Cryo-EM structure of the human NKCC1 transporter reveals mechanisms of ion coupling and specificity.

The sodium-potassium-chloride transporter NKCC1 of the SLC12 family performs Na+ -dependent Cl- - and K+ -ion uptake across plasma membranes. NKCC1 is important for regulating cell volume, hearing, blood pressure, and regulation of hyperpolarizing GABAergic and glycinergic signaling in the central nervous system. Here, we present a 2.6 Å resolution cryo-electron microscopy structure of human NKCC1 in the substrate-loaded (Na+ , K+ , and 2 Cl- ) and occluded, inward-facing state that has also been observed for the SLC6-type transporters MhsT and LeuT. Cl- binding at the Cl1 site together with the nearby K+ ion provides a crucial bridge between the LeuT-fold scaffold and bundle domains. Cl- -ion binding at the Cl2 site seems to undertake a structural role similar to conserved glutamate of SLC6 transporters and may allow for Cl- -sensitive regulation of transport. Supported by functional studies in mammalian cells and computational simulations, we describe a putative Na+ release pathway along transmembrane helix 5 coupled to the Cl2 site. The results provide insight into the structure-function relationship of NKCC1 with broader implications for other SLC12 family members.

Integrated machine learning and multimodal data fusion for patho-phenotypic feature recognition in iPSC models of dilated cardiomyopathy.

Integration of multiple data sources presents a challenge for accurate prediction of molecular patho-phenotypic features in automated analysis of data from human model systems. Here, we applied a machine learning-based data integration to distinguish patho-phenotypic features at the subcellular level for dilated cardiomyopathy (DCM). We employed a human induced pluripotent stem cell-derived cardiomyocyte (iPSC-CM) model of a DCM mutation in the sarcomere protein troponin T (TnT), TnT-R141W, compared to isogenic healthy (WT) control iPSC-CMs. We established a multimodal data fusion (MDF)-based analysis to integrate source datasets for Ca2+ transients, force measurements, and contractility recordings. Data were acquired for three additional layer types, single cells, cell monolayers, and 3D spheroid iPSC-CM models. For data analysis, numerical conversion as well as fusion of data from Ca2+ transients, force measurements, and contractility recordings, a non-negative blind deconvolution (NNBD)-based method was applied. Using an XGBoost algorithm, we found a high prediction accuracy for fused single cell, monolayer, and 3D spheroid iPSC-CM models (≥92 ± 0.08 %), as well as for fused Ca2+ transient, beating force, and contractility models (>96 ± 0.04 %). Integrating MDF and XGBoost provides a highly effective analysis tool for prediction of patho-phenotypic features in complex human disease models such as DCM iPSC-CMs.

Bayesian methods in integrative structure modeling.

There is a growing interest in characterizing the structure and dynamics of large biomolecular assemblies and their interactions within the cellular environment. A diverse array of experimental techniques allows us to study biomolecular systems on a variety of length and time scales. These techniques range from imaging with light, X-rays or electrons, to spectroscopic methods, cross-linking mass spectrometry and functional genomics approaches, and are complemented by AI-assisted protein structure prediction methods. A challenge is to integrate all of these data into a model of the system and its functional dynamics. This review focuses on Bayesian approaches to integrative structure modeling. We sketch the principles of Bayesian inference, highlight recent applications to integrative modeling and conclude with a discussion of current challenges and future perspectives.

Fast-forward on P-type ATPases: recent advances on structure and function.

P-type ATPase are present in nearly all organisms. They maintain electrochemical gradients for many solutes, in particular ions, they control membrane lipid asymmetry, and are crucial components of intricate signaling networks. All P-type ATPases share a common topology with a transmembrane and three cytoplasmic domains and their transport cycle follows a general scheme - the Post-Albers-cycle. Recently, P-type ATPase research has been advanced most significantly by the technological advancements in cryo-EM analysis, which has elucidated many new P-type ATPase structures and mechanisms and revealed several new ways of regulation. In this review, we highlight the progress of the field and focus on special features that are present in the five subfamilies. Hence, we outline the new intersubunit transport model of KdpFABC, the ways in which heavy metal pumps have evolved to accommodate various substrates, the strategies Ca2+ pumps utilize to adapt to different environmental needs, the intricate molecular builds of the ion binding sites in Na,K- and H,K-ATPases, the remarkable hexameric assembly of fungal proton pumps, the many ways in which P4-ATPase lipid flippases are regulated, and finally the deorphanization of P5 pumps. Interestingly many of the described features are found in more than one of the five subfamilies, and mixed and matched together to provide optimal function and precise regulation.

