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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, a new fluorescent nanoMOF integrating ATTO 655 into surface defects of colloidal UiO-66 is synthesized, allowing to track the spatiotemporal localization of Single nanoMOF in live cells. Density functional theory reveals the stronger binding of ATTO 655 to the Zr 6 cluster nodes compared with phosphate and Alendronate Sodium. Parallelized tracking of the spatiotemporal localization of thousands of nanoMOFs and analysis using machine learning platforms reveals whether nanoMOFs remain outside as well as their cellular internalization pathways. To quantitatively assess their colocalization with endo/lysosomal compartments, 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 is developed. 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., (© 2024 The Author(s). Advanced Materials published by Wiley‐VCH GmbH.)

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., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Michael et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

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.

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., (© 2024. The Author(s).)

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., (© 2024. The Author(s).)

The function of most lipases is controlled by the lid, which undergoes conformational changes at a water-lipid interface to expose the active site, thus activating catalysis. Understanding how lid mutations affect lipases' function is important for designing improved variants. Lipases' function has been found to correlate with their diffusion on the substrate surface. Here, we used single-particle tracking (SPT), a powerful tool for deciphering enzymes' diffusional behavior, to study Thermomyces lanuginosus lipase (TLL) variants with different lid structures in a laundry-like application condition. Thousands of parallelized recorded trajectories and hidden Markov modeling (HMM) analysis allowed us to extract three interconverting diffusional states and quantify their abundance, microscopic transition rates, and the energy barriers for sampling them. Combining those findings with ensemble measurements, we determined that the overall activity variation in the application condition is dependent on surface binding and lipase mobility when bound. Specifically, the L4 variant with a TLL-like lid and wild-type (WT) TLL displayed similar ensemble activity, but WT bound stronger to the surface than L4, while L4 had a higher diffusion coefficient and thus activity when bound to the surface. These mechanistic elements can only be de-convoluted by our combined assays. Our findings offer fresh perspectives on the development of the next iteration of enzyme-based detergent.

Macromolecules organize themselves into discrete membrane-less compartments. Mounting evidence has suggested that nucleosomes as well as DNA itself can undergo clustering or condensation to regulate genomic activity. Current in vitro condensation studies provide insight into the physical properties of condensates, such as surface tension and diffusion. However, methods that provide the resolution needed for complex kinetic studies of multicomponent condensation are desired. Here, we use a supported lipid bilayer platform in tandem with total internal reflection microscopy to observe the two-dimensional movement of DNA and nucleosomes at the single-molecule resolution. This dimensional reduction from three-dimensional studies allows us to observe the initial condensation events and dissolution of these early condensates in the presence of physiological condensing agents. Using polyamines, we observed that the initial condensation happens on a time scale of minutes while dissolution occurs within seconds upon charge inversion. Polyamine valency, DNA length, and GC content affect the threshold polyamine concentration for condensation. Protein-based nucleosome condensing agents, HP1α and Ki-67, have much lower threshold concentrations for condensation than charge-based condensing agents, with Ki-67 being the most effective, requiring as low as 100 pM for nucleosome condensation. In addition, we did not observe condensate dissolution even at the highest concentrations of HP1α and Ki-67 tested. We also introduce a two-color imaging scheme where nucleosomes of high density labeled in one color are used to demarcate condensate boundaries and identical nucleosomes of another color at low density can be tracked relative to the boundaries after Ki-67-mediated condensation. Our platform should enable the ultimate resolution of single molecules in condensation dynamics studies of chromatin components under defined physicochemical conditions.

Insulin formulations with diverse oligomerization states are the hallmark of interventions for the treatment of diabetes. Here using single-molecule recordings we firstly reveal that insulin oligomerization can operate via monomeric additions and secondly quantify the existence, abundance and kinetic characterization of diverse insulin assembly and disassembly pathways involving addition of monomeric, dimeric or tetrameric insulin species. We propose and experimentally validate a model where the insulin self-assembly pathway is rerouted, favoring monomeric or oligomeric assembly, by solution concentration, additives and formulations. Combining our practically complete kinetic characterization with rate simulations, we calculate the abundance of each oligomeric species from nM to mM offering mechanistic insights and the relative abundance of all oligomeric forms at concentrations relevant both for secreted and administrated insulin. These reveal a high abundance of all oligomers and a significant fraction of hexamer resulting in practically halved bioavailable monomer concentration. In addition to providing fundamental new insights, the results and toolbox presented here can be universally applied, contributing to the development of optimal insulin formulations and the deciphering of oligomerization mechanisms for additional proteins., (© 2023. The Author(s).)

