Combining of transcriptome and metabolome analyses for understanding the utilization and metabolic pathways of Xylo‐oligosaccharide in Bifidobacterium adolescentis ATCC 15703

Abstract A combination of transcriptome and metabolome analyses was applied to understand the utilization and metabolism of Xylo‐oligosaccharide (XOS) in Bifidobacterium adolescentis 15703 as well as identifying the key regulatory‐related genes and metabolites. Samples of cultures grown on either XOS or xylose were collected. The transcript and metabolite profiles were obtained from high‐throughput RNA‐sequencing data analysis and UHPLC system. Compared with xylose, XOS highly promoted the growth of B. adolescentis 15703 and resulted in a growth yield about 1.5‐fold greater than xylose. The transcriptome analysis showed that XOS could enhance genes, including ABC transporters, galactosidase, xylosidase, glucosidase, and amylase, which were involved in transport and metabolism of carbohydrate compared with xylose. Furthermore, the expression profile of 16 candidate genes using qRT‐PCR has validated the accuracy of the RNA‐seq data. Also, the metabolomic analyses, particularly those related to metabolic biomarkers of fatty acids, amino acids, and sugars showed a similar trend of result and approved the advantages of XOS as growth medium for B. adolescentis 15703 compared with xylose. The expression and abundance of specific genes and metabolites highlighted the complex regulatory mechanisms involved in utilization of XOS by B. adolescentis 15703. These results are useful in the understanding of the metabolic pathway of XOS in B. adolescentis 15703 and contribute to the optimization of XOS probiotic effects as a food additive.

Xylo-oligosaccharides (XOSs) are hydrolysates of xylan and consist of a backbone of xylose, which are noncaloric and indigestible by humans. XOSs are believed to exert bifidogenic effects and are increasingly used as prebiotics. XOS may be beneficial in stimulating the intestinal Bifidobacterium without significant effect on lactobacillus (Li, Summanen, Komoriya, & Finegold, 2015;Falck et al., 2013). Also, it was found that XOS increases bifidobacteria, but not lactobacilli in human gut microbiota (Finegold et al., 2014). Due to potential bifidobacteria proliferation effects, XOSs have attracted increasing interest.
In a previous study, we have found that the growth rate of B. adolescentis was higher in the presence of XOS than xylose (unpublished).
However, the underlying molecular regulation mechanisms of XOS metabolism are not fully understood. In XOS utilization process, xylose is not neatly consumed and remaining unfermented (Amaretti et al., 2013). Although it has been established that XOSs confer positive benefits to bifidobacteria, there is a lack of knowledge regarding the molecular mechanisms that explain the metabolic pathway of XOS in B. adolescentis. Meanwhile, a recent study performed on the genome sequences from 47 Bifidobacterium (sub) species found that 5.5% of the core bifidobacterial genomic coding sequences are associated with carbohydrate metabolism (Pokusaeva et al., 2011). Therefore, an in-depth study on these functional genes has significance for understanding mechanisms of probiotic effects of Bifidobacterium. In this work, a combination of transcriptome and metabolome analyses was applied to elucidate the molecular mechanism for utilizing and metabolism of xylose and XOS in B. adolescentis 15703. Understanding of basic mechanisms may help in finding of novel ways to optimize the use of prebiotics and probiotics in the food industry.

| Bacterial cultivation and carbohydrates fermentation
Bifidobacterium adolescentis 15703 was resuscitated and precultivated twice using MRS broth. Cells were harvested and suspended as 2% inoculate into MRS medium containing xylose or XOS as well as a control medium without carbohydrate and incubated at 37°C under anaerobic conditions. Aliquots of cultures were drawn at regular intervals and cell growth was determined by measuring the optical density at 600 nm (Lei et al., 2018).

| RNA extraction
Cells were harvested from triplicate cultures at the estimated early midexponential growth phase by centrifugation at 4,000 g for 10 min at 4°C for RNA isolation and purification. The samples were used for RNA extraction following the manufacturer's recommendations of QIAGEN 74524 kit. RNA concentration was determined with a Qubit RNA Assay Kit in a Qubit 2.0 fluorometer (Life Technologies). RNA purity and integrity were assessed by a Nanodrop spectrophotometer (IMPLEN).

| Library construction and sequencing
After total RNA extraction, prokaryotic mRNA was enriched by removing rRNA using Ribo-Zero™ Magnetic Kit (Epicentre). Then the short fragments were obtained from the enriched mRNA by fragmentation buffer and were reverse transcripted into cDNA. Under the action of DNA polymerase I, RNase H and dNTP, second-strand cDNA was synthesized. Then, the cDNA fragments were purified, end repaired, poly (A) added, and ligated to Illumina sequencing adapters (Bellieny-Rabelo et al., 2019). The ligation products size were chosen, amplified, and sequenced using Illumina HiSeq™ 2500.

| Transcriptomic analysis
Raw reads were filtered to remove some adapters and low-quality reads, and the remaining reads were mapped to a reference genome by TopHat2 (Kim et al., 2013). The reconstruction of transcripts was carried out with software Cufflinks (Trapnell et al., 2012), then the transcripts were merged from multiple groups into a finally comprehensive set of transcripts for further downstream differential expression analysis. Gene abundances were quantified by software RSEM (Li & Dewey, 2011). The gene expression level was normalized with FPKM method, and the edgeR package was used to identify DEGs across groups. In comparison as significant DEGs, FDR <0.01 and fold change (FC) ≥2 were used as screening criteria. We conducted gene expression differences between xylose and XOS treatments using the DEseq package. DEGs were then subjected to enrichment analysis of COG functions and KEGG pathways.

