PRONTO-TK: a user-friendly PROtein Neural neTwOrk tool-kit for accessible protein function prediction.

Associating one or more Gene Ontology (GO) terms to a protein means making a statement about a particular functional characteristic of the protein. This association provides scientists with a snapshot of the biological context of the protein activity. This paper introduces PRONTO-TK, a Python-based software toolkit designed to democratize access to Neural-Network based complex protein function prediction workflows. PRONTO-TK is a user-friendly graphical interface (GUI) for empowering researchers, even those with minimal programming experience, to leverage state-of-the-art Deep Learning architectures for protein function annotation using GO terms. We demonstrate PRONTO-TK's effectiveness on a running example, by showing how its intuitive configuration allows it to easily generate complex analyses while avoiding the complexities of building such a pipeline from scratch.

EGCG Disrupts the LIN28B/Let-7 Interaction and Reduces Neuroblastoma Aggressiveness.

Neuroblastoma (NB) is the most commonly diagnosed extracranial solid tumor in children, accounting for 15% of all childhood cancer deaths. Although the 5-year survival rate of patients with a high-risk disease has increased in recent decades, NB remains a challenge in pediatric oncology, and the identification of novel potential therapeutic targets and agents is an urgent clinical need. The RNA-binding protein LIN28B has been identified as an oncogene in NB and is associated with a poor prognosis. Given that LIN28B acts by negatively regulating the biogenesis of the tumor suppressor let-7 miRNAs, we reasoned that selective interference with the LIN28B/let-7 miRNA interaction would increase let-7 miRNA levels, ultimately leading to reduced NB aggressiveness. Here, we selected (-)-epigallocatechin 3-gallate (EGCG) out of 4959 molecules screened as the molecule with the best inhibitory activity on LIN28B/let-7 miRNA interaction and showed that treatment with PLC/PLGA-PEG nanoparticles containing EGCG (EGCG-NPs) led to an increase in mature let-7 miRNAs and a consequent inhibition of NB cell growth. In addition, EGCG-NP pretreatment reduced the tumorigenic potential of NB cells in vivo. These experiments suggest that the LIN28B/let-7 miRNA axis is a good therapeutic target in NB and that EGCG, which can interfere with this interaction, deserves further preclinical evaluation.

Coupling dairy wastewaters for nutritional balancing and water recycling: sustainable heterologous 2-phenylethanol production by engineered cyanobacteria.

Microalgae biotechnology is hampered by the high production costs and the massive usage of water during large-volume cultivations. These drawbacks can be softened by the production of high-value compounds and by adopting metabolic engineering strategies to improve their performances and productivity. Today, the most sustainable approach is the exploitation of industrial wastewaters for microalgae cultivation, which couples valuable biomass production with water resource recovery. Among the food processing sectors, the dairy industry generates the largest volume of wastewaters through the manufacturing process. These effluents are typically rich in dissolved organic matter and nutrients, which make it a challenging and expensive waste stream for companies to manage. Nevertheless, these rich wastewaters represent an appealing resource for microalgal biotechnology. In this study, we propose a sustainable approach for high-value compound production from dairy wastewaters through cyanobacteria. This strategy is based on a metabolically engineered strain of the model cyanobacterium Synechococcus elongatus PCC 7942 (already published elsewhere) for 2-phenylethanol (2-PE). 2-PE is a high-value aromatic compound that is widely employed as a fragrance in the food and cosmetics industry thanks to its pleasant floral scent. First, we qualitatively assessed the impact of four dairy effluents on cyanobacterial growth to identify the most promising substrates. Both tank-washing water and the liquid effluent of exhausted sludge resulted as suitable nutrient sources. Thus, we created an ideal buffer system by combining the two wastewaters while simultaneously providing balanced nutrition and completely avoiding the need for fresh water. The combination of 75% liquid effluent of exhausted sludge and 25% tank-washing water with a fine-tuning ammonium supplementation yielded 180 mg L-1 of 2-PE and a biomass concentration of 0.6 gDW L-1 within 10 days. The mixture of 90% exhausted sludge and 10% washing water produced the highest yield of 2-PE (205 mg L-1) and biomass accumulation (0.7 gDW L-1), although in 16 days. Through these treatments, the phosphates were completely consumed, and nitrogen was removed in a range of 74%-77%. Overall, our approach significantly valorized water recycling and the exploitation of valuable wastewaters to circularly produce marketable compounds via microalgae biotechnology, laying a promising groundwork for subsequent implementation and scale-up.

