Conformational Activation Promotes CRISPR-Cas12a Catalysis and Resetting of the Endonuclease Activity.

Cas12a, also known as Cpf1, is a type V-A CRISPR-Cas RNA-guided endonuclease that is used for genome editing based on its ability to generate specific dsDNA breaks. Here, we show cryo-EM structures of intermediates of the cleavage reaction, thus visualizing three protein regions that sense the crRNA-DNA hybrid assembly triggering the catalytic activation of Cas12a. Single-molecule FRET provides the thermodynamics and kinetics of the conformational activation leading to phosphodiester bond hydrolysis. These findings illustrate why Cas12a cuts its target DNA and unleashes unspecific cleavage activity, degrading ssDNA molecules after activation. In addition, we show that other crRNAs are able to displace the R-loop inside the protein after target DNA cleavage, terminating indiscriminate ssDNA degradation. We propose a model whereby the conformational activation of the enzyme results in indiscriminate ssDNA cleavage. The displacement of the R-loop by a new crRNA molecule will reset Cas12a specificity, targeting new DNAs.

A systematic analysis of regression models for protein engineering.

To optimize proteins for particular traits holds great promise for industrial and pharmaceutical purposes. Machine Learning is increasingly applied in this field to predict properties of proteins, thereby guiding the experimental optimization process. A natural question is: How much progress are we making with such predictions, and how important is the choice of regressor and representation? In this paper, we demonstrate that different assessment criteria for regressor performance can lead to dramatically different conclusions, depending on the choice of metric, and how one defines generalization. We highlight the fundamental issues of sample bias in typical regression scenarios and how this can lead to misleading conclusions about regressor performance. Finally, we make the case for the importance of calibrated uncertainty in this domain.

Single-particle diffusional fingerprinting: A machine-learning framework for quantitative analysis of heterogeneous diffusion.

Single-particle tracking (SPT) is a key tool for quantitative analysis of dynamic biological processes and has provided unprecedented insights into a wide range of systems such as receptor localization, enzyme propulsion, bacteria motility, and drug nanocarrier delivery. The inherently complex diffusion in such biological systems can vary drastically both in time and across systems, consequently imposing considerable analytical challenges, and currently requires an a priori knowledge of the system. Here we introduce a method for SPT data analysis, processing, and classification, which we term "diffusional fingerprinting." This method allows for dissecting the features that underlie diffusional behavior and establishing molecular identity, regardless of the underlying diffusion type. The method operates by isolating 17 descriptive features for each observed motion trajectory and generating a diffusional map of all features for each type of particle. Precise classification of the diffusing particle identity is then obtained by training a simple logistic regression model. A linear discriminant analysis generates a feature ranking that outputs the main differences among diffusional features, providing key mechanistic insights. Fingerprinting operates by both training on and predicting experimental data, without the need for pretraining on simulated data. We found this approach to work across a wide range of simulated and experimentally diverse systems, such as tracked lipases on fat substrates, transcription factors diffusing in cells, and nanoparticles diffusing in mucus. This flexibility ultimately supports diffusional fingerprinting's utility as a universal paradigm for SPT diffusional analysis and prediction.

Carbohydrate-Derived Metal-Chelator-Triggered Lipids for Liposomal Drug Delivery.

Liposomes are versatile three-dimensional, biomaterial-based frameworks that can spatially enclose a variety of organic and inorganic biomaterials for advanced targeted-delivery applications. Implementation of external-stimuli-controlled release of their cargo will significantly augment their wide application for liposomal drug delivery. This paper presents the synthesis of a carbohydrate-derived lipid, capable of changing its conformation depending on the presence of Zn2+ : an active state in the presence of Zn2+ ions and back to an inactive state in the absence of Zn2+ or when exposed to Na2 EDTA, a metal chelator with high affinity for Zn2+ ions. This is the first report of a lipid triggered by the presence of a metal chelator. Total internal reflection fluorescence microscopy and a single-liposome study showed that it indeed was possible for the lipid to be incorporated into the bilayer of stable liposomes that remained leakage-free for the fluorescent cargo of the liposomes. On addition of EDTA to the liposomes, their fluorescent cargo could be released as a result of the membrane-incorporated lipids undergoing a conformational change.

