Overview of Enabling Technologies in the Life Sciences Professor Andrew Pitt, Aston University, Birmingham, UK
Overview of Enabling Technologies in the Life Sciences Convergence Professor Andrew Pitt, Aston University, Birmingham, UK
Overview of Enabling Technologies in the Life Sciences Convergence of Biology and Chemistry...... and Engineering and Mathematics...... and Computer Science and Technology... Professor Andrew Pitt, Aston University, Birmingham, UK
Recent changes in perspective Fundamental changes in research drivers - Personalized medicine - Heterogeneity of disease one aetiology, many faces - Healthcare no longer the main driver Climate change and food security Energy Environment Global economy Changing disease demographics - Ageing populations: e.g. resurgence of neurosciences - Quality of life issues - Third world diseases becoming first world problem -Costs
Advances in technologies in the life sciences Moving on from the post-genomic era the new genomics era driven by new technology better awareness of biological complexity useful predictive models of biology systems biology Many more biological molecules now finding their way into the pharmaceutical arsenal use of biological agents to modulate biology a reality significant advances in the bulk production of biological agents advances in the delivery of biological agents (peptides, proteins, DNA) to biological systems (usually based on nanotechnology) Designer proteins and protein binding agents Effective protein engineering New detection technologies (e.g. peptide aptamers, SOMAmers, etc)
Advances in technologies in the life sciences Moving on from the post-genomic era the new genomics era driven by new technology better awareness of biological complexity useful predictive models of biology systems biology Many more biological molecules now finding their way into the pharmaceutical arsenal use of biological agents to modulate biology a reality significant advances in the bulk production of biological agents advances in the delivery of biological agents (peptides, proteins, DNA) to biological systems (usually based on nanotechnology) Designer proteins and protein binding agents Effective protein engineering New detection technologies (e.g. peptide aptamers, SOMAmers, etc)
Advances in technologies in the life sciences Common use of genetic modulation (targeting genes) - RNAi, sirna, stable transfection, gene therapy Rapid decrease in the cost and availability of synthetic oligonucleotides - Routine gene synthesis feasible genome synthesis Ability to effectively engineer biology - Synthetic biology Effective application of microengineering - miniaturization, portability (power), distributed networks (mobile phones) New approaches to understanding biology enabled by new technologies Systems biology, Functional genomics Deciphering of biological networks
Advances in technologies in the life sciences Common use of genetic modulation (individual genes) - RNAi, sirna, stable transfection, gene therapy Rapid decrease in the cost and availability of synthetic oligonucleotides - Routine gene synthesis feasible genome synthesis Ability to effectively engineer biology - Synthetic biology Effective application of microengineering - miniaturization, portability (power), distributed networks (mobile phones), diagnostics New approaches to understanding biology enabled by new technologies Systems biology, Functional genomics Deciphering of biological networks
Drive to identify biomarkers: a measurable indicator of a biological state Interleukin 6 homocysteine Molecular Physical Observational Genetic Focus on molecular biomarkers that can be used to characterize: normal biological processes pathogenic processes, especially early markers, diagnosis, prognosis specific responses to intervention Requires rapid, sensitive, multiplexed analysis and powerful statistics (Re)discovering that biology is much more heterogeneous than we thought
Drive to identify biomarkers: a measurable indicator of a biological state Interleukin 6 homocysteine Molecular Physical Observational Genetic Focus on molecular biomarkers that can be used to characterize: normal biological processes pathogenic processes, especially early markers, diagnosis, prognosis specific responses to intervention Requires rapid, sensitive, multiplexed analysis and powerful statistics (Re)discovering that biology is much more heterogeneous than we thought
Watchpoints Systems to Synthetic biology Genome sequencing and DNA synthesis Protein engineering Directed delivery systems for biological agents
