Bacterial Systems Biology

Life is so complicated that even a free-living bacterial cell with a small genome is far beyond what we have understood. Our group are dedicated to understanding the maintenance and evolving mechanisms of the simplest independent life system, evolution of bacterial genomes, virulence systems and individual genes, and bacterial population surviving strategies, with integrated resources and computational techniques. Specifically, we are developing tools to assist bacterial gene recognition and functional annotation, to find conservation and diversification of genes and pathways, and to mimic simplest independent living life systems with minimal surviving genes or pathways. We are also making investigation on features buried in bacterial genomes, exploring the evolutionary traces, and making Salmonella as the model to well annotate and compare the genomes. Specific interests have been focussed on the evolution of bacterial Type III Secretion Systems (T3SSs) and related genes. T3SSs are closely associated with bacterial interaction with eukaryotic host cells. They are considered as an independent system since they can function as a whole to perform important biological processes independently, they can by themselves integrate into bacterial hosts, exert transcriptional regulation and translocate into host cytoplasm effectors coordinately. We curated and regularly update two databases, T3DB and T3Enc, with T3DB integrating the comprehensive research data of 36 model T3SSs and T3Enc analyzing the diversity and evolution of T3SSs. Tools and models are being developed to identify and cluster T3SSs, investigate the evolution and diversification of T3SSs, explore the coordinated regulation of T3SS genes, identify new effectors and understand the effector translocation/secretion mechanisms. For population level, we are also curious about biofilm formation and the bacteria-bacteria interaction mediated by Type VI Secretion Systems (T6SSs).

Related project news:

04 April, 2017    Our paper systematically surveying the T3SSs, category, effectors and regulatory conduits was accepted by EMI.

30 June, 2016    T3Enc 1.0 was released.

31 May, 2016    The paper describing a bacterial chromosomal labeling method was accepted by AEM.

18 May, 2016    Our Yersinia LRR paper was accepted by IAI.

Disease-Genotype Association in Chinese Population

Our achievements in technology are amazing. However, we and our relatives are still suffering death and health problems every day. As a tiny research group, we are also trying our best to make even tiny contributions to health issues of our people. We are developing various computational tools to assist analyzing the genomes and haplotypes, identify association between different diseases and genotypes, and develop models to help monitor the risks or early onset of different diseases, and guide prognosis and treatment selection. Specifically, we are developing methods to improve statistic power on capturing significant biomarkers or other features. Tools are also under development for better analysis of the haplotype genome of human or parasites. Genome variations are detected and compared between various diseased and normal Chinese people, and advanced machine learning models are developed to facilitate the application of the findings.

Related project news:

14 May, 2017    PERPer_Go, the first tool predicting PE risk in Chinese population was released.

29 April, 2017    The paper documenting EBT method was accepted by Bioinformatics for publication.

09 July, 2016    The procedure of EBT, a new binomial distribution based rate comparison method was released.

03 May, 2016    Our paper on PE-genotype association in Chinese women was accepted.