Tuning gene expression to changing environments: from rapid responses to evolutionary adaptation

The role of predictive modelling in rationally re-engineering biological systems

Technologies to synthesize and transplant a complete genome into a cell have opened limitless potential to redesign organisms for complex, specialized tasks. However, large-scale re-engineering of a biological circuit will require systems-level optimization that will come from a deep understanding of operational relationships among all the constituent parts of a cell. The integrated framework necessary for conducting such complex bioengineering requires the convergence of systems and synthetic biology. Here, we review the status of these rapidly developing interdisciplinary fields of biology and provide a perspective on plausible venues for their merger.

Mitochondria and metazoan epigenesis

In eukaryotes, mitochondrial activity controls ATP production, calcium dynamics, and redox state, thereby establishing physiological parameters governing the transduction of biochemical signals that regulate nuclear gene expression. However, these activities are commonly assumed to fulfill a 'housekeeping' function: necessary for life, but an epiphenomenon devoid of causal agency in the developmental flow of genetic information. Moreover, it is difficult to perturb mitochondrial function without generally affecting cell viability. For these reasons little is known about the extent of mitochondrial influence on gene activity in early development. Recent discoveries pertaining to the redox regulation of key developmental signaling systems together with the fact that mitochondria are often asymmetrically distributed in animal embryos suggests that they may contribute spatial information underlying differential specification of cell fate. In many cases such asymmetries correlate with localization of genetic determinants (i.e., mRNAs or proteins), particularly in embryos that rely heavily on cell-autonomous means of cell fate specification. In such embryos the localized genetic determinants play a dominant role, and any developmental information contributed by the mitochondria themselves is likely to be less obvious and more difficult to isolate experimentally. Hence, 'regulative' embryos that make more extensive use of conditional cell fate specification are better suited to experimental investigation of mitochondrial impacts on developmental gene regulation. Recent studies of the sea urchin embryo, which is a paradigmatic example of such a system, suggest that anisotropic distribution of mitochondria provides a source gradient of spatial information that directs epigenetic specification of the secondary axis via Nodal-Lefty signaling.

Functional models for large-scale gene regulation networks: realism and fiction

High-throughput experiments are shedding light on the topology of large regulatory networks and at the same time their functional states, namely the states of activation of the nodes (for example transcript or protein levels) in different conditions, times, environments. We now possess a certain amount of information about these two levels of description, stored in libraries, databases and ontologies. A current challenge is to bridge the gap between topology and function, i.e. developing quantitative models aimed at characterizing the expression patterns of large sets of genes. However, approaches that work well for small networks become impossible to master at large scales, mainly because parameters proliferate. In this review we discuss the state of the art of large-scale functional network models, addressing the issue of what can be considered as "realistic" and what the main limitations may be. We also show some directions for future work, trying to set the goals that future models should try to achieve. Finally, we will emphasize the possible benefits in the understanding of biological mechanisms underlying complex multifactorial diseases, and in the development of novel strategies for the description and the treatment of such pathologies.

Synthetic control of a fitness tradeoff in yeast nitrogen metabolism

BACKGROUND

Microbial communities are involved in many processes relevant to industrial and medical biotechnology, such as the formation of biofilms, lignocellulosic degradation, and hydrogen production. The manipulation of synthetic and natural microbial communities and their underlying ecological parameters, such as fitness, evolvability, and variation, is an increasingly important area of research for synthetic biology.

RESULTS

Here, we explored how synthetic control of an endogenous circuit can be used to regulate a tradeoff between fitness in resource abundant and resource limited environments in a population of Saccharomyces cerevisiae. We found that noise in the expression of a key enzyme in ammonia assimilation, Gdh1p, mediated a tradeoff between growth in low nitrogen environments and stress resistance in high ammonia environments. We implemented synthetic control of an endogenous Gdh1p regulatory network to construct an engineered strain in which the fitness of the population was tunable in response to an exogenously-added small molecule across a range of ammonia environments.

CONCLUSION

The ability to tune fitness and biological tradeoffs will be important components of future efforts to engineer microbial communities.

A high-throughput assay for siRNA-based circadian screens in human U2OS cells

The advent of siRNA-based screens has revolutionized the efficiency by which functional components of biological processes are identified. A notable exception has been the field of mammalian circadian rhythms. Here, we outline a medium- to high-throughput siRNA-based approach that, in combination with real-time bioluminescence measurement of a circadian reporter gene, can be utilized to elucidate the effects of gene knockdown across several days in human cells.