An integrative, multi-scale, genome-wide model reveals the phenotypic landscape of Escherichia coli.

Given the vast behavioral repertoire and biological complexity of even the simplest organisms, accurately predicting phenotypes in novel environments and unveiling their biological organization is a challenging endeavor. Here, we present an integrative modeling methodology that unifies under a common framework the various biological processes and their interactions across multiple layers. We trained this methodology on an extensive normalized compendium for the gram-negative bacterium Escherichia coli, which incorporates gene expression data for genetic and environmental perturbations, transcriptional regulation, signal transduction, and metabolic pathways, as well as growth measurements. Comparison with measured growth and high-throughput data demonstrates the enhanced ability of the integrative model to predict phenotypic outcomes in various environmental and genetic conditions, even in cases where their underlying functions are under-represented in the training set. This work paves the way toward integrative techniques that extract knowledge from a variety of biological data to achieve more than the sum of their parts in the context of prediction, analysis, and redesign of biological systems.

Computational design of genomic transcriptional networks with adaptation to varying environments.

Transcriptional profiling has been widely used as a tool for unveiling the coregulations of genes in response to genetic and environmental perturbations. These coregulations have been used, in a few instances, to infer global transcriptional regulatory models. Here, using the large amount of transcriptomic information available for the bacterium Escherichia coli, we seek to understand the design principles determining the regulation of its transcriptome. Combining transcriptomic and signaling data, we develop an evolutionary computational procedure that allows obtaining alternative genomic transcriptional regulatory network (GTRN) that still maintains its adaptability to dynamic environments. We apply our methodology to an E. coli GTRN and show that it could be rewired to simpler transcriptional regulatory structures. These rewired GTRNs still maintain the global physiological response to fluctuating environments. Rewired GTRNs contain 73% fewer regulated operons. Genes with similar functions and coordinated patterns of expression across environments are clustered into longer regulated operons. These synthetic GTRNs are more sensitive and show a more robust response to challenging environments. This result illustrates that the natural configuration of E. coli GTRN does not necessarily result from selection for robustness to environmental perturbations, but that evolutionary contingencies may have been important as well. We also discuss the limitations of our methodology in the context of the demand theory. Our procedure will be useful as a novel way to analyze global transcription regulation networks and in synthetic biology for the de novo design of genomes.

Fine-tuning tomato agronomic properties by computational genome redesign.

Considering cells as biofactories, we aimed to optimize its internal processes by using the same engineering principles that large industries are implementing nowadays: lean manufacturing. We have applied reverse engineering computational methods to transcriptomic, metabolomic and phenomic data obtained from a collection of tomato recombinant inbreed lines to formulate a kinetic and constraint-based model that efficiently describes the cellular metabolism from expression of a minimal core of genes. Based on predicted metabolic profiles, a close association with agronomic and organoleptic properties of the ripe fruit was revealed with high statistical confidence. Inspired in a synthetic biology approach, the model was used for exploring the landscape of all possible local transcriptional changes with the aim of engineering tomato fruits with fine-tuned biotechnological properties. The method was validated by the ability of the proposed genomes, engineered for modified desired agronomic traits, to recapitulate experimental correlations between associated metabolites.

Computational design of synthetic regulatory networks from a genetic library to characterize the designability of dynamical behaviors.

The engineering of synthetic gene networks has mostly relied on the assembly of few characterized regulatory elements using rational design principles. It is of outmost importance to analyze the scalability and limits of such a design workflow. To analyze the design capabilities of libraries of regulatory elements, we have developed the first automated design approach that combines such elements to search the genotype space associated to a given phenotypic behavior. Herein, we calculated the designability of dynamical functions obtained from circuits assembled with a given genetic library. By designing circuits working as amplitude filters, pulse counters and oscillators, we could infer new mechanisms for such behaviors. We also highlighted the hierarchical design and the optimization of the interface between devices. We dissected the functional diversity of a constrained library and we found that even such libraries can provide a rich variety of behaviors. We also found that intrinsic noise slightly reduces the designability of digital circuits, but it increases the designability of oscillators. Finally, we analyzed the robust design as a strategy to counteract the evolvability and noise in gene expression of the engineered circuits within a cellular background, obtaining mechanisms for robustness through non-linear negative feedback loops.

Laparoscopic Hartmann's reversal has better clinical outcomes compared to open surgery: An international multicenter cohort study involving 502 patients.

