Directing polymorph specific calcium carbonate formation with de novo protein templates.

Biomolecules modulate inorganic crystallization to generate hierarchically structured biominerals, but the atomic structure of the organic-inorganic interfaces that regulate mineralization remain largely unknown. We hypothesized that heterogeneous nucleation of calcium carbonate could be achieved by a structured flat molecular template that pre-organizes calcium ions on its surface. To test this hypothesis, we design helical repeat proteins (DHRs) displaying regularly spaced carboxylate arrays on their surfaces and find that both protein monomers and protein-Ca2+ supramolecular assemblies directly nucleate nano-calcite with non-natural {110} or {202} faces while vaterite, which forms first in the absence of the proteins, is bypassed. These protein-stabilized nanocrystals then assemble by oriented attachment into calcite mesocrystals. We find further that nanocrystal size and polymorph can be tuned by varying the length and surface chemistry of the designed protein templates. Thus, bio-mineralization can be programmed using de novo protein design, providing a route to next-generation hybrid materials.

De novo design of buttressed loops for sculpting protein functions.

In natural proteins, structured loops play central roles in molecular recognition, signal transduction and enzyme catalysis. However, because of the intrinsic flexibility and irregularity of loop regions, organizing multiple structured loops at protein functional sites has been very difficult to achieve by de novo protein design. Here we describe a solution to this problem that generates structured loops buttressed by extensive hydrogen bonding interactions with two neighboring loops and with secondary structure elements. We use this approach to design tandem repeat proteins with buttressed loops ranging from 9 to 14 residues in length. Experimental characterization shows the designs are folded and monodisperse, highly soluble, and thermally stable. Crystal structures are in close agreement with the computational design models, with the loops structured and buttressed by their neighbors as designed. We demonstrate the functionality afforded by loop buttressing by designing and characterizing binders for extended peptides in which the loops form one side of an extended binding pocket. The ability to design multiple structured loops should contribute quite generally to efforts to design new protein functions.

Quantitative and Qualitative Changes in Peripheral Chemoreceptor Activity in Preterm Infants.

Rationale: Preterm infants are at risk for ventilatory control instability that may be due to aberrant peripheral chemoreceptor activity. Although term infants have increasing peripheral chemoreceptor contribution to overall ventilatory drive with increasing postnatal age, how peripheral chemoreceptor contribution changes in preterm infants with increasing postmenstrual age is not known. Objectives: To evaluate peripheral chemoreceptor activity between 32 and 52 weeks postmenstrual age in preterm infants, using both quantitative and qualitative measures. Methods: Fifty-five infants born between 24 weeks, 0 days gestation and 28 weeks, 6 days gestation underwent hyperoxic testing at one to four time points between 32 and 52 weeks postmenstrual age. Quantitative [Formula: see text] decreases were calculated, and qualitative responses were categorized as apnea, continued breathing with a clear reduction in [Formula: see text], sigh breaths, and no response. Measurements and Main Results: A total of 280 hyperoxic tests were analyzed (2.2 ± 0.3 tests per infant at each time point). Mean peripheral chemoreceptor contribution to ventilatory drive was 85.2 ± 20.0% at 32 weeks and 64.1 ± 22.0% at 52 weeks. Apneic responses were more frequent at earlier postmenstrual ages. Conclusions: Among preterm infants, the peripheral chemoreceptor contribution to ventilatory drive was greater at earlier postmenstrual ages. Apnea was a frequent response to hyperoxic testing at earlier postmenstrual ages, suggesting high peripheral chemoreceptor activity. A clearer description of how peripheral chemoreceptor activity changes over time in preterm infants may help explain how ventilatory control instability contributes to apnea and sleep-disordered breathing later in childhood. Clinical trial registered with www.clinicaltrials.gov (NCT03464396).

Rotational dynamics and transition mechanisms of surface-adsorbed proteins.

Assembly of biomolecules at solid­water interfaces requires molecules to traverse complex orientation-dependent energy landscapes through processes that are poorly understood, largely due to the dearth of in situ single-molecule measurements and statistical analyses of the rotational dynamics that define directional selection. Emerging capabilities in high-speed atomic force microscopy and machine learning have allowed us to directly determine the orientational energy landscape and observe and quantify the rotational dynamics for protein nanorods on the surface of muscovite mica under a variety of conditions. Comparisons with kinetic Monte Carlo simulations show that the transition rates between adjacent orientation-specific energetic minima can largely be understood through traditional models of in-plane Brownian rotation across a biased energy landscape, with resulting transition rates that are exponential in the energy barriers between states. However, transitions between more distant angular states are decoupled from barrier height, with jump-size distributions showing a power law decay that is characteristic of a nonclassical Levy-flight random walk, indicating that large jumps are enabled by alternative modes of motion via activated states. The findings provide insights into the dynamics of biomolecules at solid­liquid interfaces that lead to self-assembly, epitaxial matching, and other orientationally anisotropic outcomes and define a general procedure for exploring such dynamics with implications for hybrid biomolecular­inorganic materials design.

Ion-dependent protein-surface interactions from intrinsic solvent response.