Translational efficiency in gas-fermenting bacteria: Adding a new layer of regulation to gene expression in acetogens.

Major advances in mastering metabolism of single carbon (C1) gaseous feedstocks in acetogenic microorganisms are primed to fuel the transition toward environmentally sustainable and cost-efficient production schemes of biofuels and value-added biochemicals. Since acetogens grow under autotrophic energy-limited conditions, protein synthesis is expected to be controlled. This survey integrated publicly available RNA sequencing and ribosome profiling studies of several acetogens, providing data on genome-scale transcriptional and translational responses of A. woodii, E. limosum, C. drakei, and C. ljungdahlii to autotrophic and heterotrophic growth conditions. The extent of translational efficiency turned out to vary across key functional modules in acetogens' metabolism. Translational control was confirmed to support stoichiometric protein production in multimeric complexes. Comparing the autotrophic to the heterotrophic growth condition revealed growth-dependent regulation of translational efficiency, pointing at translational buffering as a widespread phenomenon shared by acetogens.

Leveraging substrate flexibility and product selectivity of acetogens in two-stage systems for chemical production.

Carbon dioxide (CO2 ) stands out as sustainable feedstock for developing a circular carbon economy whose energy supply could be obtained by boosting the production of clean hydrogen from renewable electricity. H2 -dependent CO2 gas fermentation using acetogenic microorganisms offers a viable solution of increasingly demonstrated value. While gas fermentation advances to achieve commercial process scalability, which is currently limited to a few products such as acetate and ethanol, it is worth taking the best of the current state-of-the-art technology by its integration within innovative bioconversion schemes. This review presents multiple scenarios where gas fermentation by acetogens integrate into double-stage biotechnological production processes that use CO2 as sole carbon feedstock and H2 as energy carrier for products' synthesis. In the integration schemes here reviewed, the first stage can be biotic or abiotic while the second stage is biotic. When the first stage is biotic, acetogens act as a biological platform to generate chemical intermediates such as acetate, formate and ethanol that become substrates for a second fermentation stage. This approach holds the potential to enhance process titre/rate/yield metrics and products' spectrum. Alternatively, when the first stage is abiotic, the integrated two-stage scheme foresees, in the first stage, the catalytic transformation of CO2 into C1 products that, in the second stage, can be metabolized by acetogens. This latter scheme leverages the metabolic flexibility of acetogens in efficient utilization of the products of CO2 abiotic hydrogenation, namely formate and methanol, to synthesize multicarbon compounds but also to act as flexible catalysts for hydrogen storage or production.

Current progress on engineering microbial strains and consortia for production of cellulosic butanol through consolidated bioprocessing.

In the last decades, fermentative production of n-butanol has regained substantial interest mainly owing to its use as drop-in-fuel. The use of lignocellulose as an alternative to traditional acetone-butanol-ethanol fermentation feedstocks (starchy biomass and molasses) can significantly increase the economic competitiveness of biobutanol over production from non-renewable sources (petroleum). However, the low cost of lignocellulose is offset by its high recalcitrance to biodegradation which generally requires chemical-physical pre-treatment and multiple bioreactor-based processes. The development of consolidated processing (i.e., single-pot fermentation) can dramatically reduce lignocellulose fermentation costs and promote its industrial application. Here, strategies for developing microbial strains and consortia that feature both efficient (hemi)cellulose depolymerization and butanol production will be depicted, that is, rational metabolic engineering of native (hemi)cellulolytic or native butanol-producing or other suitable microorganisms; protoplast fusion of (hemi)cellulolytic and butanol-producing strains; and co-culture of (hemi)cellulolytic and butanol-producing microbes. Irrespective of the fermentation feedstock, biobutanol production is inherently limited by the severe toxicity of this solvent that challenges process economic viability. Hence, an overview of strategies for developing butanol hypertolerant strains will be provided.

Combining metabolite doping and metabolic engineering to improve 2-phenylethanol production by engineered cyanobacteria.

