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

Study information

Reviewed Marked as Reviewed by Peace Sandy on 2024-3-18

study design

case-control

Citation

PMID PubMed identifier for scientific articles.

36453905

DOI Digital object identifier for electronic documents.

https://doi.org/10.1128/spectrum.01593-22

URI

https://journals.asm.org/doi/10.1128/spectrum.01593-22

Authors

Han S, Zhuang J, Pan Y, Wu W, Ding K

Journal

Microbiology spectrum

Year

2022

Keywords:

SNP, artificial intelligence, colorectal cancer, gut microbiome, metagenomic sequencing

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.

Experiment 1

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Reviewed Marked as Reviewed by Peace Sandy on 2024-3-18

Curated date: 2024/03/07

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Subjects

Location of subjects: China

Host species Species from which microbiome was sampled. Contact us to have more species added.: Homo sapiens

Body site Anatomical site where microbial samples were extracted from according to the Uber Anatomy Ontology: Feces Cow dung,Cow pat,Droppings,Dung,Excrement,Excreta,Faeces,Fecal material,Fecal matter,Fewmet,Frass,Guano,Matières fécales@fr,Merde@fr,Ordure,Partie de la merde@fr,Piece of shit,Porción de mierda@es,Portion of dung,Portion of excrement,Portion of faeces,Portion of fecal material,Portion of fecal matter,Portion of feces,Portion of guano,Portion of scat,Portionem cacas,Scat,Spoor,Spraint,Stool,Teil der fäkalien@de,Feces,feces

Condition The experimental condition / phenotype studied according to the Experimental Factor Ontology: Colorectal carcinoma

Group 0 name Corresponds to the control (unexposed) group for case-control studies: Advanced Adenoma Patients

Group 1 name Corresponds to the case (exposed) group for case-control studies: Colorectal Cancer Patients

Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group: Patients with fully developed Colorectal cancer

Group 0 sample size Number of subjects in the control (unexposed) group: 26

Group 1 sample size Number of subjects in the case (exposed) group: 26

Antibiotics exclusion Number of days without antibiotics usage (if applicable) and other antibiotics-related criteria used to exclude participants (if any): 2 Months

Lab analysis

Sequencing type: WMS

16S variable region One or more hypervariable region(s) of the bacterial 16S gene: Not specified

Sequencing platform Manufacturer and experimental platform used for quantifying microbial abundance: Illumina

Statistical Analysis

Data transformation Data transformation applied to microbial abundance measurements prior to differential abundance testing (if any).: relative abundances

Statistical test: LEfSe

Significance threshold p-value or FDR threshold used for differential abundance testing (if any): 0.05

MHT correction Have statistical tests be corrected for multiple hypothesis testing (MHT)?: Yes

LDA Score above Threshold for the linear discriminant analysis (LDA) score for studies using the popular LEfSe tool: 2

Signature 1

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Curated date: 2024/03/07

Curator: Imaspecial

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Source: Fig 2 G and H

Description: LEfSe analysis filtered out the biomarkers of the microbial community between AA and CRC patients. and cladogram plot of LEfSe analysis (G) and histogram of LDA analysis (H) of bacteria.

Abundance in Group 1: increased abundance in

NCBI	Quality Control	Links
Acidihalobacter
Kushneria
Lelliottia
Parvimonas

Revision editor(s): Imaspecial, Peace Sandy, WikiWorks

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Mark reviewed

Your review change was submitted

Needs review

Curated date: 2024/03/07

Curator: Imaspecial

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Source: Fig 2 G and H

Description: LEfSe analysis filtered out the biomarkers of the microbial community between AA and CRC patients. and cladogram plot of LEfSe analysis (G) and histogram of LDA analysis (H) of bacteria.

Abundance in Group 1: decreased abundance in

NCBI	Quality Control	Links
Bacillota
Eubacteriales
Clostridia
Lachnospiraceae
Blautia
Clostridiaceae
Clostridium
Ruminococcus
Roseburia
Erysipelotrichaceae
Erysipelotrichia
Erysipelotrichales
Fusicatenibacter
Pasteurellaceae
Pasteurellales
Haemophilus
Lachnospira
Peptostreptococcaceae
Romboutsia
Dorea
Oscillospiraceae
Oscillibacter
Negativibacillus
Eubacteriaceae
Eubacterium
Angelakisella
Christensenella
Christensenellaceae
Faecalicatena
Merdimonas
Intestinimonas
Massilioclostridium
Anaerostipes
Merdibacter
Holdemania
Megasphaera
Acetivibrio
Levyella
Lachnoanaerobaculum
Sutterellaceae
Allofournierella
Anaerotruncus
Turicibacter
Robinsoniella
Stomatobaculum

Revision editor(s): Imaspecial, Peace Sandy, WikiWorks