Label-Free Fluorescence Quantification of Hydrolytic Enzyme Activity on Native Substrates Reveals How Lipase Function Depends on Membrane Curvature.

Lipases are important hydrolytic enzymes used in a spectrum of technological applications, such as the pharmaceutical and detergent industries. Because of their versatile nature and ability to accept a broad range of substrates, they have been extensively used for biotechnological and industrial applications. Current assays to measure lipase activity primarily rely on low-sensitivity measurements of pH variations or visible changes of material properties, like hydration, and often require high amounts of proteins. Fluorescent readouts, on the other hand, offer high contrast and even single-molecule sensitivity, albeit they are reliant on fluorogenic substrates that structurally resemble the native ones. Here we present a method that combines the highly sensitive readout of fluorescent techniques while reporting enzymatic lipase function on native substrates. The method relies on embedding the environmentally sensitive fluorescent dye pHrodo and native substrates into the bilayer of liposomes. The charged products of the enzymatic hydrolysis alter the local membrane environment and thus the fluorescence intensity of pHrodo. The fluorescence can be accurately quantified and directly assigned to product formation and thus enzymatic activity. We illustrated the capacity of the assay to report the function of diverse lipases and phospholipases both in a microplate setup and at the single-particle level on individual nanoscale liposomes using total internal reflection fluorescence (TIRF). The parallelized sensitive readout of microscopy combined with the inherent polydispersity in sizes of liposomes allowed us to screen the effect of membrane curvature on lipase function and identify how mutations in the lid region control the membrane curvature-dependent activity. We anticipate this methodology to be applicable for sensitive activity readouts for a spectrum of enzymes where the product of the enzymatic reaction is charged.

Membrane curvature regulates ligand-specific membrane sorting of GPCRs in living cells.

The targeted spatial organization (sorting) of Gprotein-coupled receptors (GPCRs) is essential for their biological function and often takes place in highly curved membrane compartments such as filopodia, endocytic pits, trafficking vesicles or endosome tubules. However, the influence of geometrical membrane curvature on GPCR sorting remains unknown. Here we used fluorescence imaging to establish a quantitative correlation between membrane curvature and sorting of three prototypic class A GPCRs (the neuropeptide Y receptor Y2, the ß1 adrenergic receptor and the ß2 adrenergic receptor) in living cells. Fitting of a thermodynamic model to the data enabled us to quantify how sorting is mediated by an energetic drive to match receptor shape and membrane curvature. Curvature-dependent sorting was regulated by ligands in a specific manner. We anticipate that this curvature-dependent biomechanical coupling mechanism contributes to the sorting, trafficking and function of transmembrane proteins in general.

Half-Life Extending Modifications of Peptide YY3-36 Direct Receptor-Mediated Internalization.

Peptide YY3-36 (PYY3-36) is an endogenous ligand of the neuropeptide Y2 receptor (Y2R), on which it acts to reduce food intake. Chemically modified PYY3-36 analogues with extended half-lives are potential therapeutics for the treatment of obesity. Here we show that the common half-life extending strategies PEGylation and lipidation not only control PYY3-36's pharmacokinetics but also affect central aspects of its pharmacodynamics. PEGylation of PYY3-36 inhibited endocytosis by increasing receptor dissociation rates (koff), which reduced arrestin-3 (Arr3) activity. This is the first link between Arr3 recruitment and Y2R residence time. C16-lipidation of PYY3-36 had a negligible impact on Y2R signaling, binding, and endocytosis. In contrast, C18acid-lipidation minimized endocytosis, which indicated a decreased internalization through non-arrestin-related mechanisms. We propose a temporal model that connects the properties and position of the half-life extender with receptor Gi versus Arr3 signaling bias. We believe that this will be important for future design of peptide therapeutics.

Membrane Curvature and Lipid Composition Synergize To Regulate N-Ras Anchor Recruitment.

