Magnetic Resonance Spectroscopy Quantification Aided by Deep Estimations of Imperfection Factors and Macromolecular Signal

OBJECTIVE

Magnetic Resonance Spectroscopy (MRS) is an important technique for biomedical detection. However, it is challenging to accurately quantify metabolites with proton MRS due to serious overlaps of metabolite signals, imperfections because of non-ideal acquisition conditions, and interference with strong background signals mainly from macromolecules. The most popular method, LCModel, adopts complicated non-linear least square to quantify metabolites and addresses these problems by designing empirical priors such as basis-sets, imperfection factors. However, when the signal-to-noise ratio of MRS signal is low, the solution may have large deviation.

METHODS

Linear Least Squares (LLS) is integrated with deep learning to reduce the complexity of solving this overall quantification. First, a neural network is designed to explicitly predict the imperfection factors and the overall signal from macromolecules. Then, metabolite quantification is solved analytically with the introduced LLS. In our Quantification Network (QNet), LLS takes part in the backpropagation of network training, which allows the feedback of the quantification error into metabolite spectrum estimation. This scheme greatly improves the generalization to metabolite concentrations unseen in training compared to the end-to-end deep learning method.

RESULTS

Experiments show that compared with LCModel, the proposed QNet, has smaller quantification errors for simulated data, and presents more stable quantification for 20 healthy in vivo data at a wide range of signal-to-noise ratio. QNet also outperforms other end-to-end deep learning methods.

CONCLUSION

This study provides an intelligent, reliable and robust MRS quantification.

SIGNIFICANCE

QNet is the first LLS quantification aided by deep learning.

Discovering optimal kinetic pathways for self-assembly using automatic differentiation

Macromolecular complexes are often composed of diverse subunits. The self-assembly of these subunits is inherently nonequilibrium and must avoid kinetic traps to achieve high yield over feasible timescales. We show how the kinetics of self-assembly benefits from diversity in subunits because it generates an expansive parameter space that naturally improves the "expressivity" of self-assembly, much like a deeper neural network. By using automatic differentiation algorithms commonly used in deep learning, we searched the parameter spaces of mass-action kinetic models to identify classes of kinetic protocols that mimic biological solutions for productive self-assembly. Our results reveal how high-yield complexes that easily become kinetically trapped in incomplete intermediates can instead be steered by internal design of rate-constants or external and active control of subunits to efficiently assemble. Internal design of a hierarchy of subunit binding rates generates self-assembly that can robustly avoid kinetic traps for all concentrations and energetics, but it places strict constraints on selection of relative rates. External control via subunit titration is more versatile, avoiding kinetic traps for any system without requiring molecular engineering of binding rates, albeit less efficiently and robustly. We derive theoretical expressions for the timescales of kinetic traps, and we demonstrate our optimization method applies not just for design but inference, extracting intersubunit binding rates from observations of yield-vs.-time for a heterotetramer. Overall, we identify optimal kinetic protocols for self-assembly as a powerful mechanism to achieve efficient and high-yield assembly in synthetic systems whether robustness or ease of "designability" is preferred.

A validation strategy to assess the role of phase separation as a determinant of macromolecular localization

Liquid-liquid phase separation (LLPS) of putative assembly scaffolds has been proposed to drive the biogenesis of membraneless compartments. LLPS scaffolds are usually identified through in vitro LLPS assays with single macromolecules (homotypic), but the predictive value of these assays remains poorly characterized. Here, we apply a strategy to evaluate the robustness of homotypic LLPS assays. When applied to the chromosomal passenger complex (CPC), which undergoes LLPS in vitro and localizes to centromeres to promote chromosome biorientation, LLPS propensity in vitro emerged as an unreliable predictor of subcellular localization. In vitro CPC LLPS in aqueous buffers was enhanced by commonly used crowding agents. Conversely, diluted cytomimetic media dissolved condensates of the CPC and of several other proteins. We also show that centromeres do not seem to nucleate LLPS, nor do they promote local, spatially restrained LLPS of the CPC. Our strategy can be adapted to purported LLPS scaffolds of other membraneless compartments.