Systems Biology Construction of predictive models of biology from molecules to ecosystems Enables rational engineering of biological systems (model: prediction: biological validation: refine) cycle complex and time consuming - identifies where models do not fit - leads to new discoveries. Developing enabling stochastic and multiscale modelling (molecule-cell-tissue-organ-organism-ecosystem) Enabled by data rich post-genomic technologies, high power computing, scientific collaboration, faster/cheaper biological data collection, www. analyze my data.com
We still don t have a full model 211 reactions and 322 components that take part in them 202 proteins, 3 ions, 21 small molecules, 73 oligomers, 7 genes, 7 RNAs but already providing biological insight Oda, K., Matsuoka, Y., Funahashi, A. & Kitano, H., Molecular Systems Biology 1:2005.0010
Computational power: distributed Computing Supercomputer power from low level computing Easy access to required hardware over internet GPUs particularly suited to many calculations Applicable to many complex computational problems Grid computing architectures Folding@home Cells@home POEM@home Rosetta@home. (>50 projects) Folding@home - 426,787 processors (Feb 2012) 6.588 petaflop/s (IBM Sequoia, 16.32 petaflop/s)
Synthetic Biology Generation of new biological entities by the engineering of organisms or intervention in biological processes Use non-biological molecules to generate life in vivo application of systems biology Enabled by DNA synthesis and delivery Understanding biological pathways and control systems Generation of cell-like self-assembling physical systems Computational modelling
Synthetic Biology huge potential suppressed a step in the pathway that allows yeast to make sterols from farnesyl pyrophosphate (FPP) added a gene from the wormwood plant itself, encoding the enzyme that converts FPP to amorphadiene. identified another enzyme from A. annua (P450 family) which oxidises amorphadiene to artemisinic acid "Engineering a mevalonate pathway in Escherichia coli for production of terpenoids," by Vincent J. J. Martin, Douglas J. Pitera, Sydnor T. Withers, Jack D. Newman, and Jay D. Keasling, Nature Biotechnology, 1 July 2003. Competitive with breeding programmes for Artemesia
Synthetic Biology Bacterium Genetic engineering Systems biology Synthetic biology Yeast Solar powered chemical plant Insect
Next generation Genomics Technologies Next-(next)-generation sequencing massively parallel, extremely rapid, high fidelity easy genomes Concomitant decreasing cost of DNA synthesis Easy access to DNA tools Genetic regulation Non-coding DNA and RNA Epigenetic information Small samples (single cell sampling) Can isolate small numbers of cells (LMD, FACS, etc) and now have sensitivity and speed to analyze whole (or parts of) cells Direct sampling without expansion (growth of bacteria, etc)
Genomics From GOLD: www.genomesonline.org
The new genomics revolution High throughput next generation sequencing has completely changed the landscape New breakthroughs offer real-time single molecule sequencing - reduce data collection time to hours The $1000 human genome is just round the corner
The new genomics revolution What does it provide? Rapid genotyping identification of organisms, personalized medicine (susceptibility genome wide association studies) Potential for phenotyping link to characteristics Rapid identification of pathogenicity factors e.g. virulence Understanding of biological paradigms, e.g. drug resistance Genetic manipulation; insertion/modulation of pathways cheap and easy Genome synthesis build a bug
Prediction of Protein Structure and Design of New Entities Many toxin structures available (>1400 toxins, mutants or toxin binding on RCSB) Mechanisms of action known for most Principles of protein structure prediction improving Proof of concept for chimeric toxins PA 63 The finding also points to a possible way to design anthrax toxin molecules that selectively attack tumor cells,. 2004 Leppla 2008
New biology does not make a drug or a weapon Ricin: weapon of choice? is this a battlefield? Nanomaterial and nanoparticle technologies for targeted delivery of chemical and biological agents Focus on smart delivery systems - many of these systems are self assembling (and disassembling) and can be made responsive to environment - transdermal and aerosol delivery - neurological targetting
When is Control Required/Justified? High level science openly available but is it enough in itself: is biology simple enough to manipulate easily? Only by dissemination can we get input of wider community and raise community awareness of dual use issues Validation/peer review is vital to identify relevance An open policy will allow us to stay ahead of the terrorists; including Nature How best to police the biology (e.g. DNA synthesis)
Watchpoints Systems to Synthetic biology Genome sequencing and DNA synthesis Protein engineering Directed delivery systems for biological agents