Amyloid aggregation is associated with many diseases and may also occur in therapeutic protein formulations. Addition of co-solutes is a key strategy to modulate the stability of proteins in pharmaceutical formulations and select inhibitors for drug design in the context of diseases. However, the heterogeneous nature of this multicomponent system in terms of structures and mechanisms poses a number of challenges for the analysis of the chemical reaction. Using insulin as protein system and polysorbate 80 as co-solute, we combine a spatially resolved fluorescence approach with single molecule microscopy and machine learning methods to kinetically disentangle the different contributions from multiple species within a single aggregation experiment. We link the presence of interfaces to the degree of heterogeneity of the aggregation kinetics and retrieve the rate constants and underlying mechanisms for single aggregation events. Importantly, we report that the mechanism of inhibition of the self-assembly process depends on the details of the growth pathways of otherwise macroscopically identical species. This information can only be accessed by the analysis of single aggregate events, suggesting our method as a general tool for a comprehensive physicochemical characterization of self-assembly reactions.

The immunogenicity risk of therapeutic protein aggregates has been extensively investigated over the past decades. While it is established that not all aggregates are equally immunogenic, the specific aggregate characteristics, which are most likely to induce an immune response, remain ambiguous. The aim of this study was to perform comprehensive in vitro and in vivo immunogenicity assessment of human insulin aggregates varying in size, structure and chemical modifications, while keeping other morphological characteristics constant. We found that flexible aggregates with highly altered secondary structure were most immunogenic in all setups, while compact aggregates with native-like structure were found to be immunogenic primarily in vivo. Moreover, sub-visible (1-100 µm) aggregates were found to be more immunogenic than sub-micron (0.1-1 µm) aggregates, while chemical modifications (deamidation, ethylation and covalent dimers) were not found to have any measurable impact on immunogenicity. The findings highlight the importance of utilizing aggregates varying in few characteristics for assessment of immunogenicity risk of specific morphological features and may provide a workflow for reliable particle analysis in biotherapeutics., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Vito Foderà reports financial support was provided by Novo Nordisk A/S., (Copyright © 2022 The Author(s). Published by Elsevier B.V. All rights reserved.)

Drug delivery systems (DDS) for oral delivery of peptide drugs contain excipients that facilitate and enhance absorption. However, little knowledge exists on how DDS excipients such as permeation enhancers interact with the gastrointestinal mucus barrier. This study aimed to investigate interactions of the permeation enhancer sodium 8-[(2-hydroxybenzoyl)amino]octanoate (SNAC) with ex vivo porcine intestinal mucus (PIM), ex vivo porcine gastric mucus (PGM), as well as with in vitro biosimilar mucus (BM) by profiling their physical and barrier properties upon exposure to SNAC. Bulk mucus permeability studies using the peptides cyclosporine A and vancomycin, ovalbumin as a model protein, as well as fluorescein-isothiocyanate dextrans (FDs) of different molecular weights and different surface charges were conducted in parallel to mucus retention force studies using a texture analyzer, rheological studies, cryo-scanning electron microscopy (cryo-SEM), and single particle tracking of fluorescence-labelled nanoparticles to investigate the effects of the SNAC-mucus interaction. The exposure of SNAC to PIM increased the mucus retention force, storage modulus, viscosity, increased nanoparticle confinement within PIM as well as decreased the permeation of cyclosporine A and ovalbumin through PIM. Surprisingly, the viscosity of PGM and the permeation of cyclosporine A and ovalbumin through PGM was unaffected by the presence of SNAC, thus the effect of SNAC depended on the regional site that mucus was collected from. In the absence of SNAC, the permeation of different molecular weight and differently charged FDs through PIM was comparable to that through BM. However, while bulk permeation of neither of the FDs through PIM was affected by SNAC, the presence of SNAC decreased the permeation of FD4 and increased the permeation of FD150 kDa through BM. Additionally, and in contrast to observations in PIM, nanoparticle confinement within BM remained unaffected by the presence of SNAC. In conclusion, the present study showed that SNAC altered the physical and barrier properties of PIM, but not of PGM. The effects of SNAC in PIM were not observed in the BM in vitro model. Altogether, the study highlights the need for further understanding how permeation enhancers influence the mucus barrier and illustrates that the selected mucus model for such studies should be chosen with care., Competing Interests: Declaration of Competing Interest The authors declare no conflicts of interest., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Single-molecule FRET (smFRET) is a versatile technique to study the dynamics and function of biomolecules since it makes nanoscale movements detectable as fluorescence signals. The powerful ability to infer quantitative kinetic information from smFRET data is, however, complicated by experimental limitations. Diverse analysis tools have been developed to overcome these hurdles but a systematic comparison is lacking. Here, we report the results of a blind benchmark study assessing eleven analysis tools used to infer kinetic rate constants from smFRET trajectories. We test them against simulated and experimental data containing the most prominent difficulties encountered in analyzing smFRET experiments: different noise levels, varied model complexity, non-equilibrium dynamics, and kinetic heterogeneity. Our results highlight the current strengths and limitations in inferring kinetic information from smFRET trajectories. In addition, we formulate concrete recommendations and identify key targets for future developments, aimed to advance our understanding of biomolecular dynamics through quantitative experiment-derived models., (© 2022. The Author(s).)