Proteins anchored to membranes through covalently linked fatty acids and/or isoprenoid groups play crucial roles in all forms of life. Sorting and trafficking of lipidated proteins has traditionally been discussed in the context of partitioning to membrane domains of different lipid composition. We recently showed that membrane shape/curvature can in itself mediate the recruitment of lipidated proteins. However, exactly how membrane curvature and composition synergize remains largely unexplored. Here we investigated how three critical structural parameters of lipids, namely acyl chain saturation, headgroup size, and acyl chain length, modulate the capacity of membrane curvature to recruit lipidated proteins. As a model system we used the lipidated minimal membrane anchor of the GTPase, N-Ras (tN-Ras). Our data revealed complex synergistic effects, whereby tN-Ras binding was higher on planar DOPC than POPC membranes, but inversely higher on curved POPC than DOPC membranes. This variation in the binding to both planar and curved membranes leads to a net increase in the recruitment by membrane curvature of tN-Ras when reducing the acyl chain saturation state. Additionally, we found increased recruitment by membrane curvature of tN-Ras when substituting PC for PE, and when decreasing acyl chain length from 14 to 12 carbons (DMPC versus DLPC). However, these variations in recruitment ability had different origins, with the headgroup size primarily influencing tN-Ras binding to planar membranes whereas the change in acyl chain length primarily affected binding to curved membranes. Molecular field theory calculations recapitulated these findings and revealed lateral pressure as an underlying biophysical mechanism dictating how curvature and composition synergize to modulate recruitment of lipidated proteins. Our findings suggest that the different compositions of cellular compartments could modulate the potency of membrane curvature to recruit lipidated proteins and thereby synergistically regulate the trafficking and sorting of lipidated proteins.

Effects of membrane curvature and pH on proton pumping activity of single cytochrome bo3 enzymes.

The molecular mechanism of proton pumping by heme-copper oxidases (HCO) has intrigued the scientific community since it was first proposed. We have recently reported a novel technology that enables the continuous characterisation of proton transport activity of a HCO and ubiquinol oxidase from Escherichia coli, cytochrome bo3, for hundreds of seconds on the single enzyme level (Li et al. J Am Chem Soc 137 (2015) 16055-16063). Here, we have extended these studies by additional experiments and analyses of the proton transfer rate as a function of proteoliposome size and pH at the N- and P-side of single HCOs. Proton transport activity of cytochrome bo3 was found to decrease with increased curvature of the membrane. Furthermore, proton uptake at the N-side (proton entrance) was insensitive to pH between pH6.4-8.4, while proton release at the P-side had an optimum pH of ~7.4, suggesting that the pH optimum is related to proton release from the proton exit site. Our previous single-enzyme experiments identified rare, long-lived conformation states of cytochrome bo3 where protons leak back under turn-over conditions. Here, we analyzed and found that ~23% of cytochrome bo3 proteoliposomes show ΔpH half-lives below 50s after stopping turnover, while only ~5% of the proteoliposomes containing a non-pumping mutant, E286C cytochrome bo3 exhibit such fast decays. These single-enzyme results confirm our model in which HCO exhibit heterogeneous pumping rates and can adopt rare leak states in which protons are able to rapidly flow back.

Membrane curvature enables N-Ras lipid anchor sorting to liquid-ordered membrane phases.

Trafficking and sorting of membrane-anchored Ras GTPases are regulated by partitioning between distinct membrane domains. Here, in vitro experiments and microscopic molecular theory reveal membrane curvature as a new modulator of N-Ras lipid anchor and palmitoyl chain partitioning. Membrane curvature was essential for enrichment in raft-like liquid-ordered phases; enrichment was driven by relief of lateral pressure upon anchor insertion and most likely affects the localization of lipidated proteins in general.

Single Enzyme Experiments Reveal a Long-Lifetime Proton Leak State in a Heme-Copper Oxidase.

