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

From BugSigDB
Reviewed Marked as Reviewed by Peace Sandy on 2024-3-18
study design
Citation
PMID PubMed identifier for scientific articles.
DOI Digital object identifier for electronic documents.
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


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

Curated date: 2024/03/07

Curator: Imaspecial

Revision editor(s): Imaspecial, Peace Sandy

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 cancer cancer of colorectum,cancer of large bowel,cancer of large intestine,cancer of the large bowel,colon cancer,colorectal cancer,colorectum cancer,CRC,large intestine cancer,malignant colorectal neoplasm,malignant colorectal tumor,malignant colorectum neoplasm,malignant large bowel neoplasm,malignant large bowel tumor,malignant large intestine neoplasm,malignant large intestine tumor,malignant neoplasm of colorectum,malignant neoplasm of large bowel,malignant neoplasm of large intestine,malignant neoplasm of the large bowel,malignant neoplasm of the large intestine,malignant tumor of large bowel,malignant tumor of large intestine,malignant tumor of the large bowel,malignant tumor of the large intestine,Colorectal cancer
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

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

Curated date: 2024/03/07

Curator: Imaspecial

Revision editor(s): Imaspecial, Peace Sandy

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 Colorectal Cancer Patients

NCBI Quality ControlLinks
Acidihalobacter
Kushneria
Lelliottia
Parvimonas

Revision editor(s): Imaspecial, Peace Sandy

Signature 2

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

Curated date: 2024/03/07

Curator: Imaspecial

Revision editor(s): Imaspecial, Peace Sandy

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 Colorectal Cancer Patients

NCBI Quality ControlLinks
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