Protein misfolding in the form of fibrils or spherulites is involved in a spectrum of pathological abnormalities. Our current understanding of protein aggregation mechanisms has primarily relied on the use of spectrometric methods to determine the average growth rates and diffraction-limited microscopes with low temporal resolution to observe the large-scale morphologies of intermediates. We developed a REal-time kinetics via binding and Photobleaching LOcalization Microscopy (REPLOM) super-resolution method to directly observe and quantify the existence and abundance of diverse aggregate morphologies of human insulin, below the diffraction limit and extract their heterogeneous growth kinetics. Our results revealed that even the growth of microscopically identical aggregates, e.g., amyloid spherulites, may follow distinct pathways. Specifically, spherulites do not exclusively grow isotropically but, surprisingly, may also grow anisotropically, following similar pathways as reported for minerals and polymers. Combining our technique with machine learning approaches, we associated growth rates to specific morphological transitions and provided energy barriers and the energy landscape at the level of single aggregate morphology. Our unifying framework for the detection and analysis of spherulite growth can be extended to other self-assembled systems characterized by a high degree of heterogeneity, disentangling the broad spectrum of diverse morphologies at the single-molecule level., (© 2022. The Author(s).)

Reconstitution of membrane proteins into model membranes is an essential approach for their functional analysis under chemically defined conditions. Established model-membrane systems used in ensemble average measurements are limited by sample heterogeneity and insufficient knowledge of lipid and protein content at the single vesicle level, which limits quantitative analysis of vesicle properties and prevents their correlation with protein activity. Here, we describe a versatile total internal reflection fluorescence microscopy-based bleaching protocol that permits parallel analysis of multiple parameters (physical size, tightness, unilamellarity, membrane protein content, and orientation) of individual proteoliposomes prepared with fluorescently tagged membrane proteins and lipid markers. The approach makes use of commercially available fluorophores including the commonly used nitrobenzoxadiazole dye and may be applied to deduce functional molecular characteristics of many types of reconstituted fluorescently tagged membrane proteins.

The dopamine transporter facilitates dopamine reuptake from the extracellular space to terminate neurotransmission. The transporter belongs to the neurotransmitter:sodium symporter family, which includes transporters for serotonin, norepinephrine, and GABA that utilize the Na + gradient to drive the uptake of substrate. Decades ago, it was shown that the serotonin transporter also antiports K + , but investigations of K + -coupled transport in other neurotransmitter:sodium symporters have been inconclusive. Here, we show that ligand binding to the Drosophila- and human dopamine transporters are inhibited by K + , and the conformational dynamics of the Drosophila dopamine transporter in K + are divergent from the apo- and Na + -states. Furthermore, we find that K + increases dopamine uptake by the Drosophila dopamine transporter in liposomes, and visualize Na + and K + fluxes in single proteoliposomes using fluorescent ion indicators. Our results expand on the fundamentals of dopamine transport and prompt a reevaluation of the impact of K + on other transporters in this pharmacologically important family., (© 2022. The Author(s).)

