Third-generation PacBio sequencing to explore gut bacteria and gender in colorectal cancer.

BACKGROUND: Gut bacteria have an important influence on colorectal cancer (CRC). The differences of gut bacteria between genders have been the hot spots. OBJECTIVE: To analyze the relationship between gut bacteria and gender differences in patients with CRC. METHODS: A total of 212 patients with CRC and 212 healthy volunteers were recruited. The subjects' fecal samples were obtained, and the fecal microorganisms were analyzed by the third-generation sequencing PacBio. The composition of gut bacteria was analyzed. Linear discriminant analysis Effect Size (LEfSe) was used to analyze the differences in gut bacteria. Pearson coefficient was used to calculate the correlation between differential bacteria. CRC risk prediction models were used to rank the importance of effective differential bacteria. RESULTS: Escherichia flexneri and Phocaeicola vulgatus were the most frequent bacteria in both male and female CRC patients. Bacteroides, Verrucomicrobia and Akkermansiaceae were highly enriched in male CRC group, while Bacteroidetes, Phocaeicola and Tissierellales were highly enriched in female CRC group. Peptostreptococcus anaerobius and Phocaeicola vulgatus were important CRC related bacteria in males and females, respectively. Peptostreptococcus anaerobius was the most important characteristic bacterium of males (AUC = 0.951), and the sensitivity and specificity of the discovery set were 78.74 % and 93.98 %, respectively. Blautia stercoris was the most important characteristic bacterium of females (AUC = 0.966), and the sensitivity and specificity of the discovery set were 90.63 % and 90.63 %, respectively. CONCLUSION: Gut bacteria varied in different genders. Therefore, gender should be considered when gut bacteria are applied in the diagnose and prevention of CRC.

Advances in single-cell sequencing technology in microbiome research.

With the rapid development of histological techniques and the widespread application of single-cell sequencing in eukaryotes, researchers desire to explore individual microbial genotypes and functional expression, which deepens our understanding of microorganisms. In this review, the history of the development of microbial detection technologies was revealed and the difficulties in the application of single-cell sequencing in microorganisms were dissected as well. Moreover, the characteristics of the currently emerging microbial single-cell sequencing (Microbe-seq) technology were summarized, and the prospects of the application of Microbe-seq in microorganisms were distilled based on the current development status. Despite its mature development, the Microbe-seq technology was still in the optimization stage. A retrospective study was conducted, aiming to promote the widespread application of single-cell sequencing in microorganisms and facilitate further improvement in the technology.

Transcriptional profile and immune infiltration in colorectal cancer reveal the significance of inducible T-cell costimulator as a crucial immune checkpoint molecule.

BACKGROUND: Emergence of novel immuno-therapeutics has shown promising improvement in the clinical outcome of colorectal cancer (CRC). OBJECTIVE: To identify robust immune checkpoints based on expression and immune infiltration profiles of clinical CRC samples. METHODS: One dataset from The Cancer Genome Atlas database and two from Gene Expression Omnibus were independently employed for the analysis. Genes associated with overall survival were identified, and distribution of each immune checkpoint with respect to different clinical features was determined to explore key immune checkpoints. Multiple staining methods were used to verify the correlation between key immune checkpoint ICOS and clinical pathological features. Differentially expressed mRNA and long non-coding RNA (lncRNA) were then detected for gene set enrichment analysis and gene set variation analysis to investigate the differentially enriched biological processes between low- and high-expression groups. Significant immune-related mRNAs and lncRNA were subjected to competing endogenous RNA (ceRNA) network analysis. Correlation of inducible T-cell costimulator (ICOS) and top 10 genes in ceRNA network were further considered for validation. RESULTS: ICOS was identified from 14 immune checkpoints as the most highly correlated gene with survival and clinical features in CRC. The expression of ICOS protein in the poorly differentiated group was lower than that in the moderately differentiated group, and the expression in different pathological stages was significant. In addition, the expressions of ICOS were negatively correlated with Ki67. A conspicuous number of immune-related pathways were enriched in differentially expressed genes in the ICOS high- and low-expression groups. Integration with immune infiltration data revealed a multitude of differentially expressed immune-related genes enriched for ceRNA network. Furthermore, expression of top 10 genes investigated from ceRNA network showed high correlation with ICOS. CONCLUSION: ICOS might serve as a robust immune checkpoint for prognosis with several genes being potential targets of ICOS-directed immunotherapy in CRC.

