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bioRxiv2018

Visualizing metabolic network dynamics through time-series metabolomics data

New technologies have given rise to an abundance of -omics data, particularly metabolomics data. The scale of these data introduces new challenges for the interpretation and extraction of knowledge, requiring the development of new computational visualization methodologies. Here, we present a new method for the visualization of time-course metabolomics data within the context of metabolic network maps. We demonstrate the utility of this method by examining previously published data for two cellular systems--the human platelet and erythrocyte under cold storage for use in transfusion medicine.\n\nThe results comprise two animated videos that allow for new insights into the metabolic state of both cell types. In the case study of the platelet metabolome during storage, the new visualization technique elucidates a nicotinamide accumulation which mirrors that of hypoxanthine and might, therefore, reflect similar pathway usage. This visual analysis provides a possible explanation for why the salvage reactions in purine metabolism exhibit lower activity during the first few days of the storage period. The second case study displays drastic changes in specific erythrocyte metabolite pools at different times during storage at different temperatures.\n\nIn conclusion, this new visualization technique introduced in this article constitutes a well-suitable approach for large-scale network exploration and advances hypothesis generation. This method can be applied to any system with data and a metabolic map to promote visualization and understand physiology at the network level. More broadly, we hope that our approach will provide the blueprints for new visualizations of other longitudinal -omics data types.\n\nAUTHOR SUMMARYProfiling the dynamic state of a metabolic network through the use of time-course metabolomics technologies allows insights into cellular biochemistry. Interpreting these data together at the systems level provides challenges that can be addressed through the development of new visualization approaches. Here, we present a new method for the visualization of time-course metabolomics data that integrates data into an existing metabolic network map. In brief, the metabolomics data are visualized directly on a network map with dynamic elements (nodes that either change size, fill level, or color corresponding with the concentration) while the user controls the time series (i.e., which time point is being displayed) through a graphical interface. We provide short videos that illustrate the utility of this method through its application to existing data sets for the human platelet and erythrocyte. The results presented here give blueprints for the development of visualization methods for other time-course -omics data types that attempt to understand systems-level physiology.

systems biology↗
bioRxiv2018

Effect of the macroalgae Asparagopsis taxiformis on methane production and the rumen microbiome assemblage

BackgroundRecent studies using batch-fermentation suggest that the red macroalgae Asparagopsis taxiformis might reduce methane (CH4) emission from beef cattle by up to ~99% when added to rhodes grass hay, a common feed in the Australian beef industry. These experiments have shown significant reductions in methane without compromising other fermentation parameters (i.e. volatile fatty acid production) with A. taxiformis organic matter (OM) inclusion rates of up to 5%. In the study presented here, A. taxiformis was evaluated for its ability to reduce methane production from dairy cattle fed a mixed ration widely utilized in California; the largest milk producer in the US.\n\nResultsFermentation in a semi-continuous in-vitro rumen system suggests that A. taxiformis can reduce methane production from enteric fermentation in dairy cattle by 95% when added at a 5% OM inclusion rate without any obvious negative impacts on volatile fatty acid production. High-throughput 16S ribosomal RNA (rRNA) gene amplicon sequencing showed that seaweed amendment effects rumen microbiome communities consistent with the Anna Karenina hypothesis, with increased beta-diversity, over time scales of approximately three days. The relative abundance of methanogens in the fermentation vessels amended with A. taxiformis decreased significantly compared to control vessels, but this reduction in methanogen abundance was only significant when averaged over the course of the experiment. Alternatively, significant reductions of methane in the A. taxiformis amended vessels was measured in the early stages of the experiment. This suggests that A. taxiformis has an immediate effect on the metabolic functionality of rumen methanogens whereas its impact on microbiome assemblage, specifically methanogen abundance, is delayed.\n\nConclusionsThe methane reducing effect of A. taxiformis during rumen fermentation makes this macroalgae a promising candidate as a biotic methane mitigation strategy in the largest milk producing state in the US. But its effect in-vivo (i.e. in dairy cattle) remains to be investigated in animal trials. Furthermore, to obtain a holistic understanding of the biochemistry responsible for the significant reduction of methane, gene expression profiles of the rumen microbiome and the host animal are warranted.

systems biology↗
bioRxiv2018

Kinetic models of metabolism that consider alternative steady-state solutions of intracellular fluxes and concentrations