Combinatorial high-throughput methodologies are central for both screening and discovery in synthetic biochemistry and biomedical sciences. They are, however, often reliant on large-scale analyses and thus limited by a long running time and excessive materials cost. We here present a single-particle combinatorial multiplexed liposome fusion mediated by DNA for parallelized multistep and non-deterministic fusion of individual subattolitre nanocontainers. We observed directly the efficient (>93%) and leakage free stochastic fusion sequences for arrays of surface-tethered target liposomes with six freely diffusing populations of cargo liposomes, each functionalized with individual lipidated single-stranded DNA and fluorescently barcoded by a distinct ratio of chromophores. The stochastic fusion resulted in a distinct permutation of fusion sequences for each autonomous nanocontainer. Real-time total internal reflection imaging allowed the direct observation of >16,000 fusions and 566 distinct fusion sequences accurately classified using machine learning. The high-density arrays of surface-tethered target nanocontainers (~42,000 containers per mm 2 ) offers entire combinatorial multiplex screens using only picograms of material., (© 2022. The Author(s), under exclusive licence to Springer Nature Limited.)

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., Competing Interests: The authors declare no competing interest., (Copyright © 2021 the Author(s). Published by PNAS.)

Lipases comprise one of the major enzyme classes in biotechnology with applications within, e.g., baking, brewing, biocatalysis, and the detergent industry. Understanding the mechanisms of lipase function and regulation is therefore important to facilitate the optimization of their function by protein engineering. Advances in single-molecule studies in model systems have provided deep mechanistic insights on lipase function, such as the existence of functional states, their dependence on regulatory cues, and their correlation to activity. However, it is unclear how these observations translate to enzyme behavior in applied settings. Here, single-molecule tracking of individual Thermomyces lanuginosus lipase (TLL) enzymes in a detergency application system allowed real-time direct observation of spatiotemporal localization, and thus diffusional behavior, of TLL enzymes on a lard substrate. Parallelized imaging of thousands of individual enzymes allowed us to observe directly the existence and quantify the abundance and interconversion kinetics between three diffusional states that we recently provided evidence to correlate with function. We observe redistribution of the enzyme's diffusional pattern at the lipid-water interface as well as variations in binding efficiency in response to surfactants and calcium, demonstrating that detergency effectors can drive the sampling of lipase functional states. Our single-molecule results combined with ensemble activity assays and enzyme surface binding efficiency readouts allowed us to deconvolute how application conditions can significantly alter protein functional dynamics and/or surface binding, both of which underpin enzyme performance. We anticipate that our results will inspire further efforts to decipher and integrate the dynamic nature of lipases, and other enzymes, in the design of new biotechnological solutions.

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 Zn 2+ : an active state in the presence of Zn 2+ ions and back to an inactive state in the absence of Zn 2+ or when exposed to Na 2 EDTA, a metal chelator with high affinity for Zn 2+ 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., (© 2021 Wiley-VCH GmbH.)

Cell-penetrating peptides (CPPs) are known to interact with cell membranes and by doing so enhance cellular interaction and subsequent cellular internalization of nanoparticles. Yet, the early events of membrane interactions are still not elucidated, which is the aim of the present work. Surface conjugation of polymeric nanoparticles with cationic CPPs of different architecture (short, long linear, and branched) influences the surface properties, especially the charge of the nanoparticles, and therefore provides the possibility of increased electrostatic interactions between nanoparticles with the cell membrane. In this study, the physicochemical properties of CPP-tagged poly(lactic- co -glycolic acid) (PLGA) nanoparticles were characterized, and nanoparticle-cell interactions were investigated in HeLa cells. With the commonly applied methods of flow cytometry as well as confocal laser scanning microscopy, low and similar levels of nanoparticle association were detected for the PLGA and CPP-tagged PLGA nanoparticles with the cell membrane. However, single particle tracking of CPP-tagged PLGA nanoparticles allowed direct observation of the interactions of individual nanoparticles with cells and consequently elucidated the impact that the CPP architecture on the nanoparticle surface can have. Interestingly, the results revealed that nanoparticles with the branched CPP architecture on the surface displayed decreased diffusion modes likely due to increased interactions with the cell membrane when compared to the other nanoparticles investigated. It is anticipated that single particle approaches like the one used here can be widely employed to reveal currently unresolved characteristics of nanoparticle-cell interaction and aid in the design of improved surface-modified nanoparticles for efficient delivery of therapeutics.

