A bird's-eye overview of molecular mechanisms regulating feed intake in chickens-with mammalian comparisons.

In recent decades, a lot of research has been conducted to explore poultry feeding behavior. However, up to now, the processes behind poultry feeding behavior remain poorly understood. The review generalizes modern expertise about the hormonal regulation of feeding behavior in chickens, focusing on signaling pathways mediated by insulin, leptin, and ghrelin and regulatory pathways with a cross-reference to mammals. This overview also summarizes state-of-the-art research devoted to hypothalamic neuropeptides that control feed intake and are prime candidates for predictors of feeding efficiency. Comparative analysis of the signaling pathways that mediate the feed intake regulation allowed us to conclude that there are major differences in the processes by which hormones influence specific neuropeptides and their contrasting roles in feed intake control between two vertebrate clades.

Physiologically based pharmacokinetic model for predicting the biodistribution of albumin nanoparticles after induction and recovery from acute lung injury.

The application of nanomedicine in the treatment of acute lung injury (ALI) has great potential for the development of new therapeutic strategies. To gain insight into the kinetics of nanocarrier distribution upon time-dependent changes in tissue permeability after ALI induction in mice, we developed a physiologically based pharmacokinetic model for albumin nanoparticles (ANP). The model was calibrated using data from mice treated with intraperitoneal LPS (6 mg/kg), followed by intravenous ANP (0.5 mg/mouse or about 20.8 mg/kg) at 0.5, 6, and 24 h. The simulation results reproduced the experimental observations and indicated that the accumulation of ANP in the lungs increased, reaching a peak 6 h after LPS injury, whereas it decreased in the liver, kidney, and spleen. The model predicted that LPS caused an immediate (within the first 30 min) dramatic increase in lung and kidney tissue permeability, whereas splenic tissue permeability gradually increased over 24 h after LPS injection. This information can be used to design new therapies targeting specific organs affected by bacterial infections and potentially by other inflammatory insults.

State-of the-Art Constraint-Based Modeling of Microbial Metabolism: From Basics to Context-Specific Models with a Focus on Methanotrophs.

Methanotrophy is the ability of an organism to capture and utilize the greenhouse gas, methane, as a source of energy-rich carbon. Over the years, significant progress has been made in understanding of mechanisms for methane utilization, mostly in bacterial systems, including the key metabolic pathways, regulation and the impact of various factors (iron, copper, calcium, lanthanum, and tungsten) on cell growth and methane bioconversion. The implementation of -omics approaches provided vast amount of heterogeneous data that require the adaptation or development of computational tools for a system-wide interrogative analysis of methanotrophy. The genome-scale mathematical modeling of its metabolism has been envisioned as one of the most productive strategies for the integration of muti-scale data to better understand methane metabolism and enable its biotechnological implementation. Herein, we provide an overview of various computational strategies implemented for methanotrophic systems. We highlight functional capabilities as well as limitations of the most popular web resources for the reconstruction, modification and optimization of the genome-scale metabolic models for methane-utilizing bacteria.

Numerous Trigger-like Interactions of Kinases/Protein Phosphatases in Human Skeletal Muscles Can Underlie Transient Processes in Activation of Signaling Pathways during Exercise.

Optimizing physical training regimens to increase muscle aerobic capacity requires an understanding of the internal processes that occur during exercise that initiate subsequent adaptation. During exercise, muscle cells undergo a series of metabolic events that trigger downstream signaling pathways and induce the expression of many genes in working muscle fibers. There are a number of studies that show the dependence of changes in the activity of AMP-activated protein kinase (AMPK), one of the mediators of cellular signaling pathways, on the duration and intensity of single exercises. The activity of various AMPK isoforms can change in different directions, increasing for some isoforms and decreasing for others, depending on the intensity and duration of the load. This review summarizes research data on changes in the activity of AMPK, Ca2+/calmodulin-dependent protein kinase II (CaMKII), and other components of the signaling pathways in skeletal muscles during exercise. Based on these data, we hypothesize that the observed changes in AMPK activity may be largely related to metabolic and signaling transients rather than exercise intensity per se. Probably, the main events associated with these transients occur at the beginning of the exercise in a time window of about 1-10 min. We hypothesize that these transients may be partly due to putative trigger-like kinase/protein phosphatase interactions regulated by feedback loops. In addition, numerous dynamically changing factors, such as [Ca2+], metabolite concentration, and reactive oxygen and nitrogen species (RONS), can shift the switching thresholds and change the states of these triggers, thereby affecting the activity of kinases (in particular, AMPK and CaMKII) and phosphatases. The review considers the putative molecular mechanisms underlying trigger-like interactions. The proposed hypothesis allows for a reinterpretation of the experimental data available in the literature as well as the generation of ideas to optimize future training regimens.