The phyllosilicate mineral muscovite mica is widely used as a surface template for the patterning of macromolecules, yet a molecular understanding of its surface chemistry under varying solution conditions, required to predict and control the self-assembly of adsorbed species, is lacking. We utilize all-atom molecular dynamics simulations in conjunction with an electrostatic analysis based in local molecular field theory that affords a clean separation of long-range and short-range electrostatics. Using water polarization response as a measure of the electric fields that arise from patterned, surface-bound ions that direct the adsorption of charged macromolecules, we apply a Landau theory of forces induced by asymmetrically polarized surfaces to compute protein-surface interactions for two muscovite-binding proteins (DHR10-mica6 and C98RhuA). Comparison of the pressure between surface and protein in high-concentration KCl and NaCl aqueous solutions reveals ion-specific differences in far-field protein-surface interactions, neatly capturing the ability of ions to modulate the surface charge of muscovite that in turn selectively attracts one binding face of each protein over all others.

Disentangling Rotational Dynamics and Ordering Transitions in a System of Self-Organizing Protein Nanorods via Rotationally Invariant Latent Representations.

The dynamics of complex ordering systems with active rotational degrees of freedom exemplified by protein self-assembly is explored using a machine learning workflow that combines deep learning-based semantic segmentation and rotationally invariant variational autoencoder-based analysis of orientation and shape evolution. The latter allows for disentanglement of the particle orientation from other degrees of freedom and compensates for lateral shifts. The disentangled representations in the latent space encode the rich spectrum of local transitions that can now be visualized and explored via continuous variables. The time dependence of ensemble averages allows insight into the time dynamics of the system and, in particular, illustrates the presence of the potential ordering transition. Finally, analysis of the latent variables along the single-particle trajectory allows tracing these parameters on a single-particle level. The proposed approach is expected to be universally applicable for the description of the imaging data in optical, scanning probe, and electron microscopy seeking to understand the dynamics of complex systems where rotations are a significant part of the process.

Engineering Biomolecular Self-Assembly at Solid-Liquid Interfaces.

Biomolecular self-assembly is a key process used by life to build functional materials from the "bottom up." In the last few decades, bioengineering and bionanotechnology have borrowed this strategy to design and synthesize numerous biomolecular and hybrid materials with diverse architectures and properties. However, engineering biomolecular self-assembly at solid-liquid interfaces into predesigned architectures lags the progress made in bulk solution both in practice and theory. Here, recent achievements in programming self-assembly of peptides, proteins, and peptoids at solid-liquid interfaces are summarized and corresponding applications are described. Recent advances in the physical understandings of self-assembly pathways obtained using in situ atomic force microscopy are also discussed. These advances will lead to novel strategies for designing biomaterials organized at and interfaced with inorganic surfaces.

Quantifying the Dynamics of Protein Self-Organization Using Deep Learning Analysis of Atomic Force Microscopy Data.

The dynamics of protein self-assembly on the inorganic surface and the resultant geometric patterns are visualized using high-speed atomic force microscopy. The time dynamics of the classical macroscopic descriptors such as 2D fast Fourier transforms, correlation, and pair distribution functions are explored using the unsupervised linear unmixing, demonstrating the presence of static ordered and dynamic disordered phases and establishing their time dynamics. The deep learning (DL)-based workflow is developed to analyze detailed particle dynamics and explore the evolution of local geometries. Finally, we use a combination of DL feature extraction and mixture modeling to define particle neighborhoods free of physics constraints, allowing for a separation of possible classes of particle behavior and identification of the associated transitions. Overall, this work establishes the workflow for the analysis of the self-organization processes in complex systems from observational data and provides insight into the fundamental mechanisms.

Sequence-Structure-Binding Relationships Reveal Adhesion Behavior of the Car9 Solid-Binding Peptide: An Integrated Experimental and Simulation Study.

Solid-binding peptides (SBPs) recognizing inorganic and synthetic interfaces have enabled a broad range of materials science applications and hold promise as adhesive or morphogenetic control units that can be genetically encoded within desirable or designed protein frameworks. To date, the underlying relationships governing both SBP-surface and SBP-SBP interactions and how they give rise to different adsorption mechanisms remain unclear. Here, we combine protein engineering, surface plasmon resonance characterization, and molecular dynamics (MD) simulations initiated from Rosetta predictions to gain insights on the interplay of amino acid composition, structure, self-association, and adhesion modality in a panel of variants of the Car9 silica-binding peptide (DSARGFKKPGKR) fused to the C-terminus of superfolder green fluorescent protein (sfGFP). Analysis of kinetics, energetics, and MD-predicted structures shows that the high-affinity binding of Car9 to the silanol-rich surface of silica is dominated by electrostatic contributions and a spectrum of several persistent interactions that, along with a high surface population of bound molecules, promote cooperative interactions between neighboring SBPs and higher order structure formation. Transition from cooperative to Langmuir adhesion in sfGFP-Car9 variants occurs in concert with a reduction of stable surface interactions and self-association, as confirmed by atomic force microscopy imaging of proteins exhibiting the two different binding behaviors. We discuss the implications of these results for the de novo design of SBP-surface binding systems.

