Computer-aided biochemical programming of synthetic microreactors as diagnostic devices.

Biological systems have evolved efficient sensing and decision-making mechanisms to maximize fitness in changing molecular environments. Synthetic biologists have exploited these capabilities to engineer control on information and energy processing in living cells. While engineered organisms pose important technological and ethical challenges, de novo assembly of non-living biomolecular devices could offer promising avenues toward various real-world applications. However, assembling biochemical parts into functional information processing systems has remained challenging due to extensive multidimensional parameter spaces that must be sampled comprehensively in order to identify robust, specification compliant molecular implementations. We introduce a systematic methodology based on automated computational design and microfluidics enabling the programming of synthetic cell-like microreactors embedding biochemical logic circuits, or protosensors, to perform accurate biosensing and biocomputing operations in vitro according to temporal logic specifications. We show that proof-of-concept protosensors integrating diagnostic algorithms detect specific patterns of biomarkers in human clinical samples. Protosensors may enable novel approaches to medicine and represent a step toward autonomous micromachines capable of precise interfacing of human physiology or other complex biological environments, ecosystems, or industrial bioprocesses.

Cell-cell communication enhances the capacity of cell ensembles to sense shallow gradients during morphogenesis.

Collective cell responses to exogenous cues depend on cell-cell interactions. In principle, these can result in enhanced sensitivity to weak and noisy stimuli. However, this has not yet been shown experimentally, and little is known about how multicellular signal processing modulates single-cell sensitivity to extracellular signaling inputs, including those guiding complex changes in the tissue form and function. Here we explored whether cell-cell communication can enhance the ability of cell ensembles to sense and respond to weak gradients of chemotactic cues. Using a combination of experiments with mammary epithelial cells and mathematical modeling, we find that multicellular sensing enables detection of and response to shallow epidermal growth factor (EGF) gradients that are undetectable by single cells. However, the advantage of this type of gradient sensing is limited by the noisiness of the signaling relay, necessary to integrate spatially distributed ligand concentration information. We calculate the fundamental sensory limits imposed by this communication noise and combine them with the experimental data to estimate the effective size of multicellular sensory groups involved in gradient sensing. Functional experiments strongly implicated intercellular communication through gap junctions and calcium release from intracellular stores as mediators of collective gradient sensing. The resulting integrative analysis provides a framework for understanding the advantages and limitations of sensory information processing by relays of chemically coupled cells.

Computing with synthetic protocells.

In this article we present a new kind of computing device that uses biochemical reactions networks as building blocks to implement logic gates. The architecture of a computing machine relies on these generic and composable building blocks, computation units, that can be used in multiple instances to perform complex boolean functions. Standard logical operations are implemented by biochemical networks, encapsulated and insulated within synthetic vesicles called protocells. These protocells are capable of exchanging energy and information with each other through transmembrane electron transfer. In the paradigm of computation we propose, protoputing, a machine can solve only one problem and therefore has to be built specifically. Thus, the programming phase in the standard computing paradigm is represented in our approach by the set of assembly instructions (specific attachments) that directs the wiring of the protocells that constitute the machine itself. To demonstrate the computing power of protocellular machines, we apply it to solve a NP-complete problem, known to be very demanding in computing power, the 3-SAT problem. We show how to program the assembly of a machine that can verify the satisfiability of a given boolean formula. Then we show how to use the massive parallelism of these machines to verify in less than 20 min all the valuations of the input variables and output a fluorescent signal when the formula is satisfiable or no signal at all otherwise.

Sensor potency of the moonlighting enzyme-decorated cytoskeleton: the cytoskeleton as a metabolic sensor.

