Lei Su

Prof. Dr. Lei Su

Institute of Medical Laboratory Animal Science, Chinese Academy of Medical Sciences
orcid

Research Focus & Metrics

Academic Career Length

14Years (2013-Present)

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

Representative Publications

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1 January 2020 in Microbiological Research
Verified
Journal Article
Closed access
LHLin-Qi Huang
Lin-Qi Huang
YNYong-Chun Niu
Yong-Chun Niu
Lei SuLei Su
Lei Su
HDHui Deng
Hui Deng
HLHeng Lyu
Heng Lyu

2 November 2021 in Microorganisms
Verified
Journal Article
Open access
PDF file
PSPeilin Sun
Peilin Sun
Lei SuLei Su
Lei Su
HZHua Zhu
Hua Zhu
XLXue Li
Xue Li
YGYaxi Guo
Yaxi Guo
CQChuan Qin
Chuan Qin
In recent years, human gut microbiota have become one of the most promising areas of microorganism research; meanwhile, the inter-relation between the gut microbiota and various human diseases is a primary focus. As is demonstrated by the accumulating evidence, the gastrointestinal tract and central nervous system interact through the gut–brain axis, which includes neuronal, immune-mediated and metabolite-mediated pathways. Additionally, recent progress from both preclinical and clinical studies indicated that gut microbiota play a pivotal role in gut–brain interactions, whereas the imbalance of the gut microbiota composition may be associated with the pathogenesis of neurological diseases (particularly neurodegenerative diseases), the underlying mechanism of which is insufficiently studied. This review aims to highlight the relationship between gut microbiota and neurodegenerative diseases, and to contribute to our understanding of the function of gut microbiota in neurodegeneration, as well as their relevant mechanisms. Furthermore, we also discuss the current application and future prospects of microbiota-associated therapy, including probiotics and fecal microbiota transplantation (FMT), potentially shedding new light on the research of neurodegeneration.

24 September 2020 in Journal of Fungi
Verified
Journal Article
Open access
PDF file
WSWei Sun
Wei Sun
Lei SuLei Su
Lei Su
SYShun Yang
Shun Yang
JSJingzu Sun
Jingzu Sun
BLBingjie Liu
Bingjie Liu
MXMeichun Xiang
Meichun Xiang
Rock-inhabiting fungi (RIF) are nonlichenized fungi that naturally colonize rock surfaces and subsurfaces. The extremely slow growth rate and lack of distinguishing morphological characteristics of RIF resulted in a poor understanding on their biodiversity. In this study, we surveyed RIF colonizing historical stone monuments and natural rock formations from throughout China. Among over 1000 isolates, after preliminary delimitation using the internal transcribed spacer region (ITS) sequences, representative isolates belonging to Trichomeriaceae and Herpotrichiellaceae were selected for a combined analysis of ITS and the nuclear ribosomal large subunit (nucLSU) to determine the generic placements. Eight clades representing seven known genera and one new genus herein named as Anthracina were placed in Trichomeriaceae. While, for Herpotrichiellaceae, two clades corresponded to two genera: Cladophialophora and Exophiala. Fine-scale phylogenetic analyses using combined sequences of the partial actin gene (ACT), ITS, mitochondrial small subunit ribosomal DNA (mtSSU), nucLSU, the largest subunit of RNA polymerase II (RPB1), small subunit of nuclear ribosomal RNA gene (SSU), translation elongation factor (TEF), and β-tubulin gene (TUB) revealed that these strains represented 11 and 6 new species, respectively, in Trichomeriaceae and Herpotrichiellaceae. The 17 new species were described, illustrated for their morphologies and compared with similar taxa. Our study demonstrated that the diversity of RIF is surprisingly high and still poorly understood. In addition, a rapid strategy for classifying RIF was proposed to determine the generic and familial placements through preliminary ITS and nucLSU analyses, followed by combined analyses of five loci selected from ACT, ITS, mtSSU, nucLSU, RPB1, and/or the second subunit of RNA polymerase II gene (RPB2), SSU, TEF, and TUB regions to classify RIF to the species level.

