Our group expertise is in computational protein sequence and structure analysis to predict various aspects of molecular and cellular functions (enzymatic activities, posttranslational modifications, cleavage, translocation signals, 3D structures, effects of mutations, phylogenetic relationships, cellular pathways etc.) for discovering the molecular mechanisms of biological and clinical phenotypes and experimental validation together with collaborators. Our repertoire of computational analysis methods is applicable and useful in multiple research areas but our main focus currently is on infectious diseases, human mutations, allergy and enzyme function prediction.
One of our traditional strongholds since the swine flu in 2009 is infectious disease research. Our FluSurver (https://flusurver.bii.a-star.edu.sg/) is the most complete one-stop influenza mutation analysis tool being used by researchers and surveillance experts globally. We have several published and ongoing projects with the WHO CC in Australia and National Influenza Centres relating to influenza drug resistance, viral fitness, host specificity and antigenic changes. The FluSurver is also a primary analysis tool for the global data science initiative GISAID, the most complete influenza database used by WHO flu surveillance networks. BII/A*STAR has been a technical and scientific partner to GISAID for several years providing analysis tools.
When the new coronavirus was discovered by Chinese colleagues, the sequences were shared using GISAID’s platform on January 10th 2020 (https://gisaid.org). Since it was a new virus, this required a new database system to be designed and built, as well as a new workflow to curate and release sequences. GISAID called on the Singapore team to help. In addition to the expert advice contributing to build the new system and annotation tools like the CoVsurver (https://gisaid.org/covsurver), the Singapore team has been critical in processing the incoming genomes with quality checks and analysis reports since the beginning and was reinforced soon by more international colleagues. This has enabled global genome sharing from the first day to over 16 million genomes from 215 countries and territories by 2023, earning the WHO Chief Scientist’s commendation of GISAID as a “game changer”. (Swaminathan, Nature 2020). This had significant impact for Singapore and the world. Diagnostics, drugs, and vaccine development were started based on sequences in GISAID and are constantly checked with new incoming data if they are still working well and help to identify new variants. In Singapore, BII has become a hub for multiple institutions and agencies to access and benefit from the GISAID work, from other A*STAR colleagues to NPHL/NCID, MOH, Duke-NUS, hospitals and DSO.
Because we can quickly go from genomes to protein structures through modelling in our computers often only requiring the new sequences as input, our group offers powerful support in infectious disease surveillance and rapid outbreak investigations to get a quick handle on bugs here and around the world. Besides Influenza and hCoV-19, we also helped characterizing MERS, Ebola, HIV, Noro, Adeno, RSV, Hepatitis C, West Nile, Dengue and Zika viruses. Through close collaboration with the National Public Health Laboratory at the National Centre for Infectious Diseases of the Ministry of Health we contribute our knowledge and computational expertise at the national frontline for infectious disease surveillance.
We aim at bridging the gap from nucleotide variation to protein structures to interpret effects of human mutations. For example, we have helped clinical collaborators to analyze variants found in patients and tried to mechanistically explain their possible role in a range of diseases like cancer, myopia, leprosy or atopic dermatitis. We are participating in the National Precision Medicine Programme to help mapping mutations into 3D protein structures relative to drug binding sites supporting our colleagues at GIS, LKC and PRECISE.
Multinational Procter & Gamble and BII have jointly developed animal-testing-free Bioinformatics techniques for assessing the allergy potential of proteins using their amino acid sequence and tertiary structure (https://research.a-star.edu.sg/articles/highlights/predicting-protein-allergens-accurately/) with AllerCatPro (https://allercatpro.bii.a-star.edu.sg/). Our team, together with the Singapore Institute of Food and Biotechnology Innovation (SIFBI), NTU FRESH and James Cook University, apply AllerCatPro to the safety assessment of proteins found in novel foods, such as those replacing meat with alternative protein sources including as advisor to the Singapore Food Authority. In other notable projects with SIFBI and other institutes often including industry collaborations, we are applying our sequence function and pathway analysis capabilities to support the Natural Product Library, Biotransformation and Synthetic Biology programmes as well as the Pharma Innovation Programme Singapore.
Sebastian Maurer-Stroh studied theoretical biochemistry at the University of Vienna and wrote his master and PhD thesis at the Institute of Molecular Pathology (IMP). After FEBS and Marie Curie fellowships at the VIB-SWITCH lab in Brussels, he has been leading a group of experts in protein sequence analysis as a senior principal investigator in the A*STAR Bioinformatics Institute (BII) since 2007. He is Executive Director of BII since January 2021. His protein function analysis skills are supporting A*STAR’s efforts at the public-private interface and through computational analysis and modelling his team is critically contributing to national and global viral pathogen surveillance. He is also adjunct Professor at the National University of Singapore (NUS) and infectious disease expert for A*STAR ID labs and the National Public Health Laboratory of the Ministry of Health, Singapore.
Sebastian Maurer-Stroh's research interests lies in mapping the uncharted islands in functional protein sequence space. This includes inferring functions for uncharacterized genes/proteins based on remote evolutionary relationships, prediction of the 3-dimensional structure of proteins, identification of biologically important residues and disease-related mutations, as well as developing predictors for short functional motifs in protein sequences.
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