal and colonic mucosa were Firmicutes, Bacteroidetes, Actinobacteria and Proteobacteria. This finding provides further details of the differences between the fecal bacterial flora and the mucosal flora, even the mucosal microbiota of different locations. As RC development is strongly influenced by multiple elements, red and processed meat consumption increases the risk of RC, which may also be associated with a decrease in Bifidobacterium abundance[44], which is consistent with our findings. In fact, many of these commensal bacteria use glycan containing mucin molecules as a primary source of energy. To achieve a precise analysis and understand the importance of spatial heterogeneity, we analyzed only the microbiota of the rectal mucosa, excluding that of the colon and cecum.

We found that the Prevotella/Ruminococcus ratio and P. stercorea/P. acnes ratio is relatively high in RC patients, suggesting the potential value of these two ratios for use as biomarkers for the mucosa-based diagnosis of RC. Notably, we found that the ratios in females had a greater ability to diagnose RC than did these ratios in both sexes or males. Additionally, this finding was well validated in an independent cohort. As genetics and dietary habits vary among different populations, which have also been associated with the shaping of or changes in the gut microbiome[45], whether the bacterial markers verified in this study could be applied in other populations needs further investigation. In conclusion, the composition of the mucosa-associated microbiota significantly differed between RC patients and healthy controls. The ratios of Prevotella/Ruminococcus and P. stercorea/P. acnes showed certain abilities to diagnose RC, especially in females. Several fecal microbiota studies from China have indicated that some Prevotella spp. are associated with CRC[46,47], which is similar to our findings, and the mucosa-based detection of bacterial markers complements fecal-based diagnostic approaches, which can serve as a potential diagnostic method for patients with RC and provide a broader clinical perspective.

CONCLUSION

In summary, RC patients had an altered rectal mucosal microbiota, characterized by enrichment of Bacteroidetes, Fusobacteria and Firmicutes and depletion of Proteobacteria and Thermi. The ratio of Prevotella to Ruminococcus or the ratio of P. stercorea to P. acnes from the rectal mucosal microbiota may serve as markers for RC diagnosis.

ACKNOWLEDGEMENTS

We would like to thank all the medical staff of the Department of Colorectal Surgery and Department of Pathology in the First Affiliated Hospital of Wenzhou Medical University for providing convenient conditions for implementing this study.