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At least 883 records · Page 49

Substrate stiffness modulates endothelial cell function via the YAP-Dll4-Notch1 pathway

Highlights: • Soft stiffness increases Dll4 expression in endothelial cells via YAP suppression. • Soft substrate-induced Dll4-Notch1 signaling is facilitated by VEGF stimulation. • Elevated Dll4-Notch1 signaling contributes to the regulation of VEGFRs expression. • Substrate stiffness modulates gene expression linked to endothelial cell function. Endothelial cells adapt their functions as a consequence of sensing extracellular substrate stiffness; these alterations allow them to maintain their vascular structure and function. Substrate stiffness-mediated yes-associated protein 1 (YAP) activation plays an important role in mechano-transduction and pro-angiogenic phenotype of endothelial cells, and Delta-like ligand 4 (Dll4)-Notch1 signaling is closely related to angiogenesis; however, the impact of substrate stiffness-mediated interrelation of these pathways on endothelial cell functions remains elusive. We confirmed that endothelial cells on softer substrates not only elongate cellular aspects but also attenuate YAP activation compared to cells on stiffer substrates. Endothelial cells on softer substrates also upregulate the vascular endothelial growth factor receptor 1 (VEGFR1) and VEGFR2 mRNA expression that is enhanced by VEGF stimulation. We determined that endothelial cells on softer substrates increased Dll4 expression, but not Notch1 expression, via YAP signaling. Moreover, endothelial cells on soft substrates induced not only VEGFRs upregulation but also suppression of pro-inflammatory interleukin-6 and plasminogen activator inhibitor-1 mRNA expression and the facilitation of anti-coagulant thrombomodulin and pro-coagulant tissue factor mRNA expression. Our results suggest that endothelial cells activate the YAP-Dll4-Notch signaling pathway in response to substrate stiffness and dictate cellular function.

60 APPLIED LIFE SCIENCES↗

REC protein family expansion by the emergence of a new signaling pathway

This report presents multi-genome evidence that REC protein family expansion occurs when the emergence of new pathways gives rise to functional discordance. Specificity between residues in REC domain containing response regulators with paired histidine kinases is under negative purifying selection, constrained by the presence of other bacterial two-component systems signaling cascades that share sequence and structural identity. Presuming that the two-component systems can evolve by neutral amino acid changes (neutral drift) when purifying evolutionary constraints are relaxed, how might the REC protein family expand by amino acid changes when these constraints remain intact? Using an unsupervised machine learning approach to observe the sequence landscape of REC domains across long phylogenetic distances, we find that within-gene recombination, a subcategory of gene conversion, switched the effector domain and, consequently, the regulatory context of a duplicated response regulator from transcriptional regulation by σ54 to that by σ70. We determined that the recombined response regulator diverged from its parent by episodic diversifying selection and neutral drift. Functional experiments of the parent of recombined response regulators in a model Pseudomonas putida KT2440 model system revealed that the parent and recombined response regulators sense and respond to different carboxylic acids. Finally, a residue-switching experiment using structural predictions and functional characterization suggests that the new residues in the recombined regulator could form a new interaction interface and mediate condition-specific phosphotransfer. Overall, our study finds that genetic perturbations can create conditions of functional discordance, whereby the REC protein family can evolve by episodic diversifying selection.

59 BASIC BIOLOGICAL SCIENCES↗

In Silico Insights into Protein–Protein Interaction Disruptive Mutations in the PCSK9-LDLR Complex