BACKGROUND: There is extensive evidence for the interaction of metabolic enzymes with the eukaryotic cytoskeleton. The significance of these interactions is far from clear. PRESENTATION OF THE HYPOTHESIS: In the cytoskeletal integrative sensor hypothesis presented here, the cytoskeleton senses and integrates the general metabolic activity of the cell. This activity depends on the binding to the cytoskeleton of enzymes and, depending on the nature of the enzyme, this binding may occur if the enzyme is either active or inactive but not both. This enzyme-binding is further proposed to stabilize microtubules and microfilaments and to alter rates of GTP and ATP hydrolysis and their levels. TESTING THE HYPOTHESIS: Evidence consistent with the cytoskeletal integrative sensor hypothesis is presented in the case of glycolysis. Several testable predictions are made. There should be a relationship between post-translational modifications of tubulin and of actin and their interaction with metabolic enzymes. Different conditions of cytoskeletal dynamics and enzyme-cytoskeleton binding should reveal significant differences in local and perhaps global levels and ratios of ATP and GTP. The different functions of moonlighting enzymes should depend on cytoskeletal binding. IMPLICATIONS OF THE HYPOTHESIS: The physical and chemical effects arising from metabolic sensing by the cytoskeleton would have major consequences on cell shape, dynamics and cell cycle progression. The hypothesis provides a framework that helps the significance of the enzyme-decorated cytoskeleton be determined.

BioNetCAD: design, simulation and experimental validation of synthetic biochemical networks.

MOTIVATION: Synthetic biology studies how to design and construct biological systems with functions that do not exist in nature. Biochemical networks, although easier to control, have been used less frequently than genetic networks as a base to build a synthetic system. To date, no clear engineering principles exist to design such cell-free biochemical networks. RESULTS: We describe a methodology for the construction of synthetic biochemical networks based on three main steps: design, simulation and experimental validation. We developed BioNetCAD to help users to go through these steps. BioNetCAD allows designing abstract networks that can be implemented thanks to CompuBioTicDB, a database of parts for synthetic biology. BioNetCAD enables also simulations with the HSim software and the classical Ordinary Differential Equations (ODE). We demonstrate with a case study that BioNetCAD can rationalize and reduce further experimental validation during the construction of a biochemical network. AVAILABILITY AND IMPLEMENTATION: BioNetCAD is freely available at http://www.sysdiag.cnrs.fr/BioNetCAD. It is implemented in Java and supported on MS Windows. CompuBioTicDB is freely accessible at http://compubiotic.sysdiag.cnrs.fr/.

The construction of a library of synthetic promoters revealed some specific features of strong Streptomyces promoters.

Streptomyces are bacteria of industrial interest whose genome contains more than 73% of bases GC. In order to define, in these GC-rich bacteria, specific sequence features of strong promoters, a library of synthetic promoters of various sequence composition was constructed in Streptomyces. To do so, the sequences located upstream, between and downstream of the -35 and -10 consensus promoter sequences were completely randomized and some variability was introduced in the -35 (position 6) and -10 (positions 3, 4 and 5) hexamers recognized by the major vegetative sigma factor HrdB. The synthetic promoters were cloned into the promoter-probe plasmid pIJ487 just upstream of the promoter-less aphII gene that confers resistance to neomycin. This synthetic promoter library was transformed into Streptomyces lividans, and the resulting transformants were screened for their ability to grow in the presence of different concentrations of neomycin (20, 50, and 100 µgml(-1)). Promoter strengths varied up to 12-fold, in small increments of activity increase, as determined by reverse transcriptase-PCR. This collection of promoters of various strengths can be useful for the fine-tuning of gene expression in genetic engineering projects. Thirty-eight promoters were sequenced, and the sequences of the 14 weakest and 14 strongest promoters were compared using the WebLogo software with small sample correction. This comparison revealed that the -10 box, the -10 extended motif as well as the spacer of the strong Streptomyces promoters are more G rich than those of the weak promoters.

Pandæsim: An Epidemic Spreading Stochastic Simulator.