CFViSA: A comprehensive and free platform for visualization and statistics in omics-data.

INTRODUCTION: The rapid growth of omics technologies has led to the use of bioinformatics as a powerful tool for unravelling scientific puzzles. However, the obstacles of bioinformatics are compounded by the complexity of data processing and the distinct nature of omics data types, particularly in terms of visualization and statistics. OBJECTIVES: We developed a comprehensive and free platform, CFViSA, to facilitate effortless visualization and statistical analysis of omics data by the scientific community. METHODS: CFViSA was constructed using the Scala programming language and utilizes the AKKA toolkit for the web server and MySQL for the database server. The visualization and statistical analysis were performed with the R program. RESULTS: CFViSA integrates two omics data analysis pipelines (microbiome and transcriptome analysis) and an extensive array of 79 analysis tools spanning simple sequence processing, visualization, and statistics available for various omics data, including microbiome and transcriptome data. CFViSA starts from an analysis interface, paralleling a demonstration full course to help users understand operating principles and scientifically set the analysis parameters. Once analysis is conducted, users can enter the task history interface for figure adjustments, and then a complete series of results, including statistics, feature tables and figures. All the graphic layouts were printed with necessary statistics and a traceback function recording the options for analysis and visualization; these statistics were excluded from the five competing methods. CONCLUSION: CFViSA is a user-friendly bioinformatics cloud platform with detailed guidelines for integrating functions in multi-omics analysis with real-time visualization adjustment and complete series of results provision. CFViSA is available at http://www.cloud.biomicroclass.com/en/CFViSA/.

STAB2: an updated spatio-temporal cell atlas of the human and mouse brain.

The brain is constituted of heterogeneous types of neuronal and non-neuronal cells, which are organized into distinct anatomical regions, and show precise regulation of gene expression during development, aging and function. In the current database release, STAB2 provides a systematic cellular map of the human and mouse brain by integrating recently published large-scale single-cell and single-nucleus RNA-sequencing datasets from diverse regions and across lifespan. We applied a hierarchical strategy of unsupervised clustering on the integrated single-cell transcriptomic datasets to precisely annotate the cell types and subtypes in the human and mouse brain. Currently, STAB2 includes 71 and 61 different cell subtypes defined in the human and mouse brain, respectively. It covers 63 subregions and 15 developmental stages of human brain, and 38 subregions and 30 developmental stages of mouse brain, generating a comprehensive atlas for exploring spatiotemporal transcriptomic dynamics in the mammalian brain. We also augmented web interfaces for querying and visualizing the gene expression in specific cell types. STAB2 is freely available at https://mai.fudan.edu.cn/stab2.

Classification of Colorectal Cancer Subtypes Based on Endoplasmic Reticulum Stress.

