On-line optimal input design increases the efficiency and accuracy of the modelling of an inducible synthetic promoter

Synthetic biology seeks to design biological parts and circuits that implement new functions in cells. Major accomplishments have been reported in this field, yet predicting a priori the in vivo behaviour of synthetic gene circuits is major a challenge. Mathematical models offer a means to address this bottleneck. However, in biology, modelling is perceived as an expensive, time-consuming task. Indeed, the quality of predictions depends on the accuracy of parameters, which are traditionally inferred from poorly informative data. How much can parameter accuracy be improved by using model-based optimal experimental design (MBOED)? To tackle this question, we considered an inducible promoter in the yeast S. cerevisiae. Using in vivo data, we re-fit a dynamic model for this component and then compared the performance of standard (e.g., step inputs) and optimally designed experiments for parameter inference. We found that MBOED improves the quality of model calibration by ∼60%. Results further improve up to 84% when considering on-line optimal experimental design (OED). Our in silico results suggest that MBOED provides a significant advantage in the identification of models of biological parts and should thus be integrated into their characterisation.This research was partially supported by EC funding H2020 FET OPEN 766840-COSY-BIO and a Royal Society of Edinburgh-MoST grant (to F.M.), EPSRC funding EP/P017134/1-CONDSYC (to L.B.) and Spanish MINECO, grant ref. AGL2015-67504-C3-2-R (to E.B.-C.).Peer reviewe

External Control of the GAL Network in S. cerevisiae: A View from Control Theory

While there is a vast literature on the control systems that cells utilize to regulate their own state, there is little published work on the formal application of control theory to the external regulation of cellular functions. This paper chooses the GAL network in S. cerevisiae as a well understood benchmark example to demonstrate how control theory can be employed to regulate intracellular mRNA levels via extracellular galactose. Based on a mathematical model reduced from the GAL network, we have demonstrated that a galactose dose necessary to drive and maintain the desired GAL genes' mRNA levels can be calculated in an analytic form. And thus, a proportional feedback control can be designed to precisely regulate the level of mRNA. The benefits of the proposed feedback control are extensively investigated in terms of stability and parameter sensitivity. This paper demonstrates that feedback control can both significantly accelerate the process to precisely regulate mRNA levels and enhance the robustness of the overall cellular control system

Indirizzi operativi per la sorveglianza clinica e ambientale della legionellosi nelle strutture sanitarie e assistenziali della Regione Puglia

La prima epidemia di legionellosi, verificatasi nel luglio del 1976 durante l'American Legion Annua/ Convention a Philadelphia, fece registrare oltre 200 casi con 34 decessi. Solo un anno più tardi, nei laboratori dei Centers far Disease Contrai and Prevention (CDC) dì Atlanta , fu isolato e identificato il microrganismo che, in memoria della prima epidemia, fu chiamato Legionella pneumophila. la sorgente dell' infezione fu individuata nell' impianto di aria condizionata presente nell'hotel. La scoperta suscitò un grande interesse, tale da incoraggiare alcuni studiosi ad effettuare indagini sierologiche retrospettive su campioni di siero provenienti da soggetti affetti da polmonite di origine sconosciuta. Fu possibile in tal modo risalire ad altri episodi epidemici, quali gli eventi accaduti nel 1965 tra i pazienti dell'Ospedale Psichiatrico St. Elisabeth di Washington e nel 1968 tra coloro che lavoravano nel Servizio di Sanità Pubblica di Pontiac (in Michigan). In seguito, si verificarono altre epidemie che hanno contribuito ad approfondire le conoscenze scientifiche non solo sull'etiologia, patogenesi, diagnosi e terapia della legionellosi, ma anche sulle caratteristiche biochimiche, morfologiche e immunologiche dell'agente patogeno, compreso il suo habitat natura le. In Italia, il primo focolaio epidemico risale al 1978 sul Lago di Garda ed interessò 10 soggetti. Da allora le segnalazioni di casi, sia sporadici sia epidemici , sono diventate sempre più frequ enti, anche se è difficile stabilire se questo incremento sia dovuto ad un reale aumento dell' incidenza, al perfezionam ento delle tecniche diagnostiche o ad una maggiore att enzione alla diagnosi e segnalazione dei casi. Nel Sud Italia, la Puglia è tra le regioni con il maggior numero di casi di legionellosi notificati [Notiziar io ISS 2017]. I fattori che rendono diff icile il controllo e la gestione del probl ema sono la disomogeneità nelle procedure di campionamento, le difformità negli intervent i di bonif ica, la scarsa esperienza nella gestione del rischio associato alle diverse concentrazioni di Legionella rilevate nelle reti idriche. L'entità del problema, per la sua complessità, richiede sempre piu un'accurata attenzione a causa delle pesanti conseguenze legali e di immagine che possono coinvolgere sia le strutture sanitarie sia quelle turistico-ricettive, pertanto la Giunta regionale ha approvato nel 2012 il documento Indirizzi per l'Adozione di un Sistema per la sorveglianza e il controllo delle infezioni da Legionella in Puglia, con il quale ha istituito un sistema di rete regionale formato da due livelli organizzativi: uno centrale e l'altro periferico [D.G.R. n. 2261/2012] . Il livello organizzativo centrale è rappresentato da un apposito Nucleo di Riferimento Regionale che definisce percorsi comun i e codificati nell'ambito delle attività di prevenzione e controllo della malattia ed esercita funzioni chiave per la governance del sistema . Il mandato strategico è quello di assumere l'impegno di "regolare" la rete, attraverso un ruolo di att ivazione, sviluppo e manutenzione di procedure codificate tra i componenti della rete stessa. Il livello organizzativo periferico , costituito dal Nucleo Operativo Territo riale presso ogni Azienda Sanitaria Locale, è incaricato delle attività in materia di prevenzione e controllo della legionellosi e rappresenta, a livello aziendale, il momento d'incontro e condivisione tra il Dipartimento di Prevenzione, la Direzione Sanitaria, i reparti di ricovero, i laborato ri di analisi aziendali, oltre che di coordinamento e collaborazione con l'Agenzia Regionale per la Prevenzione e la Protezione dell'Ambiente (ARPA) provinciale. I punti deboli di ogni strategia di controllo della legionellosi sono riportabili alla mancanza di una chiara correlazione dose-effetto e di una soglia limi te ben definita , ancora oggi associate all'impossibilità di bonificare il sistema idrico in maniera definitiva. Per ridurre il rischio e il numero dei casi di malattia , il presente documento si propone di pianificare un iter omogeneo di procedure da applicare per il controllo e la prevenzione della legionellosi, ponendosi nella linea della prevenzione primaria piuttosto che in quella dell'intervento al verificarsi dei casi. - Il presente documento è rivolto a tutte le strutture sanitarie e assistenziali della Regione Puglia e fornisce indicazioni su: 1. metodi più appropriati per lo screening e la diagnosi della legionellosi; 2. modalità di campionamento per la ricerca di Legionella negli impianti idrici e aeraulici; 3. sistemi efficaci per la sorveglianza e il controllo delle reti idriche; 4. procedure e mezzi per la bonifica e la ridu zione del rischio; 5. attività di comunicaz ione e formazione degli operatori sanitari e degli addetti al controllo; 6. responsabilità medico-legali connesse al verificarsi di casi di malattia associati alle strutture coinvolte

