Information, Coding, and Biological Function: The Dynamics of Life.

In the mid-20th century, two new scientific disciplines emerged forcefully: molecular biology and information-communication theory. At the beginning, cross-fertilization was so deep that the term genetic code was universally accepted for describing the meaning of triplets of mRNA (codons) as amino acids. However, today, such synergy has not taken advantage of the vertiginous advances in the two disciplines and presents more challenges than answers. These challenges not only are of great theoretical relevance but also represent unavoidable milestones for next-generation biology: from personalized genetic therapy and diagnosis to Artificial Life to the production of biologically active proteins. Moreover, the matter is intimately connected to a paradigm shift needed in theoretical biology, pioneered a long time ago, that requires combined contributions from disciplines well beyond the biological realm. The use of information as a conceptual metaphor needs to be turned into quantitative and predictive models that can be tested empirically and integrated in a unified view. Successfully achieving these tasks requires a wide multidisciplinary approach, including Artificial Life researchers, to address such an endeavour.

Backbone 1H, 15N and 13C resonance assignments of the 27kDa fluorescent protein mCherry.

mCherry is one of the most successfully applied monomeric red fluorescent proteins (RFPs) for in vivo and in vitro imaging. However, questions pertaining to the photostability of the RFPs remain and rational further engineering of their photostability requires information about the fluorescence quenching mechanism in solution. To this end, NMR spectroscopic investigations might be helpful, and we present the near-complete backbone NMR chemical shift assignment to aid in this pursuit.

4-Oxo-2-nonenal-Induced α-Synuclein Oligomers Interact with Membranes in the Cell, Leading to Mitochondrial Fragmentation.

Oxidative stress and formation of cytotoxic oligomers by the natively unfolded protein α-synuclein (α-syn) are both connected to the development of Parkinson's disease. This effect has been linked to lipid peroxidation and membrane disruption, but the specific mechanisms behind these phenomena remain unclear. To address this, we have prepared α-syn oligomers (αSOs) in vitro in the presence of the lipid peroxidation product 4-oxo-2-nonenal and investigated their interaction with live cells using in-cell NMR as well as stimulated emission depletion (STED) super-resolution and confocal microscopy. We find that the αSOs interact strongly with organellar components, leading to strong immobilization of the protein's otherwise flexible C-terminus. STED microscopy reveals that the oligomers localize to small circular structures inside the cell, while confocal microscopy shows mitochondrial fragmentation and association with both late endosome and retromer complex before the SOs interact with mitochondria. Our study provides direct evidence for close contact between cytotoxic α-syn aggregates and membraneous compartments in the cell.

Practical considerations for rapid and quantitative NMR-based metabolomics.

NMR is a key technology for metabolomics because of its robustness and reproducibility. Herein we discuss practical considerations that extend the utility of NMR spectroscopy. First, the long T1 spin relaxation times of small molecules limits high-throughput data acquisition because most experimental time is lost while waiting for signal recovery. In principle, the addition of a small amount of commercially-available paramagnetic gadolinium chelate allows cost-effective and efficient high-throughput mixture analysis with correct concentration determination. However, idle time caused by slow temperature regulation during sample exchanges, poses a next constraint. We show how, with proper care, NMR sample scanning times can be reduced additionally by a factor of two. Lastly, we describe how equidistant bucketing is a simple and fast procedure for metabolomic fingerprinting. The combination of these advancements help to make NMR metabolomics more versatile than it is today.

Solvent paramagnetic relaxation enhancement as a versatile method for studying structure and dynamics of biomolecular systems.

Solvent paramagnetic relaxation enhancement (sPRE) is a versatile nuclear magnetic resonance (NMR)-based method that allows characterization of the structure and dynamics of biomolecular systems through providing quantitative experimental information on solvent accessibility of NMR-active nuclei. Addition of soluble paramagnetic probes to the solution of a biomolecule leads to paramagnetic relaxation enhancement in a concentration-dependent manner. Here we review recent progress in the sPRE-based characterization of structural and dynamic properties of biomolecules and their complexes, and aim to deliver a comprehensive illustration of a growing number of applications of the method to various biological systems. We discuss the physical principles of sPRE measurements and provide an overview of available co-solute paramagnetic probes. We then explore how sPRE, in combination with complementary biophysical techniques, can further advance biomolecular structure determination, identification of interaction surfaces within protein complexes, and probing of conformational changes and low-population transient states, as well as deliver insights into weak, nonspecific, and transient interactions between proteins and co-solutes. In addition, we present examples of how the incorporation of solvent paramagnetic probes can improve the sensitivity of NMR experiments and discuss the prospects of applying sPRE to NMR metabolomics, drug discovery, and the study of intrinsically disordered proteins.