Modulation of bacterial membranes and cellular macromolecules by dimethyl sulfoxide: A dose-dependent study providing novel insights

Using Escherichia coli as a model, this manuscript delves into the intricate interactions between dimethyl sulfoxide (DMSO) and membranes, cellular macromolecules, and the effects on various aspects of bacterial physiology. Given DMSO's wide-ranging use as a solvent in microbiology, we investigate the impacts of both non-growth inhibitory (1.0 % and 2.5 % v/v) and slightly growth-inhibitory (5.0 % v/v) concentrations of DMSO. The results demonstrate that DMSO causes alterations in bacterial membrane potential, influences the electrochemical characteristics of the cell surface, and exerts substantial effects on the composition and structure of cellular biomolecules. Genome-wide gene expression data from DMSO-treated E. coli was used to further investigate and bolster the results. The findings of this study provide valuable insights into the complex relationship between DMSO and biological systems, with potential implications in drug delivery and cellular manipulation. However, it is essential to exercise caution when utilizing DMSO to enhance the solubility and delivery of bioactive compounds, as even at low concentrations, DMSO exerts non-inert effects on cellular macromolecules and processes.

Macromolecular crowding has opposite effects on two critical sub-steps of transcription initiation

Transcription initiation, the first step in gene expression, has been studied extensively in dilute buffer, a condition which fails to consider the crowded environment in live cells. Recent reports indicate the kinetics of promoter escape is altered in crowded conditions for a consensus bacterial promoter. Here, we use a real-time fluorescence enhancement assay to study the kinetics of unwound bubble formation and promoter escape for three separate promoters. We find that the effect of crowding on transcription initiation is complex, with lower rates of unwound bubble formation, higher rates of promoter escape, and large variations depending on promoter identity. Based on our results, we suggest that altered conditions of crowding inside a live cell can trigger global changes.

RNA: The Unsuspected Conductor in the Orchestra of Macromolecular Crowding

This comprehensive Review delves into the chemical principles governing RNA-mediated crowding events, commonly referred to as granules or biological condensates. We explore the pivotal role played by RNA sequence, structure, and chemical modifications in these processes, uncovering their correlation with crowding phenomena under physiological conditions. Additionally, we investigate instances where crowding deviates from its intended function, leading to pathological consequences. By deepening our understanding of the delicate balance that governs molecular crowding driven by RNA and its implications for cellular homeostasis, we aim to shed light on this intriguing area of research. Our exploration extends to the methodologies employed to decipher the composition and structural intricacies of RNA granules, offering a comprehensive overview of the techniques used to characterize them, including relevant computational approaches. Through two detailed examples highlighting the significance of noncoding RNAs, NEAT1 and XIST, in the formation of phase-separated assemblies and their influence on the cellular landscape, we emphasize their crucial role in cellular organization and function. By elucidating the chemical underpinnings of RNA-mediated molecular crowding, investigating the role of modifications, structures, and composition of RNA granules, and exploring both physiological and aberrant phase separation phenomena, this Review provides a multifaceted understanding of the intriguing world of RNA-mediated biological condensates.

Bridging structural and cell biology with cryo-electron microscopy

Most life scientists would agree that understanding how cellular processes work requires structural knowledge about the macromolecules involved. For example, deciphering the double-helical nature of DNA revealed essential aspects of how genetic information is stored, copied and repaired. Yet, being reductionist in nature, structural biology requires the purification of large amounts of macromolecules, often trimmed off larger functional units. The advent of cryogenic electron microscopy (cryo-EM) greatly facilitated the study of large, functional complexes and generally of samples that are hard to express, purify and/or crystallize. Nevertheless, cryo-EM still requires purification and thus visualization outside of the natural context in which macromolecules operate and coexist. Conversely, cell biologists have been imaging cells using a number of fast-evolving techniques that keep expanding their spatial and temporal reach, but always far from the resolution at which chemistry can be understood. Thus, structural and cell biology provide complementary, yet unconnected visions of the inner workings of cells. Here we discuss how the interplay between cryo-EM and cryo-electron tomography, as a connecting bridge to visualize macromolecules in situ, holds great promise to create comprehensive structural depictions of macromolecules as they interact in complex mixtures or, ultimately, inside the cell itself.