Bayesian inference of chromatin structure ensembles from population-averaged contact data.

Mounting experimental evidence suggests a role for the spatial organization of chromatin in crucial processes of the cell nucleus such as transcription regulation. Chromosome conformation capture techniques allow us to characterize chromatin structure by mapping contacts between chromosomal loci on a genome-wide scale. The most widespread modality is to measure contact frequencies averaged over a population of cells. Single-cell variants exist, but suffer from low contact numbers and have not yet gained the same resolution as population methods. While intriguing biological insights have already been garnered from ensemble-averaged data, information about three-dimensional (3D) genome organization in the underlying individual cells remains largely obscured because the contact maps show only an average over a huge population of cells. Moreover, computational methods for structure modeling of chromatin have mostly focused on fitting a single consensus structure, thereby ignoring any cell-to-cell variability in the model itself. Here, we propose a fully Bayesian method to infer ensembles of chromatin structures and to determine the optimal number of states in a principled, objective way. We illustrate our approach on simulated data and compute multistate models of chromatin from chromosome conformation capture carbon copy (5C) data. Comparison with independent data suggests that the inferred ensembles represent the underlying sample population faithfully. Harnessing the rich information contained in multistate models, we investigate cell-to-cell variability of chromatin organization into topologically associating domains, thus highlighting the ability of our approach to deliver insights into chromatin organization of great biological relevance.

A graph-based algorithm for detecting rigid domains in protein structures.

BACKGROUND: Conformational transitions are implicated in the biological function of many proteins. Structural changes in proteins can be described approximately as the relative movement of rigid domains against each other. Despite previous efforts, there is a need to develop new domain segmentation algorithms that are capable of analysing the entire structure database efficiently and do not require the choice of protein-dependent tuning parameters such as the number of rigid domains. RESULTS: We develop a graph-based method for detecting rigid domains in proteins. Structural information from multiple conformational states is represented by a graph whose nodes correspond to amino acids. Graph clustering algorithms allow us to reduce the graph and run the Viterbi algorithm on the associated line graph to obtain a segmentation of the input structures into rigid domains. In contrast to many alternative methods, our approach does not require knowledge about the number of rigid domains. Moreover, we identified default values for the algorithmic parameters that are suitable for a large number of conformational ensembles. We test our algorithm on examples from the DynDom database and illustrate our method on various challenging systems whose structural transitions have been studied extensively. CONCLUSIONS: The results strongly suggest that our graph-based algorithm forms a novel framework to characterize structural transitions in proteins via detecting their rigid domains. The web server is available at http://azifi.tz.agrar.uni-goettingen.de/webservice/ .

Specific phospholipid binding to Na,K-ATPase at two distinct sites.

Membrane protein function can be affected by the physical state of the lipid bilayer and specific lipid-protein interactions. For Na,K-ATPase, bilayer properties can modulate pump activity, and, as observed in crystal structures, several lipids are bound within the transmembrane domain. Furthermore, Na,K-ATPase activity depends on phosphatidylserine (PS) and cholesterol, which stabilize the protein, and polyunsaturated phosphatidylcholine (PC) or phosphatidylethanolamine (PE), known to stimulate Na,K-ATPase activity. Based on lipid structural specificity and kinetic mechanisms, specific interactions of both PS and PC/PE have been inferred. Nevertheless, specific binding sites have not been identified definitively. We address this question with native mass spectrometry (MS) and site-directed mutagenesis. Native MS shows directly that one molecule each of 18:0/18:1 PS and 18:0/20:4 PC can bind specifically to purified human Na,K-ATPase (α1ß1). By replacing lysine residues at proposed phospholipid-binding sites with glutamines, the two sites have been identified. Mutations in the cytoplasmic αL8-9 loop destabilize the protein but do not affect Na,K-ATPase activity, whereas mutations in transmembrane helices (TM), αTM2 and αTM4, abolish the stimulation of activity by 18:0/20:4 PC but do not affect stability. When these data are linked to crystal structures, the underlying mechanism of PS and PC/PE effects emerges. PS (and cholesterol) bind between αTM 8, 9, 10, near the FXYD subunit, and maintain topological integrity of the labile C terminus of the α subunit (site A). PC/PE binds between αTM2, 4, 6, and 9 and accelerates the rate-limiting E1P-E2P conformational transition (site B). We discuss the potential physiological implications.