INTRODUCTION: Endoplasmic reticulum stress (ERS) is associated with the occurrence and development of colorectal cancer (CRC). METHODS: One thousand nine CRC samples and 3 ERS gene sets from GEO database were used to screen and validate genes related to stage and prognosis of CRC. Twenty thousand five hundred thirty samples from the TCGA database validated the ERS genes related to prognosis. PPI network construction and coexpression analysis were used to investigate the correlation of genes. ConsensusClusterPlus analysis was used to classify CRC subtypes. Cox regression and the LASSO algorithm were used to screen ERS genes related to prognosis. HE staining, immunohistochemical staining, and RT-qPCR of 50 owner-central samples were used to verify the genes. The ERscore model was constructed based on the ERS genes related to prognosis. The nomogram model was used to verify that different subtypes of CRC patients have different prognosis. RESULTS: Fifty ERS differentially expressed genes related to CRC stage and 8 ERS model genes related to prognosis were screened. Three subtypes of CRC were classified based on the former 50 genes. The clinical characteristics were significantly different among the subtypes. The ERscore model was constructed based on the latter 8 genes, and its accuracy was verified by clinical samples. Finally, the nomogram was constructed based on ERscore, age, and CRC stage, and the accuracy of the nomogram prediction was verified. CONCLUSION: ERS-related genes can be used as classification criteria for CRC, and the related clinical characteristics of different CRC subtypes are different.

Application of roadside air purifiers in urban street canyons: A pilot-scale study in Hong Kong.

The implementation of roadside air purifiers has emerged as an effective active control measure to alleviate air pollution in urban street canyons. However, technical questions raised under real conditions remain challenging. In this study, we conducted a pilot-scale investigation involving seven units of self-designed roadside air purifiers in an urban street canyon in Hong Kong. The air cleaning effects were quantified with an air quality sensor network after rigorous quality control. The removal efficiencies of Nitrogen dioxide (NO2), Fine suspended particulates (PM2.5), Carbon monoxide (CO), and Nitric oxide (NO) were determined by comparing with simultaneously measured ambient concentrations, with hourly average efficiencies of 14.0 %-16.9 %, 3.5-10.0 %, 11.9 %-18.7 %, and 19.2 %-44.9 %, respectively. Generally, the purification effects presented variations depending on the ambient pollutants' levels. Higher ambient concentrations of NO2, PM2.5, CO correlated with increased purification effects, while NO presented the opposite trend. The influence of interval distance combined with spatial distribution indicated the operation of purifiers will induce local NO2 attenuation even at an interval distance of four meters. Statistical analysis delivered evidence the air cleaning ability exhibited optimal performance when relative humidity level is ranged from 70 % to 90 %, aligning with the prevailing conditions in Hong Kong. Additionally, improved purification effects were observed at the downwind direction, and their performance was enhanced when the wind speed exceeded 2.5 m/s. Moreover, we estimated the operational lifetime of the air purifiers to be approximately 130 days, offering crucial information regarding the filter replacement cycle. This work serves as a pioneering case study, showcasing the feasibility and deployment considerations of roadside air purifiers in effectively controlling air pollution in urban environments.

Advances in immunotyping of colorectal cancer.

Immunotherapy has transformed treatment for various types of malignancy. However, the benefit of immunotherapy is limited to a minority of patients with mismatch-repair-deficient (dMMR) and microsatellite instability-high (MSI-H) (dMMR-MSI-H) colorectal cancer (CRC). Understanding the complexity and heterogeneity of the tumor immune microenvironment (TIME) and identifying immune-related CRC subtypes will improve antitumor immunotherapy. Here, we review the current status of immunotherapy and typing schemes for CRC. Immune subtypes have been identified based on TIME and prognostic gene signatures that can both partially explain clinical responses to immune checkpoint inhibitors and the prognosis of patients with CRC. Identifying immune subtypes will improve understanding of complex CRC tumor heterogeneity and refine current immunotherapeutic strategies.

Aging characteristics of colorectal cancer based on gut microbiota.