Impact of acquisition and modeling parameters on the test-retest reproducibility of edited GABA

Literature values vary widely for within-subject test-retest reproducibility of gamma-aminobutyric acid (GABA) measured with edited magnetic resonance spectroscopy (MRS). Reasons for this variation remain unclear. Here, we tested whether three acquisition parameters-(1) sequence complexity (two-experiment MEscher-GArwood Point RESolved Spectroscopy [MEGA-PRESS] vs. four-experiment Hadamard Encoding and Reconstruction of MEGA-Edited Spectroscopy [HERMES]); (2) editing pulse duration (14 vs. 20 ms); and (3) scanner frequency drift (interleaved water referencing [IWR] turned ON vs. OFF)-and two linear combination modeling variations-(1) three different coedited macromolecule models (called "1to1GABA", "1to1GABAsoft", and "3to2MM" in the Osprey software package); and (2) 0.55- versus 0.4-ppm spline baseline knot spacing-affected the within-subject coefficient of variation of GABA + macromolecules (GABA+). We collected edited MRS data from the dorsal anterior cingulate cortex from 20 participants (mean age: 30.8 ± 9.5 years; 10 males). Test and retest scans were separated by removing the participant from the scanner for 5-10 min. Each acquisition consisted of two MEGA-PRESS and two HERMES sequences with editing pulse durations of 14 and 20 ms (referred to here as MEGA-14, MEGA-20, HERMES-14, and HERMES-20; all TE = 80 ms, 224 averages). We identified the best test-retest reproducibility following postprocessing with a composite model of the 0.9- and 3-ppm macromolecules ("3to2MM"); this model performed particularly well for the HERMES data. Furthermore, sparser (0.55- compared with 0.4-ppm) spline baseline knot spacing yielded generally better test-retest reproducibility for GABA+. Replicating our prior results, linear combination modeling in Osprey compared with simple peak fitting in Gannet resulted in substantially better test-retest reproducibility. However, reproducibility did not consistently differ for MEGA-PRESS compared with HERMES, for 14- compared with 20-ms editing pulses, or for IWR-ON versus IWR-OFF. These results highlight the importance of model selection for edited MRS studies of GABA+, particularly for clinical studies that focus on individual patient differences in GABA+ or changes following an intervention.

Uncertainty propagation in absolute metabolite quantification for in vivo MRS of the human brain

PURPOSE

Absolute spectral quantification is the standard method for deriving estimates of the concentration from metabolite signals measured using in vivo proton MRS (1 H-MRS). This method is often reported with minimum variance estimators, specifically the Cramér-Rao lower bound (CRLB) of the metabolite signal amplitude's scaling factor from linear combination modeling. This value serves as a proxy for SD and is commonly reported in MRS experiments. Characterizing the uncertainty of absolute quantification, however, depends on more than simply the CRLB. The uncertainties of metabolite-specific (T1m , T2m ), reference-specific (T1ref , T2ref ), and sequence-specific (TR , TE ) parameters are generally ignored, potentially leading to an overestimation of precision. In this study, the propagation of uncertainty is used to derive a comprehensive estimate of the overall precision of concentrations from an internal reference.

METHODS

The propagated uncertainty is calculated using analytical derivations and Monte Carlo simulations and subsequently analyzed across a set of commonly measured metabolites and macromolecules. The effect of measurement error from experimentally obtained quantification parameters is estimated using published uncertainties and CRLBs from in vivo 1 H-MRS literature.

RESULTS

The additive effect of propagated measurement uncertainty from applied quantification correction factors can result in up to a fourfold increase in the concentration estimate's coefficient of variation compared to the CRLB alone. A case study analysis reveals similar multifold increases across both metabolites and macromolecules.

CONCLUSION

The precision of absolute metabolite concentrations derived from 1 H-MRS experiments is systematically overestimated if the uncertainties of commonly applied corrections are neglected as sources of error.