Metabolic control is mediated by the dynamic assemblies and function of multiple redox enzymes. A key element in these assemblies, the P450 oxidoreductase (POR), donates electrons and selectively activates numerous (>50 in humans and >300 in plants) cytochromes P450 (CYPs) controlling metabolism of drugs, steroids and xenobiotics in humans and natural product biosynthesis in plants. The mechanisms underlying POR-mediated CYP metabolism remain poorly understood and to date no ligand binding has been described to regulate the specificity of POR. Here, using a combination of computational modeling and functional assays, we identify ligands that dock on POR and bias its specificity towards CYP redox partners, across mammal and plant kingdom. Single molecule FRET studies reveal ligand binding to alter POR conformational sampling, which results in biased activation of metabolic cascades in whole cell assays. We propose the model of biased metabolism, a mechanism akin to biased signaling of GPCRs, where ligand binding on POR stabilizes different conformational states that are linked to distinct metabolic outcomes. Biased metabolism may allow designing pathway-specific therapeutics or personalized food suppressing undesired, disease-related, metabolic pathways.

Single-molecule FRET (smFRET) has become a mainstream technique for studying biomolecular structural dynamics. The rapid and wide adoption of smFRET experiments by an ever-increasing number of groups has generated significant progress in sample preparation, measurement procedures, data analysis, algorithms and documentation. Several labs that employ smFRET approaches have joined forces to inform the smFRET community about streamlining how to perform experiments and analyze results for obtaining quantitative information on biomolecular structure and dynamics. The recent efforts include blind tests to assess the accuracy and the precision of smFRET experiments among different labs using various procedures. These multi-lab studies have led to the development of smFRET procedures and documentation, which are important when submitting entries into the archiving system for integrative structure models, PDB-Dev. This position paper describes the current 'state of the art' from different perspectives, points to unresolved methodological issues for quantitative structural studies, provides a set of 'soft recommendations' about which an emerging consensus exists, and lists openly available resources for newcomers and seasoned practitioners. To make further progress, we strongly encourage 'open science' practices., Competing Interests: EL, AB, JH, BA, VB, SB, RB, HS, TC, TC, AD, JD, JF, RG, IG, TH, CH, GH, NH, SH, SH, TH, AI, CJ, AK, HK, TL, NL, TL, EL, EM, JM, XM, SM, DN, TP, EP, YR, NR, BS, HS, CT, RV, DL, CS, SW No competing interests declared

Single-molecule Förster Resonance energy transfer (smFRET) is an adaptable method for studying the structure and dynamics of biomolecules. The development of high throughput methodologies and the growth of commercial instrumentation have outpaced the development of rapid, standardized, and automated methodologies to objectively analyze the wealth of produced data. Here we present DeepFRET, an automated, open-source standalone solution based on deep learning, where the only crucial human intervention in transiting from raw microscope images to histograms of biomolecule behavior, is a user-adjustable quality threshold. Integrating standard features of smFRET analysis, DeepFRET consequently outputs the common kinetic information metrics. Its classification accuracy on ground truth data reached >95% outperforming human operators and commonly used threshold, only requiring ~1% of the time. Its precise and rapid operation on real data demonstrates DeepFRET's capacity to objectively quantify biomolecular dynamics and the potential to contribute to benchmarking smFRET for dynamic structural biology., Competing Interests: JT, MS, SJ, SS, BP, MM, GM, TP, NH No competing interests declared, (© 2020, Thomsen et al.)

Sophorolipids (SLs) are naturally produced glycolipids that acts as drug delivery for a spectrum of biomedical applications, including as an antibacterial antifungal and anticancer agent, where they induce apoptosis selectively in cancerous cells. Despite their utility, the mechanisms underlying their membrane interactions, and consequently cell entry, remains unknown. Here, we combined a single liposome assay to observe directly and quantify the kinetics of interaction of SL micelles with model membrane systems, and single particle studies on live cells to record their interaction with cell membranes and their cytotoxicity. Our single particle readouts revealed several repetitive docking events on individual liposomes and quantified how pH and membrane charges, which are known to vary in cancer cells, affect the docking of SL micelles on model membranes. Docking of sophorolipids micelles was found to be optimal at pH 6.5 and for membranes with -5% negatively charge lipids. Single particle studies on mammalian cells reveled a two-fold increased interaction on Hela cells as compared to HEK-293 cells. This is in line with our cell viability readouts recording an approximate two-fold increased cytotoxicity by SLs interactions for Hela cells as compared to HEK-293 cells. The combined in vitro and cell assays thus support the increased cytotoxicity of SLs on cancer cells to originate from optimal charge and pH interactions between membranes and SL assemblies. We anticipate studies combining quantitative single particle studies on model membranes and live cell may reveal hitherto unknown molecular insights on the interactions of sophorolipid and additional nanocarriers mechanism.

