SynBioFromLeukipposInstitute

Escherichia coli (E. coli) has played a pivotal role in the development of genetics and molecular biology as scientific fields. It is therefore not surprising that synthetic biology (SB) was built upon E. coli and continues to dominate the field. However, scientific capabilities have advanced from simple gene mutations to the insertion of rationally designed, complex synthetic circuits and creation of entirely synthetic genomes. The point is rapidly approaching where E. coli is no longer an adequate host for the increasingly sophisticated genetic designs of SB. It is time to develop the next generation of SB chassis; robust organisms that can provide the advanced physiology novel synthetic circuits will require to move SB from the laboratory into fieldable technologies. This can be accomplished by developing chassis-specific genetic toolkits that are as extensive as those for E. coli. However, the holy grail of SB would be the development of a universal toolkit that can be ported into any chassis. This viewpoint article underscores the need for new bacterial chassis, as well as discusses some of the important considerations in their selection. It also highlights a few examples of robust, tractable bacterial species that can meet the demands of tomorrow’s state-of-the-art in SB. Significant advances have been made in the first 15 years since this field has emerged. However, the advances over the next 15 years will occur not in laboratory organisms, but in fieldable species where the potential of SB can be fully realized in game changing technology.

Infectious diseases outpace all other causes of death in low-income countries, posing global health risks, laying stress on healthcare systems and societies, and taking an avoidable human toll. One solution to this crisis is early diagnosis of infectious disease, which represents a powerful way to optimize treatment, increase patient survival rate, and decrease healthcare costs. However, conventional early diagnosis methods take a long time to generate results, lack accuracy, and are known to seriously underperform with regard to fungal and viral infections. Synthetic biology offers a fast and highly accurate alternative to conventional infectious disease diagnosis. In this review, we outline obstacles to infectious disease diagnostics and discuss two emerging alternatives: synthetic viral diagnostic systems and biosensors. We argue that these synthetic biology-based approaches may overcome diagnostic obstacles in infectious disease and improve health outcomes.

INTRODUCTION
Genetic interactions occur when mutations in two or more genes combine to generate an unexpected phenotype. An extreme negative or synthetic lethal genetic interaction occurs when two mutations, neither lethal individually, combine to cause cell death. Conversely, positive genetic interactions occur when two mutations produce a phenotype that is less severe than expected. Genetic interactions identify functional relationships between genes and can be harnessed for biological discovery and therapeutic target identification. They may also explain a considerable component of the undiscovered genetics associated with human diseases. Here, we describe construction and analysis of a comprehensive genetic interaction network for a eukaryotic cell.
RATIONALE
Genome sequencing projects are providing an unprecedented view of genetic variation. However, our ability to interpret genetic information to predict inherited phenotypes remains limited, in large part due to the extensive buffering of genomes, making most individual eukaryotic genes dispensable for life. To explore the extent to which genetic interactions reveal cellular function and contribute to complex phenotypes, and to discover the general principles of genetic networks, we used automated yeast genetics to construct a global genetic interaction network.
RESULTS
We tested most of the ~6000 genes in the yeast Saccharomyces cerevisiae for all possible pairwise genetic interactions, identifying nearly 1 million interactions, including ~550,000 negative and ~350,000 positive interactions, spanning ~90% of all yeast genes. Essential genes were network hubs, displaying five times as many interactions as nonessential genes. The set of genetic interactions or the genetic interaction profile for a gene provides a quantitative measure of function, and a global network based on genetic interaction profile similarity revealed a hierarchy of modules reflecting the functional architecture of a cell. Negative interactions connected functionally related genes, mapped core bioprocesses, and identified pleiotropic genes, whereas positive interactions often mapped general regulatory connections associated with defects in cell cycle progression or cellular proteostasis. Importantly, the global network illustrates how coherent sets of negative or positive genetic interactions connect protein complex and pathways to map a functional wiring diagram of the cell.
CONCLUSION
A global genetic interaction network highlights the functional organization of a cell and provides a resource for predicting gene and pathway function. This network emphasizes the prevalence of genetic interactions and their potential to compound phenotypes associated with single mutations. Negative genetic interactions tend to connect functionally related genes and thus may be predicted using alternative functional information. Although less functionally informative, positive interactions may provide insights into general mechanisms of genetic suppression or resiliency. We anticipate that the ordered topology of the global genetic network, in which genetic interactions connect coherently within and between protein complexes and pathways, may be exploited to decipher genotype-to-phenotype relationships.

The base pair d5SICS·dNaM was recently reported to incorporate and replicate in the DNA of a modified strain of Escherichia coli, thus making the world’s first stable semisynthetic organism. This newly expanded genetic alphabet may allow organisms to store considerably more information in order to translate proteins with unprecedented enzymatic activities. Importantly, however, there is currently no knowledge of the photochemical properties of d5SICS or dNaM—properties that are central to the chemical integrity of cellular DNA. In this contribution, it is shown that excitation of d5SICS or dNaM with near-visible light leads to efficient trapping of population in the nucleoside’s excited triplet state in high yield. Photoactivation of these long-lived, reactive states is shown to photosensitize cells, leading to the generation of reactive oxygen species and to a marked decrease in cell proliferation, thus warning scientists of the potential phototoxic side effects of expanding the genetic alphabet.