Analysis of the Effects of the Vrn-1 and Ppd-1 Alleles on Adaptive and Agronomic Traits in Common Wheat (Triticum aestivum L.).

Wheat heading time is primarily governed by two loci: VRN-1 (response to vernalization) and PPD-1 (response to photoperiod). Five sets of near-isogenic lines (NILs) were studied with the aim of investigating the effect of the aforementioned genes on wheat vegetative period duration and 14 yield-related traits. Every NIL was sown in the hydroponic greenhouse of the Institute of Cytology and Genetics, SB RAS. To assess their allelic composition at the VRN-1 and PPD-1 loci, molecular markers were used. It was shown that HT in plants with the Vrn-A1vrn-B1vrn-D1 genotype was reduced by 29 and 21 days (p < 0.001) in comparison to HT in plants with the vrn-A1Vrn-B1vrn-D1 and the vrn-A1vrn-B1Vrn-D1 genotypes, respectively. In our study, we noticed a decrease in spike length as well as spikelet number per spike parameter for some NIL carriers of the Vrn-A1a allele in comparison to carriers of the Vrn-B1 allele. PCA revealed three first principal components (PC), together explaining more than 70% of the data variance. Among the studied genetic traits, the Vrn-A1a and Ppd-D1a alleles showed significant correlations with PCs. Regarding genetic components, significant correlations were calculated between PC3 and Ppd-B1a (-0.26, p < 0.05) and Vrn-B1 (0.57, p < 0.05) alleles. Thus, the presence of the Vrn-A1a allele affects heading time, while Ppd-D1a is associated with plant height reduction.

Bioinformatic Analysis Reveals the Role of Translation Elongation Efficiency Optimisation in the Evolution of Ralstonia Genus.

Translation efficiency modulates gene expression in prokaryotes. The comparative analysis of translation elongation efficiency characteristics of Ralstonia genus bacteria genomes revealed that these characteristics diverge in accordance with the phylogeny of Ralstonia. The first branch of this genus is a group of bacteria commonly found in moist environments such as soil and water that includes the species R. mannitolilytica, R. insidiosa, and R. pickettii, which are also described as nosocomial infection pathogens. In contrast, the second branch is plant pathogenic bacteria consisting of R. solanacearum, R. pseudosolanacearum, and R. syzygii. We found that the soil Ralstonia have a significantly lower number and energy of potential secondary structures in mRNA and an increased role of codon usage bias in the optimization of highly expressed genes' translation elongation efficiency, not only compared to phytopathogenic Ralstonia but also to Cupriavidus necator, which is closely related to the Ralstonia genus. The observed alterations in translation elongation efficiency of orthologous genes are also reflected in the difference of potentially highly expressed gene' sets' content among Ralstonia branches with different lifestyles. Analysis of translation elongation efficiency characteristics can be considered a promising approach for studying complex mechanisms that determine the evolution and adaptation of bacteria in various environments.

Trait-Based Method of Quantitative Assessment of Ecological Functional Groups in the Human Intestinal Microbiome.

We propose the trait-based method for quantifying the activity of functional groups in the human gut microbiome based on metatranscriptomic data. It allows one to assess structural changes in the microbial community comprised of the following functional groups: butyrate-producers, acetogens, sulfate-reducers, and mucin-decomposing bacteria. It is another way to perform a functional analysis of metatranscriptomic data by focusing on the ecological level of the community under study. To develop the method, we used published data obtained in a carefully controlled environment and from a synthetic microbial community, where the problem of ambiguity between functionality and taxonomy is absent. The developed method was validated using RNA-seq data and sequencing data of the 16S rRNA amplicon on a simplified community. Consequently, the successful verification provides prospects for the application of this method for analyzing natural communities of the human intestinal microbiota.

Bioinformatic Assessment of Factors Affecting the Correlation between Protein Abundance and Elongation Efficiency in Prokaryotes.