Gain-of-function mutations in PCSK9 (proprotein convertase subtilisin/kexin type 9) lead to reduced uptake of LDL (low density lipoprotein) cholesterol and, therefore, increased plasma LDL levels. However, the mechanism by which these mutants reduce LDL reuptake is not fully understood. Here, we have used molecular dynamics simulations, MM/PBSA (Molecular Mechanics/Poisson–Boltzmann Surface Area) binding affinity calculations, and residue interaction networks, to investigate the protein–protein interaction (PPI) disruptive effects of two of PCSK9's gain-of-function mutations, Ser127Arg and Asp374Tyr on the PCSK9 and LDL receptor complex. In addition to these PPI disruptive mutants, a third, non-interface mutation (Arg496Trp) is included as a positive control. Our results indicate that Ser127Arg and Asp374Tyr confer significantly improved binding affinity, as well as different binding modes, when compared to the wild-type. These PPI disruptive mutations lie between the EGF(A) (epidermal growth factor precursor homology domain A) of the LDL receptor and the catalytic domain of PCSK9 (Asp374Tyr) and between the prodomain of PCSK9 and the β-propeller of the LDL receptor (Ser127Arg). The interactions involved in these two interfaces result in an LDL receptor that is sterically inhibited from entering its closed conformation. This could potentially implicate the prodomain as a target for small molecule inhibitors.

59 BASIC BIOLOGICAL SCIENCES↗

Immunohistochemical detection of active transforming growth factor-beta in situ using engineered tissue

The biological activity of transforming growth factor-beta 1 (TGF-beta) is governed by dissociation from its latent complex. Immunohistochemical discrimination of active and latent TGF-beta could provide insight into TGF-beta activation in physiological and pathological processes. However, evaluation of immunoreactivity specificity in situ has been hindered by the lack of tissue in which TGF-beta status is known. To provide in situ analysis of antibodies to differentiate between these functional forms, we used xenografts of human tumor cells modified by transfection to overexpress latent TGF-beta or constitutively active TGF-beta. This comparison revealed that, whereas most antibodies did not differentiate between TGF-beta activation status, the immunoreactivity of some antibodies was activation dependent. Two widely used peptide antibodies to the amino-terminus of TGF-beta, LC(1-30) and CC(1-30) showed marked preferential immunoreactivity with active TGF-beta versus latent TGF-beta in cryosections. However, in formalin-fixed, paraffin-embedded tissue, discrimination of active TGF-beta by CC(1-30) was lost and immunoreactivity was distinctly extracellular, as previously reported for this antibody. Similar processing-dependent extracellular localization was found with a neutralizing antibody raised to recombinant TGF-beta. Antigen retrieval recovered cell-associated immunoreactivity of both antibodies. Two antibodies to peptides 78-109 showed mild to moderate preferential immunoreactivity with active TGF-beta only in paraffin sections. LC(1-30) was the only antibody tested that discriminated active from latent TGF-beta in both frozen and paraffin-embedded tissue. Thus, in situ discrimination of active versus latent TGF-beta depends on both the antibody and tissue preparation. We propose that tissues engineered to express a specific form of a given protein provide a physiological setting in which to evaluate antibody reactivity with specific functional forms of a protein.

NASA Discipline Radiation Health↗

CryoFold: Determining protein structures and data-guided ensembles from cryo-EM density maps

Cryoelectron microscopy requires molecular modeling for refinement of structures. Ensemble models arrive at low free-energy molecular structures, but are computationally expensive and limited to resolving only small proteins. Here, we introduce CryoFold, a pipeline of molecular dynamics simulations that determines ensembles of protein structures by integrating density data of varying sparsity at 3–5 Å resolution with sequence information and coarse-grained topological knowledge of the protein folds. We present six examples, folding proteins between 72 and 2,000 residues, including large membrane and multi-domain systems, and results from two Electron Microscopy Data Bank (EMDB) competitions. Driven by data from a single state, CryoFold discovers ensembles of common low-energy models together with rare low-probability structures that capture the equilibrium distribution of proteins constrained by the density maps. Many of these conformations are experimentally validated and functionally relevant. We arrive at a set of best practices for data-guided protein folding that are controlled using a Python graphical user interface (GUI).