Controlling protein assembly on inorganic crystals through designed protein interfaces.

The ability of proteins and other macromolecules to interact with inorganic surfaces is essential to biological function. The proteins involved in these interactions are highly charged and often rich in carboxylic acid side chains1-5, but the structures of most protein-inorganic interfaces are unknown. We explored the possibility of systematically designing structured protein-mineral interfaces, guided by the example of ice-binding proteins, which present arrays of threonine residues (matched to the ice lattice) that order clathrate waters into an ice-like structure6. Here we design proteins displaying arrays of up to 54 carboxylate residues geometrically matched to the potassium ion (K+) sublattice on muscovite mica (001). At low K+ concentration, individual molecules bind independently to mica in the designed orientations, whereas at high K+ concentration, the designs form two-dimensional liquid-crystal phases, which accentuate the inherent structural bias in the muscovite lattice to produce protein arrays ordered over tens of millimetres. Incorporation of designed protein-protein interactions preserving the match between the proteins and the K+ lattice led to extended self-assembled structures on mica: designed end-to-end interactions produced micrometre-long single-protein-diameter wires and a designed trimeric interface yielded extensive honeycomb arrays. The nearest-neighbour distances in these hexagonal arrays could be set digitally between 7.5 and 15.9 nanometres with 2.1-nanometre selectivity by changing the number of repeat units in the monomer. These results demonstrate that protein-inorganic lattice interactions can be systematically programmed and set the stage for designing protein-inorganic hybrid materials.

Essential Genome of the Metabolically Versatile Alphaproteobacterium Rhodopseudomonas palustris.

UNLABELLED: Rhodopseudomonas palustris is an alphaproteobacterium that has served as a model organism for studies of photophosphorylation, regulation of nitrogen fixation, production of hydrogen as a biofuel, and anaerobic degradation of aromatic compounds. This bacterium is able to transition between anaerobic photoautotrophic growth, anaerobic photoheterotrophic growth, and aerobic heterotrophic growth. As a starting point to explore the genetic basis for the metabolic versatility of R. palustris, we used transposon mutagenesis and Tn-seq to identify 552 genes as essential for viability in cells growing aerobically on semirich medium. Of these, 323 have essential gene homologs in the alphaproteobacterium Caulobacter crescentus, and 187 have essential gene homologs in Escherichia coli. There were 24 R. palustris genes that were essential for viability under aerobic growth conditions that have low sequence identity but are likely to be functionally homologous to essential E. coli genes. As expected, certain functional categories of essential genes were highly conserved among the three organisms, including translation, ribosome structure and biogenesis, secretion, and lipid metabolism. R. palustris cells divide by budding in which a sessile cell gives rise to a motile swarmer cell. Conserved cell cycle genes required for this developmental process were essential in both C. crescentus and R. palustris. Our results suggest that despite vast differences in lifestyles, members of the alphaproteobacteria have a common set of essential genes that is specific to this group and distinct from that of gammaproteobacteria like E. coli. IMPORTANCE: Essential genes in bacteria and other organisms are those absolutely required for viability. Rhodopseudomonas palustris has served as a model organism for studies of anaerobic aromatic compound degradation, hydrogen gas production, nitrogen fixation, and photosynthesis. We used the technique of Tn-seq to determine the essential genes of R. palustris grown under heterotrophic aerobic conditions. The transposon library generated in this study will be useful for future studies to identify R. palustris genes essential for viability under specialized growth conditions and also for survival under conditions of stress.

Solution Structure of CCL19 and Identification of Overlapping CCR7 and PSGL-1 Binding Sites.

CCL19 and CCL21 are chemokines involved in the trafficking of immune cells, particularly within the lymphatic system, through activation of CCR7. Concurrent expression of PSGL-1 and CCR7 in naive T-cells enhances recruitment of these cells to secondary lymphoid organs by CCL19 and CCL21. Here the solution structure of CCL19 is reported. It contains a canonical chemokine domain. Chemical shift mapping shows the N-termini of PSGL-1 and CCR7 have overlapping binding sites for CCL19 and binding is competitive. Implications for the mechanism of PSGL-1's enhancement of resting T-cell recruitment are discussed.

Advancements in using TiO2 bionanoconjugates for precision degradation of intracellular biological structures.

Due to their low cost, photocatalytic properties, and unique surface chemistry, titanium dioxide (TiO2) nanoparticles are among the most widely used nanoparticles in industry today. Over the last decade, TiO2 nanoparticles have also been chemically and biologically enhanced to create TiO2 bionanoconjugates that can be used for biological applications such as imaging and manipulating desired biological structures. This review particularly focuses on the manner in which these specific chemical and biological modifications in TiO2 bionanoconjugates alter pre and post photoexcitation events to enable precision degradation of intracellular biological structures. Secondary emphasis is given to imaging aspects when necessary to understanding the effects that targeting these bionanoconjugates has on degradation of neighboring biological structures. The advantages of TiO2 bionanoconjugates to standard techniques, as well as future research directions, are also discussed.