Protein abundance is crucial for the majority of genetically regulated cell functions to act properly in prokaryotic organisms. Therefore, developing bioinformatic methods for assessing the efficiency of different stages of gene expression is of great importance for predicting the actual protein abundance. One of these steps is the evaluation of translation elongation efficiency based on mRNA sequence features, such as codon usage bias and mRNA secondary structure properties. In this study, we have evaluated correlation coefficients between experimentally measured protein abundance and predicted elongation efficiency characteristics for 26 prokaryotes, including non-model organisms, belonging to diverse taxonomic groups The algorithm for assessing elongation efficiency takes into account not only codon bias, but also number and energy of secondary structures in mRNA if those demonstrate an impact on predicted elongation efficiency of the ribosomal protein genes. The results show that, for a number of organisms, secondary structures are a better predictor of protein abundance than codon usage bias. The bioinformatic analysis has revealed several factors associated with the value of the correlation coefficient. The first factor is the elongation efficiency optimization type-the organisms whose genomes are optimized for codon usage only have significantly higher correlation coefficients. The second factor is taxonomical identity-bacteria that belong to the class Bacilli tend to have higher correlation coefficients among the analyzed set. The third is growth rate, which is shown to be higher for the organisms with higher correlation coefficients between protein abundance and predicted translation elongation efficiency. The obtained results can be useful for further improvement of methods for protein abundance prediction.

Web-MCOT Server for Motif Co-Occurrence Search in ChIP-Seq Data.

(1) Background: The widespread application of ChIP-seq technology requires annotation of cis-regulatory modules through the search of co-occurred motifs. (2) Methods: We present the web server Motifs Co-Occurrence Tool (Web-MCOT) that for a single ChIP-seq dataset detects the composite elements (CEs) or overrepresented homo- and heterotypic pairs of motifs with spacers and overlaps, with any mutual orientations, uncovering various similarities to recognition models within pairs of motifs. The first (Anchor) motif in CEs respects the target transcription factor of the ChIP-seq experiment, while the second one (Partner) can be defined either by a user or a public library of Partner motifs being processed. (3) Results: Web-MCOT computes the significances of CEs without reference to motif conservation and those with more conserved Partner and Anchor motifs. Graphic results show histograms of CE abundance depending on orientations of motifs, overlap and spacer lengths; logos of the most common CE structural types with an overlap of motifs, and heatmaps depicting the abundance of CEs with one motif possessing higher conservation than another. (4) Conclusions: Novel capacities of Web-MCOT allow retrieving from a single ChIP-seq dataset with maximal information on the co-occurrence of motifs and potentiates planning of next ChIP-seq experiments.

Agent-Based Modeling of Autosomal Recessive Deafness 1A (DFNB1A) Prevalence with Regard to Intensity of Selection Pressure in Isolated Human Population.

An increase in the prevalence of autosomal recessive deafness 1A (DFNB1A) in populations of European descent was shown to be promoted by assortative marriages among deaf people. Assortative marriages became possible with the widespread introduction of sign language, resulting in increased genetic fitness of deaf individuals and, thereby, relaxing selection against deafness. However, the effect of this phenomenon was not previously studied in populations with different genetic structures. We developed an agent-based computer model for the analysis of the spread of DFNB1A. Using this model, we tested the impact of different intensities of selection pressure against deafness in an isolated human population over 400 years. Modeling of the "purifying" selection pressure on deafness ("No deaf mating" scenario) resulted in a decrease in the proportion of deaf individuals and the pathogenic allele frequency. Modeling of the "relaxed" selection ("Assortative mating" scenario) resulted in an increase in the proportion of deaf individuals in the first four generations, which then quickly plateaued with a subsequent decline and a decrease in the pathogenic allele frequency. The results of neutral selection pressure modeling ("Random mating" scenario) showed no significant changes in the proportion of deaf individuals or the pathogenic allele frequency after 400 years.

Abnormal mTOR Activity in Pediatric Autoimmune Neuropsychiatric and MIA-Associated Autism Spectrum Disorders.

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by the early onset of communication and behavioral problems. ASD is highly heritable; however, environmental factors also play a considerable role in this disorder. A significant part of both syndromic and idiopathic autism cases could be attributed to disorders caused by mammalian target of rapamycin (mTOR)-dependent translation deregulation. This narrative review analyzes both bioinformatic and experimental evidence that connects mTOR signaling to the maternal autoantibody-related (MAR) autism spectrum and autoimmune neuropsychiatric disorders simultaneously. In addition, we reconstruct a network presenting the interactions between the mTOR signaling and eight MAR ASD genes coding for ASD-specific maternal autoantibody target proteins. The research discussed in this review demonstrates novel perspectives and validates the need for a subtyping of ASD on the grounds of pathogenic mechanisms. The utter necessity of designing ELISA-based test panels to identify all antibodies related to autism-like behavior is also considered.