Heme-copper oxidases (HCOs) are key enzymes in prokaryotes and eukaryotes for energy production during aerobic respiration. They catalyze the reduction of the terminal electron acceptor, oxygen, and utilize the Gibbs free energy to transport protons across a membrane to generate a proton (ΔpH) and electrochemical gradient termed proton motive force (PMF), which provides the driving force for the adenosine triphosphate (ATP) synthesis. Excessive PMF is known to limit the turnover of HCOs, but the molecular mechanism of this regulatory feedback remains relatively unexplored. Here we present a single-enzyme study that reveals that cytochrome bo3 from Escherichia coli, an HCO closely homologous to Complex IV in human mitochondria, can enter a rare, long-lifetime leak state during which proton flow is reversed. The probability of entering the leak state is increased at higher ΔpH. By rapidly dissipating the PMF, we propose that this leak state may enable cytochrome bo3, and possibly other HCOs, to maintain a suitable ΔpH under extreme redox conditions.

Shedding light on protein folding, structural and functional dynamics by single molecule studies.

The advent of advanced single molecule measurements unveiled a great wealth of dynamic information revolutionizing our understanding of protein dynamics and behavior in ways unattainable by conventional bulk assays. Equipped with the ability to record distribution of behaviors rather than the mean property of a population, single molecule measurements offer observation and quantification of the abundance, lifetime and function of multiple protein states. They also permit the direct observation of the transient and rarely populated intermediates in the energy landscape that are typically averaged out in non-synchronized ensemble measurements. Single molecule studies have thus provided novel insights about how the dynamic sampling of the free energy landscape dictates all aspects of protein behavior; from its folding to function. Here we will survey some of the state of the art contributions in deciphering mechanisms that underlie protein folding, structural and functional dynamics by single molecule fluorescence microscopy techniques. We will discuss a few selected examples highlighting the power of the emerging techniques and finally discuss the future improvements and directions.

Everything, everywhere, almost at once.

A new platform that can follow the movement of individual proteins inside millions of cells in a single day will help contribute to existing knowledge of cell biology and identify new therapeutics.

SEMORE: SEgmentation and MORphological fingErprinting by machine learning automates super-resolution data analysis.

The morphology of protein assemblies impacts their behaviour and contributes to beneficial and aberrant cellular responses. While single-molecule localization microscopy provides the required spatial resolution to investigate these assemblies, the lack of universal robust analytical tools to extract and quantify underlying structures limits this powerful technique. Here we present SEMORE, a semi-automatic machine learning framework for universal, system- and input-dependent, analysis of super-resolution data. SEMORE implements a multi-layered density-based clustering module to dissect biological assemblies and a morphology fingerprinting module for quantification by multiple geometric and kinetics-based descriptors. We demonstrate SEMORE on simulations and diverse raw super-resolution data: time-resolved insulin aggregates, and published data of dSTORM imaging of nuclear pore complexes, fibroblast growth receptor 1, sptPALM of Syntaxin 1a and dynamic live-cell PALM of ryanodine receptors. SEMORE extracts and quantifies all protein assemblies, their temporal morphology evolution and provides quantitative insights, e.g. classification of heterogeneous insulin aggregation pathways and NPC geometry in minutes. SEMORE is a general analysis platform for super-resolution data, and being a time-aware framework can also support the rise of 4D super-resolution data.

Constitutive Endolysosomal Perforation in Neurons allows Induction of α-Synuclein Aggregation by Internalized Pre-Formed Fibrils.