Innate immune sensing of macromolecule homeostasis

The innate immune system uses a distinct set of germline-encoded pattern recognition receptors to recognize molecular patterns initially thought to be unique to microbial invaders, named pathogen-associated molecular patterns. The concept was later further developed to include similar molecular patterns originating from host cells during tissue damage, known as damage-associated molecular patterns. However, recent advances in the mechanism of monogenic inflammatory diseases have highlighted a much more expansive repertoire of cellular functions that are monitored by innate immunity. Here, we summarize several examples in which an innate immune response is triggered when homeostasis of macromolecule in the cell is disrupted in non-infectious or sterile settings. These ever-growing sensing mechanisms expand the repertoire of innate immune recognition, positioning it not only as a key player in host defense but also as a gatekeeper of cellular homeostasis. Therapeutics inspired by these advances to restore cellular homeostasis and correct the immune system could have far-reaching implications.

Macromolecular Crowding, Phase Separation, and Homeostasis in the Orchestration of Bacterial Cellular Functions

Macromolecular crowding affects the activity of proteins and functional macromolecular complexes in all cells, including bacteria. Crowding, together with physicochemical parameters such as pH, ionic strength, and the energy status, influences the structure of the cytoplasm and thereby indirectly macromolecular function. Notably, crowding also promotes the formation of biomolecular condensates by phase separation, initially identified in eukaryotic cells but more recently discovered to play key functions in bacteria. Bacterial cells require a variety of mechanisms to maintain physicochemical homeostasis, in particular in environments with fluctuating conditions, and the formation of biomolecular condensates is emerging as one such mechanism. In this work, we connect physicochemical homeostasis and macromolecular crowding with the formation and function of biomolecular condensates in the bacterial cell and compare the supramolecular structures found in bacteria with those of eukaryotic cells. We focus on the effects of crowding and phase separation on the control of bacterial chromosome replication, segregation, and cell division, and we discuss the contribution of biomolecular condensates to bacterial cell fitness and adaptation to environmental stress.

RNA-mediated ribonucleoprotein assembly controls TDP-43 nuclear retention

TDP-43 is an essential RNA-binding protein strongly implicated in the pathogenesis of neurodegenerative disorders characterized by cytoplasmic aggregates and loss of nuclear TDP-43. The protein shuttles between nucleus and cytoplasm, yet maintaining predominantly nuclear TDP-43 localization is important for TDP-43 function and for inhibiting cytoplasmic aggregation. We previously demonstrated that specific RNA binding mediates TDP-43 self-assembly and biomolecular condensation, requiring multivalent interactions via N- and C-terminal domains. Here, we show that these complexes play a key role in TDP-43 nuclear retention. TDP-43 forms macromolecular complexes with a wide range of size distribution in cells and we find that defects in RNA binding or inter-domain interactions, including phase separation, impair the assembly of the largest species. Our findings suggest that recruitment into these macromolecular complexes prevents cytoplasmic egress of TDP-43 in a size-dependent manner. Our observations uncover fundamental mechanisms controlling TDP-43 cellular homeostasis, whereby regulation of RNA-mediated self-assembly modulates TDP-43 nucleocytoplasmic distribution. Moreover, these findings highlight pathways that may be implicated in TDP-43 proteinopathies and identify potential therapeutic targets.

Two-photon excited-state dynamics of mEGFP-linker-mScarlet-I crowding biosensor in controlled environments

Macromolecular crowding affects many cellular processes such as diffusion, biochemical reaction kinetics, protein-protein interactions, and protein folding. Mapping the heterogeneous, dynamic crowding in living cells or tissues requires genetically encoded, site-specific, crowding sensors that are compatible with quantitative, noninvasive fluorescence micro-spectroscopy. Here, we carried out time-resolved 2P-fluorescence measurements of a new mEGFP-linker-mScarlet-I macromolecular crowding construct (GE2.3) to characterize its environmental sensitivity in biomimetic crowded solutions (Ficoll-70, 0-300 g L-1) via Förster resonance energy transfer (FRET) analysis. The 2P-fluorescence lifetime of the donor (mEGFP) was measured under magic-angle polarization, in the presence (intact) and absence (enzymatically cleaved) of the acceptor (mScarlet-I), as a function of the Ficoll-70 concentration. The FRET efficiency was used to quantify the sensitivity of GE2.3 to macromolecular crowding and to determine the environmental dependence of the mEGFP-mScarlet-I distance. We also carried out time-resolved 2P-fluorescence depolarization anisotropy to examine both macromolecular crowding and linker flexibility effects on GE2.3 rotational dynamics within the context of the Stokes-Einstein model as compared with theoretical predictions based on its molecular weight. These time-resolved 2P-fluorescence depolarization measurements and conformational population analyses of GE2.3 were also used to estimate the free energy gain upon the structural collapse in crowded environment. Our results further the development of a rational engineering design for bioenvironmental sensors without the interference of cellular autofluorescence. Additionally, these results in well-defined environments will inform our future in vivo studies of genetically encoded GE2.3 towards the mapping of the crowded intracellular environment under different physiological conditions.