ICBrainDB: An Integrated Database for Finding Associations between Genetic Factors and EEG Markers of Depressive Disorders.

In this study, we collected and systemized diverse information related to depressive and anxiety disorders as the first step on the way to investigate the associations between molecular genetics, electrophysiological, behavioral, and psychological characteristics of people. Keeping that in mind, we developed an internet resource including a database and tools for primary presentation of the collected data of genetic factors, the results of electroencephalography (EEG) tests, and psychological questionnaires. The sample of our study was 1010 people from different regions of Russia. We created the integrated ICBrainDB database that enables users to easily access, download, and further process information about individual behavioral characteristics and psychophysiological responses along with inherited trait data. The data obtained can be useful in training neural networks and in machine learning construction processes in Big Data analysis. We believe that the existence of such a resource will play an important role in the further search for associations of genetic factors and EEG markers of depression.

Antitumor efficacy of multi-target in situ vaccinations with CpG oligodeoxynucleotides, anti-OX40, anti-PD1 antibodies, and aptamers.

To overcome immune tolerance to cancer, the immune system needs to be exposed to a multi-target action intervention. Here, we investigated the activating effect of CpG oligodeoxynucleotides (ODNs), mesyl phosphoramidate CpG ODNs, anti-OX40 antibodies, and OX40 RNA aptamers on major populations of immunocompetent cells ex vivo. Comparative analysis of the antitumor effects of in situ vaccination with CpG ODNs and anti-OX40 antibodies, as well as several other combinations, such as mesyl phosphoramidate CpG ODNs and OX40 RNA aptamers, was conducted. Antibodies against programmed death 1 (PD1) checkpoint inhibitors or their corresponding PD1 DNA aptamers were also added to vaccination regimens for analytical purposes. Four scenarios were considered: a weakly immunogenic Krebs-2 carcinoma grafted in CBA mice; a moderately immunogenic Lewis carcinoma grafted in C57Black/6 mice; and an immunogenic A20 B cell lymphoma or an Ehrlich carcinoma grafted in BALB/c mice. Adding anti-PD1 antibodies (CpG+αOX40+αPD1) to in situ vaccinations boosts the antitumor effect. When to be used instead of antibodies, aptamers also possess antitumor activity, although this effect was less pronounced. The strongest effect across all the tumors was observed in highly immunogenic A20 B cell lymphoma and Ehrlich carcinoma.

Leave or Stay: Simulating Motility and Fitness of Microorganisms in Dynamic Aquatic Ecosystems.

Motility is a key adaptation factor in scarce marine environments inhabited by bacteria. The question of how a capacity for adaptive migrations influences the success of a microbial population in various conditions is a challenge addressed in this study. We employed the agent-based model of competition of motile and sedentary microbial populations in a confined aquatic environment supplied with a periodic batch nutrient source to assess the fitness of both. Such factors as nutrient concentration in a batch, batch period, mortality type and energetic costs of migration were considered to determine the conditions favouring different strategies: Nomad of a motile population and Settler of a sedentary one. The modelling results demonstrate that dynamic and nutrient-scarce environments favour motile populations, whereas nutrient-rich and stagnant environments promote sedentary microorganisms. Energetic costs of migration determine whether or not the Nomad strategy of the motile population is successful, though it also depends on such conditions as nutrient availability. Even without penalties for migration, under certain conditions, the sedentary Settler population dominates in the ecosystem. It is achieved by decreasing the local nutrient availability near the nutrient source, as motile populations relying on a local optimizing strategy tend to follow benign conditions and fail, enduring stress associated with crossing the valleys of suboptimal nutrient availability.

Experimental Comparison of the In Vivo Efficacy of Two Novel Anticancer Therapies.