The endocytic pathway is both an essential route of molecular uptake in cells and a potential entry point for pathology-inducing cargo. The cell-to-cell spread of cytotoxic aggregates, such as those of α-synuclein (α-syn) in Parkinson's Disease (PD), exemplifies this duality. Here we used a human iPSC-derived induced neuronal model (iNs) prone to death mediated by aggregation in late endosomes and lysosomes of endogenous α-syn, seeded by internalized pre-formed fibrils of α-syn (PFFs). This PFF-mediated death was not observed with parental iPSCs or other non-neuronal cells. Using live-cell optical microscopy to visualize the read out of biosensors reporting endo-lysosome wounding, we discovered that up to about 10% of late endosomes and lysosomes in iNs exhibited spontaneous constitutive perforations, regardless of the presence of internalized PFFs. This wounding, absent in parental iPSCs and non-neuronal cells, corresponded to partial damage by nanopores in the limiting membranes of a subset of endolysosomes directly observed by volumetric focused ion beam scanning electron microscopy (FIB-SEM) in iNs and in CA1 pyramidal neurons from mouse brain, and not found in iPSCs or in other non-neuronal cells in culture or in mouse liver and skin. We suggest that the compromised limiting membranes in iNs and neurons in general are the primary conduit for cytosolic α-syn to access PFFs entrapped within endo-lysosomal lumens, initiating PFF-mediated α-syn aggregation. Significantly, eradicating the intrinsic endolysosomal perforations in iNs by inhibiting the endosomal Phosphatidylinositol-3-Phosphate/Phosphatidylinositol 5-Kinase (PIKfyve kinase) using Apilimod or Vacuolin-1 markedly reduced PFF-induced α-syn aggregation, despite PFFs continuing to enter the endolysosomal compartment. Crucially, this intervention also diminished iN death associated with PFF incubation. Our results reveal the surprising presence of intrinsically perforated endo-lysosomes in neurons, underscoring their crucial early involvement in the genesis of toxic α-syn aggregates induced by internalized PFFs. This discovery offers a basis for employing PIKfyve kinase inhibition as a potential therapeutic strategy to counteract synucleinopathies.

Defect-Engineered Metal-Organic Frameworks as Nanocarriers for Pharmacotherapy: Insights into Intracellular Dynamics at The Single Particle Level.

Nanoscale Metal-Organic Frameworks (nanoMOFs) are widely implemented in a host of assays involving drug delivery, biosensing catalysis, and bioimaging. However, the cell pathways and cell fate remain poorly understood. Here, we have synthesized a new fluorescent nanoMOF integrating ATTO 655 into surface defects of colloidal UiO-66, allowing us to track the spatiotemporal localization of Single nanoMOF in live cells. DFT reveals the stronger binding of ATTO 655 to the Zr6 cluster nodes compared with phosphate and Alendronate Sodium. Parallelized tracking of the spatiotemporal localization of thousands of nanoMOFs and analysis using machine learning platforms revealed whether nanoMOFs remain outside as well as their cellular internalization pathways. To quantitatively assess their colocalization with endo/lysosomal compartments, we developed a colocalization proxy approach relying on the nanoMOF detection of particles in one channel to the signal in the corresponding endo/lysosomal compartments channel, considering signal versus local background intensity ratio and signal-to-noise ratio. This strategy mitigates colocalization value inflation from high or low signal expression in endo/lysosomal compartments. The results accurately measure the nanoMOFs' colocalization from early to late endosomes and lysosomes and emphasize the importance of understanding their intracellular dynamics based on single-particle tracking for optimal and safe drug delivery. This article is protected by copyright. All rights reserved.

Probing Activation and Conformational Dynamics of the Vesicle-Reconstituted ß2 Adrenergic Receptor at the Single-Molecule Level.

G-protein-coupled receptors (GPCRs) are structurally flexible membrane proteins that mediate a host of physiological responses to extracellular ligands like hormones and neurotransmitters. Fine features of their dynamic structural behavior are hypothesized to encode the functional plasticity seen in GPCR activity, where ligands with different efficacies can direct the same receptor toward different signaling phenotypes. Although the number of GPCR crystal structures is increasing, the receptors are characterized by complex and poorly understood conformational landscapes. Therefore, we employed a fluorescence microscopy assay to monitor conformational dynamics of single ß2 adrenergic receptors (ß2ARs). To increase the biological relevance of our findings, we decided not to reconstitute the receptor in detergent micelles but rather lipid membranes as proteoliposomes. The conformational dynamics were monitored by changes in the intensity of an environmentally sensitive boron-dipyrromethene (BODIPY 493/503) fluorophore conjugated to an endogenous cysteine (located at the cytoplasmic end of the sixth transmembrane helix of the receptor). Using total internal reflection fluorescence microscopy (TIRFM) and a single small unilamellar liposome assay that we previously developed, we followed the real-time dynamic properties of hundreds of single ß2ARs reconstituted in a native-like environment─lipid membranes. Our results showed that ß2AR-BODIPY fluctuates between several states of different intensity on a time scale of seconds, compared to BODIPY-lipid conjugates that show almost entirely stable fluorescence emission in the absence and presence of the full agonist BI-167107. Agonist stimulation changes the ß2AR dynamics, increasing the population of states with higher intensities and prolonging their durations, consistent with bulk experiments. The transition density plot demonstrates that ß2AR-BODIPY, in the absence of the full agonist, interconverts between states of low and moderate intensity, while the full agonist renders transitions between moderate and high-intensity states more probable. This redistribution is consistent with a mechanism of conformational selection and is a promising first step toward characterizing the conformational dynamics of GPCRs embedded in a lipid bilayer.