59 BASIC BIOLOGICAL SCIENCES↗

Substituent Effects on Transient, Carbodiimide-Induced Geometry Changes in Diphenic Acids

Nucleotide-induced conformational changes in motor proteins are key to many important cell functions. Inspired by this biological behavior, we report a simple chemically fueled system that exhibits carbodiimide-induced geometry changes. Bridging via transient anhydride formation leads to a significant reduction of the twist about the biaryl bond of substituted diphenic acids, giving a simple molecular clamp. The kinetics are well-described by a simple mechanism, allowing structure–property effects to be determined. The kinetic parameters can be used to derive important characteristics of the system such as the efficiencies (anhydride yields), maximum anhydride concentrations, and overall lifetimes. Transient diphenic anhydrides tolerate steric hindrance ortho to the biaryl bond but are significantly affected by electronic effects, with electron-deficient substituents giving lower yields, peak conversions, and lifetimes. Furthermore, the results provide useful guidelines for the design of functional systems incorporating diphenic acid units.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Human Coronavirus-229E Hijacks Key Host-Cell RNA-Processing Complexes for Replication

The recent rise in zoonotic coronavirus outbreaks underscores the urgency to understand virus-host interactions and develop potent antiviral therapeutics. Systems biology approaches, particularly proteomics have been invaluable in providing a global overview of such interactions. However, these conventional approaches rely on measuring protein abundance changes which don’t reflect functional shifts. In this study, we employed a high-throughput structural proteomics approach called limited proteolysis-based mass spectrometry (LiP-MS) to capture conformational changes, which we demonstrate are better proxies for functional alterations. We applied this tool to both immortalized and primary human lung cells following human coronavirus 229E (HCoV-229E) infection. We identified significant infection-induced structural changes within RNA processing complexes such as the spliceosome-C and NOP56-associated complex. These observations emphasize that HCoV-229E infection propagates a multi-pronged effort to obstruct the house keeping RNA processing functions in the host. Finally, we show that HCoV-229E replication can be attenuated by the targeted disruption of these complexes, indicating that the identified cellular factories are viable targets to prevent coronavirus infection.

coronavirus↗

Detecting macroevolutionary genotype–phenotype associations using error-corrected rates of protein convergence

On macroevolutionary timescales, extensive mutations and phylogenetic uncertainty mask the signals of genotype–phenotype associations underlying convergent evolution. To overcome this problem, we extended the widely used framework of non-synonymous to synonymous substitution rate ratios and developed the novel metric ω C , which measures the error-corrected convergence rate of protein evolution. While ω C distinguishes natural selection from genetic noise and phylogenetic errors in simulation and real examples, its accuracy allows an exploratory genome-wide search of adaptive molecular convergence without phenotypic hypothesis or candidate genes. Using gene expression data, we explored over 20 million branch combinations in vertebrate genes and identified the joint convergence of expression patterns and protein sequences with amino acid substitutions in functionally important sites, providing hypotheses on undiscovered phenotypes. We further extended our method with a heuristic algorithm to detect highly repetitive convergence among computationally non-trivial higher-order phylogenetic combinations. Our approach allows bidirectional searches for genotype–phenotype associations, even in lineages that diverged for hundreds of millions of years.

59 BASIC BIOLOGICAL SCIENCES↗

Joint neutron/molecular dynamics vibrational spectroscopy reveals softening of HIV-1 protease upon binding of a tight inhibitor

Biomacromolecules are inherently dynamic, and their dynamics are interwoven into function. The fast collective vibrational dynamics in proteins occurs in the low picosecond timescale corresponding to frequencies of ~5-50 cm -1 . This sub-to-low THz frequency regime covers the low-amplitude collective breathing motions of a whole protein and vibrations of the constituent secondary structure elements, such as α-helices, β-sheets and loops. We have used inelastic neutron scattering experiments in combination with molecular dynamics simulations to demonstrate the vibrational dynamics softening of HIV-1 protease, a target of HIV/AIDS antivirals, upon binding of a tight clinical inhibitor darunavir. Changes in the vibrational density of states of matching structural elements in the two monomers of the homodimeric protein are not identical, indicating asymmetric effect of darunavir on the vibrational dynamics. Three of the 11 major secondary structure elements contribute over 40% to the overall changes in the vibrational density of states upon darunavir binding. Molecular dynamics simulations informed by experiments allowed us to estimate that the altered vibrational dynamics of the protease would contribute -3.6 kcal/mol -1 at 300 K, or 25%, to the free energy of darunavir binding. As HIV-1 protease drug resistance remains a concern, our results open a new avenue to help establish a direct quantitative link between protein vibrational dynamics and drug resistance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Spectral broadening and vibronic dynamics of the S2 state of canthaxanthin in the orange carotenoid protein