Large-scale kinetic models are used for designing, predicting, and understanding the metabolic responses of living cells. Kinetic models are particularly attractive for the biosynthesis of target molecules in cells as they are typically better than other types of models at capturing the complex cellular biochemistry. Using simpler stoichiometric models as scaffolds, kinetic models are built around a steady-state flux profile and a metabolite concentration vector that are typically determined via optimization. However, as the underlying optimization problem is underdetermined, even after incorporating available experimental omics data, one cannot uniquely determine the operational configuration in terms of metabolic fluxes and metabolite concentrations. As a result, some reactions can operate in either the forward or reverse direction while still agreeing with the observed physiology. Here, we analyze how the underlying uncertainty in intracellular fluxes and concentrations affects predictions of constructed kinetic models and their design in metabolic engineering and systems biology studies. To this end, we integrated the omics data of optimally grown Escherichia coli into a stoichiometric model and constructed populations of non-linear large-scale kinetic models of alternative steady-state solutions consistent with the physiology of the E. coli aerobic metabolism. We performed metabolic control analysis (MCA) on these models, highlighting that MCA-based metabolic engineering decisions are strongly affected by the selected steady state and appear to be more sensitive to concentration values rather than flux values. To incorporate this into future studies, we propose a workflow for moving towards more reliable and robust predictions that are consistent with all alternative steady-state solutions. This workflow can be applied to all kinetic models to improve the consistency and accuracy of their predictions. Additionally, we show that, irrespective of the alternative steady-state solution, increased activity of phosphofructokinase and decreased ATP maintenance requirements would improve cellular growth of optimally grown E. coli.

systems biology↗
bioRxiv2018

Draft genome of the liver fluke Fasciola gigantica

Fascioliasis is a neglected food-borne disease caused by liver flukes (genus Fasciola) and affects more than 200 million people worldwide. Despite technological advances, little is known about the molecular biology and biochemistry of the fluke. We present the draft genome of Fasciola gigantica for the first time. The assembled draft genome has a size of ~1.04 Gb with an N50 of 129 kb. A total of 20,858 genes were predicted. The de novo repeats identified in the draft genome were 46.85%. In pathway analysis, all the genes of glycolysis, Krebs cycle and fatty acid metabolism were found to be present, but the key genes for fatty acid production in fatty acid biosynthesis were missing. This indicates that the fatty acid required for the survival of the fluke may be acquired from the host bile. The genomic information will provide a comprehensive resource to facilitate the development of novel interventions for fascioliasis control.

bioinformatics↗
bioRxiv2013

Varing chemical equilibrium gives kinetic parameters

We are interested in finding the kinetic parameters of a chemical reaction. Previous methods for finding these parameters rely on the dynamic behaviour of the system. This means that the methods are time-sensitive and often rely on non-linear curve fitting.

Biochemistry↗
bioRxiv2014

Correcting a SHAPE-directed RNA structure by a mutate-map-rescue approach

The three-dimensional conformations of non-coding RNAs underpin their biochemical functions but have largely eluded experimental characterization. Here, we report that integrating a classic mutation/rescue strategy with high-throughput chemical mapping enables rapid RNA structure inference with unusually strong validation. We revisit a paradigmatic 16S rRNA domain for which SHAPE (selective 2'-hydroxyl acylation with primer extension) suggested a conformational change between apo-and holo-ribosome conformations. Computational support estimates, data from alternative chemical probes, and mutate-and-map (M2) experiments expose limitations of prior methodology and instead give a near-crystallographic secondary structure. Systematic interrogation of single base pairs via a high-throughput mutation/rescue approach then permits incisive validation and refinement of the M2-based secondary structure and further uncovers the functional conformation as an excited state (25{+/-}5% population) accessible via a single-nucleotide register shift. These results correct an erroneous SHAPE inference of a ribosomal conformational change and suggest a general mutate-map-rescue approach for dissecting RNA dynamic structure landscapes.

Biochemistry↗
bioRxiv2014

ATOMIC STRUCTURES OF GLUCOSE, FRUCTOSE AND SUCROSE AND EXPLANATION OF ANOMERIC CARBON

Presented here are the structures of three biologically important sweet sugars, based on the additivity of covalent atomic radii in bond lengths. The observed smaller carbon-oxygen distances involving the anomeric carbons of the open chain hexoses are explained here, for the first time, as due to the smaller covalent double bond radii of carbon and oxygen than their single bond radii in the cyclic forms and in sucrose. The atomic structures of all the three carbohydrates, drawn to scale in colour, have been presented here also for the first time.