Impact of Negative Feedbacks on De Novo Pyrimidines Biosynthesis in Escherichia coli.

Earlier studies aimed at investigating the metabolism of endogenous nucleoside triphosphates in synchronous cultures of E. coli cells revealed an auto-oscillatory mode of functioning of the pyrimidine and purine nucleotide biosynthesis system, which the authors associated with the dynamics of cell division. Theoretically, this system has an intrinsic oscillatory potential, since the dynamics of its functioning are controlled through feedback mechanisms. The question of whether the nucleotide biosynthesis system has its own oscillatory circuit is still open. To address this issue, an integral mathematical model of pyrimidine biosynthesis was developed, taking into account all experimentally verified negative feedback in the regulation of enzymatic reactions, the data of which were obtained under in vitro conditions. Analysis of the dynamic modes of the model functioning has shown that in the pyrimidine biosynthesis system, both the steady-state and oscillatory functioning modes can be realized under certain sets of kinetic parameters that fit in the physiological boundaries of the investigated metabolic system. It has been demonstrated that the occurrence of the oscillatory nature of metabolite synthesis depended on the ratio of two parameters: the Hill coefficient, hUMP1-the nonlinearity of the UMP effect on the activity of carbamoyl-phosphate synthetase, and the parameter r characterizing the contribution of the noncompetitive mechanism of UTP inhibition to the regulation of the enzymatic reaction of UMP phosphorylation. Thus, it has been theoretically shown that the E. coli pyrimidine biosynthesis system possesses its own oscillatory circuit whose oscillatory potential depends to a significant degree on the mechanism of regulation of UMP kinase activity.

Physiologically Based Pharmacokinetic Modeling of Nanoparticle Biodistribution: A Review of Existing Models, Simulation Software, and Data Analysis Tools.

Cancer treatment and pharmaceutical development require targeted treatment and less toxic therapeutic intervention to achieve real progress against this disease. In this scenario, nanomedicine emerged as a reliable tool to improve drug pharmacokinetics and to translate to the clinical biologics based on large molecules. However, the ability of our body to recognize foreign objects together with carrier transport heterogeneity derived from the combination of particle physical and chemical properties, payload and surface modification, make the designing of effective carriers very difficult. In this scenario, physiologically based pharmacokinetic modeling can help to design the particles and eventually predict their ability to reach the target and treat the tumor. This effort is performed by scientists with specific expertise and skills and familiarity with artificial intelligence tools such as advanced software that are not usually in the "cords" of traditional medical or material researchers. The goal of this review was to highlight the advantages that computational modeling could provide to nanomedicine and bring together scientists with different background by portraying in the most simple way the work of computational developers through the description of the tools that they use to predict nanoparticle transport and tumor targeting in our body.

A Modular Mathematical Model of Exercise-Induced Changes in Metabolism, Signaling, and Gene Expression in Human Skeletal Muscle.

Skeletal muscle is the principal contributor to exercise-induced changes in human metabolism. Strikingly, although it has been demonstrated that a lot of metabolites accumulating in blood and human skeletal muscle during an exercise activate different signaling pathways and induce the expression of many genes in working muscle fibres, the systematic understanding of signaling-metabolic pathway interrelations with downstream genetic regulation in the skeletal muscle is still elusive. Herein, a physiologically based computational model of skeletal muscle comprising energy metabolism, Ca2+, and AMPK (AMP-dependent protein kinase) signaling pathways and the expression regulation of genes with early and delayed responses was developed based on a modular modeling approach and included 171 differential equations and more than 640 parameters. The integrated modular model validated on diverse including original experimental data and different exercise modes provides a comprehensive in silico platform in order to decipher and track cause-effect relationships between metabolic, signaling, and gene expression levels in skeletal muscle.