Many methods have been used to model epidemic spreading. They include ordinary differential equation systems for globally homogeneous environments and partial differential equation systems to take into account spatial localisation and inhomogeneity. Stochastic differential equations systems have been used to model the inherent stochasticity of epidemic spreading processes. In our case study, we wanted to model the numbers of individuals in different states of the disease, and their locations in the country. Among the many existing methods we used our own variant of the well known Gillespie stochastic algorithm, along with the sub-volumes method to take into account the spatial localisation. Our algorithm allows us to easily switch from stochastic discrete simulation to continuous deterministic resolution using mean values. We applied our approaches on the study of the Covid-19 epidemic in France. The stochastic discrete version of Pandæsim showed very good correlations between the simulation results and the statistics gathered from hospitals, both on day by day and on global numbers, including the effects of the lockdown. Moreover, we have highlighted interesting differences in behaviour between the continuous and discrete methods that may arise in some particular conditions.

Successful Treatment of Extensive Esophageal Squamous Papillomatosis With Cryotherapy.

Esophageal squamous papilloma is a rare endoscopic finding, and esophageal squamous papillomatosis (ESP) is considered exceptionally rare, with only a limited number of cases reported to date. There is a paucity of literature about the management of these lesions, and it remains largely controversial. We report a 61-year-old man who presented for endoscopic treatment of ESP detected during endoscopic evaluation for heartburn. Given the potential risk of malignant transformation, a decision was made to proceed with spray cryoablation, requiring a total of 3 sessions of ablative therapy. The histopathological assessment confirmed the diagnosis, and the specimens tested negative for all low- and high-risk human papillomavirus subtypes. Follow-up endoscopies revealed near-complete resolution. To our knowledge, the present report describes the second successful treatment of ESP using endoscopic spray cryotherapy.

Steady-state kinetic behaviour of functioning-dependent structures.

A fundamental problem in biochemistry is that of the nature of the coordination between and within metabolic and signalling pathways. It is conceivable that this coordination might be assured by what we term functioning-dependent structures (FDSs), namely those assemblies of proteins that associate with one another when performing tasks and that disassociate when no longer performing them. To investigate a role in coordination for FDSs, we have studied numerically the steady-state kinetics of a model system of two sequential monomeric enzymes, E(1) and E(2). Our calculations show that such FDSs can display kinetic properties that the individual enzymes cannot. These include the full range of basic input/output characteristics found in electronic circuits such as linearity, invariance, pulsing and switching. Hence, FDSs can generate kinetics that might regulate and coordinate metabolism and signalling. Finally, we suggest that the occurrence of terms representative of the assembly and disassembly of FDSs in the classical expression of the density of entropy production are characteristic of living systems.

Marijuana use in the immediate 5-year premorbid period is associated with increased risk of onset of schizophrenia and related psychotic disorders.

OBJECTIVES: Several studies suggest that adolescent marijuana use predicts earlier age at onset of schizophrenia, which is a crucial prognostic indicator. Yet, many investigations have not adequately established a clear temporal relationship between the use and onset. METHODS: We enrolled 247 first-episode psychosis patients from six psychiatric units and collected data on lifetime marijuana/alcohol/tobacco use, and ages at onset of prodrome and psychosis in 210 of these patients. Cox regression (survival analysis) was employed to quantify hazard ratios (HRs) for effects of diverse premorbid use variables on psychosis onset. RESULTS: Escalation of premorbid use in the 5years prior to onset was highly predictive of an increased risk for onset (e.g., increasing from no use to daily use, HR=3.6, p<0.0005). Through the analysis of time-specific measures, we determined that daily use approximately doubled the rate of onset (HR=2.2, p<0.0005), even after controlling for simultaneous alcohol/tobacco use. Building on previous studies, we were able to determine that cumulative marijuana exposure was associated with an increased rate of onset of psychosis (p=0.007), independent of gender and family history, and this is possibly the reason for age at initiation of marijuana use also being associated with rate of onset in this cohort. CONCLUSIONS: These data provide evidence of a clear temporal relationship between escalations in use in the five years pre-onset and an increased rate of onset, demonstrate that the strength of the association is similar pre- and post-onset of prodromal symptoms, and determine that early adult use may be just as important as adolescent use in these associations.

Personality domains, duration of untreated psychosis, functioning, and symptom severity in first-episode psychosis.