BACKGROUND/AIM: We compared the therapeutic efficacy of two recently developed experimental anticancer technologies: 1) in situ vaccination based on local immunotherapy with CpG oligonucleotides and anti-OX40 antibodies to activate antitumor immune response and 2) "Karanahan" technology [from the Sanskrit karana ('source') + han ('to kill')] based on the combined injection of cyclophosphamide and double-stranded DNA to eradicate cancer stem cells. MATERIALS AND METHODS: The anticancer approaches were compared on three types of mouse malignant tumors with different grades of immunogenicity: weakly immunogenic carcinoma Krebs-2, moderately immunogenic Lewis carcinoma, and highly immunogenic A20 В-cellular lymphoma. RESULTS: Our results indicated that in situ vaccination was the most effective against the highly immunogenic tumor А20. In addition, "Karanahan" demonstrated high efficiency in all types of tumors, regardless of their immunogenicity or size. CONCLUSION: "Karanahan" therapy showed higher efficacy relative to in situ vaccination with CpG oligonucleotides and anti-OX40 antibodies.

Do Autism Spectrum and Autoimmune Disorders Share Predisposition Gene Signature Due to mTOR Signaling Pathway Controlling Expression?

Autism spectrum disorder (ASD) is characterized by uncommon genetic heterogeneity and a high heritability concurrently. Most autoimmune disorders (AID), similarly to ASD, are characterized by impressive genetic heterogeneity and heritability. We conducted gene-set analyses and revealed that 584 out of 992 genes (59%) included in a new release of the SFARI Gene database and 439 out of 871 AID-associated genes (50%) could be attributed to one of four groups: 1. FMRP (fragile X mental retardation protein) target genes, 2. mTOR signaling network genes, 3. mTOR-modulated genes, and 4. vitamin D3-sensitive genes. With the exception of FMRP targets, which are obviously associated with the direct involvement of local translation disturbance in the pathological mechanisms of ASD, the remaining categories are represented among AID genes in a very similar percentage as among ASD predisposition genes. Thus, mTOR signaling pathway genes make up 4% of ASD and 3% of AID genes, mTOR-modulated genes-31% of both ASD and AID genes, and vitamin D-sensitive genes-20% of ASD and 23% of AID genes. The network analysis revealed 3124 interactions between 528 out of 729 AID genes for the 0.7 cutoff, so the great majority (up to 67%) of AID genes are related to the mTOR signaling pathway directly or indirectly. Our present research and available published data allow us to hypothesize that both a certain part of ASD and AID comprise a connected set of disorders sharing a common aberrant pathway (mTOR signaling) rather than a vast set of different disorders. Furthermore, an immune subtype of the autism spectrum might be a specific type of autoimmune disorder with an early manifestation of a unique set of predominantly behavioral symptoms.

A new approach to estimating the prevalence of hereditary hearing loss: An analysis of the distribution of sign language users based on census data in Russia.

The absence of comparable epidemiological data challenges the correct estimation of the prevalence of congenital hearing loss (HL) around the world. Sign language (SL) is known as the main type of communication of deaf people. We suggest that the distribution of SL can be interpreted as an indirect indicator of the prevalence of congenital HL. Since a significant part of congenital HL is due to genetic causes, an assessment of the distribution of SL users can reveal regions with an extensive accumulation of hereditary HL. For the first time, we analyzed the data on the distribution of SL users that became available for the total population of Russia by the 2010 census. Seventy-three out of 85 federal regions of Russia were ranked into three groups by the 25th and 75th percentiles of the proportion of SL users: 14 regions-"low proportion"; 48 regions-"average proportion"; and 11 regions-"high proportion". We consider that the observed uneven prevalence of SL users can reflect underlying hereditary forms of congenital HL accumulated in certain populations by specific genetic background and population structure. At least, the data from this study indicate that the highest proportions of SL users detected in some Siberian regions are consistent with the reported accumulation of specific hereditary HL forms in indigenous Yakut, Tuvinian and Altaian populations.

Fold-Change-Specific Enrichment Analysis (FSEA): Quantification of Transcriptional Response Magnitude for Functional Gene Groups.

Gene expression profiling data contains more information than is routinely extracted with standard approaches. Here we present Fold-Change-Specific Enrichment Analysis (FSEA), a new method for functional annotation of differentially expressed genes from transcriptome data with respect to their fold changes. FSEA identifies Gene Ontology (GO) terms, which are shared by the group of genes with a similar magnitude of response, and assesses these changes. GO terms found by FSEA are fold-change-specifically (e.g., weakly, moderately, or strongly) affected by a stimulus under investigation. We demonstrate that many responses to abiotic factors, mutations, treatments, and diseases occur in a fold-change-specific manner. FSEA analyses suggest that there are two prevailing responses of functionally-related gene groups, either weak or strong. Notably, some of the fold-change-specific GO terms are invisible by classical algorithms for functional gene enrichment, Singular Enrichment Analysis (SEA), and Gene Set Enrichment Analysis (GSEA). These are GO terms not enriched compared to the genome background but strictly regulated by a factor within specific fold-change intervals. FSEA analysis of a cancer-related transcriptome suggested that the gene groups with a tightly coordinated response can be the valuable source to search for possible regulators, markers, and therapeutic targets in oncogenic processes. Availability and Implementation: FSEA is implemented as the FoldGO Bioconductor R package and a web-server.