Deconvoluting the Effect of Cell-Penetrating Peptides for Enhanced and Controlled Insertion of Large-Scale DNA Nanopores.

DNA nanopores have emerged as powerful tools for molecular sensing, but the efficient insertion of large DNA nanopores into lipid membranes remains challenging. In this study, we investigate the potential of cell-penetrating peptides (CPPs), specifically SynB1 and GALA, to enhance the insertion efficiency of large DNA nanopores. We constructed SynB1- or GALA-functionalized DNA nanopores with an 11 nm inner diameter and visualized and quantified their membrane insertion using a TIRF microscopy-based single-liposome assay. The results demonstrated that incorporating an increasing number of SynB1 or GALA peptides into the DNA nanopore significantly enhanced the membrane perforation. Kinetic analysis revealed that the DNA nanopore scaffold played a role in prearranging the CPPs, which facilitated membrane interaction and pore formation. Notably, the use of pH-responsive GALA peptides allowed highly efficient and pH-controlled insertion of large DNA pores. Furthermore, single-channel recording elucidated that the insertion process of single GALA-modified nanopores into planar lipid bilayers was dynamic, likely forming transient large toroidal pores. Overall, our study highlights the potential of CPPs as insertion enhancers for DNA nanopores, which opens avenues for improved molecule sensing and the controlled release of cargo molecules.

Deep learning assisted single particle tracking for automated correlation between diffusion and function.

Sub-cellular diffusion in living systems reflects cellular processes and interactions. Recent advances in optical microscopy allow the tracking of this nanoscale diffusion of individual objects with an unprecedented level of precision. However, the agnostic and automated extraction of functional information from the diffusion of molecules and organelles within the sub-cellular environment, is labor-intensive and poses a significant challenge. Here we introduce DeepSPT, a deep learning framework to interpret the diffusional 2D or 3D temporal behavior of objects in a rapid and efficient manner, agnostically. Demonstrating its versatility, we have applied DeepSPT to automated mapping of the early events of viral infections, identifying distinct types of endosomal organelles, and clathrin-coated pits and vesicles with up to 95% accuracy and within seconds instead of weeks. The fact that DeepSPT effectively extracts biological information from diffusion alone illustrates that besides structure, motion encodes function at the molecular and subcellular level.

Neonatal intestinal mucus barrier changes in response to maturity, inflammation, and sodium decanoate supplementation.

The integrity of the intestinal mucus barrier is crucial for human health, as it serves as the body's first line of defense against pathogens. However, postnatal development of the mucus barrier and interactions between maturity and its ability to adapt to external challenges in neonatal infants remain unclear. In this study, we unveil a distinct developmental trajectory of the mucus barrier in preterm piglets, leading to enhanced mucus microstructure and reduced mucus diffusivity compared to term piglets. Notably, we found that necrotizing enterocolitis (NEC) is associated with increased mucus diffusivity of our large pathogen model compound, establishing a direct link between the NEC condition and the mucus barrier. Furthermore, we observed that addition of sodium decanoate had varying effects on mucus diffusivity depending on maturity and health state of the piglets. These findings demonstrate that regulatory mechanisms governing the neonatal mucosal barrier are highly complex and are influenced by age, maturity, and health conditions. Therefore, our results highlight the need for specific therapeutic strategies tailored to each neonatal period to ensure optimal gut health.