We have performed a series of broadband multidimensional electronic spectroscopy experiments to probe the electronic and vibrational dynamics of the canthaxanthin chromophore of the Orange Carotenoid Protein (OCP) from Synechocystis sp. PCC 6803 in its photoactivated red state, OCPR. Cross-peaks observed below the diagonal of the two-dimensional electronic spectrum indicate that absorption transitions prepare the bright S2 state of the ketocarotenoid canthaxanthin near to a sequence of conical intersections, allowing passage to the dark S1 state via the Sx intermediate in <50 fs. Rapid damping of excited-state coherent wavepacket motions suggests that the branching coordinates of the conical intersections include out-of-plane deformation and C=C stretching coordinates of the π-conjugated isoprenoid backbone. The unusual proximity of the Franck–Condon S2 state structure to the conical intersections with Sx and S1 suggests that the protein surroundings of canthaxanthin prepare it to function as an excitation energy trap in the OCPR–phycobilisome complex. Numerical simulations using the multimode Brownian oscillator model demonstrate that the ground-state absorption spectrum of OCPR overlaps with the fluorescence emission spectrum of allophycocyanin due to spectral broadening derived especially from the intramolecular motions of the canthaxanthin chromophore in its binding site.

Yang, Kunwei↗

A Sec14 domain protein is required for photoautotrophic growth and chloroplast vesicle formation in Arabidopsis thaliana

In eukaryotic photosynthetic organisms, the conversion of solar into chemical energy occurs in thylakoid membranes in the chloroplast. How thylakoid membranes are formed and maintained is poorly understood. However, previous observations of vesicles adjacent to the stromal side of the inner envelope membrane of the chloroplast suggest a possible role of membrane transport via vesicle trafficking from the inner envelope to the thylakoids. Here we show that the model plant Arabidopsis thaliana has a chloroplast-localized Sec14-like protein (CPSFL1) that is necessary for photoautotrophic growth and vesicle formation at the inner envelope membrane of the chloroplast. The cpsfl1 mutants are seedling lethal, show a defect in thylakoid structure, and lack chloroplast vesicles. Sec14 domain proteins are found only in eukaryotes and have been well characterized in yeast, where they regulate vesicle budding at the trans -Golgi network. Like the yeast Sec14p, CPSFL1 binds phosphatidylinositol phosphates (PIPs) and phosphatidic acid (PA) and acts as a phosphatidylinositol transfer protein in vitro, and expression of Arabidopsis CPSFL1 can complement the yeast sec14 mutation. CPSFL1 can transfer PIP into PA-rich membrane bilayers in vitro, suggesting that CPSFL1 potentially facilitates vesicle formation by trafficking PA and/or PIP, known regulators of membrane trafficking between organellar subcompartments. These results underscore the role of vesicles in thylakoid biogenesis and/or maintenance. CPSFL1 appears to be an example of a eukaryotic cytosolic protein that has been coopted for a function in the chloroplast, an organelle derived from endosymbiosis of a cyanobacterium.

