2.5 Gut microbiota metatranscriptome analysis
Total RNA extraction was conducted using the RNeasy Plus Mini Kit
(QIAGEN, Germany) in accordance with the manufacturer’s protocol. The
quality and integrity of the RNA were evaluated using a NanoDrop
spectrophotometer (Thermo Fisher Scientific, MA, USA). Only samples that
met the following criteria were utilized for further analysis: a 260/280
ratio between 1.8 and 2.1, and a 260/230 ratio between 2.0 and 2.4.
In total, we sequenced four transcriptome samples (one sample per group)
and twelve metatranscriptome samples (triplicate samples per group). For
eukaryotic RNA sequencing, one RNA sample from both toxic and non-toxic
diets on D1 and D2 was processed using Poly(A) RNA sequencing (RNA-seq),
selecting only RNAs with poly(A) tails, such as eukaryotic mRNAs.
Library construction utilized poly-A oligo-attached magnetic beads. For
both eukaryotic and prokaryotic RNA sequencing, triplicate RNA samples
from the toxic and non-toxic diets on D1 and D2 were subjected to
metatranscriptome sequencing, using all RNAs except ribosomal RNAs for
library construction. RNA-seq and metatranscriptome sequencing were
performed on a NovaSeq 6000 system (Illumina, CA, USA), generating
150-bp paired-end reads. Clean reads were obtained by removing adapters,
barcodes, poly-N reads, and low-quality reads from the raw data. Quality
control, assembly, and annotation of the transcriptome and
metatranscriptome data were conducted following the methods described by
Chen et al. (2024).
The host transcriptome was co-assembled using RNA-seq data with Trinity
v2.14.0 (Grabherr et al. 2011). To obtain prokaryotic reads, the
metatranscriptome reads were aligned to the host assembly, and the
mapped reads were subsequently removed. Prokaryotic metatranscriptome
reads were then co-assembled using Trinity v2.14.0 (Grabherr et al.
2011). Similar transcripts were clustered with CD-HIT (Fu et al. 2012)
with ‘-c 0.95’ parameter, retaining a single representative transcript
for each cluster. The longest open reading frame (ORF) for each
transcript was identified using TransDecoder v5.5.0
(https://github.com/TransDecoder/TransDecoder) and annotated against the
Kyoto Encyclopedia of Genes and Genomes (KEGG) (Kanehisa and Goto 2000)
with ‘–sensitive -e 1e-20’ parameters.
Raw reads from the metatranscriptome were aligned to host assembly and
prokaryotic assembly using Bowtie2 v2.4.4 (Langmead and Salzberg 2012)
with default settings, respectively. Based on the results (SAM files)
from Bowtie2, the read counts of all genes at all samples were
summarized using featureCounts v.2.0.0 (Liao, Smyth, and Shi 2014) with
the following parameters: ‘-M, -O, –fraction’. After separating the
expressed gene profiles of the gut microbiota and A. erythraea ,
differentially expressed genes (DEGs) were identified using the edgeR
v.3.30.3 R package (Robinson, McCarthy, and Smyth 2010). Genes with a
P-value < 0.05 and |log2 (fold change)|
> 1 were considered DEGs. KEGG enrichment analysis was
performed using the ‘enricher’ function in the clusterProfiler v.3.16.1
R package (Yu et al. 2012), defining significantly enriched pathways as
those with an adjusted p -value < 0.05.