2-Phenylethanol (2-PE) is a rose-scented aromatic compound, with broad application in cosmetic, pharmaceutical, food and beverage industries. Many plants naturally synthesize 2-PE via Shikimate Pathway, but its extraction is expensive and low-yielding. Consequently, most 2-PE derives from chemical synthesis, which employs petroleum as feedstock and generates unwanted by products and health issues. The need for "green" processes and the increasing public demand for natural products are pushing biotechnological production systems as promising alternatives. So far, several microorganisms have been investigated and engineered for 2-PE biosynthesis, but a few studies have focused on autotrophic microorganisms. Among them, the prokaryotic cyanobacteria can represent ideal microbial factories thanks to their ability to photosynthetically convert CO2 into valuable compounds, their minimal nutritional requirements, high photosynthetic rate and the availability of genetic and bioinformatics tools. An engineered strain of Synechococcus elongatus PCC 7942 for 2-PE production, i.e., p120, was previously published elsewhere. The strain p120 expresses four heterologous genes for the complete 2-PE synthesis pathway. Here, we developed a combined approach of metabolite doping and metabolic engineering to improve the 2-PE production kinetics of the Synechococcus elongatus PCC 7942 p120 strain. Firstly, the growth and 2-PE productivity performances of the p120 recombinant strain were analyzed to highlight potential metabolic constraints. By implementing a BG11 medium doped with L-phenylalanine, we covered the metabolic burden to which the p120 strain is strongly subjected, when the 2-PE pathway expression is induced. Additionally, we further boosted the carbon flow into the Shikimate Pathway by overexpressing the native Shikimate Kinase in the Synechococcus elongatus PCC 7942 p120 strain (i.e., 2PE_aroK). The combination of these different approaches led to a 2-PE yield of 300 mg/gDW and a maximum 2-PE titer of 285 mg/L, 2.4-fold higher than that reported in literature for the p120 recombinant strain and, to our knowledge, the highest recorded for photosynthetic microorganisms, in photoautotrophic growth condition. Finally, this work provides the basis for further optimization of the process aimed at increasing 2-PE productivity and concentration, and could offer new insights about the use of cyanobacteria as appealing microbial cell factories for the synthesis of aromatic compounds.

Genome-Scale Mining of Acetogens of the Genus Clostridium Unveils Distinctive Traits in [FeFe]- and [NiFe]-Hydrogenase Content and Maturation.

Knowledge of the organizational and functional properties of hydrogen metabolism is pivotal to the construction of a framework supportive of a hydrogen-fueled low-carbon economy. Hydrogen metabolism relies on the mechanism of action of hydrogenases. In this study, we investigated the genomes of several industrially relevant acetogens of the genus Clostridium (C. autoethanogenum, C. ljungdahlii, C. carboxidivorans, C. drakei, C. scatologenes, C. coskatii, C. ragsdalei, C. sp. AWRP) to systematically identify their intriguingly diversified hydrogenases' repertoire. An entirely computational annotation pipeline unveiled common and strain-specific traits in the functional content of [NiFe]- and [FeFe]-hydrogenases. Hydrogenases were identified and categorized into functionally distinct classes by the combination of sequence homology, with respect to a database of curated nonredundant hydrogenases, with the analysis of sequence patterns characteristic of the mode of action of [FeFe]- and [NiFe]-hydrogenases. The inspection of the genes in the neighborhood of the catalytic subunits unveiled a wide agreement between their genomic arrangement and the gene organization templates previously developed for the predicted hydrogenase classes. Subunits' characterization of the identified hydrogenases allowed us to glean some insights on the redox cofactor-binding determinants in the diaphorase subunits of the electron-bifurcating [FeFe]-hydrogenases. Finally, the reliability of the inferred hydrogenases was corroborated by the punctual analysis of the maturation proteins necessary for the biosynthesis of [NiFe]- and [FeFe]-hydrogenases. IMPORTANCE Mastering hydrogen metabolism can support a sustainable carbon-neutral economy. Of the many microorganisms metabolizing hydrogen, acetogens of the genus Clostridium are appealing, with some of them already in usage as industrial workhorses. Having provided detailed information on the hydrogenase content of an unprecedented number of clostridial acetogens at the gene level, our study represents a valuable knowledge base to deepen our understanding of hydrogenases' functional specificity and/or redundancy and to develop a large array of biotechnological processes. We also believe our study could serve as a basis for future strain-engineering approaches, acting at the hydrogenases' level or at the level of their maturation proteins. On the other side, the wealth of functional elements discussed in relation to the identified hydrogenases is worthy of further investigation by biochemical and structural studies to ultimately lead to the usage of these enzymes as valuable catalysts.