OBJECTIVES: Early-course psychotic disorders have been extensively studied in terms of phenomenology, but little is known about the influence of personality traits on clinical features of first-episode psychosis. The aim of this study was to explore how the "big five" personality domains (neuroticism, extraversion, openness, agreeableness, and conscientiousness) are associated with treatment delay (duration of untreated psychosis, DUP), functioning, and positive and negative symptom severity. METHODS: Data for these analyses were obtained from 104 participants enrolled from psychiatric inpatient units in Atlanta, Georgia, between August 2008 and March 2011. The NEO Five-Factor Inventory (NEO-FFI) was used to assess personality domains, and all other variables were measured in a standardized and rigorous manner using psychometrically sound instruments. Correlational analyses and multiple linear regressions were carried out to examine the strength of associations between variables of interest. RESULTS: Findings indicated that except for openness, all of the other personality variables contributed to some extent to the variance in DUP. Conscientiousness was positively correlated with functioning. Agreeableness was independently negatively associated with positive symptom severity and extraversion was independently negatively correlated with negative symptom severity. CONCLUSIONS: We report the first evidence suggesting that DUP is in part driven by personality domains. Functioning and symptom severity are also associated with those domains. Personality should be taken into account in order to better understand the phenomenology of early-course psychotic disorders as well as treatment-seeking behaviors.

Novel insights regarding the sigmoidal pattern of resistance to neomycin conferred by the aphII gene, in Streptomyces lividans.

A library of synthetic promoters of various strengths, specifically constructed for Streptomyces species, was cloned in the promoter-probe plasmid pIJ487, upstream of the promoter-less aphII gene that confers resistance to neomycin. The survival rates conferred by promoters were assessed in the presence of 100 µg.ml-1 neomycin. The correlation between the transcriptional activity of the aphII gene (estimated by RT-PCR) and the resistance to neomycin (expressed as survival rate) indicated a sigmoid rather than a linear correlation. In this issue, we propose a tentative explanation for this sigmoidal pattern of resistance in relation with the level of aphII gene expression. Beyond this specific example, our model might constitute a sound explanation for the generally observed but never explained sigmoidal shape of classical inhibition curves obtained in the presence of linearly increasing antibiotic concentrations.

Chromosome Replication in Escherichia coli: Life on the Scales.

At all levels of Life, systems evolve on the 'scales of equilibria'. At the level of bacteria, the individual cell must favor one of two opposing strategies and either take risks to grow or avoid risks to survive. It has been proposed in the Dualism hypothesis that the growth and survival strategies depend on non-equilibrium and equilibrium hyperstructures, respectively. It has been further proposed that the cell cycle itself is the way cells manage to balance the ratios of these types of hyperstructure so as to achieve the compromise solution of living on the two scales. Here, we attempt to re-interpret a major event, the initiation of chromosome replication in Escherichia coli, in the light of scales of equilibria. This entails thinking in terms of hyperstructures as responsible for intensity sensing and quantity sensing and how this sensing might help explain the role of the DnaA protein in initiation of replication. We outline experiments and an automaton approach to the cell cycle that should test and refine the scales concept.

The mimic chain reaction.

It is sometimes speculated that the equivalent of the polymerase chain reaction might be developed for identification of peptides, proteins or other molecules. In general, though, it is believed that there can be no way to amplify targets such as proteins. Natural amplification systems do, however, exist as in the case of certain autoinducer systems in bacteria. Here, we outline a possible, generic method, the mimic chain reaction, for obtaining peptides with 3-D structures that mimic the 3-D structure of their targets. These targets would include a variety of molecules, including proteins. There are therefore two categories of applications: the ability via amplification firstly to detect a known protein or other target at an extremely low concentration, and secondly to obtain a set of peptides that mimic the structure of an unknown target and that can be used to obtain a 'photofit'.

Computing with bacterial constituents, cells and populations: from bioputing to bactoputing.

