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1.  Nanoscratch Characterization of GaN Epilayers on c- and a-Axis Sapphire Substrates 
Nanoscale Research Letters  2010;5(11):1812-1816.
In this study, we used metal organic chemical vapor deposition to form gallium nitride (GaN) epilayers on c- and a-axis sapphire substrates and then used the nanoscratch technique and atomic force microscopy (AFM) to determine the nanotribological behavior and deformation characteristics of the GaN epilayers, respectively. The AFM morphological studies revealed that pile-up phenomena occurred on both sides of the scratches formed on the GaN epilayers. It is suggested that cracking dominates in the case of GaN epilayers while ploughing during the process of scratching; the appearances of the scratched surfaces were significantly different for the GaN epilayers on the c- and a-axis sapphire substrates. In addition, compared to the c-axis substrate, we obtained higher values of the coefficient of friction (μ) and deeper penetration of the scratches on the GaN a-axis sapphire sample when we set the ramped force at 4,000 μN. This discrepancy suggests that GaN epilayers grown on c-axis sapphire have higher shear resistances than those formed on a-axis sapphire. The occurrence of pile-up events indicates that the generation and motion of individual dislocation, which we measured under the sites of critical brittle transitions of the scratch track, resulted in ductile and/or brittle properties as a result of the deformed and strain-hardened lattice structure.
doi:10.1007/s11671-010-9717-8
PMCID: PMC2964479  PMID: 21124631
Gallium nitride; Metal organic chemical vapor deposition; Nanoscratch; Atomic force microscopy
2.  Nanoscratch Characterization of GaN Epilayers on c- and a-Axis Sapphire Substrates 
Nanoscale Research Letters  2010;5(11):1812-1816.
In this study, we used metal organic chemical vapor deposition to form gallium nitride (GaN) epilayers on c- and a-axis sapphire substrates and then used the nanoscratch technique and atomic force microscopy (AFM) to determine the nanotribological behavior and deformation characteristics of the GaN epilayers, respectively. The AFM morphological studies revealed that pile-up phenomena occurred on both sides of the scratches formed on the GaN epilayers. It is suggested that cracking dominates in the case of GaN epilayers while ploughing during the process of scratching; the appearances of the scratched surfaces were significantly different for the GaN epilayers on the c- and a-axis sapphire substrates. In addition, compared to the c-axis substrate, we obtained higher values of the coefficient of friction (μ) and deeper penetration of the scratches on the GaN a-axis sapphire sample when we set the ramped force at 4,000 μN. This discrepancy suggests that GaN epilayers grown on c-axis sapphire have higher shear resistances than those formed on a-axis sapphire. The occurrence of pile-up events indicates that the generation and motion of individual dislocation, which we measured under the sites of critical brittle transitions of the scratch track, resulted in ductile and/or brittle properties as a result of the deformed and strain-hardened lattice structure.
doi:10.1007/s11671-010-9717-8
PMCID: PMC2964479  PMID: 21124631
Gallium nitride; Metal organic chemical vapor deposition; Nanoscratch; Atomic force microscopy
3.  Molecular Dynamics and Quantum Mechanics of RNA: Conformational and Chemical Change We Can Believe In 
Accounts of Chemical Research  2009;43(1):40-47.
Structure and dynamics are both critical to RNA’s vital functions in biology. Numerous techniques can elucidate the structural dynamics of RNA, but computational approaches based on experimental data arguably hold the promise of providing the most detail. In this Account, we highlight areas wherein molecular dynamics (MD) and quantum mechanical (QM) techniques are applied to RNA, particularly in relation to complementary experimental studies.
We have expanded on atomic-resolution crystal structures of RNAs in functionally relevant states by applying explicit solvent MD simulations to explore their dynamics and conformational changes on the submicrosecond time scale. MD relies on simplified atomistic, pairwise additive interaction potentials (force fields). Because of limited sampling, due to the finite accessible simulation time scale and the approximated force field, high-quality starting structures are required.
Despite their imperfection, we find that currently available force fields empower MD to provide meaningful and predictive information on RNA dynamics around a crystallographically defined energy minimum. The performance of force fields can be estimated by precise QM calculations on small model systems. Such calculations agree reasonably well with the Cornell et al. AMBER force field, particularly for stacking and hydrogen-bonding interactions. A final verification of any force field is accomplished by simulations of complex nucleic acid structures.
The performance of the Cornell et al. AMBER force field generally corresponds well with and augments experimental data, but one notable exception could be the capping loops of double-helical stems. In addition, the performance of pairwise additive force fields is obviously unsatisfactory for inclusion of divalent cations, because their interactions lead to major polarization and charge-transfer effects neglected by the force field. Neglect of polarization also limits, albeit to a lesser extent, the description accuracy of other contributions, such as interactions with monovalent ions, conformational flexibility of the anionic sugar−phosphate backbone, hydrogen bonding, and solute polarization by solvent. Still, despite limitations, MD simulations are a valid tool for analyzing the structural dynamics of existing experimental structures. Careful analysis of MD simulations can identify problematic aspects of an experimental RNA structure, unveil structural characteristics masked by experimental constraints, reveal functionally significant stochastic fluctuations, evaluate the structural role of base ionization, and predict structurally and potentially functionally important details of the solvent behavior, including the presence of tightly bound water molecules. Moreover, combining classical MD simulations with QM calculations in hybrid QM/MM approaches helps in the assessment of the plausibility of chemical mechanisms of catalytic RNAs (ribozymes).
In contrast, the reliable prediction of structure from sequence information is beyond the applicability of MD tools. The ultimate utility of computational studies in understanding RNA function thus requires that the results are neither blindly accepted nor flatly rejected, but rather considered in the context of all available experimental data, with great care given to assessing limitations through the available starting structures, force field approximations, and sampling limitations. The examples given in this Account showcase how the judicious use of basic MD simulations has already served as a powerful tool to help evaluate the role of structural dynamics in biological function of RNA.
doi:10.1021/ar900093g
PMCID: PMC2808146  PMID: 19754142
4.  Global Nanotribology Research Output (1996–2010): A Scientometric Analysis 
PLoS ONE  2013;8(12):e81094.
This study aims to assess the nanotribology research output at global level using scientometric tools. The SCOPUS database was used to retrieve records related to the nanotribology research for the period 1996–2010. Publications were counted on a fractional basis. The level of collaboration and its citation impact were examined. The performance of the most productive countries, institutes and most preferred journals is assessed. Various visualization tools such as the Sci2 tool and Ucinet were employed. The USA ranked top in terms of number of publications, citations per paper and h-index, while Switzerland published a higher percentage of international collaborative papers. The most productive institution was Tsinghua University followed by Ohio State University and Lanzhou Institute of Chemical Physics, CAS. The most preferred journals were Tribology Letters, Wear and Journal of Japanese Society of Tribologists. The result of author keywords analysis reveals that Molecular Dynamics, MEMS, Hard Disk and Diamond like Carbon are major research topics.
doi:10.1371/journal.pone.0081094
PMCID: PMC3855179  PMID: 24339900
5.  Effects of Grazing Intensity and Environmental Factors on Species Composition and Diversity in Typical Steppe of Inner Mongolia, China 
PLoS ONE  2012;7(12):e52180.
In the present study, we aim to analyze the effect of grazing, precipitation and temperature on plant species dynamics in the typical steppe of Inner Mongolia, P.R. China. By uncoupling biotic and abiotic factors, we provide essential information on the main drivers determining species composition and species diversity. Effects of grazing by sheep were studied in a controlled experiment along a gradient of seven grazing intensities (from ungrazed to very heavily grazed) during six consecutive years (2005–2010). The results show that plant species composition and diversity varied among years but were little affected by grazing intensity, since the experimental years were much dryer than the long term average, the abiotic constraints may have overridden any grazing effect. Among-year differences were predominantly determined by the abiotic factors of precipitation and temperature. Most of the variation in species dynamics and coexistence between C3 and C4 species was explained by seasonal weather conditions, i.e. precipitation and temperature regime during the early-season (March-June) were most important in determining vegetation dynamics. The dominant C3 species Stipa grandis was highly competitive in March-June, when the temperature levels were low and rainfall level was high. In contrast, the most common C4 species Cleistogenes squarrosa benefited from high early-season temperature levels and low early-season rainfall. However, biomass of Stipa grandis was positively correlated with temperature in March, when effective mean temperature ranges from 0 to 5°C and thus promotes vernalization and vegetative sprouting. Our results suggest that, over a six-year term, it is temporal variability in precipitation and temperature rather than grazing that determines vegetation dynamics and species co-existence of grazed steppe ecosystems. Furthermore, our data support that the variability in the biomass of dominant species, rather than diversity, determine ecosystem functioning. The present study provides fundamental knowledge on the complex interaction of grazing – vegetation – climate.
doi:10.1371/journal.pone.0052180
PMCID: PMC3528763  PMID: 23284925
6.  On the Origins of the Weak Folding Cooperativity of a Designed ββα Ultrafast Protein FSD-1 
PLoS Computational Biology  2010;6(11):e1000998.