Structures of the human and Drosophila 80S ribosome.

Protein synthesis in all cells is carried out by macromolecular machines called ribosomes. Although the structures of prokaryotic, yeast and protist ribosomes have been determined, the more complex molecular architecture of metazoan 80S ribosomes has so far remained elusive. Here we present structures of Drosophila melanogaster and Homo sapiens 80S ribosomes in complex with the translation factor eEF2, E-site transfer RNA and Stm1-like proteins, based on high-resolution cryo-electron-microscopy density maps. These structures not only illustrate the co-evolution of metazoan-specific ribosomal RNA with ribosomal proteins but also reveal the presence of two additional structural layers in metazoan ribosomes, a well-ordered inner layer covered by a flexible RNA outer layer. The human and Drosophila ribosome structures will provide the basis for more detailed structural, biochemical and genetic experiments.

A probabilistic network model for structural transitions in biomolecules.

Biological macromolecules often undergo large conformational rearrangements during a functional cycle. To simulate these structural transitions with full atomic detail typically demands extensive computational resources. Moreover, it is unclear how to incorporate, in a principled way, additional experimental information that could guide the structural transition. This article develops a probabilistic model for conformational transitions in biomolecules. The model can be viewed as a network of anharmonic springs that break, if the experimental data support the rupture of bonds. Hamiltonian Monte Carlo in internal coordinates is used to infer structural transitions from experimental data, thereby sampling large conformational transitions without distorting the structure. The model is benchmarked on a large set of conformational transitions. Moreover, we demonstrate the use of the probabilistic network model for integrative modeling of macromolecular complexes based on data from crosslinking followed by mass spectrometry.

Digoxin derivatives with selectivity for the α2ß3 isoform of Na,K-ATPase potently reduce intraocular pressure.

The ciliary epithelium in the eye consists of pigmented epithelial cells that express the α1ß1 isoform of Na,K-ATPase and nonpigmented epithelial cells that express mainly the α2ß3 isoform. In principle, a Na,K-ATPase inhibitor with selectivity for α2ß3 that penetrates the cornea could effectively reduce intraocular pressure, with minimal systemic or local toxicity. We have recently synthesized perhydro-1,4-oxazepine derivatives of digoxin by NaIO4 oxidation of the third digitoxose and reductive amination with various R-NH2 substituents and identified derivatives with significant selectivity for human α2ß1 over α1ß1 (up to 7.5-fold). When applied topically, the most α2-selective derivatives effectively prevented or reversed pharmacologically raised intraocular pressure in rabbits. A recent structure of Na,K-ATPase, with bound digoxin, shows the third digitoxose approaching one residue in the ß1 subunit, Gln84, suggesting a role for ß in digoxin binding. Gln84 in ß1 is replaced by Val88 in ß3. Assuming that alkyl substituents might interact with ß3Val88, we synthesized perhydro-1,4-oxazepine derivatives of digoxin with diverse alkyl substituents. The methylcyclopropyl and cyclobutyl derivatives are strongly selective for α2ß3 over α1ß1 (22-33-fold respectively), as determined either with purified human isoform proteins or intact bovine nonpigmented epithelium cells. When applied topically on rabbit eyes, these derivatives potently reduce both pharmacologically raised and basal intraocular pressure. The cyclobutyl derivative is more efficient than Latanoprost, the most widely used glaucoma drug. Thus, the conclusion is that α2ß3-selective digoxin derivatives effectively penetrate the cornea and inhibit the Na,K-ATPase, hence reducing aqueous humor production. The new digoxin derivatives may have potential for glaucoma drug therapy.