59 BASIC BIOLOGICAL SCIENCES↗

How cholesterol stiffens unsaturated lipid membranes

Cholesterol is an integral component of eukaryotic cell membranes and a key molecule in controlling membrane fluidity, organization, and other physicochemical parameters. It also plays a regulatory function in antibiotic drug resistance and the immune response of cells against viruses, by stabilizing the membrane against structural damage. While it is well understood that, structurally, cholesterol exhibits a densification effect on fluid lipid membranes, its effects on membrane bending rigidity are assumed to be nonuniversal; i.e., cholesterol stiffens saturated lipid membranes, but has no stiffening effect on membranes populated by unsaturated lipids, such as 1,2-dioleoyl- sn -glycero-3-phosphocholine (DOPC). This observation presents a clear challenge to structure–property relationships and to our understanding of cholesterol-mediated biological functions. Here, using a comprehensive approach—combining neutron spin-echo (NSE) spectroscopy, solid-state deuterium NMR ( 2 H NMR) spectroscopy, and molecular dynamics (MD) simulations—we report that cholesterol locally increases the bending rigidity of DOPC membranes, similar to saturated membranes, by increasing the bilayer’s packing density. All three techniques, inherently sensitive to mesoscale bending fluctuations, show up to a threefold increase in effective bending rigidity with increasing cholesterol content approaching a mole fraction of 50%. Our observations are in good agreement with the known effects of cholesterol on the area-compressibility modulus and membrane structure, reaffirming membrane structure–property relationships. The current findings point to a scale-dependent manifestation of membrane properties, highlighting the need to reassess cholesterol’s role in controlling membrane bending rigidity over mesoscopic length and time scales of important biological functions, such as viral budding and lipid–protein interactions.

59 BASIC BIOLOGICAL SCIENCES↗

NTRC regulates CP12 to activate Calvin–Benson cycle during cold acclimation

NADPH-dependent thioredoxin reductase C (NTRC) is a chloroplast redox regulator in algae and plants. Here, we used site-specific mutation analyses of the thioredoxin domain active site of NTRC in the green alga Chlamydomonas reinhardtii to show that NTRC mediates cold tolerance in a redox-dependent manner. By means of coimmunoprecipitation and mass spectrometry, a redox- and cold-dependent binding of the Calvin–Benson Cycle Protein 12 (CP12) to NTRC was identified. NTRC was subsequently demonstrated to directly reduce CP12 of C. reinhardtii as well as that of the vascular plant Arabidopsis thaliana in vitro. As a scaffold protein, CP12 joins the Calvin–Benson cycle enzymes phosphoribulokinase (PRK) and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) to form an autoinhibitory supracomplex. Using size-exclusion chromatography, NTRC from both organisms was shown to control the integrity of this complex in vitro and thereby PRK and GAPDH activities in the cold. Thus, NTRC apparently reduces CP12, hence triggering the dissociation of the PRK/CP12/GAPDH complex in the cold. Like the ntrc::aphVIII mutant, CRISPR-based cp12::emx1 mutants also exhibited a redox-dependent cold phenotype. In addition, CP12 deletion resulted in robust decreases in both PRK and GAPDH protein levels implying a protein protection effect of CP12. Both CP12 functions are critical for preparing a repertoire of enzymes for rapid activation in response to environmental changes. This provides a crucial mechanism for cold acclimation.

54 ENVIRONMENTAL SCIENCES↗

A reference tissue atlas for the human kidney

Kidney Precision Medicine Project (KPMP) is building a spatially specified human kidney tissue atlas in health and disease with single-cell resolution. Here, we describe the construction of an integrated reference map of cells, pathways, and genes using unaffected regions of nephrectomy tissues and undiseased human biopsies from 56 adult subjects. We use single-cell/nucleus transcriptomics, subsegmental laser microdissection transcriptomics and proteomics, near-single-cell proteomics, 3D and CODEX imaging, and spatial metabolomics to hierarchically identify genes, pathways, and cells. Integrated data from these different technologies coherently identify cell types/subtypes within different nephron segments and the interstitium. These profiles describe cell-level functional organization of the kidney following its physiological functions and link cell subtypes to genes, proteins, metabolites, and pathways. They further show that messenger RNA levels along the nephron are congruent with the subsegmental physiological activity. This reference atlas provides a framework for the classification of kidney disease when multiple molecular mechanisms underlie convergent clinical phenotypes.