FSD-1, a designed small ultrafast folder with a ββα fold, has been actively studied in the last few years as a model system for studying protein folding mechanisms and for testing of the accuracy of computational models. The suitability of this protein to describe the folding of naturally occurring α/β proteins has recently been challenged based on the observation that the melting transition is very broad, with ill-resolved baselines. Using molecular dynamics simulations with the AMBER protein force field (ff96) coupled with the implicit solvent model (IGB = 5), we shed new light into the nature of this transition and resolve the experimental controversies. We show that the melting transition corresponds to the melting of the protein as a whole, and not solely to the helix-coil transition. The breadth of the folding transition arises from the spread in the melting temperatures (from ∼325 K to ∼302 K) of the individual transitions: formation of the hydrophobic core, β-hairpin and tertiary fold, with the helix formed earlier. Our simulations initiated from an extended chain accurately predict the native structure, provide a reasonable estimate of the transition barrier height, and explicitly demonstrate the existence of multiple pathways and multiple transition states for folding. Our exhaustive sampling enables us to assess the quality of the Amber ff96/igb5 combination and reveals that while this force field can predict the correct native fold, it nonetheless overstabilizes the α-helix portion of the protein (Tm = ∼387K) as well as the denatured structures.
Author Summary
The protein folding process, in which a linear chain of amino acids reaches its biologically active three-dimensional shape, is fundamental to life. Small “ultrafast” folders, proteins that fold in microseconds, have received considerable attention, because these proteins serve as model systems for the folding of larger proteins, and thus permit a testing of the accuracy of computational models as well as an assessment of protein folding theories. FSD-1, a designed small ultrafast folder with a ββα fold, has been actively studied in the last few years as a model system for mixed α/β fold proteins. The suitability of this protein to describe the folding of naturally occurring proteins has however recently been challenged based on the observation that the melting transition is very broad, with ill-resolved baselines. Prior simulations have not been successful in providing an interpretation of this broad melting transition. In the present study, our extensive molecular dynamics simulations using the AMBER protein force field (ff96) coupled with the implicit solvent model (IGB = 5) shed new light on the nature of the folding transition of this protein, as well as reveal the strengths and weaknesses of the force field in predicting the thermodynamics and kinetics of folding.
doi:10.1371/journal.pcbi.1000998
PMCID: PMC2987907  PMID: 21124953
7.  Lateral Diffusion of Peripheral Membrane Proteins on Supported Lipid Bilayers Is Controlled by the Additive Frictional Drags of 1) Bound Lipids and 2) Protein Domains Penetrating into the Bilayer Hydrocarbon Core 
Peripheral membrane proteins bound to lipids on bilayer surfaces play central roles in a wide array of cellular processes, including many signaling pathways. These proteins diffuse in the plane of the bilayer and often undergo complex reactions involving the binding of regulatory and substrate lipids and proteins they encounter during their 2-D diffusion. Some peripheral proteins, for example pleckstrin homology (PH) domains, dock to the bilayer in a relatively shallow position with little penetration into the bilayer. Other peripheral proteins exhibit more complex bilayer contacts, for example classical protein kinase C isoforms (PKCs) bind as many as six lipids in stepwise fashion, resulting in the penetration of three PKC domains (C1A, C1B, C2) into the bilayer headgroup and hydrocarbon regions. A molecular understanding of the molecular features that control the diffusion speeds of proteins bound to supported bilayers would enable key molecular information to be extracted from experimental diffusion constants, revealing protein-lipid and protein-bilayer interactions difficult to study by other methods. The present study investigates a range of 11 different peripheral protein constructs comprised by 1 to 3 distinct domains (PH, C1A, C1B, C2, anti-lipid antibody). By combining these constructs with various combinations of target lipids, the study measures 2-D diffusion constants on supported bilayers for 17 different protein-lipid complexes. The resulting experimental diffusion constants, together with the known membrane interaction parameters of each complex, are used to analyze the molecular features correlated with diffusional slowing and bilayer friction. The findings show that both 1) individual bound lipids and 2) individual protein domains that penetrate into the hydrocarbon core make additive contributions to the friction against the bilayer, thereby defining the 2-D diffusion constant. An empirical formula is developed that accurately estimates the diffusion constant and bilayer friction of a peripheral protein in terms of its number of bound lipids and its geometry of penetration into the bilayer hydrocarbon core, yielding an excellent global best fit (R2 of 0.97) to the experimental diffusion constants. Finally, the observed additivity of the frictional contributions suggests that further development of current theory describing bilayer dynamics may be needed. The present findings provide constraints that will be useful in such theory development.
doi:10.1016/j.chemphyslip.2013.04.005
PMCID: PMC3707953  PMID: 23701821
PKC; GRP1; cPLA2; PH domain; C1 domain; C2 domain; phosphatidylinositol lipid
8.  Thermal Adaptation of Conformational Dynamics in Ribonuclease H 
PLoS Computational Biology  2013;9(10):e1003218.
The relationship between inherent internal conformational processes and enzymatic activity or thermodynamic stability of proteins has proven difficult to characterize. The study of homologous proteins with differing thermostabilities offers an especially useful approach for understanding the functional aspects of conformational dynamics. In particular, ribonuclease HI (RNase H), an 18 kD globular protein that hydrolyzes the RNA strand of RNA:DNA hybrid substrates, has been extensively studied by NMR spectroscopy to characterize the differences in dynamics between homologs from the mesophilic organism E. coli and the thermophilic organism T. thermophilus. Herein, molecular dynamics simulations are reported for five homologous RNase H proteins of varying thermostabilities and enzymatic activities from organisms of markedly different preferred growth temperatures. For the E. coli and T. thermophilus proteins, strong agreement is obtained between simulated and experimental values for NMR order parameters and for dynamically averaged chemical shifts, suggesting that these simulations can be a productive platform for predicting the effects of individual amino acid residues on dynamic behavior. Analyses of the simulations reveal that a single residue differentiates between two different and otherwise conserved dynamic processes in a region of the protein known to form part of the substrate-binding interface. Additional key residues within these two categories are identified through the temperature-dependence of these conformational processes.
Author Summary
The relationship between enzymatic activity and protein stability has long been a difficult problem in the study of protein biochemistry. Enzymes may undergo structural changes in order to bind substrates, catalyze chemical reactions, and release products, but flexibility often is inversely correlated with thermodynamic stability. Proteins from organisms that are adapted to high temperature can be both more rigid and less active at ambient temperature than their homologs from organisms that grow at lower temperatures. For this reason, studying homologous pairs of proteins from organisms adapted to different thermal environments is a productive way to identify functionally important motions. In this work we perform comparative analyses of molecular dynamics simulations for five ribonuclease H proteins of varying thermal stabilities, isolated from organisms that grow in varying thermal environments. We identify two different mechanisms of motion in a region of the protein that interacts with substrate molecules, suggesting at least two forms of thermal adaptation in this protein family.
doi:10.1371/journal.pcbi.1003218
PMCID: PMC3789780  PMID: 24098095
9.  Expanding the Druggable Space of the LSD1/CoREST Epigenetic Target: New Potential Binding Regions for Drug-Like Molecules, Peptides, Protein Partners, and Chromatin 
PLoS Computational Biology  2013;9(7):e1003158.