2 September 2020 in Communications Biology
Verified
Journal Article
Open access
PDF file
HQHoubao Qi
Houbao Qi
JWJianmei Wei
Jianmei Wei
YGYunhuan Gao
Yunhuan Gao
YYYazheng Yang
Yazheng Yang
YLYuanyuan Li
Yuanyuan Li
RYRongcun Yang
Rongcun Yang
The expansion ofEnterobacteriaceae, such asE. coliis a main characteristic of gut inflammation and is related to multiple human diseases. However, how to control theseE. coliovergrowth is not well understood. Here, we demonstrate that gut complement factor D (CFD) plays an important role in eliminatingE. coli. IncreasedE. coli, which could stimulate inflammatory macrophages to induce colitis, were found in the gut of CFD deficient mice. We also showed that gut Reg4, which is expressed in gut epithelial cells, stimulated complement-mediated attack complexes to eliminateE. coli.Reg4deficient mice also had increasedE. coli. The dominantE. coliwere isolated from colitis tissues of mice and found to be sensitive to both CFD- and Reg4-mediated attack complexes. Thus, gut Reg4- and CFD-mediated membrane attack complexes may maintain gut homeostasis by killing inflammatoryE. coli.

Verified
Journal Article
Open access
PDF file
PSPeilin Sun
Peilin Sun
HZHua Zhu
Hua Zhu
XLXue Li
Xue Li
WSWeixiong Shi
Weixiong Shi
YGYaxi Guo
Yaxi Guo
CQChuan Qin
Chuan Qin
A common symptom in Alzheimer’s disease (AD) is cognitive decline, of which the potential pathogenesis remains unclear. In order to understand the mechanism of gut microbiota in AD, it is necessary to clarify the relationship between gut microbiota and metabolites. Behavioral tests, pathological examination, metagenomics, and metabolomics were applied to analyze the difference of gut microbiota and metabolome between APPswe/PS1ΔE9 (PAP) mice with cognitive decline and age-matched controls, and their possible correlations. Our results showed that PAP mice and health mice had different structures of the bacterial communities in the gut. The abundances and diversities of the bacterial communities in health mice were higher than in PAP mice by metagenomics analysis. The abundances of Libanicoccus massiliensis, Paraprevotella clara, and Lactobacillus amylovorus were significantly increased in PAP mice, while the abundances of Turicibacter sanguinis, Dubosiella newyorkensis, and Prevotella oris were greatly reduced. Furthermore, PAP mice possessed peculiar metabolic phenotypes in stool, serum, and hippocampus relative to WT mice, as is demonstrated by alterations in neurotransmitters metabolism, lipid metabolism, aromatic amino acids metabolism, energy metabolism, vitamin digestion and absorption, and bile metabolism. Microbiota–host metabolic correlation analysis suggests that abnormal metabolism in stool, serum, and hippocampus of PAP mice may be modulated by the gut microbiota, especially T. sanguinis, D. newyorkensis, and P. oris. Therefore, abnormal metabolism activity is associated with gut microbiota in Alzheimer’s disease mice. Our results imply that modifying host metabolism through targeting gut microbiota may be a novel and viable strategy for the prevention and treatment of AD in the future.

29 August 2017 in Frontiers in Microbiology
Verified
Journal Article
Open access
YWYaqin Wen
Yaqin Wen
LWLin Wang
Lin Wang
YJYue Jin
Yue Jin
JZJinzhen Zhang
Jinzhen Zhang
Lei SuLei Su
Lei Su
YLYi Li
Yi Li
The bacterial and fungal communities of vitex honey were surveyed by sequencing the 16S rRNA gene and the internal transcribed spacer region of ribosomal DNA. Vitex honey samples were analyzed at different stage of ripening; the vitex flower was also analyzed, and the effect of the chemical composition in the experimental setup was assessed. The results confirmed the presence of dominant Bacillus spp. as the dominant bacterial in honey, and yeast related genera was the main fungal in the honey, respectively. Lactococcus and Enterococcus were detected for the first time in honey. The proportion of most of the fungal community decreased during the honey ripening process. Multivariate analyses also showed that the fungal community of 5, 10 and 15 d honey samples tended to cluster together and were completely separated from the 1 d honey sample. The change in the fungal community showed a correlation with the variation in the chemical components, such as moisture and phenolic compounds. Together, these results suggest that ripening of honey could change its microbial composition, and decrease the potential risk of microbiology.