Biochemistry↗
bioRxiv2014

Average oxidation state of carbon in proteins

The degree of oxidation of carbon atoms in organic molecules depends on the covalent structure. In proteins, the average oxidation state of carbon (ZC) can be calculated as an elemental ratio from the chemical formula. To investigate oxidation-reduction (redox) patterns, groups of proteins from different subcellular locations and phylogenetic divisions were selected for comparison. Extracellular proteins of yeast have a relatively high oxidation state of carbon, corresponding with oxidizing conditions outside of the cell. However, an inverse relationship between ZC and redox potential occurs between the endoplasmic reticulum and cytoplasm; this trend is interpreted as resulting from overall coupling of protein turnover to the formation of a lower glutathione redox potential in the cytoplasm. In Rubisco homologues, lower ZC tends to occur in organisms with higher optimal growth temperature, and there are broad changes in ZC in whole-genome protein compositions in microbes from different environments. Energetic costs calculated from thermodynamic models suggest that thermophilic organisms exhibit molecular adaptation to not only high temperature but also the reducing nature of many hydrothermal fluids. A view of protein metabolism that depends on the chemical conditions of cells and environments raises new questions linking biochemical processes to changes on evolutionary timescales.

Biochemistry↗
bioRxiv2014

MOHCA-seq: RNA 3D models from single multiplexed proximity-mapping experiments

Large RNAs control myriad biological processes but challenge tertiary structure determination. We report that integrating multiplexed *OH cleavage analysis with tabletop deep sequencing (MOHCA-seq) gives nucleotide-resolution proximity maps of RNA structure from single straightforward experiments. After achieving 1-nm resolution models for RNAs of known structure, MOHCA-seq reveals previously unattainable 3D information for ligand-induced conformational changes in a double glycine riboswitch and the sixth community-wide RNA puzzle, an adenosylcobalamin riboswitch.

Biochemistry↗
bioRxiv2014

Efficient isolation of specific genomic regions retaining molecular interactions by the iChIP system using recombinant exogenous DNA-binding proteins

BackgroundComprehensive understanding of mechanisms of genome functions requires identification of molecules interacting with genomic regions of interest in vivo. We have developed the insertional chromatin immunoprecipitatin (iChIP) technology to isolate specific genomic regions retaining molecular interactions and identify their associated molecules. iChIP consists of locus-tagging and affinity purification. The recognition sequences of an exogenous DNA-binding protein such as LexA are inserted into a genomic region of interest in the cell to be analyzed. The exogenous DNA-binding protein fused with a tag(s) is expressed in the cell and the target genomic region is purified with antibody against the tag(s). In this study, we developed the iChIP system using recombinant DNA-binding proteins to make iChIP more straightforward.\n\nResultsIn this system, recombinant 3xFNLDD-D (r3xFNLDD-D) consisting of the 3xFLAG-tag, a nuclear localization signal, the DNA-binding domain plus the dimerization domain of the LexA protein, and the Dock-tag is used for isolation of specific genomic regions. 3xFNLDD-D was expressed using a silkworm-baculovirus expression system and purified by affinity purification. iChIP using r3xFNLDD-D could efficiently isolate the single-copy chicken Pax5 (cPax5) locus, in which LexA binding elements were inserted, with negligible contamination of other genomic regions. In addition, we could detect RNA associated with the cPax5 locus using this form of the iChIP system combined with RT-PCR.\n\nConclusionsThe iChIP system using r3xFNLDD-D can isolate specific genomic regions retaining molecular interactions without expression of the exogenous DNA-binding protein in the cell to be analyzed. iChIP using r3xFNLDD-D would be more straightforward and useful for analysis of specific genomic regions to elucidate their functions.

Biochemistry↗
bioRxiv2015

An homology- and coevolution-consistent structural model of bacterial copper-tolerance protein CopM supports function as a ‘metal sponge’ and suggests regions for metal-dependent interactions with other proteins