Lysine specific demethylase-1 (LSD1/KDM1A) in complex with its corepressor protein CoREST is a promising target for epigenetic drugs. No therapeutic that targets LSD1/CoREST, however, has been reported to date. Recently, extended molecular dynamics (MD) simulations indicated that LSD1/CoREST nanoscale clamp dynamics is regulated by substrate binding and highlighted key hinge points of this large-scale motion as well as the relevance of local residue dynamics. Prompted by the urgent need for new molecular probes and inhibitors to understand LSD1/CoREST interactions with small-molecules, peptides, protein partners, and chromatin, we undertake here a configurational ensemble approach to expand LSD1/CoREST druggability. The independent algorithms FTMap and SiteMap and our newly developed Druggable Site Visualizer (DSV) software tool were used to predict and inspect favorable binding sites. We find that the hinge points revealed by MD simulations at the SANT2/Tower interface, at the SWIRM/AOD interface, and at the AOD/Tower interface are new targets for the discovery of molecular probes to block association of LSD1/CoREST with chromatin or protein partners. A fourth region was also predicted from simulated configurational ensembles and was experimentally validated to have strong binding propensity. The observation that this prediction would be prevented when using only the X-ray structures available (including the X-ray structure bound to the same peptide) underscores the relevance of protein dynamics in protein interactions. A fifth region was highlighted corresponding to a small pocket on the AOD domain. This study sets the basis for future virtual screening campaigns targeting the five novel regions reported herein and for the design of LSD1/CoREST mutants to probe LSD1/CoREST binding with chromatin and various protein partners.
Author Summary
Protein dynamics plays a major role in determining the molecular interactions available to molecular binding partners, including druggable hot spots. The LSD1/CoREST complex is one of the most relevant epigenetic targets discovered and was shown to be a highly dynamic nanoscale clamp using molecular dynamics simulations. The general relationship between LSD1/CoREST dynamics and the molecular sites available for non-covalent interactions with an array of known binding partners (from relatively small drug-like molecules and peptides, to larger proteins and chromatin) remains relatively unexplored. We employed an integrated experimental and computational biology approach to effectively capture the nature of non-covalent binding interactions available to the LSD1/CoREST nanoscale complex. This ensemble approach relies on the newly developed graphical visualization by Druggable Site Visualizer (DSV) that allows treatment of large-size protein configurational ensembles data and is freely distributed to the public and readily transferable to other protein targets of pharmacological interest.
doi:10.1371/journal.pcbi.1003158
PMCID: PMC3715402  PMID: 23874194
10.  Kinetic nanofriction: a mechanism transition from quasi-continuous to ballistic-like Brownian regime 
Nanoscale Research Letters  2012;7(1):148.
Surface diffusion of mobile adsorbates is not only the key to control the rate of dynamical processes on solid surfaces, e.g. epitaxial growth, but also of fundamental importance for recent technological applications, such as nanoscale electro-mechanical, tribological, and surface probing devices. Though several possible regimes of surface diffusion have been suggested, the nanoscale surface Brownian motion, especially in the technologically important low friction regimes, remains largely unexplored. Using molecular dynamics simulations, we show for the first time, that a C60 admolecule on a graphene substrate exhibits two distinct regimes of nanoscale Brownian motion: a quasi-continuous and a ballistic-like. A crossover between these two regimes is realized by changing the temperature of the system. We reveal that the underlying physical origin for this crossover is a mechanism transition of kinetic nanofriction arising from distinctive ways of interaction between the admolecule and the graphene substrate in these two regimes due to the temperature change. Our findings provide insight into surface mass transport and kinetic friction control at the nanoscale.
doi:10.1186/1556-276X-7-148
PMCID: PMC3366869  PMID: 22353343
11.  Utilizing a Dynamical Description of IspH to Aid in the Development of Novel Antimicrobial Drugs 
PLoS Computational Biology  2013;9(12):e1003395.
The nonmevalonate pathway is responsible for isoprenoid production in microbes, including H. pylori, M. tuberculosis and P. falciparum, but is nonexistent in humans, thus providing a desirable route for antibacterial and antimalarial drug discovery. We coordinate a structural study of IspH, a [4Fe-4S] protein responsible for converting HMBPP to IPP and DMAPP in the ultimate step in the nonmevalonate pathway. By performing accelerated molecular dynamics simulations on both substrate-free and HMBPP-bound [Fe4S4]2+ IspH, we elucidate how substrate binding alters the dynamics of the protein. Using principal component analysis, we note that while substrate-free IspH samples various open and closed conformations, the closed conformation observed experimentally for HMBPP-bound IspH is inaccessible in the absence of HMBPP. In contrast, simulations with HMBPP bound are restricted from accessing the open states sampled by the substrate-free simulations. Further investigation of the substrate-free simulations reveals large fluctuations in the HMBPP binding pocket, as well as allosteric pocket openings – both of which are achieved through the hinge motions of the individual domains in IspH. Coupling these findings with solvent mapping and various structural analyses reveals alternative druggable sites that may be exploited in future drug design efforts.
Author Summary
Drug resistance has recently entered into media conversations through the lens of MRSA (methicillin-resistant Staphylococcus aureus) infections, but conventional therapies are also failing to address resistance in cases of malaria and other bacterial infections, such as tuberculosis. To address these problems, we must develop new antibacterial and antimalarial medications. Our research focuses on understanding the structure and dynamics of IspH, an enzyme whose function is necessary for the survival of most bacteria and malaria-causing protozoans. Using computer simulations, we track how the structure of IspH changes in the presence and absence of its natural substrate. By inspecting the pockets that form in the normal motions of IspH, we propose a couple new routes by which new molecules may be developed to disrupt the function of IspH. It is our hope that these structural studies may be precursors to the development of novel therapies that may add to our current arsenal against bacterial and malarial infections.
doi:10.1371/journal.pcbi.1003395
PMCID: PMC3868525  PMID: 24367248
12.  Evolutionary fates within a microbial population highlight an essential role for protein folding during natural selection 
Physicochemical properties of molecules can be linked directly to evolutionary fates of a population in a quantitative and predictive manner.Reversible- and irreversible-folding pathways must be accounted for to accurately determine in vitro kinetic parameters (KM and kcat) at temperatures or conditions in which a significant fraction of free enzyme is unfolded.In vivo population dynamics can be reproduced using in vitro physicochemical measurements within a model that imposes an activity threshold above which there is no added fitness benefit.
In nature, evolution occurs through the continuous adaptation of a population to its environment. The success or failure of organisms during adaptation is based on changes in molecular structure that give rise to changes in fitness that dictate evolutionary fates within a population. Although the conceptual link between genotype, phenotype, and fitness is clear, the ability to relate these complex adaptive landscapes in a quantitative manner remains difficult (Kacser and Burns, 1981; Dykhuizen et al, 1987; Weinreich et al, 2006). Dean and Thornton (2007) coined the term ‘functional synthesis' to capture the synergy between evolutionary and molecular biology to address important questions such as the evolution of complexity. The ‘functional synthesis,' in its most fully realized form, is an integrated systems biology approach to evolutionary dynamics that links physicochemical properties of molecules to evolutionary fates in a quantitative and predictive manner.
Functional synthesis flourishes in an experimental framework that allows investigators to directly link population dynamics (fitness) to changes in molecular function that result from alterations at the nucleotide level. The ‘weak link' approach was developed to tightly couple adaptive changes within the genome to changes in fitness and provide a population-based approach that can be used to examine alterations in function and fitness at the level of atomic structure and function (Counago and Shamoo, 2005; Counago et al, 2006). A homologous recombination strategy was used to replace the chromosomal copy of the essential adenylate kinase gene (adk) of the thermophilic bacterium Geobacillus stearothermophilus with that of the mesophile Bacillus subtilis. Recombinant G. stearothermophilus cells that expressed only B. subtilis adenylate kinase (AKBSUB) were unable to grow at temperatures higher than 55°C because of heat inactivation of the mesophilic enzyme and consequent disruption of adenylate homeostasis (Counago and Shamoo, 2005). Continuously growing populations of bacteria were then subjected to selection at increasing temperatures (from 55 to 70°C) that favor changes in the one gene not adapted for thermostability, adk. During the course of selection, the population was sampled and intermediates of adaptation were observed as mutations to adk. The first mutant to reach fixation was a single mutation AKBSUB Q199R (the glutamine at position 199 replaced with arginine). AKBSUB Q199R was eventually replaced at 62–63°C by five double mutants that arose nearly simultaneously within the population and share AKBSUB Q199R as their progenitor (Figure 4C). Changes to AK activity and thermal stability that resulted from mutation had direct consequences for cellular fitness and, therefore, met our goal for an experimental system that allows us to develop and test models for quantitative molecular evolution. These enzyme activities and stabilities were examined to determine how the mutant populations traversed the adaptive landscape to increased fitness (Counago et al, 2006).