Metabolic Engineering Interventions for Sustainable 2,3-Butanediol Production in Gas-Fermenting Clostridium autoethanogenum.

Gas fermentation provides a promising platform to turn low-cost and readily available single-carbon waste gases into commodity chemicals, such as 2,3-butanediol. Clostridium autoethanogenum is usually used as a robust and flexible chassis for gas fermentation. Here, we leveraged constraint-based stoichiometric modeling and kinetic ensemble modeling of the C. autoethanogenum metabolic network to provide a systematic in silico analysis of metabolic engineering interventions for 2,3-butanediol overproduction and low carbon substrate loss in dissipated CO2. Our analysis allowed us to identify and to assess comparatively the expected performances for a wide range of single, double, and triple interventions. Our analysis managed to individuate bottleneck reactions in relevant metabolic pathways when suggesting intervening strategies. Besides recapitulating intuitive and/or previously attempted genetic modifications, our analysis neatly outlined that interventions-at least partially-impinging on by-products branching from acetyl coenzyme A (acetyl-CoA) and pyruvate (acetate, ethanol, amino acids) offer valuable alternatives to the interventions focusing directly on the specific branch from pyruvate to 2,3-butanediol. IMPORTANCE Envisioning value chains inspired by environmental sustainability and circularity in economic models is essential to counteract the alterations in the global natural carbon cycle induced by humans. Recycling carbon-based waste gas streams into chemicals by devising gas fermentation bioprocesses mediated by acetogens of the genus Clostridium is one component of the solution. Carbon monoxide originates from multiple biogenic and abiogenic sources and bears a significant environmental impact. This study aims at identifying metabolic engineering interventions for increasing 2,3-butanediol production and avoiding carbon loss in CO2 dissipation via C. autoethanogenum fermenting a substrate comprising CO and H2. 2,3-Butanediol is a valuable biochemical by-product since, due to its versatility, can be transformed quite easily into chemical compounds such as butadiene, diacetyl, acetoin, and methyl ethyl ketone. These compounds are usable as building blocks to manufacture a vast range of industrially produced chemicals.

Channeling Anabolic Side Products toward the Production of Nonessential Metabolites: Stable Malate Production in Synechocystis sp. PCC6803.

Powered by (sun)light to oxidize water, cyanobacteria can directly convert atmospheric CO2 into valuable carbon-based compounds and meanwhile release O2 to the atmosphere. As such, cyanobacteria are promising candidates to be developed as microbial cell factories for the production of chemicals. Nevertheless, similar to other microbial cell factories, engineered cyanobacteria may suffer from production instability. The alignment of product formation with microbial fitness is a valid strategy to tackle this issue. We have described previously the "FRUITS" algorithm for the identification of metabolites suitable to be coupled to growth (i.e., side products in anabolic reactions) in the model cyanobacterium Synechocystis. sp PCC6803. However, the list of candidate metabolites identified using this algorithm can be somewhat limiting, due to the inherent structure of metabolic networks. Here, we aim at broadening the spectrum of candidate compounds beyond the ones predicted by FRUITS, through the conversion of a growth-coupled metabolite to downstream metabolites via thermodynamically favored conversions. We showcase the feasibility of this approach for malate production using fumarate as the growth-coupled substrate in Synechocystis mutants. A final titer of ∼1.2 mM was achieved for malate during photoautotrophic batch cultivations. Under prolonged continuous cultivation, the most efficient malate-producing strain can maintain its productivity for at least 45 generations, sharply contrasting with other producing Synechocystis strains engineered with classical approaches. Our study also opens a new possibility for extending the stable production concept to derivatives of growth-coupled metabolites, increasing the list of suitable target compounds.

Clostridium cellulovorans Proteomic Responses to Butanol Stress.