Copper is essential for life but toxic, therefore all organisms control tightly its intracellular abundance. Bacteria have indeed whole operons devoted to copper resistance, with genes that code for efflux pumps, oxidases, etc. Recently, the CopM protein of the CopMRS operon was described as a novel important element for copper tolerance in Synechocystis. This protein consists of a domain of unknown function, and was proposed to act as a periplasmic/extracellular copper binder. This work describes a bioinformatic study of CopM including structural models based on homology modeling and on residue coevolution, to help expand on its recent biochemical characterization. The protein is predicted to be periplasmic but membrane-anchored, not secreted. Two disordered regions are predicted, both possibly involved in protein-protein interactions. The 3D models disclose a 4-helix bundle with several potential copper-binding sites, most of them largely buried inside the bundle lumen. Some of the predicted copper-binding sites involve residues from the disordered regions, suggesting they could gain structure upon copper binding and thus possibly modulate the interactions they mediate. All models are provided as PDB files in the Supporting Information and can be visualized online at http://lucianoabriata.altervista.org/modelshome.html Note (January 2017): Recent X-ray structures of apo, copper- and silver-bound CopM are < 3[A] RMSD away from the models, and reveal metal-dependent structural flexibility (Zhao et al Acta Crystallogr D Struct Biol. 2016)

Biochemistry↗
bioRxiv2015

The biological functions of Naa10—from amino-terminal acetylation to human disease

1AO_SCPLOWBSTRACTC_SCPLOWN-terminal acetylation (NTA) is one of the most abundant protein modifications known, and the N-terminal acetyltransferase (NAT) machinery is conserved throughout all Eukarya. Over the past 50 years, the function of NTA has begun to be slowly elucidated, and this includes the modulation of protein-protein interaction, protein-stability, protein function, and protein targeting to specific cellular compartments. Many of these functions have been studied in the context of Naa10/NatA; however, we are only starting to really understand the full complexity of this picture. Roughly, about 40 % of all human proteins are substrates of Naa10 and the impact of this modification has only been studied for a few of them. Besides acting as a NAT in the NatA complex, recently other functions have been linked to Naa10, including post-translational NTA, lysine acetylation, and NAT/KAT-independent functions. Also, recent publications have linked mutations in Naa10 to various diseases, emphasizing the importance of Naa10 research in humans. The recent design and synthesis of the first bisubstrate inhibitors that potently and selectively inhibit the NatA/Naa10 complex, monomeric Naa10, and hNaa50 further increases the toolset to analyze Naa10 function.

Biochemistry↗
bioRxiv2015

Chemical integration of proteins in signaling and development

In developing embryos of eukaryotes, varying concentrations and/or duration of exposure to morphogens induce and repress transcription factors (TFs) in a regular order, thereby acting as signals for cell differentiation. I present a chemical thermodynamic model for the formation and degradation of the morphogen Sonic hedgehog (Shh) and the major TFs involved in dorsal-ventral patterning of the vertebrate neural tube. This two-stage model first considers introduction of Shh into a chemically defined (oxidizing) environment. As the system is driven away from metastable equilibrium, the TFs progressively become more stable than Shh, as indicated by comparison of the calculated overall energies of formation (chemical affinity). In the second stage, a gradual return to metastable equilibrium with Shh drives transitions in the relative stabilities of the TFs that follow the experimental patterns of TF expression. At the intracellular level, the major proteins in the signal transduction network show a metastability progression among reactions of Shh and its cell-surface receptor and the intracellular Gli proteins that act as activators and repressors of transcription. If the endocytosis and degradation of receptor-ligand complexes are coupled to localized protein translation, the consequent thermodynamic constraints may represent a high-level source of specificity that coexists with molecular mechanisms of signal transduction.

Biochemistry↗
bioRxiv2015

Rich structure landscapes in both natural and artificial RNAs revealed by mutate-and-map analysis

Landscapes exhibiting multiple secondary structures arise in natural RNA molecules that modulate gene expression, protein synthesis, and viral infection, but it is unclear whether such rich landscapes are special features of biological sequences or whether they can arise without explicit selection. We report herein that high-throughput chemical experiments can isolate an RNAs multiple alternative secondary structures as they are stabilized by systematic mutagenesis (mutate-and-map, M2) and that a computational algorithm, REEFFIT, enables unbiased reconstruction of these states structures and populations. In an in silico benchmark on noncoding RNAs with complex landscapes, M2-REEFFIT recovers 95% of RNA helices present with at least 25% population while maintaining a low false discovery rate (10%) and conservative error estimates. In experimental benchmarks, M2-REEFFIT recovers the structure landscapes of a 35-nt MedLoop hairpin, a 110-nt 16S rRNA fourway junction with an excited state, a 25-nt bistable hairpin, and a 112-nt three-state adenine riboswitch with its expression platform, molecules whose characterization previously required expert mutational analysis and specialized NMR or chemical mapping experiments. With this validation, M2-REEFFIT enabled tests of whether artificial RNA sequences might exhibit complex landscapes in the absence of explicit design. An artificial flavin mononucleotide riboswitch and a randomly generated RNA sequence are found to interconvert between three or more states, including structures for which there was no design, but that could be stabilized through mutations. These results highlight the likely pervasiveness of rich landscapes with multiple secondary structures in both natural and artificial RNAs and demonstrate an automated chemical/computational route for their empirical characterization.