BACKGROUND: Aging is one of the factors leading to cancer. Gut microbiota is related to aging and colorectal cancer (CRC). METHODS: A total of 11 metagenomic data sets related to CRC were collected from the R package curated Metagenomic Data. After batch effect correction, healthy individuals and CRC samples were divided into three age groups. Ggplot2 and Microbiota Process packages were used for visual description of species composition and PCA in healthy individuals and CRC samples. LEfSe analysis was performed for species relative abundance data in healthy/CRC groups according to age. Spearman correlation coefficient of age-differentiated bacteria in healthy individuals and CRC samples was calculated separately. Finally, the age prediction model and CRC risk prediction model were constructed based on the age-differentiated bacteria. RESULTS: The structure and composition of the gut microbiota were significantly different among the three groups. For example, the abundance of Bacteroides vulgatus in the old group was lower than that in the other two groups, the abundance of Bacteroides fragilis increased with aging. In addition, seven species of bacteria whose abundance increases with aging were screened out. Furthermore, the abundance of pathogenic bacteria (Escherichia_coli, Butyricimonas_virosa, Ruminococcus_bicirculans, Bacteroides_fragilis and Streptococcus_vestibularis) increased with aging in CRCs. The abundance of probiotics (Eubacterium_eligens) decreased with aging in CRCs. The age prediction model for healthy individuals based on the 80 age-related differential bacteria and model of CRC patients based on the 58 age-related differential bacteria performed well, with AUC of 0.79 and 0.71, respectively. The AUC of CRC risk prediction model based on 45 disease differential bacteria was 0.83. After removing the intersection between the disease-differentiated bacteria and the age-differentiated bacteria from the healthy samples, the AUC of CRC risk prediction model based on remaining 31 bacteria was 0.8. CRC risk prediction models for each of the three age groups showed no significant difference in accuracy (young: AUC=0.82, middle: AUC=0.83, old: AUC=0.85). CONCLUSION: Age as a factor affecting microbial composition should be considered in the application of gut microbiota to predict the risk of CRC.

Single-cell transcriptome analysis reveals T population heterogeneity and functions in tumor microenvironment of colorectal cancer metastases.

Cell mediated immune escape, a microenvironment factor, induces tumorigenesis and metastasis. The purpose of this study was to display the characteristics of T cell populations in immune microenvironments for colorectal cancer (CRC) metastasis. Unsupervised cluster analysis was conducted to identify functionally distinct T cell clusters from 3,003 cells in peripheral blood and 4,656 cells in tissues. Subsequently, a total of 8 and 4 distinct T cell population clusters were identified from tumor tissue and peripheral blood, respectively. High levels of CD8+TEX, CD4+TRM, TH1-like T cells, CD8+TEM, tumor-Treg from tissues, and CD4+TN from peripheral blood are essential components of immune microenvironment for the prediction of CRC metastasis. Moreover, exhausted T cells are characterized by higher expression of multiple inhibitory receptors, including PDCD1 and LAG3. Some genes such as PFKFB3, GNLY, circDCUN1D4, TXNIP and NR4A2 in T cells of cluster were statistically different between CRC metastasis and non-metastasis. The ligand-receptor interactions identified between different cluster cells and metastases-related DEGs identified from each cluster revealed that the communications of cells, alterations of functions, and numbers of T subsets may contribute to the metastasis of CRC. The mutation frequency of KiAA1551, ATP8B4 and LNPEP in T cells from tissues and SOR1 from peripheral blood were higher in metastatic CRC than that in non-metastatic CRC. In conclusion, the discovery of differential genes in T cells may provide potential targets for immunotherapy of CRC metastasis and relevant insights into the clinical prediction and prognosis of CRC metastasis.

Comprehensive Assessment of Pollution Sources and Health Impacts in Suburban Area of Shanghai.

Shanghai, one of China's largest metropolises, faces significant environmental pollution challenges due to rapid economic development. Suburban areas of Shanghai are affected by both long-distance transport and local sources of pollutants. This study conducted an integrated analysis that links health-risk assessment of heavy metals and source apportionment of atmospheric constituents to distinguish the contributions of emission sources and the major sources of health risks. Source-apportionment analysis revealed that secondary sources had the greatest contribution to the local pollutants, indicating the significant influence of peripheral and long-distance transport. Health-risk assessment of Cr, Ni, As, and Cd revealed that local residents were exposed to respiratory health risks, in which Cr is the major contributor. This health risk was primarily associated with emissions from nearby industry-related sources. Our study highlights the significant effects of both long-distance transport and local source emissions on atmospheric composition and human health in large urban agglomerations. The findings can inform future efforts to develop more precise emission-reduction strategies and policy improvements to mitigate environmental pollution and protect public health.