Probing Methyl Group Dynamics in Proteins by NMR Cross-Correlated Dipolar Relaxation and Molecular Dynamics Simulations.

Nuclear magnetic resonance (NMR) spin relaxation is the most informative approach to experimentally probe the internal dynamics of proteins on the picosecond to nanosecond time scale. At the same time, molecular dynamics (MD) simulations of biological macromolecules are steadily improving through better physical models, enhanced sampling methods, and increased computational power, and they provide exquisite information about flexibility and its role in protein stability and molecular interactions. Many examples have shown that MD is now adept in probing protein backbone motion, but improvements are still required toward a quantitative description of the dynamics of side chains, for example, probed by the dynamics of methyl groups. Thus far, the comparison of computation with experiment for side chain dynamics has primarily focused on the relaxation of 13C and 2H nuclei induced by autocorrelated variation of spin interactions. However, the cross-correlation of 13C-1H dipolar interactions in methyl groups offers an attractive alternative. Here, we establish a computational framework to extract cross-correlation relaxation parameters of methyl groups in proteins from all-atom MD simulations. To demonstrate the utility of the approach, cross-correlation relaxation rates of ubiquitin are computed from MD simulations performed with the AMBER99SB*-ILDN and CHARMM36 force fields. Simulation results were found to agree well with those obtained by experiment. Moreover, the data obtained with the two force fields are highly consistent.

A Lactobacilli diet that confers MRSA resistance causes amino acid depletion and increased antioxidant levels in the C. elegans host.

Probiotic bacteria are increasingly popular as dietary supplements and have the potential as alternatives to traditional antibiotics. We have recently shown that pretreatment with Lactobacillus spp. Lb21 increases the life span of C. elegans and results in resistance toward pathogenic methicillin-resistant Staphylococcus aureus (MRSA). The Lb21-mediated MRSA resistance is dependent on the DBL-1 ligand of the TGF-ß signaling pathway. However, the underlying changes at the metabolite level are not understood which limits the application of probiotic bacteria as timely alternatives to traditional antibiotics. In this study, we have performed untargeted nuclear magnetic resonance-based metabolic profiling. We report the metabolomes of Lactobacillus spp. Lb21 and control E. coli OP50 bacteria as well as the nematode-host metabolomes after feeding with these diets. We identify 48 metabolites in the bacteria samples and 51 metabolites in the nematode samples and 63 across all samples. Compared to the control diet, the Lactobacilli pretreatment significantly alters the metabolic profile of the worms. Through sparse Partial Least Squares discriminant analyses, we identify the 20 most important metabolites distinguishing probiotics from the regular OP50 food and worms fed the two different bacterial diets, respectively. Among the changed metabolites, we find lower levels of essential amino acids as well as increased levels of the antioxidants, ascorbate, and glutathione. Since the probiotic diet offers significant protection against MRSA, these metabolites could provide novel ways of combatting MRSA infections.

Solution Structure of the Cutibacterium acnes-Specific Protein RoxP and Insights Into Its Antioxidant Activity.

Cutibacterium acnes is a predominant bacterium on human skin and is generally regarded as commensal. Recently, the abundantly secreted protein produced by C. acnes, RoxP, was shown to alleviate radical-induced cell damage, presumably via antioxidant activity, which could potentially be harnessed to fortify skin barrier function. The aim of this study was to determine the structure of RoxP and elucidate the mechanisms behind its antioxidative effect. Here, we present the solution structure of RoxP revealing a compact immunoglobulin-like domain containing a long flexible loop which, in concert with the core domain, forms a positively charged groove that could function as a binding site for cofactors or substrates. Although RoxP shares structural features with cell-adhesion proteins, we show that it does not appear to be responsible for adhesion of C. acnes bacteria to human keratinocytes. We identify two tyrosine-containing stretches located in the flexible loop of RoxP, which appear to be responsible for the antioxidant activity of RoxP.