Genome-Wide Atlas of Promoter Expression Reveals Contribution of Transcribed Regulatory Elements to Genetic Control of Disuse-Mediated Atrophy of Skeletal Muscle.

The prevention of muscle atrophy carries with it clinical significance for the control of increased morbidity and mortality following physical inactivity. While major transcriptional events associated with muscle atrophy-recovery processes are the subject of active research on the gene level, the contribution of non-coding regulatory elements and alternative promoter usage is a major source for both the production of alternative protein products and new insights into the activity of transcription factors. We used the cap-analysis of gene expression (CAGE) to create a genome-wide atlas of promoter-level transcription in fast (m. EDL) and slow (m. soleus) muscles in rats that were subjected to hindlimb unloading and subsequent recovery. We found that the genetic regulation of the atrophy-recovery cycle in two types of muscle is mediated by different pathways, including a unique set of non-coding transcribed regulatory elements. We showed that the activation of "shadow" enhancers is tightly linked to specific stages of atrophy and recovery dynamics, with the largest number of specific regulatory elements being transcriptionally active in the muscles on the first day of recovery after a week of disuse. The developed comprehensive database of transcription of regulatory elements will further stimulate research on the gene regulation of muscle homeostasis in mammals.

The Phylogeny of Class B Flavoprotein Monooxygenases and the Origin of the YUCCA Protein Family.

YUCCA (YUCCA flavin-dependent monooxygenase) is one of the two enzymes of the main auxin biosynthesis pathway (tryptophan aminotransferase enzyme (TAA)/YUCCA) in land plants. The evolutionary origin of the YUCCA family is currently controversial: YUCCAs are assumed to have emerged via a horizontal gene transfer (HGT) from bacteria to the most recent common ancestor (MRCA) of land plants or to have inherited it from their ancestor, the charophyte algae. To refine YUCCA origin, we performed a phylogenetic analysis of the class B flavoprotein monooxygenases and comparative analysis of the sequences belonging to different families of this protein class. We distinguished a new protein family, named type IIb flavin-containing monooxygenases (FMOs), which comprises homologs of YUCCA from Rhodophyta, Chlorophyta, and Charophyta, land plant proteins, and FMO-E, -F, and -G of the bacterium Rhodococcus jostii RHA1. The type IIb FMOs differ considerably in the sites and domain composition from the other families of class B flavoprotein monooxygenases, YUCCAs included. The phylogenetic analysis also demonstrated that the type IIb FMO clade is not a sibling clade of YUCCAs. We have also identified the bacterial protein group named YUC-like FMOs as the closest to YUCCA homologs. Our results support the hypothesis of the emergence of YUCCA via HGT from bacteria to MRCA of land plants.

A Genome-Scale Metabolic Model of 2,3-Butanediol Production by Thermophilic Bacteria Geobacillus icigianus.

The thermophilic strain of the genus Geobacillus, Geobacillus icigianus is a promising bacterial chassis for a wide range of biotechnological applications. In this study, we explored the metabolic potential of Geobacillus icigianus for the production of 2,3-butanediol (2,3-BTD), one of the cost-effective commodity chemicals. Here we present a genome-scale metabolic model iMK1321 for Geobacillus icigianus constructed using an auto-generating pipeline with consequent thorough manual curation. The model contains 1321 genes and includes 1676 reactions and 1589 metabolites, representing the most-complete and publicly available model of the genus Geobacillus. The developed model provides new insights into thermophilic bacterial metabolism and highlights new strategies for biotechnological applications of the strain. Our analysis suggests that Geobacillus icigianus has a potential for 2,3-butanediol production from a variety of utilized carbon sources, including glycerine, a common byproduct of biofuel production. We identified a set of solutions for enhancing 2,3-BTD production, including cultivation under anaerobic or microaerophilic conditions and decreasing the TCA flux to succinate via reducing citrate synthase activity. Both in silico predicted metabolic alternatives have been previously experimentally verified for closely related strains including the genus Bacillus.

Rare Earth Elements Alter Redox Balance in Methylomicrobium alcaliphilum 20ZR.