Determining Macromolecular Structures Using Cryo-Electron Microscopy

Structural insights into macromolecular and protein complexes provide key clues about the molecular basis of the function. Cryogenic electron microscopy (cryo-EM) has emerged as a powerful structural biology method for studying protein and macromolecular structures at high resolution in both native and near-native states. Despite the ability to get detailed structural insights into the processes underlying protein function using cryo-EM, there has been hesitancy amongst plant biologists to apply the method for biomolecular interaction studies. This is largely evident from the relatively fewer structural depositions of proteins and protein complexes from plant origin in electron microscopy databank. Even though the progress has been slow, cryo-EM has significantly contributed to our understanding of the molecular biology processes underlying photosynthesis, energy transfer in plants, besides viruses infecting plants. This chapter introduces sample preparation for both negative-staining electron microscopy (NSEM) and cryo-EM for plant proteins and macromolecular complexes and data analysis using single particle analysis for beginners.

Macromolecular condensation buffers intracellular water potential

Optimum protein function and biochemical activity critically depends on water availability because solvent thermodynamics drive protein folding and macromolecular interactions1. Reciprocally, macromolecules restrict the movement of 'structured' water molecules within their hydration layers, reducing the available 'free' bulk solvent and therefore the total thermodynamic potential energy of water, or water potential. Here, within concentrated macromolecular solutions such as the cytosol, we found that modest changes in temperature greatly affect the water potential, and are counteracted by opposing changes in osmotic strength. This duality of temperature and osmotic strength enables simple manipulations of solvent thermodynamics to prevent cell death after extreme cold or heat shock. Physiologically, cells must sustain their activity against fluctuating temperature, pressure and osmotic strength, which impact water availability within seconds. Yet, established mechanisms of water homeostasis act over much slower timescales2,3; we therefore postulated the existence of a rapid compensatory response. We find that this function is performed by water potential-driven changes in macromolecular assembly, particularly biomolecular condensation of intrinsically disordered proteins. The formation and dissolution of biomolecular condensates liberates and captures free water, respectively, quickly counteracting thermal or osmotic perturbations of water potential, which is consequently robustly buffered in the cytoplasm. Our results indicate that biomolecular condensation constitutes an intrinsic biophysical feedback response that rapidly compensates for intracellular osmotic and thermal fluctuations. We suggest that preserving water availability within the concentrated cytosol is an overlooked evolutionary driver of protein (dis)order and function.

Potentiating Tweezer Affinity to a Protein Interface with Sequence-Defined Macromolecules on Nanoparticles

Survivin, a well-known member of the inhibitor of apoptosis protein family, is upregulated in many cancer cells, which is associated with resistance to chemotherapy. To circumvent this, inhibitors are currently being developed to interfere with the nuclear export of survivin by targeting its protein-protein interaction (PPI) with the export receptor CRM1. Here, we combine for the first time a supramolecular tweezer motif, sequence-defined macromolecular scaffolds, and ultrasmall Au nanoparticles (us-AuNPs) to tailor a high avidity inhibitor targeting the survivin-CRM1 interaction. A series of biophysical and biochemical experiments, including surface plasmon resonance measurements and their multivalent evaluation by EVILFIT, reveal that for divalent macromolecular constructs with increasing linker distance, the longest linkers show superior affinity, slower dissociation, as well as more efficient PPI inhibition. As a drawback, these macromolecular tweezer conjugates do not enter cells, a critical feature for potential applications. The problem is solved by immobilizing the tweezer conjugates onto us-AuNPs, which enables efficient transport into HeLa cells. On the nanoparticles, the tweezer valency rises from 2 to 16 and produces a 100-fold avidity increase. The hierarchical combination of different scaffolds and controlled multivalent presentation of supramolecular binders was the key to the development of highly efficient survivin-CRM1 competitors. This concept may also be useful for other PPIs.