How Much Entropy Is Contained in NMR Relaxation Parameters?

Solution-state NMR relaxation experiments are the cornerstone to study internal protein dynamics at an atomic resolution on time scales that are faster than the overall rotational tumbling time τR. Since the motions described by NMR relaxation parameters are connected to thermodynamic quantities like conformational entropies, the question arises how much of the total entropy is contained within this tumbling time. Using all-atom molecular dynamics simulations of the T4 lysozyme, we found that entropy buildup is rather fast for the backbone, such that the majority of the entropy is indeed contained in the short-time dynamics. In contrast, the contribution of the slow dynamics of side chains on time scales beyond τR on the side-chain conformational entropy is significant and should be taken into account for the extraction of accurate thermodynamic properties.

Lipid Peroxidation Products HNE and ONE Promote and Stabilize Alpha-Synuclein Oligomers by Chemical Modifications.

The aggregation of α-synuclein (αSN) and increased oxidative stress leading to lipid peroxidation are pathological characteristics of Parkinson's disease (PD). Here, we report that aggregation of αSN in the presence of lipid peroxidation products 4-hydroxy-2-nonenal (HNE) and 4-oxo-2-nonenal (ONE) increases the stability and the yield of αSN oligomers (αSO). Further, we show that ONE is more efficient than HNE at inducing αSO. In addition, we demonstrate that the two αSO differ in both size and shape. ONE-αSO are smaller in size than HNE-αSO, except when they are formed at a high molar excess of aldehyde. In both monomeric and oligomeric αSN, His50 is the main target of HNE modification, and HNE-induced oligomerization is severely retarded in the mutant His50Ala αSN. In contrast, ONE-induced aggregation of His50Ala αSN occurs readily, demonstrating the different pathways for inducing αSN aggregation by HNE and ONE. Our results show different morphologies of the HNE-treated and ONE-treated αSO and different roles of His50 in their modification of αSN, but we also observe structural similarities between these αSO and the non-treated αSO, e.g., flexible C-terminus, a folded core composed of the N-terminal and NAC region. Furthermore, HNE-αSO show a similar deuterium uptake as a previously characterized oligomer formed by non-treated αSO, suggesting that the backbone conformational dynamics of their folded cores resemble one another.

The contribution of electrostatics to hydrogen exchange in the unfolded protein state.

Although electrostatics have long been recognized to play an important role in hydrogen exchange (HX) with solvent, the quantitative assessment of its magnitude in the unfolded state has hitherto been lacking. This limits the utility of HX as a quantitative method to study protein stability, folding, and dynamics. Using the intrinsically disordered human protein α-synuclein as a proxy for the unfolded state, we show that a hybrid mean-field approach can effectively compute the electrostatic potential at all backbone amide positions along the chain. From the electrochemical potential, a fourfold reduction in hydroxide concentration near the protein backbone is predicted for the C-terminal domain, a prognosis that is in direct agreement with experimentally derived protection factors from NMR spectroscopy. Thus, impeded HX for the C-terminal region of α-synuclein is not the result of intramolecular hydrogen bonding and/or structure formation.

CheSPI: chemical shift secondary structure population inference.

NMR chemical shifts (CSs) are delicate reporters of local protein structure, and recent advances in random coil CS (RCCS) prediction and interpretation now offer the compelling prospect of inferring small populations of structure from small deviations from RCCSs. Here, we present CheSPI, a simple and efficient method that provides unbiased and sensitive aggregate measures of local structure and disorder. It is demonstrated that CheSPI can predict even very small amounts of residual structure and robustly delineate subtle differences into four structural classes for intrinsically disordered proteins. For structured regions and proteins, CheSPI provides predictions for up to eight structural classes, which coincide with the well-known DSSP classification. The program is freely available, and can either be invoked from URL www.protein-nmr.org as a web implementation, or run locally from command line as a python program. CheSPI generates comprehensive numeric and graphical output for intuitive annotation and visualization of protein structures. A number of examples are provided.

How epigallocatechin gallate binds and assembles oligomeric forms of human alpha-synuclein.