Biochemistry↗
bioRxiv2015

A novel SOD1-dependent mechanism for the iron-induced production of toxic SOD1 and oxidative stress that initiates ALS

Free iron is highly toxic and the blood-derived iron initiates early motor-neuron degeneration upon breakdown of blood-spinal cord barrier. Iron is currently known to trigger oxidative stress by Fenton chemistry but no report implies that iron manifests its toxicity through CuZn-superoxide dismutase (SOD1), the central antioxidant enzyme in all human tissues that carries >180 ALS-causing mutations. Here, by NMR we show that Zn2+ play an irreplaceable role in the maturation of the nascent hSOD1, and further decipher for the first time that out of 11 other cations only Fe2+ has the Zn2+-like capacity to induce folding to form the Fe2+-bound hSOD1. This acts to reduce or even block the maturation of wild-type and ALS-causing mutant hSOD1, consequently trapping SOD1 in toxic forms and provoking oxidative stress. Our study establishes a novel SOD1-dependent mechanism for iron to manifest cellular toxicity that contributes to pathogenesis of neurodegenerative diseases, aging and even more.\n\nOne Sentence SummaryOur study establishes a novel SOD1-dependent mechanism for iron to manifest toxicity contributing to neurodegenerative diseases, aging and even more.

Biochemistry↗
bioRxiv2015

Cooperative Binding Mitigates the High-Dose Hook Effect

BackgroundThe high-dose hook effect (also called prozone effect) refers to the observation that if a multivalent protein acts as a linker between two parts of a protein complex, then increasing the amount of linker protein in the mixture does not always increase the amount of fully formed complex. On the contrary, at a high enough concentration range the amount of fully formed complex actually decreases. It has been observed that allosterically regulated proteins seem less susceptible to this effect. The aim of this study was two-fold: First, to investigate the mathematical basis of how allostery mitigates the prozone effect. And second, to explore the consequences of allostery and the high-dose hook effect using the example of calmodulin, a calcium-sensing protein that regulates the switch between long-term potentiation and long-term depression in neurons.\n\nResultsWe use a combinatorial model of a \"perfect linker protein\" (with infinite binding affinity) to mathematically describe the hook effect and its behaviour under allosteric conditions. We show that allosteric regulation does indeed mitigate the high-dose hook effect. We then turn to calmodulin as a real-life example of an allosteric protein. Using kinetic simulations, we show that calmodulin is indeed subject to a hook effect. We also show that this effect is stronger in the presence of the allosteric activator Ca2+/calmodulin-dependent kinase II (CaMKII), because it reduces the overall cooperativity of the calcium-calmodulin system. It follows that, surprisingly, there are conditions where increased amount of allosteric activator actually decrease the activity of a protein.\n\nConclusionsWe show that cooperative binding can indeed act as a protective mechanism against the hook effect. This will have implications in vivo where the extent of cooperativity of a protein can be modulated, for instance, by allosteric activators or inhibitors. This can result in counterintuitive effects of decreased activity with increased concentrations of both the allosteric protein itself and its allosteric activators.

Biochemistry↗
bioRxiv2015

Evolution-Based Functional Decomposition of Proteins

The essential biological properties of proteins - folding, biochemical activities, and the capacity to adapt - arise from the global pattern of interactions between amino acid residues. The statistical coupling analysis (SCA) is an approach to defining this pattern that involves the study of amino acid coevolution in an ensemble of sequences comprising a protein family. This approach indicates a functional architecture within proteins in which the basic units are coupled networks of amino acids termed sectors. This evolution-based decomposition has potential for new understandings of the structural basis for protein function, but requires broad further testing by the scientific community. To facilitate this, we present here the principles and practice of the SCA and introduce new methods for sector analysis in a python-based software package. We show that the pattern of amino acid interactions within sectors is linked to the divergence of functional lineages in a multiple sequence alignment - a model for how sector properties might be differentially tuned in members of a protein family. This work provides new tools for understanding the structural basis for protein function and for generally testing the concept of sectors as the principal functional units of proteins.

Biochemistry↗