Pancreatic follicular dendritic cell sarcoma: a rare case report and systematic literature review of 7 cases.

INTRODUCTION: Pancreatic follicular dendritic cell sarcoma (FDCS) is an exceptionally rare and low-to-moderate malignancy, with only seven reported cases to date. Clinical diagnosis of FDCS is challenging due to the lack of distinct biological and radiographic features. CASE PRESENTATION: A 67-year-old woman presented to the hospital with a 4-day history of severe abdominal pain. Imaging studies (CT and MRI) revealed a large cystic mass located at the tail of the pancreas, which was suspected to be myeloid sarcoma (MS) based on EUS and CT-guided pancreatic puncture. Postoperative pathology and immunohistochemistry confirmed the diagnosis of pancreatic FDCS. After the diagnosis was confirmed, the patient received postoperative chemotherapy with the CHOP regimen. At 11 months of follow-up, there was no evidence of recurrence. Seven published cases have been reviewed to comprehensively summarize the clinical characteristics, diagnosis, and treatment options of FDCS. CONCLUSION: While imaging can be useful in detecting pancreatic FDCS, it should be interpreted with caution as it can be challenging to differentiate from other pancreatic tumors. Pathology and immunohistochemistry are considered the gold standard for diagnosis, with CD21, CD23, and CD35 being specific tumor cell markers. However, preoperative diagnosis of pancreatic FDCS remains difficult, and the pancreatic puncture may further increase the risk of misdiagnosis. The disease is highly prone to recurrence and metastasis, and surgery is the preferred method for both diagnosis and treatment of localized disease.

Mitochondria-associated endoplasmic reticulum membrane: Overview and inextricable link with cancer.

The mitochondrial-associated membrane (MAM) is a physical platform that facilitates communication between the endoplasmic reticulum (ER) and mitochondria. It is enriched with many proteins and enzymes and plays an important role in the regulation of several fundamental physiological processes, such as calcium (Ca2+ ) transfer, lipid synthesis, cellular autophagy and ER stress. Accumulating evidence suggests that oncogenes and suppressor genes are present at the ER-mitochondrial contact site, and their alterations can affect Ca2+ flux, lipid homeostasis, and the dysregulation of mitochondrial dynamics, thereby influencing the fate of cancer cells. Understanding the fundamental role of MAM-resident proteins in tumorigenesis could support the search for novel therapeutic targets in cancer. In this review, we summarize the basic structure of MAM and the core functions of MAM-resident proteins in tumorigenesis. In addition, we discuss the mechanisms by which natural compounds promote cancer cell apoptosis from the perspective of ER stress.

Volatile organic compounds at a roadside site in Hong Kong: Characteristics, chemical reactivity, and health risk assessment.

Volatile organic compounds (VOCs) and oxygenated VOCs (OVOCs) play important roles in atmospheric chemistry and are recognized as the major pollutants in roadside microenvironments of metropolitan Hong Kong, China. In this study, the ambient VOCs and OVOCs were intensively monitored at a roadside site in Hong Kong for one month during morning and evening rush hours. The emission characterizations, as well as ozone formation potentials (OFP) and hydroxyl radical (OH) loss rates (LOH) were determined. Results from the campaign showed that the average concentrations of detected VOCs/OVOCs ranged from 0.21 to 9.67 ppb, and higher toluene to benzene (T/B) ratio was observed during evening sections due to the variation of fuel types in vehicle fleets and mix of additional emission sources in this site. On average, OVOCs had much higher concentrations than the targeted VOC species. Acetone, formaldehyde, and acetaldehyde were the three most abundant species, while formaldehyde showed the highest contributions to both OFP (32.20 %) and LOH (16.80 %). Furthermore, potential health hazards with inhalation exposure to formaldehyde, acetaldehyde, propionaldehyde, methyl ethyl ketone (MEK), 1,3-butadiene, toluene, benzene, and acrylonitrile were found. These results reveal that it is imperative to implement efficient control measures to reduce vehicle emissions for both primary and secondary pollutants and to protect both roadside workers and pedestrians.