Orientationally Averaged Version of the Rotne-Prager-Yamakawa Tensor Provides a Fast but Still Accurate Treatment of Hydrodynamic Interactions in Brownian Dynamics Simulations of Biological Macromolecules

The Brownian dynamics (BD) simulation technique is widely used to model the diffusive and conformational dynamics of complex systems comprising biological macromolecules. For the diffusive properties of macromolecules to be described correctly by BD simulations, it is necessary to include hydrodynamic interactions (HIs). When modeled at the Rotne-Prager-Yamakawa (RPY) level of theory, for example, the translational and rotational diffusion coefficients of isolated macromolecules can be accurately reproduced; when HIs are neglected, however, diffusion coefficients can be underestimated by an order of magnitude or more. The principal drawback to the inclusion of HIs in BD simulations is their computational expense, and several previous studies have sought to accelerate their modeling by developing fast approximations for the calculation of the correlated random displacements. Here, we explore the use of an alternative way to accelerate the calculation of HIs, i.e., by replacing the full RPY tensor with an orientationally averaged (OA) version which retains the distance dependence of the HIs but averages out their orientational dependence. We seek here to determine whether such an approximation can be justified in application to the modeling of typical proteins and RNAs. We show that the use of an OA-RPY tensor allows translational diffusion of macromolecules to be modeled with very high accuracy at the cost of rotational diffusion being underestimated by ∼25%. We show that this finding is independent of the type of macromolecule simulated and the level of structural resolution employed in the models. We also show, however, that these results are critically dependent on the inclusion of a non-zero term that describes the divergence of the diffusion tensor: when this term is omitted from simulations that use the OA-RPY model, unfolded macromolecules undergo rapid collapse. Our results indicate that the orientationally averaged RPY tensor is likely to be a useful, fast, approximate way of including HIs in BD simulations of intermediate-scale systems.

Targeting cerebral diseases with enhanced delivery of therapeutic proteins across the blood-brain barrier

INTRODUCTION

Cerebral diseases have been threatening public physical and psychological health in the recent years. With the existence of the blood-brain barrier (BBB), it is particularly hard for therapeutic proteins like peptides, enzymes, antibodies, etc. to enter the central nervous system (CNS) and function in diagnosis and treatment in cerebral diseases. Fortunately, the past decade has witnessed some emerging strategies of delivering macromolecular therapeutic proteins across the BBB.

AREAS COVERED

Based on the structure, functions, and substances transport mechanisms, various enhanced delivery strategies of therapeutic proteins were reviewed, categorized by molecule-mediated delivery strategies, carrier-mediated delivery strategies, and other delivery strategies.

EXPERT OPINION

As for molecule-mediated delivery strategies, development of genetic engineering technology, optimization of protein expression and purification techniques, and mature of quality control systems all help to realize large-scale production of recombinant antibodies, making it possible to apply to the clinical practice. In terms of carrier-mediated delivery strategies and others, although nano-carriers/adeno-associated virus (AAV) are also promising candidates for delivering therapeutic proteins or genes across the BBB, some issues still remain to be further investigated, including safety concerns related to applied materials, large-scale production costs, quality control standards, combination therapies with auxiliary delivery strategies like focused ultrasound, etc.

Developments in describing equilibrium phase transitions of multivalent associative macromolecules

Biomolecular condensates are distinct cellular bodies that form and dissolve reversibly to organize cellular matter and biochemical reactions in space and time. Condensates are thought to form and dissolve under the influence of spontaneous and driven phase transitions of multivalent associative macromolecules. These include phase separation, which is defined by segregation of macromolecules from the solvent or from one another, and percolation or gelation, which is an inclusive networking transition driven by reversible associations among multivalent macromolecules. Considerable progress has been made to model sequence-specific phase transitions, especially for intrinsically disordered proteins. Here, we summarize the state-of-the-art of theories and computations aimed at understanding and modeling sequence-specific, thermodynamically controlled, coupled associative and segregative phase transitions of archetypal multivalent macromolecules.