Background: Hartmann's procedure (HP) is used in surgical emergencies such as colonic perforation and colonic obstruction. "Temporary" colostomy performed during HP is not always reversed in part due to potential morbidity and mortality associated with reversal. There are several contributing factors for patients requiring a permanent colostomy following HP. Therefore, there is still some discussion about which technique to use. The aim of this study was to evaluate perioperative variables of patients undergoing Hartmann's reversal using a laparoscopic and open approach. Methods: The multicenter retrospective cohort study was done between January 2009 and December 2019 at 14 institutions globally. Patients who underwent Hartmann's reversal laparoscopic (LS) and open (OS) approaches were evaluated and compared. Sociodemographic, preoperative, intraoperative variables, and surgical outcomes were analyzed. The main outcomes evaluated were 30-day mortality, length of stay, complications, and postoperative outcomes. Results: Five hundred and two patients (264 in the LS and 238 in the OS group) were included. The most prevalent sex was male in 53.7%, the most common indication was complicated diverticular disease in 69.9%, and 85% were American Society of Anesthesiologist (ASA) II-III. Intraoperative complications were noted in 5.3% and 3.4% in the LS and OS groups, respectively. Small bowel injuries were the most common intraoperative injury in 8.3%, with a higher incidence in the OS group compared with the LS group (12.2% vs. 4.9%, p < 0.5). Inadvertent injuries were more common in the small bowel (3%) in the LS group. A total of 17.2% in the OS versus 13.3% in the LS group required intensive care unit (ICU) admission (p = 0.2). The most frequent postoperative complication was ileus (12.6% in OS vs. 9.8% in LS group, p = 0.4)). Reintervention was required mainly in the OS group (15.5% vs. 5.3% in LS group, p < 0.5); mortality rate was 1%. Conclusions: Laparoscopic Hartmann's reversal is safe and feasible, associated with superior clinical outcomes compared with open surgery.

Model-based redesign of global transcription regulation.

Synthetic biology aims to the design or redesign of biological systems. In particular, one possible goal could be the rewiring of the transcription regulation network by exchanging the endogenous promoters. To achieve this objective, we have adapted current methods to the inference of a model based on ordinary differential equations that is able to predict the network response after a major change in its topology. Our procedure utilizes microarray data for training. We have experimentally validated our inferred global regulatory model in Escherichia coli by predicting transcriptomic profiles under new perturbations. We have also tested our methodology in silico by providing accurate predictions of the underlying networks from expression data generated with artificial genomes. In addition, we have shown the predictive power of our methodology by obtaining the gene profile in experimental redesigns of the E. coli genome, where rewiring the transcriptional network by means of knockouts of master regulators or by upregulating transcription factors controlled by different promoters. Our approach is compatible with most network inference methods, allowing to explore computationally future genome-wide redesign experiments in synthetic biology.

Simultaneous cross-evaluation of heterogeneous E. coli datasets via mechanistic simulation.

The extensive heterogeneity of biological data poses challenges to analysis and interpretation. Construction of a large-scale mechanistic model of Escherichia coli enabled us to integrate and cross-evaluate a massive, heterogeneous dataset based on measurements reported by various groups over decades. We identified inconsistencies with functional consequences across the data, including that the total output of the ribosomes and RNA polymerases described by data are not sufficient for a cell to reproduce measured doubling times, that measured metabolic parameters are neither fully compatible with each other nor with overall growth, and that essential proteins are absent during the cell cycle-and the cell is robust to this absence. Finally, considering these data as a whole leads to successful predictions of new experimental outcomes, in this case protein half-lives.

DESHARKY: automatic design of metabolic pathways for optimal cell growth.

MOTIVATION: The biological solution for synthesis or remediation of organic compounds using living organisms, particularly bacteria and yeast, has been promoted because of the cost reduction with respect to the non-living chemical approach. In that way, computational frameworks can profit from the previous knowledge stored in large databases of compounds, enzymes and reactions. In addition, the cell behavior can be studied by modeling the cellular context. RESULTS: We have implemented a Monte Carlo algorithm (DESHARKY) that finds a metabolic pathway from a target compound by exploring a database of enzymatic reactions. DESHARKY outputs a biochemical route to the host metabolism together with its impact in the cellular context by using mathematical models of the cell resources and metabolism. Furthermore, we provide the sequence of amino acids for the enzymes involved in the route closest phylogenetically to the considered organism. We provide examples of designed metabolic pathways with their genetic load characterizations. Here, we have used Escherichia coli as host organism. In addition, our bioinformatic tool can be applied for biodegradation or biosynthesis and its performance scales with the database size. AVAILABILITY: Software, a tutorial and examples are freely available and open source at http://soft.synth-bio.org/desharky.html

Computational design and evolution of the oscillatory response under light-dark cycles.

