Ruiyang Xia

Dr. Ruiyang Xia


Research Focus & Metrics

Academic Career Length

2Years (2025-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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2 June 2025 in Veterinary Sciences
Verified
Journal Article
Open access
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RXRuiyang Xia
Ruiyang Xia
YCYalu Chen
Yalu Chen
PYPengfei Yi
Pengfei Yi
YSYawei Sun
Yawei Sun
LCLijing Chen
Lijing Chen
刚姚刚 Mark 姚
刚 Mark 姚
Bovine viral diarrhea virus (BVDV) remains a major cause of calf diarrhea with substantial economic impacts on global cattle production. While emerging evidence suggests that the host microbiota may modulate viral infection processes, the specific gut microbial alterations induced by BVDV infection require elucidation. This study investigated gut microbiota composition and functional changes in BVDV-infected cows through 16S rRNA sequencing. Following the epidemiological screening of a large Angus cattle herd using RT-PCR, we identified four persistently infected (PI) animals and four BVDV-negative controls. Fecal analysis revealed Firmicutes and Bacteroidetes as dominant phyla in both groups. A significant increase in the Ruminococcus genus was observed in PI cows (p < 0.05), with LEfSe analysis identifying Paludibacter as a BVDV-associated biomarker. The PI group exhibited reduced alpha diversity (Faith’s PD index, p < 0.05) and elevated histidine metabolism pathway abundance compared to controls (p < 0.05). These findings demonstrate that persistent BVDV infection induces structural and functional modifications in the bovine gut microbiota, particularly through the enrichment of specific bacterial taxa and altered metabolic potential. The results provide new insights into virus–microbiota interactions, establishing a foundation for understanding how BVDV infection may influence host physiology through microbial community changes.

7 August 2026 in Microorganisms
Verified
Journal Article
Open access
PDF file
MPMengjie Pi
Mengjie Pi
BLBin Li
Bin Li
HWHaorui Wang
Haorui Wang
QZQi Zhao
Qi Zhao
XLXiaosen Li
Xiaosen Li
QGQingyong Guo
Qingyong Guo
Pontastacus leptodactylus is an aquatic resource endemic to Xinjiang, and its growth performance is closely related to the composition and structure of its intestinal microbiota. This study used male P. leptodactylus, divided into a high-growth-performance (HGP) group and a low-growth-performance (LGP) group based on growth rates, to analyze differences in intestinal microbiota using microbial sequencing technology. Results showed that the number of ASVs unique to the HGP group (7840, accounting for 65.97%) was substantially higher than that in the LGP group (3383, 28.46%). ALDEx2 analysis identified six ASVs significantly enriched in the LGP group, assigned to Methylobacterium, Devosia, order Rhizobiales, Renibacterium, Stenotrophomonas, and class Mollicutes, which were near-absent in the HGP group. At the phylum level, TM7 was differentially abundant with higher relative abundance in HGP. At the genus level, ten genera showed significant differences: Pseudomonas, Hydrogenophaga, Mesorhizobium, Reyranella, Mycobacterium, Flavobacterium, Ralstonia, Bradyrhizobium, and Aeromicrobium were enriched in HGP, whereas the opportunistic pathogen Plesiomonas was depleted. Alpha diversity analysis revealed significantly higher Chao1, observed species, Shannon, and Faith’s pd indices in the HGP group (p < 0.05). Beta diversity analysis confirmed significant separation in microbial community structure between the two groups (adonis p = 0.018). KEGG pathway analysis showed upward trends in retinol metabolism, shigellosis, geraniol degradation, and xenobiotics metabolism pathways in HGP (p < 0.10), and a significant upregulation of coumarin biosynthesis (p < 0.01). COG analysis revealed eight downregulated functional genes in HGP (p < 0.01), suggesting more complex host–microbiota interactions. This study identifies distinct intestinal microbial signatures associated with growth performance in P. leptodactylus, providing candidate targets for probiotic development and aquaculture management, while causal verification remains the critical next step.