Feasibility and implications of using subject-specific macromolecular spectra to model short echo time magnetic resonance spectroscopy data

Expert consensus recommends linear-combination modeling (LCM) of 1 H MR spectra with sequence-specific simulated metabolite basis function and experimentally derived macromolecular (MM) basis functions. Measured MM basis functions are usually derived from metabolite-nulled spectra averaged across a small cohort. The use of subject-specific instead of cohort-averaged measured MM basis functions has not been studied widely. Furthermore, measured MM basis functions are not widely available to non-expert users, who commonly rely on parameterized MM signals internally simulated by LCM software. To investigate the impact of the choice of MM modeling, this study, therefore, compares metabolite level estimates between different MM modeling strategies (cohort-mean measured; subject-specific measured; parameterized) in a lifespan cohort and characterizes its impact on metabolite-age associations. 100 conventional (TE = 30 ms) and metabolite-nulled (TI = 650 ms) PRESS datasets, acquired from the medial parietal lobe in a lifespan cohort (20-70 years of age), were analyzed in Osprey. Short-TE spectra were modeled in Osprey using six different strategies to consider the MM baseline. Fully tissue- and relaxation-corrected metabolite levels were compared between MM strategies. Model performance was evaluated by model residuals, the Akaike information criterion (AIC), and the impact on metabolite-age associations. The choice of MM strategy had a significant impact on the mean metabolite level estimates and no major impact on variance. Correlation analysis revealed moderate-to-strong agreement between different MM strategies (r > 0.6). The lowest relative model residuals and AIC values were found for the cohort-mean measured MM. Metabolite-age associations were consistently found for two major singlet signals (total creatine (tCr])and total choline (tCho)) for all MM strategies; however, findings for metabolites that are less distinguishable from the background signals associations depended on the MM strategy. A variance partition analysis indicated that up to 44% of the total variance was related to the choice of MM strategy. Additionally, the variance partition analysis reproduced the metabolite-age association for tCr and tCho found in the simpler correlation analysis. In summary, the inclusion of a single high signal-to-noise ratio MM basis function (cohort-mean) in the short-TE LCM leads to more lower model residuals and AIC values compared with MM strategies with more degrees of freedom (Gaussian parametrization) or subject-specific MM information. Integration of multiple LCM analyses into a single statistical model potentially allows to identify the robustness in the detection of underlying effects (e.g., metabolite vs. age), reduces algorithm-based bias, and estimates algorithm-related variance.

Protein Condensation, Cellular Organization, and Spatiotemporal Regulation of Cytoplasmic Properties

The cytoplasm is an aqueous, highly crowded solution of active macromolecules. Its properties influence the behavior of proteins, including their folding, motion, and interactions. In particular, proteins in the cytoplasm can interact to form phase-separated assemblies, so-called biomolecular condensates. The interplay between cytoplasmic properties and protein condensation is critical in a number of functional contexts and is the subject of this review. The authors first describe how cytoplasmic properties can affect protein behavior, in particular condensate formation, and then describe the functional implications of this interplay in three cellular contexts, which exemplify how protein self-organization can be adapted to support certain physiological phenotypes. The authors then describe the formation of RNA-protein condensates in highly polarized cells such as neurons, where condensates play a critical role in the regulation of local protein synthesis, and describe how different stressors trigger extensive reorganization of the cytoplasm, both through signaling pathways and through direct stress-induced changes in cytoplasmic properties. Finally, the authors describe changes in protein behavior and cytoplasmic properties that may occur in extremophiles, in particular organisms that have adapted to inhabit environments of extreme temperature, and discuss the implications and functional importance of these changes.

Condensed-phase signaling can expand kinase specificity and respond to macromolecular crowding

Phase separation can concentrate biomolecules and accelerate reactions. However, the mechanisms and principles connecting this mesoscale organization to signaling dynamics are difficult to dissect because of the pleiotropic effects associated with disrupting endogenous condensates. To address this limitation, we engineered new phosphorylation reactions within synthetic condensates. We generally found increased activity and broadened kinase specificity. Phosphorylation dynamics within condensates were rapid and could drive cell-cycle-dependent localization changes. High client concentration within condensates was important but not the main factor for efficient phosphorylation. Rather, the availability of many excess client-binding sites together with a flexible scaffold was crucial. Phosphorylation within condensates was also modulated by changes in macromolecular crowding. Finally, the phosphorylation of the Alzheimer's-disease-associated protein Tau by cyclin-dependent kinase 2 was accelerated within condensates. Thus, condensates enable new signaling connections and can create sensors that respond to the biophysical properties of the cytoplasm.