We found that reversible- and irreversible-folding pathways as well as a ‘physiological threshold' above which fitness changes are minimal are necessary to reproduce the in vivo evolutionary fates of the population. Protein-folding parameters must be accounted for to accurately determine in vitro kinetic parameters (KM and kcat) at temperatures in which a significant fraction of free enzyme is unfolded (Scheme I and Equation 1).
Scheme I
where
Thermostability was assayed using differential scanning calorimetry (DSC) (Figure 4A) and the fraction of unfolded protein (YU) was then extended to accurately predict the extent of stabilization, shift in Tm, in the presence of ligand. The kinetic parameters determined at specific temperatures were then used to construct a temperature-dependent formulation of Equation (1) to model in vitro activity at any given ATP concentration and any temperature (Figure 4B).
Here, we have modeled fitness as a function of in vitro enzyme activity, which is a product of both activity and stability, and the application of a threshold that provides an upper limit on fitness. We hypothesize that an activity threshold exists above which no added fitness benefit is attained (the ‘physiological threshold'). However, as activity falls below this threshold, AK becomes rate limiting and fitness is negatively affected. The experimentally observed rise and fall of mutant alleles is shown in Figure 4C, whereas those predicted from our in vitro model are shown as Figure 4D. This model can successfully reproduce frequencies of mutants in a polymorphic population, including the transient success of three minor mutants and order of disappearance from the population, given only in vitro data and allowing for the activity threshold to be fit to the observed outcomes (Figure 4D). An appealing aspect of our fitness function is that it permits an evaluation of specific and quantitative aspects of protein stability and activity relative to evolutionary fates.
In vivo, diversity within a population is generated by a variety of mechanisms that span single nucleotide changes to genome-wide rearrangements and horizontal gene transfer. However, changes are generated within an organism, it is the physicochemical characteristics of the resulting macromolecules and their resultant changes in the fitness of the organism that are the ‘grist for the mill' of natural selection. Recent work has shown that adaptability can be facilitated by the accumulation of near neutral or even modestly destabilizing mutations that provide more possibilities for success. Chaperones have an important function in buffering biological systems against these destabilizing mutations as well as mistakes in translation that lead to polymorphic populations and have been shown to increase rates of adaptation (Rutherford, 2003; Drummond and Wilke, 2008; Tokuriki and Tawfik, 2009a). Thus, adaptation through protein evolution is circumscribed by protein stability. As most mutational events will be destabilizing (Tokuriki and Tawfik, 2009b), higher mutation rates can lead to decreases in fitness eventually leading to extinction (Zeldovich et al, 2007; Chen and Shakhnovich, 2009). Although our system links the physicochemical properties of adaptive changes that increase stability, the principles apply equally to those changes that might decrease stability of the ensemble either through mutation or translational errors (Drummond and Wilke, 2008). Thus, regardless of how protein diversity is generated, evolutionary dynamics will likely be strongly coupled to stability and function.
Systems biology can offer a great deal of insight into evolution by quantitatively linking complex properties such as protein structure, folding, and function to the fitness of an organism. Although the link between diseases such as Alzheimer's and misfolding is well appreciated, directly showing the importance of protein folding to success in evolution has been more difficult. We show here that predicting success during adaptation can depend critically on enzyme kinetic and folding models. We used a ‘weak link' method to favor mutations to an essential, but maladapted, adenylate kinase gene within a microbial population that resulted in the identification of five mutants that arose nearly simultaneously and competed for success. Physicochemical characterization of these mutants showed that, although steady-state enzyme activity is important, success within the population is critically dependent on resistance to denaturation and aggregation. A fitness function based on in vitro measurements of enzyme activity, reversible and irreversible unfolding, and the physiological context reproduces in vivo evolutionary fates in the population linking organismal adaptation to its physical basis.
doi:10.1038/msb.2010.43
PMCID: PMC2925523  PMID: 20631681
adenylate kinase; enzyme kinetics; experimental evolution; fitness functions; protein folding
13.  Further optimization of a hybrid united-atom and coarse-grained force field for folding simulations: Improved backbone hydration and interactions between charged side chains 
PACE, a hybrid force field which couples united-atom protein models with coarse-grained (CG) solvent, has been further optimized, aiming to improve itse ciency for folding simulations. Backbone hydration parameters have been re-optimized based on hydration free energies of polyalanyl peptides through atomistic simulations. Also, atomistic partial charges from all-atom force fields were combined with PACE in order to provide a more realistic description of interactions between charged groups. Using replica exchange molecular dynamics (REMD), ab initio folding using the new PACE has been achieved for seven small proteins (16 – 23 residues) with different structural motifs. Experimental data about folded states, such as their stability at room temperature, melting point and NMR NOE constraints, were also well reproduced. Moreover, a systematic comparison of folding kinetics at room temperature has been made with experiments, through standard MD simulations, showing that the new PACE may speed up the actual folding kinetics 5-10 times. Together with the computational speedup benefited from coarse-graining, the force field provides opportunities to study folding mechanisms. In particular, we used the new PACE to fold a 73-residue protein, 3D, in multiple 10 – 30 μs simulations, to its native states (Cα RMSD ~ 0.34 nm). Our results suggest the potential applicability of the new PACE for the study of folding and dynamics of proteins.
doi:10.1021/ct300696c
PMCID: PMC3507460  PMID: 23204949
14.  Functional Rotation of the Transporter AcrB: Insights into Drug Extrusion from Simulations 
PLoS Computational Biology  2010;6(6):e1000806.
The tripartite complex AcrAB-TolC is the major efflux system in Escherichia coli. It extrudes a wide spectrum of noxious compounds out of the bacterium, including many antibiotics. Its active part, the homotrimeric transporter AcrB, is responsible for the selective binding of substrates and energy transduction. Based on available crystal structures and biochemical data, the transport of substrates by AcrB has been proposed to take place via a functional rotation, in which each monomer assumes a particular conformation. However, there is no molecular-level description of the conformational changes associated with the rotation and their connection to drug extrusion. To obtain insights thereon, we have performed extensive targeted molecular dynamics simulations mimicking the functional rotation of AcrB containing doxorubicin, one of the two substrates that were co-crystallized so far. The simulations, including almost half a million atoms, have been used to test several hypotheses concerning the structure-dynamics-function relationship of this transporter. Our results indicate that, upon induction of conformational changes, the substrate detaches from the binding pocket and approaches the gate to the central funnel. Furthermore, we provide strong evidence for the proposed peristaltic transport involving a zipper-like closure of the binding pocket, responsible for the displacement of the drug. A concerted opening of the channel between the binding pocket and the gate further favors the displacement of the drug. This microscopically well-funded information allows one to identify the role of specific amino acids during the transitions and to shed light on the functioning of AcrB.
Author Summary
In nature, bacteria have to resist several toxic threats to be able to survive, from bile acids in intestines up to antibiotics. The Escherichia coli bacterium, which usually is a commensal inhabitant of human intestines, can also acquire pathogenic properties which would harm the human body. To dispose of toxic compounds, E. coli has developed a protein machinery which is called “efflux pump”. Here, we studied the dynamics of the transporter protein AcrB, a component of the E. coli major efflux system, in complex with an antibiotic (doxorubicin). We used computer simulations to complement the existing experimental data. Our purpose was to gain more detailed insights into the pumping mechanism at the molecular level. In our simulations the drug leaves the binding pocket upon induction of functional rotation in the protein, although a complete extrusion was never observed. A peristaltic motion, which starts with a zipper-like closure of the interior of the protein, is an important step for the extrusion of the drug. Interestingly, such a peristaltic mechanism of pumping has been suggested before on the basis of structural data. The molecular details obtained in this study shall deepen the understanding of the functioning of the efflux pump.
doi:10.1371/journal.pcbi.1000806
PMCID: PMC2883587  PMID: 20548943
15.  Development of a laser-based heating system for in situ synchrotron-based X-ray tomographic microscopy 
Journal of Synchrotron Radiation  2012;19(Pt 3):352-358.
A laser-based heating system has been developed at the TOMCAT beamline of the Swiss Light Source for in situ observations of moderate-to-high-temperature applications of materials.