Analysis of bacterial diversity and community structure in gastric juice of patients with advanced gastric cancer.

BACKGROUND: The occurrence and development of gastric cancer are related to microorganisms, which can be used as potential biomarkers of gastric cancer. OBJECTIVE: To screen the microbiological markers of gastric cancer from the microorganisms of gastric juice. METHODS: Gastric juice samples were collected from 61 healthy people and 78 patients with gastric cancer (48 cases of early gastric cancer and 30 cases of advanced gastric cancer). The bacterial 16 S rRNA V1-V4 region of gastric juice samples was sequenced. The Shannon index, Simpson index, Ace index and Chao index were used to analyze the diversity of gastric juice samples. The RDP classifier Bayesian algorithm was used to analyze the community structure of 97% OTU representative sequences with similar levels. Linear discriminant analysis and ST-test were used to analyze the differences. Six machine learning algorithms, including the logistic regression algorithm, random forest algorithm, neural network algorithm, support vector machine algorithm, Catboost algorithm and gradient lifting tree algorithm, were used to construct risk prediction models for gastric cancer and advanced gastric cancer. RESULTS: The microbiota diversity and the abundance of bacteria was different in the healthy group, early gastric cancer and advanced gastric cancer (P < 0.05). The top five abundant bacteria among the three groups were Streptococcus, Rhodococcus, Prevotella, Pseudomonas and Helicobacter. Bacterial flora such as Streptococcus, Rhodococcus and Ochrobactrum were significantly different between the healthy group and the gastric cancer group. The accuracy of the random forest prediction model is the highest (82.73% correct). The bacteria with the highest predictive value included Streptococcus, Lactobacillus and Ochrobactrum. The abundance of bacteria such as Fusobacterium, Capnocytophaga, Atopobium, Corynebacterium was high in the advanced gastric cancer group. CONCLUSION: Gastric juice bacteria can be used as potential biomarkers to predict the occurrence and development of gastric cancer.

Long-term variation and evaluation of air quality across Hong Kong.

Study of Air Quality Objectives (AQOs) and long-term changes of air pollution plays a decisive role in formulating and refining pollution control strategies. In this study, 10-year variations of six major air pollutants were analyzed at seven monitoring sites in Hong Kong. The continuous decrease of annual averaged concentrations of NO2, SO2, CO, PM2.5 and PM10 and numbers of days with severe pollution conditions validated the efficiency of the series of air pollution control schemes implemented by the Hong Kong government. However, there is still a big gap to meet the ultimate targets described by the World Health Organization. Besides, the concentration of O3 at roadside and urban stations increased by 135% ± 25% and 37% ± 18% from 2011 to 2020, respectively, meanwhile the highest 8 hr averaged O3 concentration was observed as 294 µg/m3 at background station in 2020, which pointed out the increasing ozone pollution in Hong Kong. There was a great decrease in the annual times of air quality health index (AQHI) laying in "high", "very high" and "serious" categories from 2011 to 2020 with the decrease rate of 89.70%, 91.30% and 89.74% at roadside stations, and 79.03%, 95.98% and 72.73% at urban stations, respectively. Nevertheless, the number of days categorized as "high" or above at roadside station was twice more than that in the urban station during the past ten years. Thus, more policies and attentions should be given to the roadside air quality and its adverse health effect to pedestrians on street.

The different prognostic factors between metastatic and nonmetastatic disease of esophageal neuroendocrine carcinoma.