The mTOR Signaling Pathway Activity and Vitamin D Availability Control the Expression of Most Autism Predisposition Genes.

Autism spectrum disorder (ASD) has a strong and complex genetic component with an estimate of more than 1000 genes implicated cataloged in SFARI (Simon's Foundation Autism Research Initiative) gene database. A significant part of both syndromic and idiopathic autism cases can be attributed to disorders caused by the mechanistic target of rapamycin (mTOR)-dependent translation deregulation. We conducted gene-set analyses and revealed that 606 out of 1053 genes (58%) included in the SFARI Gene database and 179 out of 281 genes (64%) included in the first three categories of the database ("high confidence", "strong candidate", and "suggestive evidence") could be attributed to one of the four groups: 1. FMRP (fragile X mental retardation protein) target genes, 2. mTOR signaling network genes, 3. mTOR-modulated genes, 4. vitamin D3 sensitive genes. The additional gene network analysis revealed 43 new genes and 127 new interactions, so in the whole 222 out of 281 (79%) high scored genes from SFARI Gene database were connected with mTOR signaling activity and/or dependent on vitamin D3 availability directly or indirectly. We hypothesized that genetic and/or environment mTOR hyperactivation, including provocation by vitamin D deficiency, might be a common mechanism controlling the expressivity of most autism predisposition genes and even core symptoms of autism.

Phylostratigraphic Analysis Shows the Earliest Origination of the Abiotic Stress Associated Genes in A. thaliana.

Plants constantly fight with stressful factors as high or low temperature, drought, soil salinity and flooding. Plants have evolved a set of stress response mechanisms, which involve physiological and biochemical changes that result in adaptive or morphological changes. At a molecular level, stress response in plants is performed by genetic networks, which also undergo changes in the process of evolution. The study of the network structure and evolution may highlight mechanisms of plants adaptation to adverse conditions, as well as their response to stresses and help in discovery and functional characterization of the stress-related genes. We performed an analysis of Arabidopsis thaliana genes associated with several types of abiotic stresses (heat, cold, water-related, light, osmotic, salt, and oxidative) at the network level using a phylostratigraphic approach. Our results show that a substantial fraction of genes associated with various types of abiotic stress is of ancient origin and evolves under strong purifying selection. The interaction networks of genes associated with stress response have a modular structure with a regulatory component being one of the largest for five of seven stress types. We demonstrated a positive relationship between the number of interactions of gene in the stress gene network and its age. Moreover, genes of the same age tend to be connected in stress gene networks. We also demonstrated that old stress-related genes usually participate in the response for various types of stress and are involved in numerous biological processes unrelated to stress. Our results demonstrate that the stress response genes represent the ancient and one of the fundamental molecular systems in plants.

Reconstruction and Analysis of Gene Networks of Human Neurotransmitter Systems Reveal Genes with Contentious Manifestation for Anxiety, Depression, and Intellectual Disabilities.

BACKGROUND: The study of the biological basis of anxiety, depression, and intellectual disabilities in humans is one of the most actual problems of modern neurophysiology. Of particular interest is the study of complex interactions between molecular genetic factors, electrophysiological properties of the nervous system, and the behavioral characteristics of people. The neurobiological understanding of neuropsychiatric disorders requires not only the identification of genes that play a role in the molecular mechanisms of the occurrence and course of diseases, but also the understanding of complex interactions that occur between these genes. A systematic study of such interactions obviously contributes to the development of new methods of diagnosis, prevention, and treatment of disorders, as the orientation to allele variants of individual loci is not reliable enough, because the literature describes a number of genes, the same alleles of which can be associated with different, sometimes extremely different variants of phenotypic traits, depending on the genetic background, of their carriers, habitat, and other factors. RESULTS: In our study, we have reconstructed a series of gene networks (in the form of protein-protein interactions networks, as well as networks of transcription regulation) to build a model of the influence of complex interactions of environmental factors and genetic risk factors for intellectual disability, depression, and other disorders in human behavior. CONCLUSION: A list of candidate genes whose expression is presumably associated with environmental factors and has potentially contentious manifestation for behavioral and neurological traits is identified for further experimental verification.