Circadian clocks are biological systems behaving as oscillators even in constant dark conditions. We propose to use a new strategy based on computational design to provide evidence on the origin and evolution of molecular clocks. We design synthetic molecular clocks having a reduced number of genes and some of them showing architectures found in nature. We analyse the response of our models under diverse forcing light-dark (LD) cycles. Our methodology allows us to evolve networks in silico using various selective pressures, which we apply to the analysis of clocks evolved to be either autonomous or phase locked. Our designed networks either have an oscillatory response with the same period as the forcing LD cycle, or they maintain their free-running period. Our methodology will allow analysing the automatic creation of a free-running period under various LD forcing functions and learning new design principles for circadian clocks.

Pareto optimization in computational protein design with multiple objectives.

The optimization for function in computational design requires the treatment of, often competing, multiple objectives. Current algorithms reduce the problem to a single objective optimization problem, with the consequent loss of relevant solutions. We present a procedure, based on a variant of a Pareto algorithm, to optimize various competing objectives in protein design that allows reducing in several orders of magnitude the search of the solution space. Our methodology maintains the diversity of solutions and provides an iterative way to incorporate automatic design methods in the design of functional proteins. We have applied our systematic procedure to design enzymes optimized for both catalysis and stability. However, this methodology can be applied to any computational chemistry application requiring multi-objective combinatorial optimization techniques.

Genetdes: automatic design of transcriptional networks.

MOTIVATION: The rational design of biological networks with prescribed functions is limited to gene circuits of a few genes. Larger networks involve complex interactions with many parameters and the use of automated computational tools can be very valuable. We propose a new tool to design transcriptional networks with targeted behavior that could be used to better understand the design principles of genetic circuits. RESULTS: We have implemented a Simulated Annealing optimization algorithm that explores throughout the space of transcription networks to obtain a specific behavior. The software outputs a transcriptional network with all the corresponding kinetic parameters in SBML format. We provide examples of transcriptional circuits with logical and oscillatory behaviors. Our tool can also be applied to design networks with multiple external input and output genes. AVAILABILITY: The software, a tutorial manual, parameter sets and examples are freely available at http://synth-bio.yi.org/genetdes.html.

Changes in the gene expression profile of Arabidopsis thaliana after infection with Tobacco etch virus.

BACKGROUND: Tobacco etch potyvirus (TEV) has been extensively used as model system for the study of positive-sense RNA virus infecting plants. TEV ability to infect Arabidopsis thaliana varies among ecotypes. In this study, changes in gene expression of A. thaliana ecotype Ler infected with TEV have been explored using long-oligonucleotide arrays. A. thaliana Ler is a susceptible host that allows systemic movement, although the viral load is low and syndrome induced ranges from asymptomatic to mild. Gene expression profiles were monitored in whole plants 21 days post-inoculation (dpi). Microarrays contained 26,173 protein-coding genes and 87 miRNAs. RESULTS: Expression analysis identified 1727 genes that displayed significant and consistent changes in expression levels either up or down, in infected plants. Identified TEV-responsive genes encode a diverse array of functional categories that include responses to biotic (such as the systemic acquired resistance pathway and hypersensitive responses) and abiotic stresses (droughtness, salinity, temperature, and wounding). The expression of many different transcription factors was also significantly affected, including members of the R2R3-MYB family and ABA-inducible TFs. In concordance with several other plant and animal viruses, the expression of heat-shock proteins (HSP) was also increased. Finally, we have associated functional GO categories with KEGG biochemical pathways, and found that many of the altered biological functions are controlled by changes in basal metabolism. CONCLUSION: TEV infection significantly impacts a wide array of cellular processes, in particular, stress-response pathways, including the systemic acquired resistance and hypersensitive responses. However, many of the observed alterations may represent a global response to viral infection rather than being specific of TEV.

Modulation of Intracellular O2 Concentration in Escherichia coli Strains Using Oxygen Consuming Devices.

The use of cell factories for the production of bulk and value-added compounds is nowadays an advantageous alternative to the traditional petrochemical methods. Nevertheless, the efficiency and productivity of several of these processes can improve with the implementation of micro-oxic or anoxic conditions. In the industrial setting, laccases are appealing catalysts that can oxidize a wide range of substrates and reduce O2 to H2O. In this work, several laccase-based devices were designed and constructed to modulate the intracellular oxygen concentration in bacterial chassis. These oxygen consuming devices (OCDs) included Escherichia coli's native laccase (CueO) and three variants of this protein obtained by directed evolution. The OCDs were initially characterized in vitro using E. coli DH5α protein extracts and subsequently using extracts obtained from other E. coli strains and in vivo. Upon induction of the OCDs, no major effect on growth was observed in four of the strains tested, and analysis of the cell extract protein profiles revealed increased levels of laccase. Moreover, oxygen consumption associated with the OCDs occurred under all of the conditions tested, but the performance of the devices was shown to be strain-dependent, highlighting the importance of the genetic background even in closely related strains. One of the laccase variants showed 13- and 5-fold increases in oxidase activity and O2 consumption rate, respectively. Furthermore, it was also possible to demonstrate O2 consumption in vivo using l-DOPA as the substrate, which represents a proof of concept that these OCDs generate an intracellular oxygen sink, thereby manipulating the redox status of the cells. In addition, the modularity and orthogonality principles used for the development of these devices allow easy reassembly and fine-tuning, foreseeing their introduction into other chassis/systems.