PURPOSE: The specific risk factors of metastatic and nonmetastatic esophageal neuroendocrine carcinoma (NEC) are still uncertain. Whether primary site surgery is necessary for all patients with esophageal NEC is unknown. METHODS: Patients with esophageal NEC in the Surveillance, Epidemiology, and End Results (SEER) database from 2004 to 2014 were selected. STATA 12 was used to analyze the clinical and pathological features of esophageal NEC. RESULTS: In total, 241 patients with esophageal NEC were included. Metastatic patients had shorter overall survival than nonmetastatic patients (6.03 versus 11.90 months, respectively). Prognostic factors varied between metastatic and nonmetastatic esophageal NEC. The location of the primary tumor is a key point for the prognosis of esophageal NEC. For nonmetastatic esophageal NEC, patients with tumors in the upper third of the esophagus had the worst survival, and patients with metastatic esophageal NEC with a primary tumor in the lower part of the esophagus tended to have an increased risk of death. Moreover, age ≥68 years (hazard ratio [HR] = 2.05; 95% confidence interval [CI]: 1.28-3.31; P < 0.01) and large cell carcinoma (HR = 2.79; 95% CI: 1.30-6.00; P < 0.01) were independent risk factors in patients with metastatic esophageal NEC. Primary site resection benefited patients with nonmetastatic esophageal NEC (HR = 0.20; 95% CI: 0.07-0.56; P < 0.01) rather than patients with metastatic esophageal NEC (HR = 0.91; 95% CI: 0.29-2.83; P > 0.05). CONCLUSIONS: Our study presented that primary tumor location is an important risk factor for nonmetastatic esophageal NEC patients. Age and pathological type are important risk factors for patients with metastatic esophageal NEC. Nonmetastatic esophageal NEC will benefit from primary tumor resection. Systematic treatment is recommended for metastatic esophageal NEC.

Different Characteristics in Gut Microbiome between Advanced Adenoma Patients and Colorectal Cancer Patients by Metagenomic Analysis.

The occurrence and development of colorectal cancer (CRC) and advanced adenoma (AA) are closely related to the gut microbiome, and AA has a high cancerization progression rate to CRC. Current studies have revealed that bacteriological analysis cannot identify CRC from AA. The objective was to explore microbial targets that could identify CRC and AA from a microecological perspective and to figure out the best way to identify CRC based on fecal microbes. The metagenomic sequencing data were used to describe the gut microbiome profile and analyze the differences between microbial abundance and microbial single nucleotide polymorphism (SNP) characteristics in AA and CRC patients. It was found that there were no significant differences in the diversity between the two groups. The abundance of bacteria (e.g., Firmicutes, Clostridia, and Blautia), fungi (Hypocreales), archaea (Methanosarcina, Methanoculleus, and Methanolacinia), and viruses (Alphacoronavirus, Sinsheimervirus, and Gammaretrovirus) differed between AA and CRC patients. Multiple machine-learning algorithms were used to establish prediction models, aiming to identify CRC and AA. The accuracy of the random forest (RF) model based on the gut microbiome was 86.54%. Nevertheless, the accuracy of SNP was 92.31% in identifying CRC from AA. In conclusion, using microbial SNP was the best method to identify CRC, it was superior to using the gut microbiome, and it could provide new targets for CRC screening. IMPORTANCE There are differences in characteristic microorganisms between AA and CRC. However, current studies have indicated that bacteriological analysis cannot identify CC from AA, and thus, we wondered if there were some other targets that could be used to identify CRC from AA in the gut microbiome. The differences of SNPs in the gut microbiota of intraindividuals were significantly smaller than those of interindividuals. In addition, compared with intestinal microbes, SNP was less affected by time with certain stability. It was discovered that microbial SNP was better than the gut microbiome for identifying CRC from AA. Therefore, screening characteristic microbial SNP could provide a new research direction for identifying CRC from AA.