Biological membranes have distinct geometries that confer specific functions. However, the molecular mechanisms underlying the phenomenological geometry/function correlations remain elusive. We studied the effect of membrane geometry on the localization of membrane-bound proteins. Quantitative comparative experiments between the two most abundant cellular membrane geometries, spherical and cylindrical, revealed that geometry regulates the spatial segregation of proteins. The measured geometry-driven segregation reached 50-fold for membranes of the same mean curvature, demonstrating a crucial and hitherto unaccounted contribution by Gaussian curvature. Molecular-field theory calculations elucidated the underlying physical and molecular mechanisms. Our results reveal that distinct membrane geometries have specific physicochemical properties and thus establish a ubiquitous mechanistic foundation for unravelling the conserved correlations between biological function and membrane polymorphism., Competing Interests: The authors declare no competing financial interest., (Copyright © 2020 American Chemical Society.)

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.

Transmembrane nanostructures like ion channels and transporters perform key biological functions by controlling flow of molecules across lipid bilayers. Much work has gone into engineering artificial nanopores and applications in selective gating of molecules, label-free detection/sensing of biomolecules and DNA sequencing have shown promise. Here, we use DNA origami to create a synthetic 9 nm wide DNA nanopore, controlled by programmable, lipidated flaps and equipped with a size-selective gating system for the translocation of macromolecules. Successful assembly and insertion of the nanopore into lipid bilayers are validated by transmission electron microscopy (TEM), while selective translocation of cargo and the pore mechanosensitivity are studied using optical methods, including single-molecule, total internal reflection fluorescence (TIRF) microscopy. Size-specific cargo translocation and oligonucleotide-triggered opening of the pore are demonstrated showing that the DNA nanopore can function as a real-time detection system for external signals, offering potential for a variety of highly parallelized sensing applications.

Lipases are interfacially activated enzymes that catalyze the hydrolysis of ester bonds and constitute prime candidates for industrial and biotechnological applications ranging from detergent industry, to chiral organic synthesis. As a result, there is an incentive to understand the mechanisms underlying lipase activity at the molecular level, so as to be able to design new lipase variants with tailor-made functionalities. Our understanding of lipase function primarily relies on bulk assay averaging the behavior of a high number of enzymes masking structural dynamics and functional heterogeneities. Recent advances in single molecule techniques based on fluorogenic substrate analogues revealed the existence of lipase functional states, and furthermore so how they are remodeled by regulatory cues. Single particle studies of lipases on the other hand directly observed diffusional heterogeneities and suggested lipases to operate in two different modes. Here to decipher how mutations in the lid region controls Thermomyces lanuginosus lipase (TLL) diffusion and function we employed a Single Particle Tracking (SPT) assay to directly observe the spatiotemporal localization of TLL and rationally designed mutants on native substrate surfaces. Parallel imaging of thousands of individual TLL enzymes and HMM analysis allowed us to observe and quantify the diffusion, abundance and microscopic transition rates between three linearly interconverting diffusional states for each lipase. We proposed a model that correlate diffusion with function that allowed us to predict that lipase regulation, via mutations in lid region or product inhibition, primarily operates via biasing transitions to the active states.

Proton-pumping enzymes of electron transfer chains couple redox reactions to proton translocation across the membrane, creating a proton-motive force used for ATP production. The amphiphilic nature of membrane proteins requires particular attention to their handling, and reconstitution into the natural lipid environment is indispensable when studying membrane transport processes like proton translocation. Here, we detail a method that has been used for the investigation of the proton-pumping mechanism of membrane redox enzymes, taking cytochrome bo3 from Escherichia coli as an example. A combination of electrochemistry and fluorescence microscopy is used to control the redox state of the quinone pool and monitor pH changes in the lumen. Due to the spatial resolution of fluorescent microscopy, hundreds of liposomes can be measured simultaneously while the enzyme content can be scaled down to a single enzyme or transporter per liposome. The respective single enzyme analysis can reveal patterns in the enzyme functional dynamics that might be otherwise hidden by the behavior of the whole population. We include a description of a script for automated image analysis.