| Confirmation of transcriptomic results by quantitative real-time PCR
Total RNA was isolated as described above. Using a Revert Aid Premium Reverse Transcriptase, the cDNA synthesis was performed. qRT-PCR primers are listed in Table 1 and each reaction (20 μl mixture) contained 2 μl cDNA, 10 μl 2 × sybrGreen qPCR Master Mix, 0.4 μl the forward and reverse primers and 7.6 μl water. All qRT-PCR were performed in ABI Stepone plus and performed in two steps: Firstly, predenaturation for 3 min and 45 cycles of denaturation for 3 s at 95°C, then annealing/extension for 30 s at 60°C. Gene expression was normalized by the 2 −ΔΔC t method, and the 16S rRNA gene was used as the normalized standard.

| Metabolites extraction
The sample of 100 μl was accurately removed and placed in EP tube, and 300 μl methanol was added to start extraction, add 20 μl internal standard substances and followed by vortex for 30 s. Then, the mixture tube was immersed into the ultrasonic bath with ice water and ultrasonically incubated in ice water for 10.0 min and incubated for 1 hr at −20°C to precipitate proteins. Then, the mixture was centrifuged at 11,390 g for 15 min at 4°C. About 200 μl of supernatant sample was transferred to a fresh 2 ml LC/MS glass vial, 20 μl from supernatant of each sample was marked as QC samples, and another supernatant was used for the UHPLC-QTOF-MS analysis. All experiments were carried out in triplicate.

| Data processing and analysis
The mzXML format were obtained by using ProteoWizard to convert MS raw data files, and processed by R package XCMS (version 3.2).
The processed results generated a data matrix consisted of retention time (RT), massto-charge ratio (m/z) values, and peak intensity.
R package CAMERA was used for peak annotation after XCMS data processing (Kim et al., 2013). The metabolites were identified by Inhouse MS 2 database.

| Growth characteristics of B. adolescentis 15703
The growth characteristics of B. adolescentis 15703 on xylose and XOS are presented in Figure 1. Bifidobacterium adolescentis grew better on xylose and XOS as carbon sources compared with CK (control group) without carbon source. Also, a rapid growth rate was observed when XOS was used compared with xylose. The growth yield (stable phase) on XOS was about 1.5-fold greater than that on xylose, indicating that XOS was more preferred by B. adolescentis.

| RNA-seq analysis and differential gene expression
From the RNA-seq analysis data, it can be seen that over 99% of the reads were aligned to encoding regions of the B. adolescentis.
Genes were assigned to 25 functional groups, which were annotated in COG database ( Figure 2). Among these classifications, the largest group was amino acid transport and metabolism (191,13.45%), followed by carbohydrate transport and metabolism (160, 11.27%) and general function prediction (151, 10.63%).
A total number of 302 DEGs were identified for B. adolescentis grown on xylose and XOS, including 158 upregulated genes and 144 downregulated genes ( Figure 3). The top 10 upregulated genes and 10 downregulated genes of xylose and XOS treatments are presented in Table 2. Four genes of the top 10 upregulated genes encode ABC and MFS transporters. Among the remaining genes, two genes encode hsp20/alpha crystallin family protein and ATP-dependent chaperone ClpB, two genes encode RNA polymerase sigma factor and death-on-curing protein, other two genes encode enzyme proteins belonging to multiple sugar-binding transport system permease and shikimate kinase. Five genes of the top 10 downregulated genes encode structure protein, including penicillin-binding protein, von willebrand factor type A domain protein, fhiA protein, arginine repressor DUF4956, domain-containing protein, three genes are associated with membrane transport, including peptide ABC transporter ATP-binding protein, ABC transporter permease, and membrane spanning polysaccharide biosynthesis protein, while two genes encode O-antigen polymerase and hypothetical protein.

| KEGG pathway mapping of DEGs
The DEGs involved in biological functions were further analyzed by KEGG pathways, and 20 pathways were predicted ( Figure 4). ABC transporters, galactose metabolism, peptidoglycan biosynthesis pyrimidine metabolism, starch, and sucrose metabolism are the highly represented categories.
The DEGs involved in the ABC transporters are shown in

| Validation of transcript abundance using qRT-PCR
To verify the RNA-Seq results, the mRNA expression of 16 selected

| KEGG pathway mapping of metabolites
A total number of 50 enriched KEGG pathways were predicted, which were associated with different metabolites (Figure 6). The 50 pathways were classified as environmental information processing, genetic information processing, and metabolism. The environmental information processing included ABC transporters and phosphotransferase system. In metabolism processing, microbial metabolism in diverse environments and biosynthesis of unsaturated fatty acids are the most highly represented ( Figure 6).
Different metabolites involved in carbohydrate transport and metabolism are shown in

| B. adolescentis responses to xylose and XOS
To investigate the growth performance of B. adolescentis on xylose and XOS as carbon sources, growth curves of strain were determined. Bifidobacterium adolescentis showed a strong capacity in utilizing of XOS to proliferate, which may indicate that most genes and metabolites in B. adolescentis are related to XOS transport and metabolism. XOS needs to be degraded into xylose before it can be metabolized (Broekaert et al., 2011). Therefore, degradation of XOS is complicated, resulting in a relatively longer lag phase when used as a substrate compared with xylose.