Combination of butanol-hyperproducing and hypertolerant phenotypes is essential for developing microbial strains suitable for industrial production of bio-butanol, one of the most promising liquid biofuels. Clostridium cellulovorans is among the microbial strains with the highest potential for direct production of n-butanol from lignocellulosic wastes, a process that would significantly reduce the cost of bio-butanol. However, butanol exhibits higher toxicity compared to ethanol and C. cellulovorans tolerance to this solvent is low. In the present investigation, comparative gel-free proteomics was used to study the response of C. cellulovorans to butanol challenge and understand the tolerance mechanisms activated in this condition. Sequential Window Acquisition of all Theoretical fragment ion spectra Mass Spectrometry (SWATH-MS) analysis allowed identification and quantification of differentially expressed soluble proteins. The study data are available via ProteomeXchange with the identifier PXD024183. The most important response concerned modulation of protein biosynthesis, folding and degradation. Coherent with previous studies on other bacteria, several heat shock proteins (HSPs), involved in protein quality control, were up-regulated such as the chaperones GroES (Cpn10), Hsp90, and DnaJ. Globally, our data indicate that protein biosynthesis is reduced, likely not to overload HSPs. Several additional metabolic adaptations were triggered by butanol exposure such as the up-regulation of V- and F-type ATPases (involved in ATP synthesis/generation of proton motive force), enzymes involved in amino acid (e.g., arginine, lysine, methionine, and branched chain amino acids) biosynthesis and proteins involved in cell envelope re-arrangement (e.g., the products of Clocel_4136, Clocel_4137, Clocel_4144, Clocel_4162 and Clocel_4352, involved in the biosynthesis of saturated fatty acids) and a redistribution of carbon flux through fermentative pathways (acetate and formate yields were increased and decreased, respectively). Based on these experimental findings, several potential gene targets for metabolic engineering strategies aimed at improving butanol tolerance in C. cellulovorans are suggested. This includes overexpression of HSPs (e.g., GroES, Hsp90, DnaJ, ClpC), RNA chaperone Hfq, V- and F-type ATPases and a number of genes whose function in C. cellulovorans is currently unknown.

Computational Analysis of Dynamic Light Exposure of Unicellular Algal Cells in a Flat-Panel Photobioreactor to Support Light-Induced CO2 Bioprocess Development.

Cyanobacterial cell factories trace a vibrant pathway to climate change neutrality and sustainable development owing to their ability to turn carbon dioxide-rich waste into a broad portfolio of renewable compounds, which are deemed valuable in green chemistry cross-sectorial applications. Cell factory design requires to define the optimal operational and cultivation conditions. The paramount parameter in biomass cultivation in photobioreactors is the light intensity since it impacts cellular physiology and productivity. Our modeling framework provides a basis for the predictive control of light-limited, light-saturated, and light-inhibited growth of the Synechocystis sp. PCC 6803 model organism in a flat-panel photobioreactor. The model here presented couples computational fluid dynamics, light transmission, kinetic modeling, and the reconstruction of single cell trajectories in differently irradiated areas of the photobioreactor to relate key physiological parameters to the multi-faceted processes occurring in the cultivation environment. Furthermore, our analysis highlights the need for properly constraining the model with decisive qualitative and quantitative data related to light calibration and light measurements both at the inlet and outlet of the photobioreactor in order to boost the accuracy and extrapolation capabilities of the model.

Inhibition of mitochondrial translation suppresses glioblastoma stem cell growth.

Glioblastoma stem cells (GSCs) resist current glioblastoma (GBM) therapies. GSCs rely highly on oxidative phosphorylation (OXPHOS), whose function requires mitochondrial translation. Here we explore the therapeutic potential of targeting mitochondrial translation and report the results of high-content screening with putative blockers of mitochondrial ribosomes. We identify the bacterial antibiotic quinupristin/dalfopristin (Q/D) as an effective suppressor of GSC growth. Q/D also decreases the clonogenicity of GSCs in vitro, consequently dysregulating the cell cycle and inducing apoptosis. Cryoelectron microscopy (cryo-EM) reveals that Q/D binds to the large mitoribosomal subunit, inhibiting mitochondrial protein synthesis and functionally dysregulating OXPHOS complexes. These data suggest that targeting mitochondrial translation could be explored to therapeutically suppress GSC growth in GBM and that Q/D could potentially be repurposed for cancer treatment.

Novel insights in dimethyl carbonate-based extraction of polyhydroxybutyrate (PHB).

