Bacteria as control engineers

Fructose-enabled killing of antibiotic-resistant Salmonella enteritidis by gentamicin: Insight from reprogramming metabolomics

Salmonella enterica is a food-borne pathogen that poses a severe threat to both poultry production and human health. Antibiotics are critical for the initial treatment of bacterial infections. However, the overuse and misuse of antibiotics results in the rapid evolution of antibiotic-resistant bacteria, and the discovery and development of new antibiotics are declining. Therefore, understanding antibiotic resistance mechanisms and developing novel control measures are essential. In the present study, GC-MS-based metabolomics analysis was performed to determine the metabolic profile of gentamicin sensitive (SE-S) and resistant (SE-R) S. enterica. Fructose was identified as a crucial biomarker. Further analysis demonstrated a global depressed central carbon metabolism and energy metabolism in SE-R. The decrease in the pyruvate cycle reduces the production of NADH and ATP, causing a decrease in membrane potential, which contributes to gentamicin resistance. Exogenous fructose potentiated the effectiveness of gentamicin in killing SE-R by promoting the pyruvate cycle, NADH, ATP and membrane potential, thereby increasing gentamicin intake. Further, fructose plus gentamicin improved the survival rate of chicken infected with gentamicin-resistant Salmonella in vivo. Given that metabolite structures are conserved across species, fructose identified from bacteria could be used as a biomarker for breeding disease-resistant phenotypes in chicken. Therefore, a novel strategy is proposed for fighting against antibiotic-resistant S. enterica, including exploring molecules suppressed by antibiotics and providing a new approach to find pathogen targets for disease resistance in chicken breeding.

Engineering and control of biological systems: A new way to tackle complex diseases

The ongoing merge between engineering and biology has contributed to the emerging field of synthetic biology. The defining features of this new discipline are abstraction and standardisation of biological parts, decoupling between parts to prevent undesired cross-talking, and the application of quantitative modelling of synthetic genetic circuits in order to guide their design. Most of the efforts in the field of synthetic biology in the last decade have been devoted to the design and development of functional gene circuits in prokaryotes and unicellular eukaryotes. Researchers have used synthetic biology not only to engineer new functions in the cell, but also to build simpler models of endogenous gene regulatory networks to gain knowledge of the "rules" governing their wiring diagram. However, the need for innovative approaches to study and modify complex signalling and regulatory networks in mammalian cells and multicellular organisms has prompted advances of synthetic biology also in these species, thus contributing to develop innovative ways to tackle human diseases. In this work, we will review the latest progress in synthetic biology and the most significant developments achieved so far, both in unicellular and multicellular organisms, with emphasis on human health.

Construction and modelling of an inducible positive feedback loop stably integrated in a mammalian cell-line

Understanding the relationship between topology and dynamics of transcriptional regulatory networks in mammalian cells is essential to elucidate the biology of complex regulatory and signaling pathways. Here, we characterised, via a synthetic biology approach, a transcriptional positive feedback loop (PFL) by generating a clonal population of mammalian cells (CHO) carrying a stable integration of the construct. The PFL network consists of the Tetracycline-controlled transactivator (tTA), whose expression is regulated by a tTA responsive promoter (CMV-TET), thus giving rise to a positive feedback. The same CMV-TET promoter drives also the expression of a destabilised yellow fluorescent protein (d2EYFP), thus the dynamic behaviour can be followed by time-lapse microscopy. The PFL network was compared to an engineered version of the network lacking the positive feedback loop (NOPFL), by expressing the tTA mRNA from a constitutive promoter. Doxycycline was used to repress tTA activation (switch off), and the resulting changes in fluorescence intensity for both the PFL and NOPFL networks were followed for up to 43 h. We observed a striking difference in the dynamics of the PFL and NOPFL networks. Using non-linear dynamical models, able to recapitulate experimental observations, we demonstrated a link between network topology and network dynamics. Namely, transcriptional positive autoregulation can significantly slow down the “switch off” times, as comparared to the nonautoregulatated system. Doxycycline concentration can modulate the response times of the PFL, whereas the NOPFL always switches off with the same dynamics. Moreover, the PFL can exhibit bistability for a range of Doxycycline concentrations. Since the PFL motif is often found in naturally occurring transcriptional and signaling pathways, we believe our work can be instrumental to characterise their behaviour.

Synthetic Biology aims at designing and building new biological functions in living organisms. At the same time, Synthetic Biology approaches can be used to uncover the design principles of natural biological systems through the rational construction of simplified regulatory networks. Mathematical models of the networks are then derived from physical considerations and can be used to explain the observed dynamical behaviours. We have characterised a regulatory motif often found in transcriptional and signalling pathways. We constructed a positive feedback loop motif in mammalian cells, consisting of a protein controlling its own expression. We have shown that this motif exhibits a dynamic behaviour which is very different from that obtained when the autoregulation is removed. This difference is intrinsic to the specific wiring diagram chosen by the cell to control its behaviour (feedback versus non-feedback configurations), and can be instrumental in understanding the complex network of regulation occurring in a cell.