Selective Assembly of Na,K-ATPase α2ß2 Heterodimers in the Heart: DISTINCT FUNCTIONAL PROPERTIES AND ISOFORM-SELECTIVE INHIBITORS.

The Na,K-ATPase α2 subunit plays a key role in cardiac muscle contraction by regulating intracellular Ca2+, whereas α1 has a more conventional role of maintaining ion homeostasis. The ß subunit differentially regulates maturation, trafficking, and activity of α-ß heterodimers. It is not known whether the distinct role of α2 in the heart is related to selective assembly with a particular one of the three ß isoforms. We show here by immunofluorescence and co-immunoprecipitation that α2 is preferentially expressed with ß2 in T-tubules of cardiac myocytes, forming α2ß2 heterodimers. We have expressed human α1ß1, α2ß1, α2ß2, and α2ß3 in Pichia pastoris, purified the complexes, and compared their functional properties. α2ß2 and α2ß3 differ significantly from both α2ß1 and α1ß1 in having a higher K0.5K+ and lower K0.5Na+ for activating Na,K-ATPase. These features are the result of a large reduction in binding affinity for extracellular K+ and shift of the E1P-E2P conformational equilibrium toward E1P. A screen of perhydro-1,4-oxazepine derivatives of digoxin identified several derivatives (e.g. cyclobutyl) with strongly increased selectivity for inhibition of α2ß2 and α2ß3 over α1ß1 (range 22-33-fold). Molecular modeling suggests a possible basis for isoform selectivity. The preferential assembly, specific T-tubular localization, and low K+ affinity of α2ß2 could allow an acute response to raised ambient K+ concentrations in physiological conditions and explain the importance of α2ß2 for cardiac muscle contractility. The high sensitivity of α2ß2 to digoxin derivatives explains beneficial effects of cardiac glycosides for treatment of heart failure and potential of α2ß2-selective digoxin derivatives for reducing cardiotoxicity.

A probabilistic model for detecting rigid domains in protein structures.

MOTIVATION: Large-scale conformational changes in proteins are implicated in many important biological functions. These structural transitions can often be rationalized in terms of relative movements of rigid domains. There is a need for objective and automated methods that identify rigid domains in sets of protein structures showing alternative conformational states. RESULTS: We present a probabilistic model for detecting rigid-body movements in protein structures. Our model aims to approximate alternative conformational states by a few structural parts that are rigidly transformed under the action of a rotation and a translation. By using Bayesian inference and Markov chain Monte Carlo sampling, we estimate all parameters of the model, including a segmentation of the protein into rigid domains, the structures of the domains themselves, and the rigid transformations that generate the observed structures. We find that our Gibbs sampling algorithm can also estimate the optimal number of rigid domains with high efficiency and accuracy. We assess the power of our method on several thousand entries of the DynDom database and discuss applications to various complex biomolecular systems. AVAILABILITY AND IMPLEMENTATION: The Python source code for protein ensemble analysis is available at: https://github.com/thachnguyen/motion_detection CONTACT: : mhabeck@gwdg.de.

Inferential Structure Determination of Chromosomes from Single-Cell Hi-C Data.

Chromosome conformation capture (3C) techniques have revealed many fascinating insights into the spatial organization of genomes. 3C methods typically provide information about chromosomal contacts in a large population of cells, which makes it difficult to draw conclusions about the three-dimensional organization of genomes in individual cells. Recently it became possible to study single cells with Hi-C, a genome-wide 3C variant, demonstrating a high cell-to-cell variability of genome organization. In principle, restraint-based modeling should allow us to infer the 3D structure of chromosomes from single-cell contact data, but suffers from the sparsity and low resolution of chromosomal contacts. To address these challenges, we adapt the Bayesian Inferential Structure Determination (ISD) framework, originally developed for NMR structure determination of proteins, to infer statistical ensembles of chromosome structures from single-cell data. Using ISD, we are able to compute structural error bars and estimate model parameters, thereby eliminating potential bias imposed by ad hoc parameter choices. We apply and compare different models for representing the chromatin fiber and for incorporating singe-cell contact information. Finally, we extend our approach to the analysis of diploid chromosome data.