Background: Rare Earth Elements (REEs) control methanol utilization in both methane- and methanol-utilizing microbes. It has been established that the addition of REEs leads to the transcriptional repression of MxaFI-MeDH [a two-subunit methanol dehydrogenase (MeDH), calcium-dependent] and the activation of XoxF-MeDH (a one-subunit MeDH, lanthanum-dependent). Both enzymes are pyrroquinoline quinone-dependent alcohol dehydrogenases and show significant homology; however, they display different kinetic properties and substrate specificities. This study investigates the impact of the MxaFI to XoxF switch on the behavior of metabolic networks at a global scale. Results: In this study we investigated the steady-state growth of Methylomicrobium alcaliphilum 20ZR in media containing calcium (Ca) or lanthanum (La, a REE element). We found that cells supplemented with La show a higher growth rate compared to Ca-cultures; however, the efficiency of carbon conversion, estimated as biomass yield, is higher in cells grown with Ca. Three complementary global-omics approaches-RNA-seq transcriptomics, proteomics, and metabolomics-were applied to investigate the mechanisms of improved growth vs. carbon conversion. Cells grown with La showed the transcriptional activation of the xoxF gene, a homolog of the formaldehyde-activating enzyme (fae2), a putative transporter, genes for hemin-transport proteins, and nitrate reductase. In contrast, genes for mxaFI and associated cytochrome (mxaG) expression were downregulated. Proteomic profiling suggested additional adjustments of the metabolic network at the protein level, including carbon assimilation pathways, electron transport systems, and the tricarboxylic acid (TCA) cycle. Discord between gene expression and protein abundance changes points toward the possibility of post-transcriptional control of the related systems including key enzymes of the TCA cycle and a set of electron-transport carriers. Metabolomic data followed proteomics and showed the reduction of the ribulose-monophosphate (RuMP) pathway intermediates and the increase of the TCA cycle metabolites. Conclusion: Cells exposed to REEs display higher rates of growth but have lower carbon conversion efficiency compared to cells supplemented with Ca. The most plausible explanation for these physiological changes is an increased conversion of methanol into formate by XoxF-MeDH, which further stimulates methane oxidation but limits both the supply of reducing power and flux of formaldehyde into the RuMP pathway.

Author Correction: Methane utilization in Methylomicrobium alcaliphilum 20ZR: a systems approach.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

Pluripotency gene network dynamics: System views from parametric analysis.

Multiple experimental data demonstrated that the core gene network orchestrating self-renewal and differentiation of mouse embryonic stem cells involves activity of Oct4, Sox2 and Nanog genes by means of a number of positive feedback loops among them. However, recent studies indicated that the architecture of the core gene network should also incorporate negative Nanog autoregulation and might not include positive feedbacks from Nanog to Oct4 and Sox2. Thorough parametric analysis of the mathematical model based on this revisited core regulatory circuit identified that there are substantial changes in model dynamics occurred depending on the strength of Oct4 and Sox2 activation and molecular complexity of Nanog autorepression. The analysis showed the existence of four dynamical domains with different numbers of stable and unstable steady states. We hypothesize that these domains can constitute the checkpoints in a developmental progression from naïve to primed pluripotency and vice versa. During this transition, parametric conditions exist, which generate an oscillatory behavior of the system explaining heterogeneity in expression of pluripotent and differentiation factors in serum ESC cultures. Eventually, simulations showed that addition of positive feedbacks from Nanog to Oct4 and Sox2 leads mainly to increase of the parametric space for the naïve ESC state, in which pluripotency factors are strongly expressed while differentiation ones are repressed.

Methane utilization in Methylomicrobium alcaliphilum 20ZR: a systems approach.

Biological methane utilization, one of the main sinks of the greenhouse gas in nature, represents an attractive platform for production of fuels and value-added chemicals. Despite the progress made in our understanding of the individual parts of methane utilization, our knowledge of how the whole-cell metabolic network is organized and coordinated is limited. Attractive growth and methane-conversion rates, a complete and expert-annotated genome sequence, as well as large enzymatic, 13C-labeling, and transcriptomic datasets make Methylomicrobium alcaliphilum 20ZR an exceptional model system for investigating methane utilization networks. Here we present a comprehensive metabolic framework of methane and methanol utilization in M. alcaliphilum 20ZR. A set of novel metabolic reactions governing carbon distribution across central pathways in methanotrophic bacteria was predicted by in-silico simulations and confirmed by global non-targeted metabolomics and enzymatic evidences. Our data highlight the importance of substitution of ATP-linked steps with PPi-dependent reactions and support the presence of a carbon shunt from acetyl-CoA to the pentose-phosphate pathway and highly branched TCA cycle. The diverged TCA reactions promote balance between anabolic reactions and redox demands. The computational framework of C1-metabolism in methanotrophic bacteria can represent an efficient tool for metabolic engineering or ecosystem modeling.