Understanding the formation of materials at elevated temperatures is critical for determining their final properties. Synchrotron-based X-ray tomographic microscopy is an ideal technique for studying such processes because high spatial and temporal resolutions are easily achieved and the technique is non-destructive, meaning additional analyses can take place after data collection. To exploit the state-of-the-art capabilities at the tomographic microscopy and coherent radiology experiments (TOMCAT) beamline of the Swiss Light Source, a general-use moderate-to-high-temperature furnace has been developed. Powered by two diode lasers, it provides controlled localized heating, from 673 to 1973 K, to examine many materials systems and their dynamics in real time. The system can also be operated in various thermal modalities. For example, near-isothermal conditions at a given sample location can be achieved with a prescribed time-dependent temperature. This mode is typically used to study isothermal phase transformations; for example, the formation of equiaxed grains in metallic systems or to nucleate and grow bubble foams in silicate melts under conditions that simulate volcanic processes. In another mode, the power of the laser can be fixed and the specimen moved at a constant speed in a user-defined thermal gradient. This is similar to Bridgman solidification, where the thermal gradient and cooling rate control the microstructure formation. This paper details the experimental set-up and provides multiple proofs-of-concept that illustrate the versatility of using this laser-based heating system to explore, in situ, many elevated-temperature phenomena in a variety of materials.
doi:10.1107/S0909049512003287
PMCID: PMC3329956  PMID: 22514169
in situ X-ray tomographic microscopy; ultra-fast imaging; diode lasers; metals solidification; volcanic processes
16.  Long Dynamics Simulations of Proteins Using Atomistic Force Fields and a Continuum Representation of Solvent Effects: Calculation of Structural and Dynamic Properties 
Proteins  2005;60(3):464-484.
Long dynamics simulations were carried out on the B1 immunoglobulin-binding domain of streptococcal protein G (ProtG) and bovine pancreatic trypsin inhibitor (BPTI) using atomistic descriptions of the proteins and a continuum representation of solvent effects. To mimic frictional and random collision effects, Langevin dynamics (LD) were used. The main goal of the calculations was to explore the stability of tens-of-nanosecond trajectories as generated by this molecular mechanics approximation and to analyze in detail structural and dynamical properties. Conformational fluctuations, order parameters, cross correlation matrices, residue solvent accessibilities, pKa values of titratable groups, and hydrogen-bonding (HB) patterns were calculated from all of the trajectories and compared with available experimental data. The simulations comprised over 40 ns per trajectory for ProtG and over 30 ns per trajectory for BPTI. For comparison, explicit water molecular dynamics simulations (EW/MD) of 3 ns and 4 ns, respectively, were also carried out. Two continuum simulations were performed on each protein using the CHARMM program, one with the all-atom PAR22 representation of the protein force field (here referred to as PAR22/LD simulations) and the other with the modifications introduced by the recently developed CMAP potential (CMAP/LD simulations). The explicit solvent simulations were performed with PAR22 only. Solvent effects are described by a continuum model based on screened Coulomb potentials (SCP) reported earlier, i.e., the SCP-based implicit solvent model (SCP–ISM). For ProtG, both the PAR22/LD and the CMAP/LD 40-ns trajectories were stable, yielding Cα root mean square deviations (RMSD) of about 1.0 and 0.8 Å respectively along the entire simulation time, compared to 0.8 Å for the EW/MD simulation. For BPTI, only the CMAP/LD trajectory was stable for the entire 30-ns simulation, with a Cα RMSD of ≈ 1.4 Å, while the PAR22/LD trajectory became unstable early in the simulation, reaching a Cα RMSD of about 2.7 Å and remaining at this value until the end of the simulation; the Cα RMSD of the EW/MD simulation was about 1.5 Å. The source of the instabilities of the BPTI trajectories in the PAR22/LD simulations was explored by an analysis of the backbone torsion angles. To further validate the findings from this analysis of BPTI, a 35-ns SCP–ISM simulation of Ubiquitin (Ubq) was carried out. For this protein, the CMAP/LD simulation was stable for the entire simulation time (Cα RMSD of ≈1.0 Å), while the PAR22/LD trajectory showed a trend similar to that in BPTI, reaching a Cα RMSD of ≈1.5 Å at 7 ns. All the calculated properties were found to be in agreement with the corresponding experimental values, although local deviations were also observed. HB patterns were also well reproduced by all the continuum solvent simulations with the exception of solvent-exposed side chain–side chain (sc–sc) HB in ProtG, where several of the HB interactions observed in the crystal structure and in the EW/MD simulation were lost. The overall analysis reported in this work suggests that the combination of an atomistic representation of a protein with a CMAP/CHARMM force field and a continuum representation of solvent effects such as the SCP–ISM provides a good description of structural and dynamic properties obtained from long computer simulations. Although the SCP–ISM simulations (CMAP/LD) reported here were shown to be stable and the properties well reproduced, further refinement is needed to attain a level of accuracy suitable for more challenging biological applications, particularly the study of protein–protein interactions.
doi:10.1002/prot.20470
PMCID: PMC1764639  PMID: 15959866
continuum model; implicit solvent model; screened Coulomb potentials; Langevin dynamics; molecular dynamics simulation; protein G; BPTI; Ubiquitin
17.  Direct observation of microscopic reversibility in single-molecule protein folding 
Journal of molecular biology  2006;366(2):677-686.
Both folded and unfolded conformations should be observed for a protein at its melting temperature, or Tm, where the ΔG between these states is zero. In an all-atom molecular dynamics simulation of chymotrypsin inhibitor 2 (CI2) at its experimental Tm, the protein rapidly loses its low-temperature native structure, it then unfolds before refolding to a stable, native-like conformation. The initial unfolding follows the unfolding pathway described previously for higher temperature simulations: the hydrophobic core is disrupted, the β-sheet pulls apart and the α-helix unravels. The unfolded state reached under these conditions maintains a kernel of structure in the form of a nonnative hydrophobic cluster. Refolding simply reverses this path, the side chain interactions shift, the helix refolds, and the native packing and hydrogen bonds are recovered. The end result of this refolding is not the initial crystal structure; it contains the proper topology and the majority of the native contacts, but the structure is expanded and the contacts are long. We believe this state to be the native one at elevated temperature and the change in volume and contact lengths is consistent with experimental studies of other native proteins at elevated temperature and the chemical denaturant equivalent of Tm.
doi:10.1016/j.jmb.2006.11.043
PMCID: PMC1885941  PMID: 17174331
18.  Conformational changes below the Tm: Molecular dynamics studies of the thermal pretransition of ribonuclease A† 
Biochemistry  2007;47(3):880-892.
Recent work suggests that some native conformations of proteins can vary with temperature. To obtain an atomic-level description of this structural and conformational variation, we have performed all-atom, explicit-solvent molecular dynamics simulations of bovine pancreatic ribonuclease A (RNase A) up to its melting temperature (Tm ≈ 337 K). RNase A has a thermal pretransition near 320 K [Stelea, S.D, Pancoska, P., Benight, A.S., Keiderling, T.A. (2001) Prot. Sci. 10, 970—978]. Our simulations identify a conformational change that coincides with this pretransition. Between 310 and 320 K, there is a small but significant decrease in the number of native contacts, β-sheet hydrogen bonding, and deviation of backbone conformation from the starting structure, and an increase in nonnative contacts. Native contacts are lost in β-sheet regions and in α1, partially due to movement of α1 away from the β-sheet core. At 330 and 340 K, a nonnative helical segment forms at residues 15–20, corresponding to a helix observed in the N-terminal domain-swapped dimer [Liu Y.S., Hart, P.J., Schulnegger, M.P., Eisenberg, D. (1998) Proc. Natl. Acad. Sci. USA, 95, 3437—3432]. The conformations observed at the higher temperatures possess native-like topology and overall conformation, with many native contacts, but they have a disrupted active site. We propose that these conformations may represent the native state at elevated temperature, or the N′ state. These simulations show that subtle, functionally important changes in protein conformation can occur below the Tm.
doi:10.1021/bi701565b
PMCID: PMC2532537  PMID: 18161991
19.  The Effects of Timing of Grazing on Plant and Arthropod Communities in High-Elevation Grasslands 
PLoS ONE  2014;9(10):e110460.