59 BASIC BIOLOGICAL SCIENCES↗

Predicting variable gene content in Escherichia coli using conserved genes

Having the ability to predict the protein-encoding gene content of an incomplete genome or metagenome-assembled genome is important for a variety of bioinformatic tasks. In this study, as a proof of concept, we built machine learning classifiers for predicting variable gene content in Escherichia coli genomes using only the nucleotide k-mers from a set of 100 conserved genes as features. Protein families were used to define orthologs, and a single classifier was built for predicting the presence or absence of each protein family occurring in 10%–90% of all E. coli genomes. The resulting set of 3,259 extreme gradient boosting classifiers had a per-genome average macro F1 score of 0.944 [0.943–0.945, 95% CI]. We show that the F1 scores are stable across multi-locus sequence types and that the trend can be recapitulated by sampling a smaller number of core genes or diverse input genomes. Surprisingly, the presence or absence of poorly annotated proteins, including “hypothetical proteins” was accurately predicted (F1 = 0.902 [0.898–0.906, 95% CI]). Models for proteins with horizontal gene transfer-related functions had slightly lower F1 scores but were still accurate (F1s = 0.895, 0.872, 0.824, and 0.841 for transposon, phage, plasmid, and antimicrobial resistance-related functions, respectively). Finally, using a holdout set of 419 diverse E. coli genomes that were isolated from freshwater environmental sources, we observed an average per-genome F1 score of 0.880 [0.876–0.883, 95% CI], demonstrating the extensibility of the models. Overall, this study provides a framework for predicting variable gene content using a limited amount of input sequence data.

59 BASIC BIOLOGICAL SCIENCES↗

Exosomes From Induced Pluripotent Stem Cell–Derived Cardiomyocytes Promote Autophagy for Myocardial Repair

Background. Induced pluripotent stem cells and their differentiated cardiomyocytes (iCMs) have tremendous potential as patient-specific therapy for ischemic cardiomyopathy following myocardial infarctions, but difficulties in viable transplantation limit clinical translation. Exosomes secreted from iCMs (iCM-Ex) can be robustly collected in vitro and injected in lieu of live iCMs as a cell-free therapy for myocardial infarction. Methods and Results. iCM-Ex were precipitated from iCM supernatant and characterized by protein marker expression, nanoparticle tracking analysis, and functionalized nanogold transmission electron microscopy. iCM-Ex were then used in in vitro and in vivo models of ischemic injuries. Cardiac function in vivo was evaluated by left ventricular ejection fraction and myocardial viability measurements by magnetic resonance imaging. Cardioprotective mechanisms were studied by JC-1 (tetraethylbenzimidazolylcarbocyanine iodide) assay, immunohistochemistry, quantitative real-time polymerase chain reaction, transmission electron microscopy, and immunoblotting. iCM-Ex measured ≈140 nm and expressed CD63 and CD9. iCM and iCM-Ex microRNA profiles had significant overlap, indicating that exosomal content was reflective of the parent cell. Mice treated with iCM-Ex demonstrated significant cardiac improvement post–myocardial infarction, with significantly reduced apoptosis and fibrosis. In vitro iCM apoptosis was significantly reduced by hypoxia and exosome biogenesis inhibition and restored by treatment with iCM-Ex or rapamycin. Autophagosome production and autophagy flux was upregulated in iCM-Ex groups in vivo and in vitro. Conclusions. iCM-Ex improve post–myocardial infarction cardiac function by regulating autophagy in hypoxic cardiomyoytes, enabling a cell-free, patient-specific therapy for ischemic cardiomyopathy.

60 APPLIED LIFE SCIENCES↗

Multimodal Approaches for Leveraging Domain Knowledge with State-of-the-Art Machine Learning to Engineer Biocatalysts

This grant aimed to accelerate the development of specialized enzymes—biological catalysts essential for sustainable manufacturing and medicine—by integrating traditional laboratory evolution with cutting-edge artificial intelligence. To achieve this, we developed a suite of high-throughput sequencing tools and a centralized database to bridge the gap between a protein’s genetic "code" and its physical function. By training machine learning models on large datasets, we also demonstrated the ability to move beyond slow, trial-and-error testing to a "generative" approach, where AI can independently design new, versatile enzymes like tryptophan synthases. Ultimately, these findings demonstrate that combining laboratory data with computer-guided design enables the engineering of highly efficient biological tools with unprecedented speed and precision.

59 BASIC BIOLOGICAL SCIENCES↗