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., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Cytochrome P450 oxidoreductase (POR) is the primary electron donor in eukaryotic cytochrome P450 (CYP) containing systems. A wealth of ensemble biophysical studies of Cytochrome P450 oxidoreductase (POR) has reported a binary model of the conformational equilibrium directing its catalytic efficiency and biomolecular recognition. In this study, full length POR from the crop plant Sorghum bicolor was site-specifically labeled with Cy3 (donor) and Cy5 (acceptor) fluorophores and reconstituted in nanodiscs. Our single molecule fluorescence resonance energy transfer (smFRET) burst analyses of POR allowed the direct observation and quantification of at least three dominant conformational sub-populations, their distribution and occupancies. Moreover, the state occupancies were remodeled significantly by ionic strength and the nature of reconstitution environment, i.e. phospholipid bilayers (nanodiscs) composed of different lipid head group charges vs. detergent micelles. The existence of conformational heterogeneity in POR may mediate selective activation of multiple downstream electron acceptors and association in complexes in the ER membrane.

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., (Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.)

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 bo 3 , 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 bo 3 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 bo 3 where protons leak back under turn-over conditions. Here, we analyzed and found that ~23% of cytochrome bo 3 proteoliposomes show ΔpH half-lives below 50s after stopping turnover, while only ~5% of the proteoliposomes containing a non-pumping mutant, E286C cytochrome bo 3 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., (Copyright © 2017 Elsevier B.V. All rights reserved.)

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 β 1 adrenergic receptor and the β 2 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.

Metabolic highways may be orchestrated by the assembly of sequential enzymes into protein complexes, or metabolons, to facilitate efficient channeling of intermediates and to prevent undesired metabolic cross-talk while maintaining metabolic flexibility. Here we report the isolation of the dynamic metabolon that catalyzes the formation of the cyanogenic glucoside dhurrin, a defense compound produced in sorghum plants. The metabolon was reconstituted in liposomes, which demonstrated the importance of membrane surface charge and the presence of the glucosyltransferase for metabolic channeling. We used in planta fluorescence lifetime imaging microscopy and fluorescence correlation spectroscopy to study functional and structural characteristics of the metabolon. Understanding the regulation of biosynthetic metabolons offers opportunities to optimize synthetic biology approaches for efficient production of high-value products in heterologous hosts., (Copyright © 2016, American Association for the Advancement of Science.)

In eukaryotes, P-type adenosine triphosphatases (ATPases) generate the plasma membrane potential and drive secondary transport systems; however, despite their importance, their regulation remains poorly understood. We monitored at the single-molecule level the activity of the prototypic proton-pumping P-type ATPase Arabidopsis thaliana isoform 2 (AHA2). Our measurements, combined with a physical nonequilibrium model of vesicle acidification, revealed that pumping is stochastically interrupted by long-lived (~100 seconds) inactive or leaky states. Allosteric regulation by pH gradients modulated the switch between these states but not the pumping or leakage rates. The autoinhibitory regulatory domain of AHA2 reduced the intrinsic pumping rates but increased the dwell time in the active pumping state. We anticipate that similar functional dynamics underlie the operation and regulation of many other active transporters., (Copyright © 2016, American Association for the Advancement of Science.)

Single-molecule measurements are emerging as a powerful tool to study the individual behavior of biomolecules, revolutionizing our understanding of biological processes. Their ability to measure the distribution of behaviors, instead of the average behavior, allows the direct observation and quantification of the activity, abundance, and lifetime of multiple states and transient intermediates in the energy landscape that are typically averaged out in nonsynchronized ensemble measurements. Studying the function of membrane proteins at the single-molecule level remains a formidable challenge, and to date there is limited number of available functional assays. In this chapter, we describe in detail our recently developed methodology to reconstitute membrane proteins such as the integral membrane protein cytochrome P450 oxidoreductase on membrane systems such as Nanodiscs and study their functional dynamics by recordings at the fundamental resolution of individual catalytic turnovers using prefluorescent substrate analogues. We initially describe the methodology for reconstitution, surface immobilization, and data acquisition of individual enzyme catalytic turnovers. We then explain in detail the statistical analysis, with an emphasis on the model development, the potential pitfalls for correctly identifying the abundance, lifetime, and likelihood of sampling protein functional states. This methodology may enable studies of functional dynamics and their role in biology for a spectrum of membrane proteins., (© 2016 Elsevier Inc. All rights reserved.)