Structure and activity of the N-terminal substrate recognition domains in proteasomal ATPases.

The proteasome forms the core of the protein quality control system in archaea and eukaryotes and also occurs in one bacterial lineage, the Actinobacteria. Access to its proteolytic compartment is controlled by AAA ATPases, whose N-terminal domains (N domains) are thought to mediate substrate recognition. The N domains of an archaeal proteasomal ATPase, Archaeoglobus fulgidus PAN, and of its actinobacterial homolog, Rhodococcus erythropolis ARC, form hexameric rings, whose subunits consist of an N-terminal coiled coil and a C-terminal OB domain. In ARC-N, the OB domains are duplicated and form separate rings. PAN-N and ARC-N can act as chaperones, preventing the aggregation of heterologous proteins in vitro, and this activity is preserved in various chimeras, even when these include coiled coils and OB domains from unrelated proteins. The structures suggest a molecular mechanism for substrate processing based on concerted radial motions of the coiled coils relative to the OB rings.

Molecular Mechanisms and Kinetic Effects of FXYD1 and Phosphomimetic Mutants on Purified Human Na,K-ATPase.

Phospholemman (FXYD1) is a single-transmembrane protein regulator of Na,K-ATPase, expressed strongly in heart, skeletal muscle, and brain and phosphorylated by protein kinases A and C at Ser-68 and Ser-63, respectively. Binding of FXYD1 reduces Na,K-ATPase activity, and phosphorylation at Ser-68 or Ser-63 relieves the inhibition. Despite the accumulated information on physiological effects, whole cell studies provide only limited information on molecular mechanisms. As a complementary approach, we utilized purified human Na,K-ATPase (α1ß1 and α2ß1) reconstituted with FXYD1 or mutants S63E, S68E, and S63E,S68E that mimic phosphorylation at Ser-63 and Ser-68. Compared with control α1ß1, FXYD1 reduces Vmax and turnover rate and raises K0.5Na. The phosphomimetic mutants reverse these effects and reduce K0.5Na below control K0.5Na. Effects on α2ß1 are similar but smaller. Experiments in proteoliposomes reconstituted with α1ß1 show analogous effects of FXYD1 on K0.5Na, which are abolished by phosphomimetic mutants and also by increasing mole fractions of DOPS in the proteoliposomes. Stopped-flow experiments using the dye RH421 show that FXYD1 slows the conformational transition E2(2K)ATP → E1(3Na)ATP but does not affect 3NaE1P → E2P3Na. This regulatory effect is explained simply by molecular modeling, which indicates that a cytoplasmic helix (residues 60-70) docks between the αN and αP domains in the E2 conformation, but docking is weaker in E1 (also for phosphomimetic mutants). Taken together with previous work showing that FXYD1 also raises binding affinity for the Na(+)-selective site III, these results provide a rather comprehensive picture of the regulatory mechanism of FXYD1 that complements the physiological studies.

Stimulation, inhibition, or stabilization of Na,K-ATPase caused by specific lipid interactions at distinct sites.

The activity of membrane proteins such as Na,K-ATPase depends strongly on the surrounding lipid environment. Interactions can be annular, depending on the physical properties of the membrane, or specific with lipids bound in pockets between transmembrane domains. This paper describes three specific lipid-protein interactions using purified recombinant Na,K-ATPase. (a) Thermal stability of the Na,K-ATPase depends crucially on a specific interaction with 18:0/18:1 phosphatidylserine (1-stearoyl-2-oleoyl-sn-glycero-3-phospho-L-serine; SOPS) and cholesterol, which strongly amplifies stabilization. We show here that cholesterol associates with SOPS, FXYD1, and the α subunit between trans-membrane segments αTM8 and -10 to stabilize the protein. (b) Polyunsaturated neutral lipids stimulate Na,K-ATPase turnover by >60%. A screen of the lipid specificity showed that 18:0/20:4 and 18:0/22:6 phosphatidylethanolamine (PE) are the optimal phospholipids for this effect. (c) Saturated phosphatidylcholine and sphingomyelin, but not saturated phosphatidylserine or PE, inhibit Na,K-ATPase activity by 70-80%. This effect depends strongly on the presence of cholesterol. Analysis of the Na,K-ATPase activity and E1-E2 conformational transitions reveals the kinetic mechanisms of these effects. Both stimulatory and inhibitory lipids poise the conformational equilibrium toward E2, but their detailed mechanisms of action are different. PE accelerates the rate of E1 → E2P but does not affect E2(2K)ATP → E13NaATP, whereas sphingomyelin inhibits the rate of E2(2K)ATP → E13NaATP, with very little effect on E1 → E2P. We discuss these lipid effects in relation to recent crystal structures of Na,K-ATPase and propose that there are three separate sites for the specific lipid interactions, with potential physiological roles to regulate activity and stability of the pump.