BACKGROUND: Plastic plays a crucial role in everyday life of human living, nevertheless it represents an undeniable source of land and water pollution. Polyhydroxybutyrate (PHB) is a bio-based and biodegradable polyester, which can be naturally produced by microorganisms capable of converting and accumulating carbon as intracellular granules. Hence, PHB-producing strains stand out as an alternative source to fossil-derived counterparts. However, the extraction strategy affects the recovery efficiency and the quality of PHB. In this study, PHB was produced by a genetically modified Escherichia coli strain and successively extracted using dimethyl carbonate (DMC) and ethanol as alternative solvent and polishing agent to chloroform and hexane. Eventually, a Life Cycle Assessment (LCA) study was performed for evaluating the environmental and health impact of using DMC. RESULTS: Extraction yield and purity of PHB obtained via DMC, were quantified, and compared with those obtained via chloroform-based extraction. PHB yield values from DMC-based extraction were similar to or higher than those achieved by using chloroform (≥ 67%). To optimize the performance of extraction via DMC, different experimental conditions were tested, varying the biomass state (dry or wet) and the mixing time, in presence or in absence of a paper filter. Among 60, 90, 120 min, the mid-value allowed to achieve high extraction yield, both for dry and wet biomass. Physical and molecular dependence on the biomass state and solvent/antisolvent choice was established. The comparative LCA analysis promoted the application of DMC/ethanol rather than chloroform/hexane, as the best choice in terms of health prevention. However, an elevated impact score was achieved by DMC in the environmental-like categories in contrast with a minor contribution by its counterpart. CONCLUSION: The multifaceted exploration of DMC-based PHB extraction herein reported extends the knowledge of the variables affecting PHB purification process. This work offers novel and valuable insights into PHB extraction process, including environmental aspects not discussed so far. The findings of our research question the DMC as a green solvent, though also the choice of the antisolvent can influence the impact on the examined categories.

Clostridium cellulovorans metabolism of cellulose as studied by comparative proteomic approach.

Clostridium cellulovorans is among the most promising candidates for consolidated bioprocessing (CBP) of cellulosic biomass to liquid biofuels (ethanol, butanol). C. cellulovorans metabolizes all the main plant polysaccharides and mainly produces butyrate. Since most butyrate and butanol biosynthetic reactions from acetyl-CoA are common, introduction of single heterologous alcohol/aldehyde dehydrogenase can divert the branching-point intermediate (butyryl-CoA) towards butanol production in this strain. However, engineering C. cellulovorans metabolic pathways towards industrial utilization requires better understanding of its metabolism. The present study aimed at improving comprehension of cellulose metabolism in C. cellulovorans by comparing growth kinetics, substrate consumption/product accumulation and whole-cell soluble proteome (data available via ProteomeXchange, identifier PXD015487) with those of the same strain grown on a soluble carbohydrate, glucose, as the main carbon source. Growth substrate-dependent modulations of the central metabolism were detected, including regulation of several glycolytic enzymes, fermentation pathways (e.g. hydrogenase, pyruvate formate lyase, phosphate transacetylase) and nitrogen assimilation (e.g. glutamate dehydrogenase). Overexpression of hydrogenase and increased ethanol production by glucose-grown bacteria suggest a more reduced redox state. Higher energy expenditure seems to occur in cellulose-grown C. cellulovorans (likely related to overexpression and secretion of (hemi-)cellulases), which induces up-regulation of ATP synthetic pathways, e.g. acetate production and ATP synthase. SIGNIFICANCE: C. cellulovorans can metabolize all the main plant polysaccharides (cellulose, hemicelluloses and pectins) and, unlike other well established cellulolytic microorganisms, can produce butyrate. C. cellulovorans is therefore among the most attractive candidates for direct fermentation of lignocellulose to high-value chemicals and, especially, n-butanol, i.e. one of the most promising liquid biofuels for the future. Recent studies aimed at engineering n-butanol production in C. cellulovorans represent milestones towards production of biofuels through one-step fermentation of lignocellulose but also indicated that more detailed understanding of the C. cellulovorans central carbon metabolism is essential to refine metabolic engineering strategies towards improved n-butanol production in this strain. The present study helped identifying key genes associated with specific catabolic reactions and indicated modulations of central carbon metabolism (including redox and energy balance) associated with cellulose consumption. This information will be useful to determine key enzymes and possible metabolic bottlenecks to be addressed towards improved metabolic engineering of this strain.