Livestock grazing can be used as a key management tool for maintaining healthy ecosystems. However, the effectiveness of using grazing to modify habitat for species of conservation concern depends on how the grazing regime is implemented. Timing of grazing is one grazing regime component that is less understood than grazing intensity and grazer identity, but is predicted to have important implications for plant and higher trophic level responses. We experimentally assessed how timing of cattle grazing affected plant and arthropod communities in high-elevation grasslands of southwest Montana to better evaluate its use as a tool for multi-trophic level management. We manipulated timing of grazing, with one grazing treatment beginning in mid-June and the other in mid-July, in two experiments conducted in different grassland habitat types (i.e., wet meadow and upland) in 2011 and 2012. In the upland grassland experiment, we found that both early and late grazing treatments reduced forb biomass, whereas graminoid biomass was only reduced with late grazing. Grazing earlier in the growing season versus later did not result in greater recovery of graminoid or forb biomass as expected. In addition, the density of the most ubiquitous grassland arthropod order (Hemiptera) was reduced by both grazing treatments in upland grasslands. A comparison of end-of-season plant responses to grazing in upland versus wet meadow grasslands revealed that grazing reduced graminoid biomass in the wet meadow and forb biomass in the upland, irrespective of timing of grazing. Both grazing treatments also reduced end-of-season total arthropod and Hemiptera densities and Hemiptera biomass in both grassland habitat types. Our results indicate that both early and late season herbivory affect many plant and arthropod characteristics in a similar manner, but grazing earlier may negatively impact species of conservation concern requiring forage earlier in the growing season.
doi:10.1371/journal.pone.0110460
PMCID: PMC4206520  PMID: 25338008
20.  THE MELTING MECHANISM OF DNA TETHERED TO A SURFACE 
The details of melting of DNA immobilized on a chip or nanoparticle determines the sensitivity and operating characteristics of many analytical and synthetic biotechnological devices. Yet, little is known about the differences in how the DNA melting occurs between a homogeneous solution and that on a chip. We used molecular dynamics simulations to explore possible pathways for DNA melting on a chip. Simulation conditions were chosen to ensure that melting occurred in a submicrosecond timescale. The temperature was set to 400 K and the NaCl concentration was set to 0.1 M. We found less symmetry than in the solution case where for oligomeric double-stranded nucleic acids both ends melted with roughly equal probability. On a prepared silica surface we found melting is dominated by fraying from the end away from the surface. Strand separation was hindered by nonspecific surface adsorption at this temperature. At elevated temperatures the melted DNA was attracted to even uncharged organically coated surfaces demonstrating surface fouling. While hybridization is not the simple reverse of melting, this simulation has implications for the kinetics of hybridization.
PMCID: PMC2755589  PMID: 19802357
DNA; melting; and microarray
21.  GroEL dependency affects codon usage—support for a critical role of misfolding in gene evolution 
Integrating genome-scale sequence, expression, structural and protein interaction data from E. coli we establish an interaction between chaperone (GroEL) dependency and optimal codon usage.Highly expressed sporadic substrates of GroEL employ more optimal codons than expected, show enrichment for optimal codons at structurally sensitive sites and greater conservation of codon optimality under conditions of relaxed purifying selection.We suggest that highly expressed genes cannot routinely utilize GroEL for error control so that codon usage has evolved to provide complementary error limitation, whereas obligate GroEL substrates experience relaxed selection on codon usage.Our results support a critical role of misfolding prevention in gene evolution.
Errors during gene expression are relatively commonplace, which has prompted speculations that many features of gene and genome anatomy and organization have evolved to reduce or mitigate such errors. One type of error that can be particularly costly occurs when the polypeptide chain that emerges from the ribosome fails to fold into its native structure. Some aberrantly folded proteins, exposing hydrophobic residues that would normally be buried, may begin to promiscuously interact with other proteins, become toxic to the cell and thus pose a substantial fitness concern (Gregersen et al, 2006).
In trans, molecular chaperones have long been recognized to play crucial roles in misfolding prevention and remedy. In cis, it has recently been suggested that the use of optimal codons limits mistranslation-induced protein misfolding (Drummond and Wilke, 2008). Evidence for the latter is centred on the argument that synonymous codons differ in their propensity to cause mistranslation. Translationally optimal codons, typically represented by more abundant cognate tRNAs (Duret, 2000), are thought less likely to cause ribosomal stalling and/or incorporation of the wrong amino acid.
Here, we suggest that the role, if any, of error limitation in cis can be revealed by studying its interaction with well-established error management systems in trans (chaperones). If codon usage does indeed play a tangible role in misfolding prevention, we would expect selection on codon identity to vary with the degree to which a protein can rely on other error control mechanisms, namely chaperones. We use the E. coli chaperonin GroEL as a model system to explore whether there is any interaction between optimal codon usage and chaperone dependency.
Kerner et al (2005) had previously determined GroEL substrates on a genome-wide scale. Based on enrichment in GroEL complexes the authors assigned ∼250 proteins to three classes reflecting GroEL dependency: class-I proteins, only a small fraction of which (<1%) associates with GroEL and which spontaneously regain some activity; class-II proteins, which only exhibit spontaneous refolding at more permissive temperatures and class-III proteins, which are obligate substrates of GroEL and largely fail to refold even under more benign conditions. Notably, although on average less abundant than class-I/II proteins (‘sporadic clients'), class-III proteins (‘obligate clients') occupy ∼80% of GroEL's capacity in vivo. Consequently, a higher proportion (∼100% versus ∼20% for class-II and ∼1% for class-I) of these proteins is routinely processed by the GroEL system.
We demonstrate that sporadic but not obligate clients of GroEL exhibit enhanced codon adaptation, carefully controlling for possible confounding factors, notably expression level and protein length (Figure 1). We also point out that genes that recently entered the E. coli genome via horizontal gene transfer will distort equilibrium analyses of codon usage in bacteria and should thus be routinely eliminated from analysis.
Building on earlier work by Zhou et al (2009), we further show that sporadic substrates are conspicuously enriched for optimal codons at structurally sensitive sites, consistent with more severe fitness implications of codon choice for these proteins.
Lastly, we reveal that codon optimality in sporadic clients is more highly conserved in S. dysenteriae. S. dysenteriae is an E. coli clone that has diverged relatively recently from the E. coli K12 strain and has adopted an intracellular lifestyle (Balbi et al, 2009). Concomitant with that lifestyle, Shigella has experienced a lower effective population size and therefore reduced efficiency of purifying selection. This has generated conditions where, overall, codon optimality has started to decay. However, when we followed the fate of ancestrally optimal codons at buried sites in the S. dysenteriae and E. coli K12 genomes, we found that a lower fraction of buried sites has lost codon optimality in sporadic substrates (Figure 4), again consistent with greater structural importance of codon choice in these substrates.
Based on the these findings, we suggest the following explanation: As mentioned above, class-III substrates are defined not only by GroEL being critical for proper folding, but also by occupying most of GroEL's capacity (∼80%). With a high proportion of class-III protein passaged through the GroEL system, mistranslation errors in these proteins weigh less severely as GroEL can remedy at least some misfolding that ensues. In contrast, class-I and II genes are more highly expressed and cannot routinely rely on GroEL to rectify folding errors. Yet class-I/II proteins are clearly liable to misfold as testified by their sporadic association with GroEL. We argue that augmenting GroEL's capacity to address the misfolding propensity of these genes would be prohibitively costly to the organism and that, as an alternative strategy, these genes employ optimal codons to reduce the rate of misfolding error.
Our findings (a) reveal a cis–trans interaction between codon usage and chaperones in providing an integrated error management system, (b) provide independent evidence for a role of misfolding in shaping gene evolution and (c) suggest that the burden of deleterious mutations in long-term bottlenecking populations like that of the insect endosymbiont Buchnera not only comprises unfavourable amino-acid (Moran, 1996) but also synonymous substitutions.
It has recently been suggested that the use of optimal codons limits mistranslation-induced protein misfolding, yet evidence for this remains largely circumstantial. In contrast, molecular chaperones have long been recognized to play crucial roles in misfolding prevention and remedy. We propose that putative error limitation in cis can be elucidated by examining the interaction between codon usage and chaperoning processes. Using Escherichia coli as a model system, we find that codon optimality covaries with dependency on the chaperonin GroEL. Sporadic but not obligate substrates of GroEL exhibit higher average codon adaptation and are conspicuously enriched for optimal codons at structurally sensitive sites. Further, codon optimality of sporadic clients is more conserved in the E. coli clone Shigella dysenteriae. We suggest that highly expressed genes cannot routinely use GroEL for error control so that codon usage has evolved to provide complementary error limitation. These findings provide independent evidence for a role of misfolding in shaping gene evolution and highlight the need to co-characterize adaptations in cis and trans to unravel the workings of integrated molecular systems.
doi:10.1038/msb.2009.94
PMCID: PMC2824523  PMID: 20087338
codon bias; GroEL; misfolding
22.  Optimal regulatory strategies for metabolic pathways in Escherichia coli depending on protein costs 
Pathways in Escherichia coli show large differences in the extent to which enzymes from the same pathway are expressed in a coordinated manner.Using dynamic optimization, we show that regulation of the initial and terminal reactions of a pathway is the minimum requirement for a precise control of flux.We find that in E. coli a regulation of initial and terminal reactions is predominantly used to control pathways with low costs of enzymes while a regulation of all enzymes occurs if protein costs are high.A trade-off between minimization of protein investment and minimization of response time can explain the preference for transcriptional regulation at key positions (leading to high protein costs, but low response time) or coordinated transcriptional regulation of all enzymes (leading to low protein costs, but high response time).
