MICROBIAL GENOMICS

GIS has utilised cutting edge genomic technology platforms to investigate infectious diseases from multiple perspectives. By looking at the genomes of both the pathogen and the host, together with their transcriptomic responses, we have enabled a rapid understanding of the host pathogen interaction during infectious diseases.

We aim to decipher the specific effects of variation in the genomes of the host and the pathogen using global networks, both in vivo and in vitro. Our technological capabilities are being applied to patient samples, at large scales, for diagnosis and patient characterisation. These approaches allow us to perform molecular epidemiological studies on a range of disease, from Dengue, Tuberculosis, Urinary tract infections to SARS, avian influenza and a full range of others. Increasingly, this is also allowing us to evaluate the evolution of natural pathogen isolates, using population diversity to investigate the causes of disease and disease severity. Given our unique position in Southeast Asia, we are also developing the tools and the infrastructure to proactively anticipate trends in disease and resistance as well as to prioritise emerging infectious threats to human health. The raw genetic data is handled by the Computational and Systems Biology group, who is developing novel analytical approaches for data organisation and analyses that are critical to further deciphering the evolution and epidemiology of infectious diseases. These tools are being utilised across the community to ensure impact.

We also investigate human health, from understanding the genetic basis of a successful vaccine response, to understanding healthy skin and gut biomes. With pro-biotic dairy products developing into one of the most successful categories of functional foods, we are also investigating how these biomes may be enhanced, with wide applications to other, perhaps unexpected, conditions such as inflammatory and autoimmune diseases and cancer development.

FACULTY

The GIS Efficient Rapid Microbial Sequencing (Germs) Programme.

Our pathogen sequencing infrastructure (termed the GERMS platform) is dedicated to microbial sequencing, including viruses, bacteria and fungi, with both DNA and RNA (including transcriptome) analyses. We are also targeting microbial communities (biomes and metagenomics) and have a wide range of sample types under investigation (from skin, eye, throat, gut, etc.), from humans, environments and animals. Microbes often have distinct challenges compared to human sequencing and GERMS leverages ongoing improvements in sequencing (including new technologies such as Pac Bio) to be specifically designed for microbial efficiency, scalability, and reliability. The GERMS programme has many active collaborations with intra-institute, national and international collaborators from industry to academic backgrounds alike. The team is able to offer a complete package, from project design to sample handling, sequencing strategies, cutting edge analysis pipelines and comprehensive interpretation. Recent work includes clinical trial analysis of the effect of therapeutics on dengue viruses with Roche, microbiome high throughput approaches using Illumina, tuberculosis drug screening techniques using bacterial RNA with Novartis and whole genome sequencing of streptococcal pneumonia isolates from every hospital in Singapore.

Featured Publications

  • Chen SL, Wu M, Henderson JP, Hooton TM, Hibbing ME, Hultgren SJ, Gordon JI. "Genomic diversity and fitness of E. coli strains recovered from the intestinal and urinary tracts of women with recurrent urinary tract infection." Sci Transl Med. 2013 May 8;5(184):184ra60.
  • Sung WK, Zheng H, Li S, Chen R, Liu X, Li Y, Lee NP, Lee WH, Ariyaratne PN, Tennakoon C, Mulawadi FH, Wong KF, Liu AM, Poon RT, Fan ST, Chan KL, Gong Z, Hu Y, Lin Z, Wang G, Zhang Q, Barber TD, Chou WC, Aggarwal A, Hao K, Zhou W, Zhang C, Hardwick J, Buser C, Xu J, Kan Z, Dai H, Mao M, Reinhard C, Wang J, Luk JM. Genome-wide survey of recurrent HBV integration in hepatocellular carcinoma. Nature Genetics. 2012 44(7):765-9.
  • Khor CC, Chau TN, Pang J, Davila S, Long HT, Ong RT, Dunstan SJ, Wills B, Farrar J, Van Tram T, Gan TT, Binh NT, Tri le T, Lien le B, Tuan NM, Tham NT, Lanh MN, Nguyet NM, Hieu NT, Van N Vinh Chau N, Thuy TT, Tan DE, Sakuntabhai A, Teo YY, Hibberd ML, Simmons CP. Genome- wide association study identifi es susceptibility loci for dengue shock syndrome at MICB and PLCE1. Nature Genetics. 2011;43(11):1139-41.
  • Davila S, Wright VJ, Khor CC, Sim KS, Binder A, Breunis WB, Inwald D, Nadel S, Betts H, Carrol ED, de Groot R, Hermans PW, Hazelzet J, Emonts M, Lim CC, Kuijpers TW, Martinon-Torres F, Salas A, Zenz W, Levin M, Hibberd ML; International Meningococcal Genetics Consortium. Genome- wide association study identifies variants in the CFH region associated with host susceptibility to meningococcal disease. Nature Genetics. 2010;42(9):772-6.
  • Zhang FR, Huang W, Chen SM, Sun LD, Liu H, Li Y, Cui Y, Yan XX, Yang HT, Yang RD, Chu TS, Zhang C, Zhang L, Han JW, Yu GQ, Quan C, Yu YX, Zhang Z, Shi BQ, Zhang LH, Cheng H, Wang CY, Lin Y, Zheng HF, Fu XA, Zuo XB, Wang Q, Long H, Sun YP, Cheng YL, Tian HQ, Zhou FS, Liu HX, Lu WS, He SM, Du WL, Shen M, Jin QY, Wang Y, Low HQ, Erwin T, Yang NH, Li JY, Zhao X, Jiao YL, Mao LG, Yin G, Jiang ZX, Wang XD, Yu JP, Hu ZH, Gong CH, Liu YQ, Liu RY, Wang DM, Wei D, Liu JX, Cao WK, Cao HZ, Li YP, Yan WG, Wei SY, Wang KJ, Hibberd ML, Yang S, Zhang XJ, Liu JJ. Genomewide association study of leprosy. New England Journal of Medicine. 2009;361(27):2609-18.
  • Chen SL, Hung CS, Pinkner JS, Walker JN, Cusumano CK, Li Z, Bouckaert J, Gordon JI, Hultgren SJ. "Positive selection identifies an in vivo role for FimH during urinary tract infection in addition to mannose binding." Proc Natl Acad Sci U S A. 2009 Dec 29;106(52):22439-44.
  • Ruan YJ, Wei CL, Ee AL, Vega VB, Thoreau H, Su ST, Chia JM, Ng P, Chiu KP, Lim L, Zhang T, Peng CK, Lin EO, Lee NM, Yee SL, Ng LF, Chee RE, Stanton LW, Long PM, Liu ET. Comparative full-length genome sequence analysis of 14 SARS coronavirus isolates and common mutations associated with putative origins of infection. Lancet. 2003;361(9371):1779-85.