The relevance of biological materials and processes to computing-alias bioputing-has been explored for decades. These materials include DNA, RNA and proteins, while the processes include transcription, translation, signal transduction and regulation. Recently, the use of bacteria themselves as living computers has been explored but this use generally falls within the classical paradigm of computing. Computer scientists, however, have a variety of problems to which they seek solutions, while microbiologists are having new insights into the problems bacteria are solving and how they are solving them. Here, we envisage that bacteria might be used for new sorts of computing. These could be based on the capacity of bacteria to grow, move and adapt to a myriad different fickle environments both as individuals and as populations of bacteria plus bacteriophage. New principles might be based on the way that bacteria explore phenotype space via hyperstructure dynamics and the fundamental nature of the cell cycle. This computing might even extend to developing a high level language appropriate to using populations of bacteria and bacteriophage. Here, we offer a speculative tour of what we term bactoputing, namely the use of the natural behaviour of bacteria for calculating.

A stochastic automaton shows how enzyme assemblies may contribute to metabolic efficiency.

BACKGROUND: The advantages of grouping enzymes into metabolons and into higher order structures have long been debated. To quantify these advantages, we have developed a stochastic automaton that allows experiments to be performed in a virtual bacterium with both a membrane and a cytoplasm. We have investigated the general case of transport and metabolism as inspired by the phosphoenolpyruvate:sugar phosphotransferase system (PTS) for glucose importation and by glycolysis. RESULTS: We show that PTS and glycolytic metabolons can increase production of pyruvate eightfold at low concentrations of phosphoenolpyruvate. A fourfold increase in the numbers of enzyme EI led to a 40% increase in pyruvate production, similar to that observed in vivo in the presence of glucose. Although little improvement resulted from the assembly of metabolons into a hyperstructure, such assembly can generate gradients of metabolites and signaling molecules. CONCLUSION: in silico experiments may be performed successfully using stochastic automata such as HSIM (Hyperstructure Simulator) to help answer fundamental questions in metabolism about the properties of molecular assemblies and to devise strategies to modify such assemblies for biotechnological ends.

Acetaminophen safety and hepatotoxicity--where do we go from here?

Acetaminophen has been widely used for > 50 years in the treatment of pain and fever and provides for the safe and effective relief of these symptoms. In a small minority of patients, however, acetaminophen is responsible for life-threatening liver injury and accounts for up to 50% of all adult cases of acute liver failure in the US. Although approximately two-thirds of adult overdoses are associated with suicide attempts, many are inadvertent, often due to the use of multiple acetaminophen formulations over many days. Additionally, some individuals appear to experience acetaminophen toxicity at 'therapeutic' doses of < 4 g/day, for reasons unknown. In pediatric populations, the overwhelming majority of acetaminophen overdoses are due to unintentional overdoses, except for the predominance of suicidal ingestions in the teenage population. This article seeks to review the mechanism and metabolism of acetaminophen and the features of toxicity in adults, pediatric and special populations. Additionally, expert opinion is presented herein to aid in reducing the frequency and severity of liver injury from acetaminophen.

Hyperstructures, genome analysis and I-cells.

New concepts may prove necessary to profit from the avalanche of sequence data on the genome, transcriptome, proteome and interactome and to relate this information to cell physiology. Here, we focus on the concept of large activity-based structures, or hyperstructures, in which a variety of types of molecules are brought together to perform a function. We review the evidence for the existence of hyperstructures responsible for the initiation of DNA replication, the sequestration of newly replicated origins of replication, cell division and for metabolism. The processes responsible for hyperstructure formation include changes in enzyme affinities due to metabolite-induction, lipid-protein affinities, elevated local concentrations of proteins and their binding sites on DNA and RNA, and transertion. Experimental techniques exist that can be used to study hyperstructures and we review some of the ones less familiar to biologists. Finally, we speculate on how a variety of in silico approaches involving cellular automata and multi-agent systems could be combined to develop new concepts in the form of an Integrated cell (I-cell) which would undergo selection for growth and survival in a world of artificial microbiology.