Our research focus is on the discovery of new biomolecular mechanisms from biological and medical data and especially the functional characterization of yet uncharacterized genes and pathways with theoretical/computational methods. Dramatic recent improvements of nucleic acid sequencing technologies enhance the prospect of general availability of genomes from patients, patient-specific pathogens and of gene expression data. This development has profound implications for life science research and biomedical applications. As biomolecular sequencing is becoming the most informative as well as most readily available research technologies in life sciences, sequence analysis and sequence-based structure and function prediction will be more important than ever.
Typically, a project starts with sets of uncharacterized sequences, expression profiles or other type of omics data associated with known phenotypes where the driving biomolecular mechanism is sought. Most of the work is with internal and/or external collaborators, also including partners in clinics (e.g., 34863649 + 34903892 – PubMed IDs here and below) and biotech/pharma industry (e.g., MeshBio in Singapore). The work with clinical data motivated us to discuss the problem of access to patient data for biomedical research from three different perspectives: patients’, clinicians’ and researchers’ (33717311).
Unknown function of genomic regions will plague mankind for at least a century to come (22849370 + 30265449). Though it is generally believed that full human genome sequencing was a watershed event in human history that boosted biomedical research, biomolecular mechanism discovery and life science applications, there is no sign that biomolecular mechanism discovery happens at a faster pace than before. The opposite is true: Researchers in the field of genome annotation see that there is a persisting, substantial body of functionally insufficiently or completely not characterized genes (for example, ~10,000 protein-coding in the human genome) despite the availability of full genome sequences. A survey of the biomedical literature shows that the number of reported new protein functions had been steadily growing until 2000 but the trend reversed to a dramatic decline thereafter when, at the same time, the annual amount of new life science publications doubled between 2000 and 2017. So, the group is active on a fertile ground with lots of discovery potential.
Applications reach into medical data analysis, natural product, aging, and rare diseases research. Our success stories include the discovery of the SET domain methyltransferases (PMID: 10949293), ATGL (15550674), kleisins (12667442), many new protein domain functions and functional sequence patterns (for example in the GPI lipid anchor biosynthesis pathway such as the peptide synthetase activity of GPAA1 (24743167)). We discovered a new membrane-embedded protein domain evolutionarily multiplied in the GPI lipid anchor pathway proteins, BindGPILA (29764287). It functions as the unit for recognizing, binding and stabilizing the GPI lipid anchor in a modification-competent form.
Together with collaborators, we discovered that the dysfunction of the human gene SUGCT contributes to gut microbiota dysbiosis, leading to age-dependent pathological changes in kidney, liver, and adipose tissue (31722069). We contributed to the development of AllerCatPro, a tool that predicts the allergenic potential of proteins based on the similarity of their 3D structure as well as their amino acid sequence to a data set of known protein allergens (30657872). Both projects were carried out in collaboration with S. Maurer-Stroh’s team. In several cases, this research effort has involved the development of algorithms and software for biomolecular sequence, omics, clinical and other life science data analysis. Examples are PTM (GPI lipid anchoring, myristoylation, prenylation, phosphorylation) and subcellular localization prediction tools for proteins (e.g., 20221930, 20221930, 19029837, and 15575971), a sophisticated ANNOTATOR software suite for protein function discovery from sequence (27115649) or NSC, the highly cited molecular surface computation algorithm (J. Comp. Chem. 16 pp. 273-284). The collaboration with the G. Grüber crystallography lab (NTU, Singapore) resulted in a string of discoveries with regard to the structure, catalytic mechanism and sequence architecture significance of the AhpF/AhpC alkyl hydroperoxide reductase complex by studies of mutated versions of AhpF/AhpC (31047989 and references therein). The team is involved in both academic and industry-funded projects in collaboration with the A*STAR Natural Organism Library (teams of Ng Siew Bee, Y. Kanagasundaram, and P. Arumugam) (29979661). Recently, an analog of Anthracimycin, an antibiotic that, so far, is only known to be produced by Streptomyces species, was predicted and verified to be produced by Nocardiopsis kunsanensis, a non-Streptomyces actinobacterial microorganism (29805716). Together with the BII NOL team, we discovered a new cyclic lipodepsipeptide, BII-Rafflesfungin, possessing antifungal activity that is produced by fungus Phoma sp. F3723 (31088369). We identified a biosynthetic gene cluster compatible with the production of this new compound and proposed a mechanism for its biosynthesis.
Frank Eisenhaber studied mathematics at the Humboldt-University in Berlin and biophysics and medicine at the Pirogov Medical University in Moscow. He received the PhD in molecular biology from the Engelhardt Institute of Molecular Biology in Moscow 1988. After postdoctoral work at the Institute of Molecular Biology in Berlin-Buch and at the EMBL in Heidelberg, he worked as bioinformatics teamleader and head of the general IT department at the Institute of Molecular Pathology (IMP) in Vienna (1999-2007). He joined the Bioinformatics Institute A*STAR Singapore in August 2007 and was its Executive Director from 2007 to 2020.
Frank Eisenhaber’s research interest is focused on the discovery of new biomolecular mechanisms from biological and medical data and the functional characterization of yet uncharacterized genes and pathways. As mechanistic insight is the driver for biotechnology, biomedical and clinical applications, this work has catalyzed various lines of applied research. Frank Eisenhaber is one of the scientists credited with the discovery of the SET domain methyltransferases, ATGL, kleisins, many new protein domain functions (for example in the GPI lipid anchor biosynthsis pathway), with the development of accurate prediction tools for posttranslational modifications and subcellular localizations and with algorithms for omics data analysis.
Birgit Eisenhaber’s research interest is focused on the discovery of molecular functions of previously uncharacterized protein coding genes. She is interested in proteins’ posttranslational modifications with a special focus on lipid anchor modifications. Birgit Eisenhaber studied biocybernetics and medicine at the Pirogov Medical University in Moscow. After working as a professional software developer, she restarted her scientific career at the EMBL Heidelberg. She obtained her Ph.D. from Humboldt University Berlin. Subsequently, she worked as a postdoctoral research fellow at the Institute of Molecular Pathology (IMP) Vienna and at the Experimental Therapeutics Centre (ETC) Singapore. In December 2010, Birgit Eisenhaber was appointed as a Principal Investigator at the Bioinformatics Institute (BII) Singapore.
Birgit is part of the Gene Function Prediction group that is focused on the prediction of molecular and cellular functions of genes and proteins based on the theoretical analysis of biomolecular sequences, expression profiles and other omics high-throughput data.
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