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Impact of preoperative antibiotics on integrated microbiome-host transcriptomic data generated from colorectal cancer resections.

ABSTRACT: Impact of preoperative antibiotics on integrated microbiome-host transcriptomic data generated from colorectal cancer resections.

PROVIDER: PRJNA693828 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR13498200_1.fastq.gz	Fastqsanger.gz
	SRR13498200_2.fastq.gz	Fastqsanger.gz
	SRR13498300.fastq.gz	Fastqsanger.gz
	SRR13498201_1.fastq.gz	Fastqsanger.gz
	SRR13498201_2.fastq.gz	Fastqsanger.gz

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Project description:BackgroundIntegrative multi-omic approaches have been increasingly applied to discovery and functional studies of complex human diseases. Short-term preoperative antibiotics have been adopted to reduce site infections in colorectal cancer (CRC) resections. We hypothesize that the antibiotics will impact analysis of multi-omic datasets generated from resection samples to investigate biological CRC risk factors.AimTo assess the impact of preoperative antibiotics and other variables on integrated microbiome and human transcriptomic data generated from archived CRC resection samples.MethodsGenomic DNA (gDNA) and RNA were extracted from prospectively collected 51 pairs of frozen sporadic CRC tumor and adjacent non-tumor mucosal samples from 50 CRC patients archived at a single medical center from 2010-2020. The 16S rRNA gene sequencing (V3V4 region, paired end, 300 bp) and confirmatory quantitative polymerase chain reaction (qPCR) assays were conducted on gDNA. RNA sequencing (IPE, 125 bp) was performed on parallel tumor and non-tumor RNA samples with RNA Integrity Numbers scores ≥ 6.ResultsPERMANOVA detected significant effects of tumor vs nontumor histology (P = 0.002) and antibiotics (P = 0.001) on microbial β-diversity, but CRC tumor location (left vs right), diabetes mellitus vs not diabetic and Black/African Ancestry (AA) vs not Black/AA, did not reach significance. Linear mixed models detected significant tumor vs nontumor histology*antibiotics interaction terms for 14 genus level taxa. QPCR confirmed increased Fusobacterium abundance in tumor vs nontumor groups, and detected significantly reduced bacterial load in the (+)antibiotics group. Principal coordinate analysis of the transcriptomic data showed a clear separation between tumor and nontumor samples. Differentially expressed genes obtained from separate analyses of tumor and nontumor samples, are presented for the antibiotics, CRC location, diabetes and Black/AA race groups.ConclusionRecent adoption of additional preoperative antibiotics as standard of care, has a measurable impact on -omics analysis of resected specimens. This study still confirmed increased Fusobacterium nucleatum in tumor.

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Impact of preoperative antibiotics on integrated microbiome-host transcriptomic data generated from colorectal cancer resections.

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