The increasing availability and decreasing prices of experimental techniques have led to an explosion in the number of available experimental data sets (Ishii et al, 2007; Lu et al, 2007; Bennett et al, 2009; Lewis et al, 2010). However, approaches to integrate these diverse data sets into a coherent model of cellular mechanisms have lagged behind (Palsson and Zengler, 2010). In this study, we want to contribute to this effort through the analysis of a large number of data sets in order to identify global principles in the regulation of metabolism in Escherichia coli. While previous studies have shed light onto the link between the transcriptional regulation of metabolism and its structure (Ihmels et al, 2004; Reed and Palsson, 2004; Schwartz et al, 2007; Seshasayee et al, 2009), the extent to which transcriptional regulation controls metabolism has remained elusive.
To address this problem, we investigated the coexpression of enzymes within the same pathway in all biochemically annotated subsystems of E. coli metabolism. As a reference for metabolic pathways, we used elementary flux patterns, a recently introduced concept for pathway analysis in genome-scale metabolic networks (Kaleta et al, 2009). Through this analysis, we found that while pathways in many subsystems of metabolism show a high degree of coexpression, pathways in the subsystems cofactor and prosthetic group biosynthesis, glycerophospholipid metabolism, murein recycling, nucleotide salvage pathway and pentose phosphate pathway show only weak coexpression. We refer to these subsystems with a low coordination of transcriptional regulation as transcriptionally sparsely regulated subsystems.
In order to understand these different patterns of regulation, we constructed a simplified model of a linear metabolic pathway that converts a substrate s via four intermediates into a product p. We then used dynamic optimization to identify a regulatory program (i.e. a time course for the enzyme concentrations), which allows the cell to maintain the concentration of the product p in a changing environment while obeying a set of physiological constraints. As an objective function we used the minimization of the level of transcriptional regulation, specified through absolute deviations of enzyme concentrations from their initial values, and the minimization of protein costs. Protein costs are measured as the sum of the initial enzyme concentrations.
The optimization results revealed that for a full control of the flux through a pathway, transcriptional regulation of initial and terminal reactions of the pathway is sufficient (sparse transcriptional regulation). Regulation of the first reaction is required to control the flux into the pathway, and hence, the intermediate concentrations. In contrast, regulation at the terminal position is required to tightly control the rate of synthesis of the product. By performing the same optimization for randomly chosen kinetic parameters, we found that this pattern is also optimal in most cases with differences in the catalytic properties of enzymes. Moreover, we found that with increasing enzyme costs (i.e. increasing enzyme concentrations), there is a shift from sparse transcriptional regulation to coordinated transcriptional regulation of all enzymes within a pathway (pervasive transcriptional regulation).
To verify these predictions, we analyzed the position-specific frequency of regulatory events in the pathways of the transcriptionally sparsely regulated subsystems. We could confirm that there is a significant increase in the frequency of transcriptional regulation at the end and a less pronounced increase at the beginning of pathways. Performing the same analysis for post-translational regulation, we found that there is a statistically significant increase at the beginning of pathways. Thus, the control at the beginning of pathways is achieved through a combination of transcriptional and post-translational regulation. In other subsystems that were not identified as transcriptionally sparsely regulated, we did not find this pattern of transcriptional regulation while the same pattern of post-translational regulation could be observed. By analyzing protein abundance data, we confirmed that particularly pathways within subsystems, for which enzyme costs are low, are transcriptionally sparsely regulated.
Having confirmed the predictions made by the optimization, we found that there appears to be a mechanism favoring sparse transcriptional regulation in pathways with low-cost enzymes. We suggest an evolutionary trade-off between the cellular objectives of protein cost minimization and response time minimization as a cause of this mechanism. The optimal strategy to reduce average protein costs is to transcriptionally control enzymes within a pathway. However, responses on a transcriptional level are usually very slow. In contrast, short response times can be achieved through a constitutive expression of enzymes with a focused regulation of key steps within a pathway. The interplay between the two cellular objectives leads to the observation that particularly pathways with highly abundant and thus costly enzymes are transcriptionally pervasively regulated (Figure 7A). In contrast, pathways with low abundance enzymes are transcriptionally sparsely regulated (Figure 7B). In agreement with these results, we found that pathways such as the pentose phosphate pathway, for which rapid response times are required, are sparsely regulated even if they contain costly enzymes (Figure 7C). Finally, if the fitness advantage achieved through following either of the cellular objectives is low, sparse transcriptional regulation is the minimum requirement to control flux through a pathway (Figure 7D).
In summary, our results demonstrate that, in contrast to the classical picture, regulation of key positions of metabolic pathways is sufficient for full control of flux and is implemented in vivo. This pattern of sparse regulation is particularly useful if a higher fitness advantage can be achieved through rapid response times compared to the fitness advantage achieved through the reduced protein cost of pervasive transcriptional regulation.
Analysis of optimal strategies for the control of metabolic pathways in Escherichia coli reveals that the extent of transcriptional regulation reflects an evolutionary trade-off between the minimization of response time and protein costs.
While previous studies have shed light on the link between the structure of metabolism and its transcriptional regulation, the extent to which transcriptional regulation controls metabolism has not yet been fully explored. In this work, we address this problem by integrating a large number of experimental data sets with a model of the metabolism of Escherichia coli. Using a combination of computational tools including the concept of elementary flux patterns, methods from network inference and dynamic optimization, we find that transcriptional regulation of pathways reflects the protein investment into these pathways. While pathways that are associated to a high protein cost are controlled by fine-tuned transcriptional programs, pathways that only require a small protein cost are transcriptionally controlled in a few key reactions. As a reason for the occurrence of these different regulatory strategies, we identify an evolutionary trade-off between the conflicting requirements to reduce protein investment and the requirement to be able to respond rapidly to changes in environmental conditions.
doi:10.1038/msb.2011.46
PMCID: PMC3159982  PMID: 21772263
cost-optimal regulatory strategies; evolutionary optimization; genome-scale metabolic networks; proteomics; transcriptomics
23.  Metabolic network reconstruction of Chlamydomonas offers insight into light-driven algal metabolism 
A comprehensive genome-scale metabolic network of Chlamydomonas reinhardtii, including a detailed account of light-driven metabolism, is reconstructed and validated. The model provides a new resource for research of C. reinhardtii metabolism and in algal biotechnology.
The genome-scale metabolic network of Chlamydomonas reinhardtii (iRC1080) was reconstructed, accounting for >32% of the estimated metabolic genes encoded in the genome, and including extensive details of lipid metabolic pathways.This is the first metabolic network to explicitly account for stoichiometry and wavelengths of metabolic photon usage, providing a new resource for research of C. reinhardtii metabolism and developments in algal biotechnology.Metabolic functional annotation and the largest transcript verification of a metabolic network to date was performed, at least partially verifying >90% of the transcripts accounted for in iRC1080. Analysis of the network supports hypotheses concerning the evolution of latent lipid pathways in C. reinhardtii, including very long-chain polyunsaturated fatty acid and ceramide synthesis pathways.A novel approach for modeling light-driven metabolism was developed that accounts for both light source intensity and spectral quality of emitted light. The constructs resulting from this approach, termed prism reactions, were shown to significantly improve the accuracy of model predictions, and their use was demonstrated for evaluation of light source efficiency and design.