The intrinsically disordered human protein α-synuclein (αSN) can self-associate into oligomers and amyloid fibrils. Several lines of evidence suggest that oligomeric αSN is cytotoxic, making it important to devise strategies to either prevent oligomer formation and/or inhibit the ensuing toxicity. (-)-epigallocatechin gallate (EGCG) has emerged as a molecular modulator of αSN self-assembly, as it reduces the flexibility of the C-terminal region of αSN in the oligomer and inhibits the oligomer's ability to perturb phospholipid membranes and induce cell death. However, a detailed structural and kinetic characterization of this interaction is still lacking. Here, we use liquid-state NMR spectroscopy to investigate how EGCG interacts with monomeric and oligomeric forms of αSN. We find that EGCG can bind to all parts of monomeric αSN but exhibits highest affinity for the N-terminal region. Monomeric αSN binds ∼54 molecules of EGCG in total during oligomerization. Furthermore, kinetic data suggest that EGCG dimerization is coupled with the αSN association reaction. In contrast, preformed oligomers only bind ∼7 EGCG molecules per protomer, in agreement with the more compact nature of the oligomer compared with the natively unfolded monomer. In previously conducted cell assays, as little as 0.36 EGCG per αSN reduce oligomer toxicity by 50%. Our study thus demonstrates that αSN cytotoxicity can be inhibited by small molecules at concentrations at least an order of magnitude below full binding capacity. We speculate this is due to cooperative binding of protein-stabilized EGCG dimers, which in turn implies synergy between protein association and EGCG dimerization.

Genetic Variance of Metabolomic Features and Their Relationship With Malting Quality Traits in Spring Barley.

Barley is the most common source for malt to be used in brewing beer and other alcoholic beverages. This involves converting the starch of barley into fermentable sugars a process that involves malting, that is germinating of the grains, and mashing, which is an enzymatic process. Numerous metabolic processes are involved in germination, where distinct and time-dependent alterations at the metabolite levels happen. In this study, 2,628 plots of 565 spring malting barley lines from Nordic Seed A/S were investigated. Phenotypic records were available for six malting quality (MQ) traits: filtering speed (FS), wort clearness (WCL), extract yield (EY), wort color (WCO), beta glucan (BG), and wort viscosity (WV). Each line had a set of dense genomic markers. In addition, 24,018 metabolomic features (MFs) were obtained for each sample from nuclear magnetic resonance (NMR) spectra for wort samples produced from each experimental plot. The genetic variation in the MFs was investigated using a univariate model, and the relationship between MFs and the MQ traits was studied using a bivariate model. Results showed that a total of 8,604 MFs had heritability estimates significantly larger than 0 and for all MQ traits, there were genetic correlations with up to 86.77% and phenotypic correlations with up to 90.07% of the significant heritable MFs. In conclusion, around one third of all MFs were significantly heritable, among which a considerable proportion had significant additive genetic and/or phenotypic correlations with the MQ traits (WCO, WV, and BG) in spring barley. The results from this study indicate that many of the MFs are heritable and MFs have great potential to be used in breeding barley for high MQ.

ODiNPred: comprehensive prediction of protein order and disorder.

Structural disorder is widespread in eukaryotic proteins and is vital for their function in diverse biological processes. It is therefore highly desirable to be able to predict the degree of order and disorder from amino acid sequence. It is, however, notoriously difficult to predict the degree of local flexibility within structured domains and the presence and nuances of localized rigidity within intrinsically disordered regions. To identify such instances, we used the CheZOD database, which encompasses accurate, balanced, and continuous-valued quantification of protein (dis)order at amino acid resolution based on NMR chemical shifts. To computationally forecast the spectrum of protein disorder in the most comprehensive manner possible, we constructed the sequence-based protein order/disorder predictor ODiNPred, trained on an expanded version of CheZOD. ODiNPred applies a deep neural network comprising 157 unique sequence features to 1325 protein sequences together with the experimental NMR chemical shift data. Cross-validation for 117 protein sequences shows that ODiNPred better predicts the continuous variation in order along the protein sequence, suggesting that contemporary predictors are limited by the quality of training data. The inclusion of evolutionary features reduces the performance gap between ODiNPred and its peers, but analysis shows that it retains greater accuracy for the more challenging prediction of intermediate disorder.

