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From Omics to Systems Biology: Towards a More Complete Description and Understanding of Biology

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From Omics to Systems Biology: Towards a More Complete Description and Understanding of Biology First Words From omics to systems biology: towards a more complete description and understanding of biology reductionist approaches (for example, focusing on single genes and/or proteins) to generate data that is difficult to accommodate in the context of the biology of the organism being studied. And the reason for this is not that the science is flawed, it’s just that biological systems are complex and reductionist approaches, on Paul Chambers their own, do not deal well with complexity. Research Manager, The Australian Wine Research Institute What is meant by complexity in this context? The components PO Box 197, Glen Osmond SA 5064 of a biological system (for example, genes, proteins, metabolites www.awri.com.au and so on) function in networks and these networks interact [email protected] with each other. For example, a gene might be knocked out with little or no impact on a phenotype that, in other experiments, it has been shown to affect. This might be because other genes “If you try and take a cat apart to see how it works, the have compensated; there is often more than one route to a first thing you have on your hands is a non-working cat.” particular phenotype and the same gene can produce a different – Douglas Adams phenotype in different genetic backgrounds. Technology sets limits on what can be achieved in New technologies, the names of which are suffixed –omics research. The advent of genetic engineering accompanied (meaning a totality of some sort), are, however, enabling the by the development of monoclonal antibody technology development of holistic approaches in biological experiments. in the 1970s heralded the birth of modern ‘molecular High-throughput omics technologies provide the means of biology’. This revolutionised the way we approach capturing data on many genes (genomics and transcriptomics), research in the biological sciences by allowing access to proteins (proteomics), and/or metabolites (metabolomics and cellular structures and processes that were in the realm fluxomics) in a single experiment, making it possible to perform of science fiction a decade earlier. The invention of the global, holistic, analyses of biological systems. These approaches PCR in the 1980s built on this, making cloning easier and have emerged as a result of advances in high-throughput a great deal more rapid; with PCR we no longer required analytical technologies such as DNA sequencing and GC-MS, in a host and vector to amplify DNA and isolate targeted parallel with phenomenal growth in computing power, which DNA sequences. provides the means of capturing, storing and processing the The pathway to a PhD in the life sciences over this period (and massive datasets generated in omics experiments. up until today) was commonly to utilise the above technologies This edition of Microbiology Australia provides a snapshot of to focus on a gene, a protein or a biochemical reaction, in an some of the omics approaches that are being used in Australian attempt to describe it in the finest detail. This proved to be microbiology research. Anthony Borneman and Eveline a very powerful approach and led to many great advances in Bartowsky show how the adoption of comparative genomics is science; whilst early 20th century science was dominated by shedding light on the genetics of an industrially important lactic developments in physics, the second half was for the biological acid bacterium, Oenococcus oeni. This bacterium is very difficult, sciences. if not impossible, to transform and, therefore, is not amenable If, however, scientific journals were more accepting of high- to standard molecular biology approaches. Genomics requires quality experimental work that delivers negative or puzzling few of the tools of the genetics laboratory and is not reliant on results, we might get a truer picture of the backdrop to cloning technologies. Therefore, even the most intractable of this pioneering work. It is not unusual when using classical organisms is fair game. MICROBIOLOGY AUSTRALIA • NOVEMBER 2011 141 First Words In the broader context of bacterial genetics, comparative which are specific to particular developmental stages in the life genomics is challenging our view of what constitutes a ‘species’ cycle of the parasite. This highlights the power of metabolomics in the prokaryotic world. When we talk about the genome of a “in assessing … metabolic flexibility of different parasite bacterial species we now often have to accommodate a very large developmental stages, in identifying new or unanticipated pan-genome (the sum of all the genes across the species) with a metabolic pathways, and in dissecting the mode of action of anti- core (the part of the genome that is common across the group) protozoal drugs.” Metabolomic approaches are thus uncovering that might be relatively modest. Horizontal gene transfer is the potential new drug targets for the treatment of diseases such as most likely explanation for this apparent mixing and matching malaria, leishmaniasis and Chagas disease. of genes in the pan-genome; promiscuity, it would seem, is the order of the day. Malcolm’s paper also highlights the importance of metabolic flux analysis to “allow a more accurate identification of potential Stuart Cordwell gives strong endorsement to the application drug targets, such as metabolic choke points, the further of proteomic approaches to research on bacteria and provides characterisation of parasite mutants and the analysis of a drug’s a historical perspective, which shows how far the field has mode of action”. Jens Krömer would endorse this. In his paper advanced over a relatively short period of time. In bacterial he posits that fluxomics is the only approach to “quantitatively proteomics, experiments can be designed that target an almost assess the metabolic phenotype in its ultimate form”. It measures complete proteome, including membrane proteins. Stuart “… reaction rates, or metabolic fluxes inside the cell that define reminds us that, despite the dogma from some who study the the material transfer rates from one metabolite pool to another macro-end of the biology scale, bacteria are not proteomically and from pathway to pathway”. He goes on to describes how simple. In fact, proteomic “MS-based approaches … applied to metabolic flux analysis is done. bacteria [have] identified high levels of complexity, particularly based around serine/threonine/tyrosine phosphorylation, N- and Ian Dawes et al., Traude Beilharz team and Cristian Varela et al. O-linked glycosylation, acetylation and protein cleavage.” describe how omics analysis is being used in a systems biology framework. As Ian Dawes rightly points out, “there are almost as Peter Solomon, in a comparative metabolomic analysis of the many definitions of systems biology as there are workers in the wheat fungal pathogen Stagonospora nodorum and a mutant field”. For the purposes of this editorial, however, I will borrow thereof, discovered it to have the potential to generate a from the Varela et al. paper, which sets out what is probably the mycotoxin, alternariol, which is reported to be carcinogenic and most ambitious aim of this growing field: “Systems biology seeks toxigenic. This finding was somewhat surprising because Peter was not looking for a mycotoxin at the time of conducting these to study the relationships and interactions between all processes experiments and S. nodorum was not known to produce such operating in a biological system and to integrate this information a thing; whilst this fungus is recognised as causing significant in order to understand how biological systems work”. For damage to crops, no one suspected it to be a potential threat to Traude’s team, systems biologists “imagine … a kind of ‘Google human health. Cell’, that allows us to look within the three dimensions of a cell for network connections from any biological angle, between Peter’s work highlights the potential for discovery when using DNA, RNA, protein and metabolites.” omics methodologies. Omics experiments generate very large datasets that carry new information on a range of fronts, with the All three of these authors use omics technologies and potential of generating new knowledge and research questions. Saccharomyces cerevisiae as their model organism; Ian, Traude Peter comments that, as a result of his discovery: and their teams are addressing questions of fundamental importance in the biological sciences, whereas Cristian and [studies] … are now ongoing to determine the prevalence colleagues are using systems-based approaches to develop of alternariol in Australian wheat fields, its mechanism of mathematical models for the design of new, improved, industrial synthesis in S. nodorum and whether or not S. nodorum yeast strains. And all three sing the praises of S. cerevisiae as the and other related fungal pathogens synthesise other harmful best of organisms for research in systems biology; when tackling mycotoxins. the level of complexity that confronts systems biologists, it is Malcolm McConville and colleagues give an overview of the best to start with a highly tractable and relatively simple model, power of metabolomics in dissecting central carbon metabolism and preferably a one for which we already have a great deal in protozoan human parasites. The authors describe discoveries of knowledge. S. cerevisiae fits this bill better than any other of novel metabolic bypasses in central metabolism, some of organism in the eukaryotic world. 142 MICROBIOLOGY AUSTRALIA • NOVEMBER 2011 First Words
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