A Reaction-Based Model of the State Space of Chemical Reaction Systems Enables Efficient Simulations.

The choice of the state space representation of a system can turn into a prominent advantage or burden in any endeavour to mathematically model dynamical systems since it entails the analytical tractability of the related modelling formalism and the efficiency of the numerical computation. The Reaction-Based Model (RBM) of the state space, which is presented in this article, is a novel formalization of the kinetics of a system of interacting molecules. According to our representation, the state Sµ of a system of M reactions and N molecular species, is identified with the occurrence of the reaction Rµ ( µ = 1, ..., M). The transition between any two states Sµ and Sν is modelled as a first-order reaction Sµ → Sν and described by mass action-like equation for the partial time derivative of the variables P(Sµ, t) and P(Sν, t), which denote the probabilities that the system lies in the two states, respectively. The rate equations for the state probabilities are coupled with those for the abundance of molecular species. Altogether, the rate equations along with the specification of the initial conditions define the Cauchy problem whose solution describes the time-evolution of the system. The RBM has been applied to a typical severely stiff biological case study. The numerical solutions of the system's dynamics turned out to be computationally more efficient and in agreement with the results of the stochastic and hybrid stochastic/deterministic simulation algorithms.

On TD-WGcluster: Theoretical Foundations and Guidelines for the User.

We review the TD-WGcluster (time delayed weighted edge clustering) software integrating static interaction networks with time series data in order to detect modules of nodes between which the information flows at similar time delays and intensities. The software has represented an advancement of the state of the art in the software for the identification of connected components due to its peculiarity of dealing with direct and weighted graphs, where the attributes of the physical entities represented by nodes vary over time. This chapter aims to deepen those theoretical aspects of the clustering model implemented by TD-WGcluster that may be of greater interest to the user. We show the instructions necessary to run the software through some exploratory cases and comment on the results obtained.

Identifying necessary and sufficient conditions for the observability of models of biochemical processes.

The notions of observability and controllability of non-linear systems are a cornerstone of mathematical control theory and cover a wide scope of applications including process design, characterization, monitoring and control. Synthetic biology - which aims to (re)-program living functionalities - and bio-based process engineering - which aims to develop biotechnological manufacturing processes based on industrial and natural living agents - remarkably benefit of methodological improvements inspired to control theory for countless reasons including the huge variety of control mechanisms in living organisms, experimental limitations in terms of measurement feasibility, design of controllers - at single cell or population level - of synthetic production processes and process optimization purposes. Many fundamental problems of control theory such as stabilisability of unstable systems and optimal control may be solved under the assumption that the system is observable/controllable. Observability and controllability are mathematical duals, that means that the observability property can be determined analysing the controllability of the dual system and vice versa. Given this duality, we focus on observability. In this work, we revisit a generalization of the Fujisawa and Kuh theorem as a tool to explore the possibility that a system is observable. We show that the theorem, when applicable, is a sufficient but not necessary condition for observability. We revisit the theorem to propose a necessary and sufficient condition for observability for non-linear systems. Finally, we show how it is possible to identify regions of the phase space of the model in which the model is observable.

BiP/GRP78 Mediates ERAD Targeting of Proteins Produced by Membrane-Bound Ribosomes Stalled at the STOP-Codon.

Translational stalling of ribosome bound to endoplasmic reticulum (ER) membrane requires an accurate clearance of the associated polypeptides, which is not completely understood in mammals. We characterized in mammalian cells the model of ribosomal stalling at the STOP-codon based on proteins tagged at the C-terminus with the picornavirus 2A peptide followed by a termination codon instead of the Proline (2A*). We exploited the 2A* stalling model to characterize the pathway of degradation of ER-targeted polypeptides. We report that the ER chaperone BiP/GRP78 is a new main factor involved. Moreover, degradation of the ER-stalled polypeptides required the activities of the AAA-ATPase VCP/p97, its associated deubiquitinylase YOD1, the ribosome-associated ubiquitin ligase Listerin and the proteasome. In human proteome, we found two human C-terminal amino acid sequences that cause similar stalling at the STOP-codon. Our data suggest that translational stalling at the ER membrane activates protein degradation at the interface of ribosomal- and ER-associated quality control systems.