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.

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.

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.

Electron transfer between membrane spanning oxidoreductase enzymes controls vital metabolic processes. Here we studied for the first time with single molecule resolution the function of P450 oxidoreductase (POR), the canonical membrane spanning activator of all microsomal cytochrome P450 enzymes. Measurements and statistical analysis of individual catalytic turnover cycles shows POR to sample at least two major functional states. This phenotype may underlie regulatory interactions with different cytochromes P450 but to date has remained masked in bulk kinetics. To ensure that we measured the inherent behavior of POR, we reconstituted the full length POR in "native like" membrane patches, nanodiscs. Nanodisc reconstitution increased stability by ∼2-fold as compared to detergent solubilized POR and showed significantly increased activity at biologically relevant ionic strength conditions, highlighting the importance of studying POR function in a membrane environment. This assay paves the way for studying the function of additional membrane spanning oxidoreductases with single molecule resolution.

Biomolecular interactions regulate a plethora of vital cellular processes, including signal transduction, metabolism, catalysis and gene regulation. Regulation is encoded in the molecular properties of the constituent proteins; distinct conformations correspond to different functional outcomes. To describe the molecular basis of this behavior, two main mechanisms have been advanced: 'induced fit' and 'conformational selection'. Our understanding of these models relies primarily on NMR, computational studies and kinetic measurements. These techniques report the average behavior of a large ensemble of unsynchronized molecules, often masking intrinsic dynamic behavior of proteins and biologically significant transient intermediates. Single molecule measurements are emerging as a powerful tool for characterizing protein function. They offer the direct observation and quantification of the activity, abundance and lifetime of multiple states and transient intermediates in the energy landscape, that are typically averaged out in non-synchronized ensemble measurements. Here we survey new insights from single molecule studies that advance our understanding of the molecular mechanisms underlying biomolecular recognition., (Copyright © 2013 Elsevier B.V. All rights reserved.)

Nanodiscs are self-assembled ∼50-nm(2) patches of lipid bilayers stabilized by amphipathic belt proteins. We demonstrate that a well ordered dense film of nanodiscs serves for non-destructive, label-free studies of isolated membrane proteins in a native like environment using neutron reflectometry (NR). This method exceeds studies of membrane proteins in vesicle or supported lipid bilayer because membrane proteins can be selectively adsorbed with controlled orientation. As a proof of concept, the mechanism of action of the membrane-anchored cytochrome P450 reductase (POR) is studied here. This enzyme is responsible for catalyzing the transfer of electrons from NADPH to cytochrome P450s and thus is a key enzyme in the biosynthesis of numerous primary and secondary metabolites in plants. Neutron reflectometry shows a coexistence of two different POR conformations, a compact and an extended form with a thickness of 44 and 79 Å, respectively. Upon complete reduction by NADPH, the conformational equilibrium shifts toward the compact form protecting the reduced FMN cofactor from engaging in unspecific electron transfer reaction.

Allosteric regulation of enzymatic activity forms the basis for controlling a plethora of vital cellular processes. While the mechanism underlying regulation of multimeric enzymes is generally well understood and proposed to primarily operate via conformational selection, the mechanism underlying allosteric regulation of monomeric enzymes is poorly understood. Here we monitored for the first time allosteric regulation of enzymatic activity at the single molecule level. We measured single stochastic catalytic turnovers of a monomeric metabolic enzyme (Thermomyces lanuginosus Lipase) while titrating its proximity to a lipid membrane that acts as an allosteric effector. The single molecule measurements revealed the existence of discrete binary functional states that could not be identified in macroscopic measurements due to ensemble averaging. The discrete functional states correlate with the enzyme's major conformational states and are redistributed in the presence of the regulatory effector. Thus, our data support allosteric regulation of monomeric enzymes to operate via selection of preexisting functional states and not via induction of new ones.