Fatty Acid Biosynthesis Pathways in Methylomicrobium buryatense 5G(B1).

Methane utilization by methanotrophic bacteria is an attractive application for biotechnological conversion of natural or biogas into high-added-value products. Haloalcaliphilic methanotrophic bacteria belonging to the genus Methylomicrobium are among the most promising strains for methane-based biotechnology, providing easy and inexpensive cultivation, rapid growth, and the availability of established genetic tools. A number of methane bioconversions using these microbial cultures have been discussed, including the derivation of biodiesel, alkanes, and OMEGA-3 supplements. These compounds are derived from bacterial fatty acid pools. Here, we investigate fatty acid biosynthesis in Methylomicrobium buryatense 5G(B1). Most of the genes homologous to typical Type II fatty acid biosynthesis pathways could be annotated by bioinformatics analyses, with the exception of fatty acid transport and regulatory elements. Different approaches for improving fatty acid accumulation were investigated. These studies indicated that both fatty acid degradation and acetyl- and malonyl-CoA levels are bottlenecks for higher level fatty acid production. The best strain generated in this study synthesizes 111 ± 2 mg/gDCW of extractable fatty acids, which is ~20% more than the original strain. A candidate gene for fatty acid biosynthesis regulation, farE, was identified and studied. Its deletion resulted in drastic changes to the fatty acid profile, leading to an increased pool of C18-fatty acid methyl ester. The FarE-regulon was further investigated by RNA-seq analysis of gene expression in farE-knockout mutants and farE-overexpressing strains. These gene profiles highlighted a novel set of enzymes and regulators involved in fatty acid biosynthesis. The gene expression and fatty acid profiles of the different farE-strains support the hypothesis that metabolic fluxes upstream of fatty acid biosynthesis restrict fatty acid production in the methanotroph.

A new stochastic model for subgenomic hepatitis C virus replication considers drug resistant mutants.

As an RNA virus, hepatitis C virus (HCV) is able to rapidly acquire drug resistance, and for this reason the design of effective anti-HCV drugs is a real challenge. The HCV subgenomic replicon-containing cells are widely used for experimental studies of the HCV genome replication mechanisms, for drug testing in vitro and in studies of HCV drug resistance. The NS3/4A protease is essential for virus replication and, therefore, it is one of the most attractive targets for developing specific antiviral agents against HCV. We have developed a stochastic model of subgenomic HCV replicon replication, in which the emergence and selection of drug resistant mutant viral RNAs in replicon cells is taken into account. Incorporation into the model of key NS3 protease mutations leading to resistance to BILN-2061 (A156T, D168V, R155Q), VX-950 (A156S, A156T, T54A) and SCH 503034 (A156T, A156S, T54A) inhibitors allows us to describe the long term dynamics of the viral RNA suppression for various inhibitor concentrations. We theoretically showed that the observable difference between the viral RNA kinetics for different inhibitor concentrations can be explained by differences in the replication rate and inhibitor sensitivity of the mutant RNAs. The pre-existing mutants of the NS3 protease contribute more significantly to appearance of new resistant mutants during treatment with inhibitors than wild-type replicon. The model can be used to interpret the results of anti-HCV drug testing on replicon systems, as well as to estimate the efficacy of potential drugs and predict optimal schemes of their usage.

A cellular automaton to model the development of primary shoot meristems of Arabidopsis thaliana.

Development of organisms is a very complex process in which a lot of gene networks of different cell types are integrated. Development of a cellular automaton (Ermentrout and Edelshtein-Keshet, J Theor Biol 160:97-133, 1993) that models the morphodynamics of different cell types is the first step in understanding and analysis of the regulatory mechanisms underlying the functioning of developmental gene networks. A model of a cellular automaton has been developed, which simulates the embryonic development of shoot meristem in Arabidopsis thaliana. The model adequately describes the basic stages in development of this organ in wild and mutant types.