Cooperative binding: a multiple personality.

Cooperative binding has been described in many publications and has been related to or defined by several different properties of the binding behavior of the ligand to the target molecule. In addition to the commonly used Hill coefficient, other characteristics such as a sigmoidal shape of the overall titration curve in a linear plot, a change of ligand affinity of the other binding sites when a site of the target molecule becomes occupied, or complex roots of the binding polynomial have been used to define or to quantify cooperative binding. In this work, we analyze how the different properties are related in the most general model for binding curves based on the grand canonical partition function and present several examples which highlight differences between the cooperativity characterizing properties which are discussed. Our results mainly show that among the presented definitions there are not two which fully coincide. Moreover, this work poses the question whether it can make sense to distinguish between positive and negative cooperativity based on the macroscopic binding isotherm only. This article shall emphasize that scientists who investigate cooperative effects in biological systems could help avoiding misunderstandings by stating clearly which kind of cooperativity they discuss.

Bayesian inference of initial models in cryo-electron microscopy using pseudo-atoms.

Single-particle cryo-electron microscopy is widely used to study the structure of macromolecular assemblies. Tens of thousands of noisy two-dimensional images of the macromolecular assembly viewed from different directions are used to infer its three-dimensional structure. The first step is to estimate a low-resolution initial model and initial image orientations. This is a challenging global optimization problem with many unknowns, including an unknown orientation for each two-dimensional image. Obtaining a good initial model is crucial for the success of the subsequent refinement step. We introduce a probabilistic algorithm for estimating an initial model. The algorithm is fast, has very few algorithmic parameters, and yields information about the precision of estimated model parameters in addition to the parameters themselves. Our algorithm uses a pseudo-atomic model to represent the low-resolution three-dimensional structure, with isotropic Gaussian components as moveable pseudo-atoms. This leads to a significant reduction in the number of parameters needed to represent the three-dimensional structure, and a simplified way of computing two-dimensional projections. It also contributes to the speed of the algorithm. We combine the estimation of the unknown three-dimensional structure and image orientations in a Bayesian framework. This ensures that there are very few parameters to set, and specifies how to combine different types of prior information about the structure with the given data in a systematic way. To estimate the model parameters we use Markov chain Monte Carlo sampling. The advantage is that instead of just obtaining point estimates of model parameters, we obtain an ensemble of models revealing the precision of the estimated parameters. We demonstrate the algorithm on both simulated and real data.

Membrane-protein structure determination by solid-state NMR spectroscopy of microcrystals.

Membrane proteins are largely underrepresented among available atomic-resolution structures. The use of detergents in protein purification procedures hinders the formation of well-ordered crystals for X-ray crystallography and leads to slower molecular tumbling, impeding the application of solution-state NMR. Solid-state magic-angle spinning NMR spectroscopy is an emerging method for membrane-protein structural biology that can overcome these technical problems. Here we present the solid-state NMR structure of the transmembrane domain of the Yersinia enterocolitica adhesin A (YadA). The sample was derived from crystallization trials that yielded only poorly diffracting microcrystals. We solved the structure using a single, uniformly (13)C- and (15)N-labeled sample. In addition, solid-state NMR allowed us to acquire information on the flexibility and mobility of parts of the structure, which, in combination with evolutionary conservation information, presents new insights into the autotransport mechanism of YadA.