Sensitive and simplified: a combinatorial acquisition of five distinct 2D constant-time 13C-1H NMR protein correlation spectra.

A procedure is presented for the substantial simplification of 2D constant-time 13C-1H heteronuclear single-quantum correlation (HSQC) spectra of 13C-enriched proteins. In this approach, a single pulse sequence simultaneously records eight sub-spectra wherein the phases of the NMR signals depend on spin topology. Signals from different chemical groups are then stratified into different sub-spectra through linear combination based on Hadamard encoding of 13CHn multiplicity (n = 1, 2, and 3) and the chemical nature of neighboring 13C nuclei (aliphatic, carbonyl/carboxyl, aromatic). This results in five sets of 2D NMR spectra containing mutually exclusive signals from: (i) 13Cß-1Hß correlations of asparagine and aspartic acid, 13Cγ-1Hγ correlations of glutamine and glutamic acid, and 13Cα-1Hα correlations of glycine, (ii) 13Cα-1Hα correlations of all residues but glycine, and (iii) 13Cß-1Hß correlations of phenylalanine, tyrosine, histidine, and tryptophan, and the remaining (iv) aliphatic 13CH2 and (v) aliphatic 13CH/13CH3 resonances. As HSQC is a common element of many NMR experiments, the spectral simplification proposed in this article can be straightforwardly implemented in experiments for resonance assignment and structure determination and should be of widespread utility.

Quantitative Protein Disorder Assessment Using NMR Chemical Shifts.

Disorder is vital for the biological function of many proteins. The huge diversity found in disorder composition and amplitude reflects the complexity and pluripotency of intrinsically disordered proteins (IDPs). The first step toward a better understanding of IDPs is a quantitative and position-specific experimental characterization, and nuclear magnetic resonance (NMR) spectroscopy has emerged as the method of first choice. Here, we describe how to quantitatively assess the local balance between order and disorder in proteins by utilizing the Chemical shift Z-score for assessing Order/Disorder (CheZOD Z-score). This order/disorder metric is computed from the difference between experimentally determined NMR chemical shifts and computed random coil reference values. We explain in detail how CheZOD Z-scores are calculated fast and easily, either by using a python executable or by data submission to a server.

Paris-DÉCOR: A Protocol for the Determination of Fast Protein Backbone Amide Hydrogen Exchange Rates.

Determining hydrogen exchange kinetics in proteins can shed light on their structure and dynamics. Nuclear magnetic resonance (NMR) spectroscopy is an important analytical technique to determine exchange rates. In this chapter, we describe a new method (Paris-DÉCOR) to determine fast protein amide backbone hydrogen exchange rates in the range 10 to 104 s-1. Measuring fast exchange rates is particularly important for the study of intrinsically disordered proteins, where there is very little protection from exchange to the solvent by the formation of persistent structure. We provide a protocol to set up the experiment as well as MATLAB scripts for numerical simulation that is needed to determine the exchange rates.

Predicting NMR relaxation of proteins from molecular dynamics simulations with accurate methyl rotation barriers.

The internal dynamics of proteins occurring on time scales from picoseconds to nanoseconds can be sensitively probed by nuclear magnetic resonance (NMR) spin relaxation experiments, as well as by molecular dynamics (MD) simulations. This complementarity offers unique opportunities, provided that the two methods are compared at a suitable level. Recently, several groups have used MD simulations to compute the spectral density of backbone and side chain molecular motions and to predict NMR relaxation rates from these. Unfortunately, in the case of methyl groups in protein side chains, inaccurate energy barriers to methyl rotation were responsible for a systematic discrepancy in the computed relaxation rates, as demonstrated for the AMBER ff99SB*-ILDN force field (and related parameter sets), impairing quantitative agreement between simulations and experiments. However, correspondence could be regained by emending the MD force field with accurate coupled cluster quantum chemical calculations. Spurred by this positive result, we tested whether this approach could be generally applicable, in spite of the fact that different MD force fields employ different water models. Improved methyl group rotation barriers for the CHARMM36 and AMBER ff15ipq protein force fields were derived, such that the NMR relaxation data obtained from the MD simulations even now display very good agreement with the experiment. Results herein showcase the performance of present-day MD force fields and manifest their refined ability to accurately describe internal protein dynamics.