MIGREW: database on molecular identification of genes for resistance in wheat.

Population structure of fungal infections in wheat differs between wheat varieties and environments. Taking into account evolution of host-pathogen interactions, genetic diversity of both wheat and fungus must be a monitored. In order to catalogue information to support need of wheat pathologists and breeders, who use conventional methods and Molecular Assisted Selection (MAS) techniques, we have developed the Molecular Identification of Genes for Resistance in Wheat (MIGREW) database. The main goal of this database is to support wheat breeding efforts to develop immunity to rusts and powdery mildew. MIGREW is also focused on effectiveness of wheat resistance genes in different regions of Russia to provide users relevant information on the rapidly changing population structure of pathogens.

The Effect of Meditation on Comprehension of Statements About One-Self and Others: A Pilot ERP and Behavioral Study.

The main goal of this study was to examine the effect of long-term meditation practice on behavioral indicators and ERP peak characteristics during an error-recognition task, where participants were presented with emotionally negative (evoking anxiety or aggression) written sentences describing self-related or non-self-related emotional state and personality traits. In total, 200 sentences written in Russian with varying emotional coloring were presented during the task, with half of the sentences containing a grammatical error that the participants were asked to identify. The EEG was recorded in age-matched control individuals (n = 17) and two groups of Samatha meditators with relatively short- (3-5 years' experience, n = 18) and long-term (10-30 years' experience, n = 18) practice experience. Task performance time (TPT) and accuracy of error detection (AED) were chosen as behavioral values. Amplitude, time latency and cortical distribution of P300 and P600 peaks of ERP were used as a value of speech-related brain activity. All statistical effects of meditation were estimated, controlling for age and sex. No behavioral differences between two groups of meditators were found. General TPT was shorter for both groups of meditators compared to the control group. Non-meditators reacted significantly slower to sentences about aggression than to sentences about anxiety or non-emotional sentences, whereas no significance was found between meditator groups. Non-meditators had better AED for the sentences about one-self than for the sentences about other people, whereas the meditators did not show any significant difference. The amplitude of P300 peak in frontal and left temporal scalp regions was higher for long-term meditators in comparison with both intermediate and control groups. The latency of P300 and P600 in left frontal and temporal regions positively correlated with TPT, whereas the amplitude of P300 in these regions had a negative correlation with TPT. We demonstrate that long-term meditation practice increases the ability of an individual to process negative emotional stimuli. The differences in behavioral reactions after onset of negative information that was self-related and non-self-related, which is typical for non-meditators, disappeared due to the influence of meditation. ERP results could be interpreted as a value of increase in voluntary control over emotional state during meditational practice.

MAMMOTh: A new database for curated mathematical models of biomolecular systems.

MOTIVATION: Living systems have a complex hierarchical organization that can be viewed as a set of dynamically interacting subsystems. Thus, to simulate the internal nature and dynamics of the entire biological system, we should use the iterative way for a model reconstruction, which is a consistent composition and combination of its elementary subsystems. In accordance with this bottom-up approach, we have developed the MAthematical Models of bioMOlecular sysTems (MAMMOTh) tool that consists of the database containing manually curated MAMMOTh fitted to the experimental data and a software tool that provides their further integration. RESULTS: The MAMMOTh database entries are organized as building blocks in a way that the model parts can be used in different combinations to describe systems with higher organizational level (metabolic pathways and/or transcription regulatory networks). The tool supports export of a single model or their combinations in SBML or Mathematica standards. The database currently contains 110 mathematical sub-models for Escherichia coli elementary subsystems (enzymatic reactions and gene expression regulatory processes) that can be combined in at least 5100 complex/sophisticated models concerning more complex biological processes as de novo nucleotide biosynthesis, aerobic/anaerobic respiration and nitrate/nitrite utilization in E. coli. All models are functionally interconnected and sufficiently complement public model resources. AVAILABILITY: http://mammoth.biomodelsgroup.ru.