Algae have garnered significant interest in recent years, especially for their potential application in biofuel production. The hallmark, model eukaryotic microalgae Chlamydomonas reinhardtii has been widely used to study photosynthesis, cell motility and phototaxis, cell wall biogenesis, and other fundamental cellular processes (Harris, 2001). Characterizing algal metabolism is key to engineering production strains and understanding photobiological phenomena. Based on extensive literature on C. reinhardtii metabolism, its genome sequence (Merchant et al, 2007), and gene functional annotation, we have reconstructed and experimentally validated the genome-scale metabolic network for this alga, iRC1080, the first network to account for detailed photon absorption permitting growth simulations under different light sources. iRC1080 accounts for 1080 genes, associated with 2190 reactions and 1068 unique metabolites and encompasses 83 subsystems distributed across 10 cellular compartments (Figure 1A). Its >32% coverage of estimated metabolic genes is a tremendous expansion over previous algal reconstructions (Boyle and Morgan, 2009; Manichaikul et al, 2009). The lipid metabolic pathways of iRC1080 are considerably expanded relative to existing networks, and chemical properties of all metabolites in these pathways are accounted for explicitly, providing sufficient detail to completely specify all individual molecular species: backbone molecule and stereochemical numbering of acyl-chain positions; acyl-chain length; and number, position, and cis–trans stereoisomerism of carbon–carbon double bonds. Such detail in lipid metabolism will be critical for model-driven metabolic engineering efforts.
We experimentally verified transcripts accounted for in the network under permissive growth conditions, detecting >90% of tested transcript models (Figure 1B) and providing validating evidence for the contents of iRC1080. We also analyzed the extent of transcript verification by specific metabolic subsystems. Some subsystems stood out as more poorly verified, including chloroplast and mitochondrial transport systems and sphingolipid metabolism, all of which exhibited <80% of transcripts detected, reflecting incomplete characterization of compartmental transporters and supporting a hypothesis of latent pathway evolution for ceramide synthesis in C. reinhardtii. Additional lines of evidence from the reconstruction effort similarly support this hypothesis including lack of ceramide synthetase and other annotation gaps downstream in sphingolipid metabolism. A similar hypothesis of latent pathway evolution was established for very long-chain fatty acids (VLCFAs) and their polyunsaturated analogs (VLCPUFAs) (Figure 1C), owing to the absence of this class of lipids in previous experimental measurements, lack of a candidate VLCFA elongase in the functional annotation, and additional downstream annotation gaps in arachidonic acid metabolism.
The network provides a detailed account of metabolic photon absorption by light-driven reactions, including photosystems I and II, light-dependent protochlorophyllide oxidoreductase, provitamin D3 photoconversion to vitamin D3, and rhodopsin photoisomerase; this network accounting permits the precise modeling of light-dependent metabolism. iRC1080 accounts for effective light spectral ranges through analysis of biochemical activity spectra (Figure 3A), either reaction activity or absorbance at varying light wavelengths. Defining effective spectral ranges associated with each photon-utilizing reaction enabled our network to model growth under different light sources via stoichiometric representation of the spectral composition of emitted light, termed prism reactions. Coefficients for different photon wavelengths in a prism reaction correspond to the ratios of photon flux in the defined effective spectral ranges to the total emitted photon flux from a given light source (Figure 3B). This approach distinguishes the amount of emitted photons that drive different metabolic reactions. We created prism reactions for most light sources that have been used in published studies for algal and plant growth including solar light, various light bulbs, and LEDs. We also included regulatory effects, resulting from lighting conditions insofar as published studies enabled. Light and dark conditions have been shown to affect metabolic enzyme activity in C. reinhardtii on multiple levels: transcriptional regulation, chloroplast RNA degradation, translational regulation, and thioredoxin-mediated enzyme regulation. Through application of our light model and prism reactions, we were able to closely recapitulate experimental growth measurements under solar, incandescent, and red LED lights. Through unbiased sampling, we were able to establish the tremendous statistical significance of the accuracy of growth predictions achievable through implementation of prism reactions. Finally, application of the photosynthetic model was demonstrated prospectively to evaluate light utilization efficiency under different light sources. The results suggest that, of the existing light sources, red LEDs provide the greatest efficiency, about three times as efficient as sunlight. Extending this analysis, the model was applied to design a maximally efficient LED spectrum for algal growth. The result was a 677-nm peak LED spectrum with a total incident photon flux of 360 μE/m2/s, suggesting that for the simple objective of maximizing growth efficiency, LED technology has already reached an effective theoretical optimum.
In summary, the C. reinhardtii metabolic network iRC1080 that we have reconstructed offers insight into the basic biology of this species and may be employed prospectively for genetic engineering design and light source design relevant to algal biotechnology. iRC1080 was used to analyze lipid metabolism and generate novel hypotheses about the evolution of latent pathways. The predictive capacity of metabolic models developed from iRC1080 was demonstrated in simulating mutant phenotypes and in evaluation of light source efficiency. Our network provides a broad knowledgebase of the biochemistry and genomics underlying global metabolism of a photoautotroph, and our modeling approach for light-driven metabolism exemplifies how integration of largely unvisited data types, such as physicochemical environmental parameters, can expand the diversity of applications of metabolic networks.
Metabolic network reconstruction encompasses existing knowledge about an organism's metabolism and genome annotation, providing a platform for omics data analysis and phenotype prediction. The model alga Chlamydomonas reinhardtii is employed to study diverse biological processes from photosynthesis to phototaxis. Recent heightened interest in this species results from an international movement to develop algal biofuels. Integrating biological and optical data, we reconstructed a genome-scale metabolic network for this alga and devised a novel light-modeling approach that enables quantitative growth prediction for a given light source, resolving wavelength and photon flux. We experimentally verified transcripts accounted for in the network and physiologically validated model function through simulation and generation of new experimental growth data, providing high confidence in network contents and predictive applications. The network offers insight into algal metabolism and potential for genetic engineering and efficient light source design, a pioneering resource for studying light-driven metabolism and quantitative systems biology.
doi:10.1038/msb.2011.52
PMCID: PMC3202792  PMID: 21811229
Chlamydomonas reinhardtii; lipid metabolism; metabolic engineering; photobioreactor
24.  Commentary: Fatalismo Reconsidered: A Cautionary Note for Health-Related Research and Practice with Latino Populations 
Ethnicity & disease  2007;17(1):153-158.
Over recent years, interest has grown in studying whether fatalismo (fatalism) deters Latinos from engaging in various health promotion and disease detection behaviors, especially with regard to cancer screening. This commentary presents problematic issues posed by the concept of fatalism, focusing on research on Latinos and cancer screening. We discuss key findings in the literature, analyze methodologic and conceptual problems, and highlight structural contexts and other barriers to health care as critical to the fatalism concept. Although the need to better understand the role of fatalistic beliefs on health is great, we discuss the public health implications of reaching premature conclusions concerning the effect of fatalism on Latinos’ cancer screening behaviors.
PMCID: PMC3617551  PMID: 17274225
Cancer Screening; Fatalism; Latino
25.  Charge transfer through single molecule contacts: How reliable are rate descriptions? 
Summary
Background: The trend for the fabrication of electrical circuits with nanoscale dimensions has led to impressive progress in the field of molecular electronics in the last decade. However, a theoretical description of molecular contacts as the building blocks of future devices is challenging, as it has to combine the properties of Fermi liquids in the leads with charge and phonon degrees of freedom on the molecule. Outside of ab initio schemes for specific set-ups, generic models reveal the characteristics of transport processes. Particularly appealing are descriptions based on transfer rates successfully used in other contexts such as mesoscopic physics and intramolecular electron transfer. However, a detailed analysis of this scheme in comparison with numerically exact solutions is still elusive.
Results: We show that a formulation in terms of transfer rates provides a quantitatively accurate description even in domains of parameter space where strictly it is expected to fail, e.g., at lower temperatures. Typically, intramolecular phonons are distributed according to a voltage driven steady state that can only roughly be captured by a thermal distribution with an effective elevated temperature (heating). An extension of a master equation for the charge–phonon complex, to effectively include the impact of off-diagonal elements of the reduced density matrix, provides very accurate solutions even for stronger electron–phonon coupling.
Conclusion: Rate descriptions and master equations offer a versatile model to describe and understand charge transfer processes through molecular junctions. Such methods are computationally orders of magnitude less expensive than elaborate numerical simulations that, however, provide exact solutions as benchmarks. Adjustable parameters obtained, e.g., from ab initio calculations allow for the treatment of various realizations. Even though not as rigorously formulated as, e.g., nonequilibrium Green’s function methods, they are conceptually simpler, more flexible for extensions, and from a practical point of view provide accurate results as long as strong quantum correlations do not modify the properties of the relevant subunits substantially.
doi:10.3762/bjnano.2.47
PMCID: PMC3190613  PMID: 22003449
inelastic charge transfer; molecular contacts; nonequilibrium distributions; numerical simulations; rate equations

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