[Orthogeriatrics: The First multicentre regional register of hip fractures in Castilla y León (Spain)]. / Ortogeriatría: primer registro multicéntrico autonómico de fracturas de cadera en Castilla y León (España).

OBJECTIVE: The objective of this study is to describe the characteristics of the patients with hip fracture admitted to the Public Hospitals of Castilla y León during three monthly periods (November 2014, and October and November 2015). MATERIAL AND METHOD: The Castilla y León orthogeriatrics work group created a common register to collect data on hip fractures. The study included patients 75 years-old and over hospitalised with hip fractures in the 13 public hospitals in the community during November 2014, and October and November 2015. A multicentre, prospective, and observational study was conducted, in which clinical, functional, and social variables, as well as in-hospital mortality, were collected. RESULTS: The analysis included data from a total of 776 patients with a mean age of 86 (±6) years. The surgical delay was 4±2.8 days, and the mean hospital stay was 10±4.7 days. The anaesthesia risk was ASA 3±0.6. Around two-thirds (66.5%) of the patients had medical complications while in hospital, and 55.5% required a transfusion. In-hospital mortality was 4.6%. The mean pre-surgical stay was related to the overall stay: P<.001. CONCLUSIONS: Hip fracture registers are an essential tool for evaluating the process and for improving the treatment quality of these patients. This is the first multicentre register of hip fracture in the elderly created in a Spanish region, and could be a good precedent reference for a future national register.

Why Build Whole-Cell Models?

Our ability to build computational models that account for all known gene functions in a cell has increased dramatically. But why build whole-cell models, and how can they best be used? In this forum, we enumerate several areas in which whole-cell modeling can significantly impact research and technology.

[Orthogeriatric activity in public hospitals of Castilla y León: description and review of the literature]. / Actividad ortogeriátrica en los hospitales públicos de Castilla y León: descripción y revisión de la literatura.

The benefits of the collaboration between orthopaedics and geriatrics in the management and care of elderly patients admitted with hip fracture have been widely demonstrated. A questionnaire was sent to all hospital geriatricians of Castilla y León in order to determine the characteristics this collaboration between orthopaedics and geriatrics in the public hospitals of Castilla y León. They were asked about the type of collaboration with orthopaedics in the care of the elderly patient admitted with hip fracture and details of the treatment of the complications. Most of the hospitals maintain a high level of orthogeriatric collaboration with geriatricians, and the geriatrician attends to most of the medical complications of these patients. The average hospital stay is 10 days, with a surgical delay of 3 days. Management of the most frequent clinical problems in hospitals of Castilla y León are detailed in this article, comparing them with the latest articles and current recommendations from clinical practice guides.

Automated design of bacterial genome sequences.

BACKGROUND: Organisms have evolved ways of regulating transcription to better adapt to varying environments. Could the current functional genomics data and models support the possibility of engineering a genome with completely rearranged gene organization while the cell maintains its behavior under environmental challenges? How would we proceed to design a full nucleotide sequence for such genomes? RESULTS: As a first step towards answering such questions, recent work showed that it is possible to design alternative transcriptomic models showing the same behavior under environmental variations than the wild-type model. A second step would require providing evidence that it is possible to provide a nucleotide sequence for a genome encoding such transcriptional model. We used computational design techniques to design a rewired global transcriptional regulation of Escherichia coli, yet showing a similar transcriptomic response than the wild-type. Afterwards, we "compiled" the transcriptional networks into nucleotide sequences to obtain the final genome sequence. Our computational evolution procedure ensures that we can maintain the genotype-phenotype mapping during the rewiring of the regulatory network. We found that it is theoretically possible to reorganize E. coli genome into 86% fewer regulated operons. Such refactored genomes are constituted by operons that contain sets of genes sharing around the 60% of their biological functions and, if evolved under highly variable environmental conditions, have regulatory networks, which turn out to respond more than 20% faster to multiple external perturbations. CONCLUSIONS: This work provides the first algorithm for producing a genome sequence encoding a rewired transcriptional regulation with wild-type behavior under alternative environments.