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

Developing optimal input design strategies in cancer systems biology with applications to microfluidic device engineering

<p>Abstract</p> <p>Background</p> <p>Mechanistic models are becoming more and more popular in Systems Biology; identification and control of models underlying biochemical pathways of interest in oncology is a primary goal in this field. Unfortunately the scarce availability of data still limits our understanding of the intrinsic characteristics of complex pathologies like cancer: acquiring information for a system understanding of complex reaction networks is time consuming and expensive. Stimulus response experiments (SRE) have been used to gain a deeper insight into the details of biochemical mechanisms underlying cell life and functioning. Optimisation of the input time-profile, however, still remains a major area of research due to the complexity of the problem and its relevance for the task of information retrieval in systems biology-related experiments.</p> <p>Results</p> <p>We have addressed the problem of quantifying the information associated to an experiment using the Fisher Information Matrix and we have proposed an optimal experimental design strategy based on evolutionary algorithm to cope with the problem of information gathering in Systems Biology. On the basis of the theoretical results obtained in the field of control systems theory, we have studied the dynamical properties of the signals to be used in cell stimulation. The results of this study have been used to develop a microfluidic device for the automation of the process of cell stimulation for system identification.</p> <p>Conclusion</p> <p>We have applied the proposed approach to the Epidermal Growth Factor Receptor pathway and we observed that it minimises the amount of parametric uncertainty associated to the identified model. A statistical framework based on Monte-Carlo estimations of the uncertainty ellipsoid confirmed the superiority of optimally designed experiments over canonical inputs. The proposed approach can be easily extended to multiobjective formulations that can also take advantage of identifiability analysis. Moreover, the availability of fully automated microfluidic platforms explicitly developed for the task of biochemical model identification will hopefully reduce the effects of the 'data rich-data poor' paradox in Systems Biology.</p

Building a global alliance of biofoundries (vol 10, 2040, 2019)

The original version of this Comment contained errors in the legend of Figure 2, in which the locations of the fifteenth and sixteenth GBA members were incorrectly given as '(15) Australian Genome Foundry, Macquarie University; (16) Australian Foundry for Advanced Biomanufacturing, University of Queensland.'. The correct version replaces this with '(15) Australian Foundry for Advanced Biomanufacturing (AusFAB), University of Queensland and (16) Australian Genome Foundry, Macquarie University'. This has been corrected in both the PDF and HTML versions of the Comment

Developing optimal input design strategies in cancer systems biology with applications to microfluidic device engineering

Background: Mechanistic models are becoming more and more popular in Systems Biology; identification and control of models underlying biochemical pathways of interest in oncology is a primary goal in this field. Unfortunately the scarce availability of data still limits our understanding of the intrinsic characteristics of complex pathologies like cancer: acquiring information for a system understanding of complex reaction networks is time consuming and expensive. Stimulus response experiments (SRE) have been used to gain a deeper insight into the details of biochemical mechanisms underlying cell life and functioning. Optimisation of the input time-profile, however, still remains a major area of research due to the complexity of the problem and its relevance for the task of information retrieval in systems biology-related experiments. Results: We have addressed the problem of quantifying the information associated to an experiment using the Fisher Information Matrix and we have proposed an optimal experimental design strategy based on evolutionary algorithm to cope with the problem of information gathering in Systems Biology. On the basis of the theoretical results obtained in the field of control systems theory, we have studied the dynamical properties of the signals to be used in cell stimulation. The results of this study have been used to develop a microfluidic device for the automation of the process of cell stimulation for system identification. Conclusion: We have applied the proposed approach to the Epidermal Growth Factor Receptor pathway and we observed that it minimises the amount of parametric uncertainty associated to the identified model. A statistical framework based on Monte-Carlo estimations of the uncertainty ellipsoid confirmed the superiority of optimally designed experiments over canonical inputs. The proposed approach can be easily extended to multiobjective formulations that can also take advantage of identifiability analysis. Moreover, the availability of fully automated microfluidic platforms explicitly developed for the task of biochemical model identification will hopefully reduce the effects of the ‘data rich-data poor’ paradox in Systems Biology.MediamaticsElectrical Engineering, Mathematics and Computer Scienc