High Macromolecular Crowding in Liposomes from Microfluidics

The intracellular environment is crowded with macromolecules that influence biochemical equilibria and biomacromolecule diffusion. The incorporation of such crowding in synthetic cells would be needed to mimic the biochemistry of living cells. However, only a few methods provide crowded artificial cells, moreover providing cells with either heterogeneous size and composition or containing a significant oil fraction. Therefore, a method that generates monodisperse liposomes with minimal oil content and tunable macromolecular crowding using polydimethylsiloxane (PDMS)-based microfluidics is presented. Lipid stabilized water-in-oil-in-water emulsions that are stable for at least several months and with a high macromolecular crowder concentration that can be controlled with the external osmolality are formed. A crucial feature is that the oil phase can be removed using high flow conditions at any point after production, providing the highly crowded liposomes. Genetically encoded macromolecular crowding sensors show that the high level of macromolecular crowding in the emulsions is fully retained throughout the generation of minimal-oil lipid bilayers. This modular and robust platform will serve the study of biochemistry under physiologically relevant crowding conditions.

Analyzing macromolecular composition of E. Coli O157:H7 using Raman-stable isotope probing

Metabolic dynamics of bacterial cells is needed for understanding the correlation between changes in environmental conditions and cell metabolic activity. In this study, Raman spectroscopy combined with deuterium labelling was used to analyze the metabolic activity of a single Escherichia coli O157:H7 cell. The incorporation of deuterium from heavy water into cellular biomolecules resulted in the formation of carbon-deuterium (CD) peaks in the Raman spectra, indicating the cell metabolic activity. The broad vibrational peaks corresponding to CD and CH peaks encompassed different specific shifts of macromolecules such as protein, lipids, and nucleic acid. The utilization of tryptophan and oleic acid by the cell as the sole carbon source led to changes in cell lipid composition, as indicated by new peaks in the second derivative spectra. Thus, the proposed method could semi-quantitatively determine total metabolic activity, macromolecule specific identification, and lipid and protein metabolism in a single cell.

Therapeutic Ultrasound for Topical Corneal Delivery of Macromolecules

Purpose

The objective of this study was to utilize therapeutic ultrasound in enhancing delivery of topical macromolecules into the cornea.

Methods

Rabbit corneas were dissected and placed in a diffusion cell with a small ultra-red fluorescent protein (smURFP; molecular weight of 32,000 Da) as a macromolecule solution. The corneas were treated with continuous ultrasound application at frequencies of 400 or 600 kHz and intensities of 0.8 to 1.0 W/cm2 for 5 minutes, or sham-treated. Fluorescence imaging of the cornea sections was used to observe the delivery of macromolecules into individual epithelial cells. Spectrophotometric analysis at smURFP maximal absorbance of 640 nm was done to determine the presence of macromolecules in the receiver compartment. Safety of ultrasound application was studied through histology analysis.

Results

Ultrasound-treated corneas showed smURFP delivery into epithelial cells by fluorescence in the cytoplasm, whereas sham-treated corneas lacked any appreciable fluorescence in the individual cells. The sham group showed 0% of subcellular penetration, whereas the 400 kHz ultrasound-treated group and 600 kHz ultrasound-treated group showed 31% and 57% of subcellular penetration, respectively. Spectrophotometry measurements indicated negligible presence of smURFP macromolecules in the receiver compartment solution in both the sham and ultrasound treatment groups, and these macromolecules did not cross the entire depth of the cornea. Histological studies showed no significant corneal damage due to ultrasound application.

Conclusions

Therapeutic ultrasound application was shown to increase the delivery of smURFP macromolecules into the cornea.

Translational Relevance

Our study offers a clinical potential for a minimally invasive macromolecular treatment of corneal diseases.

Quantitative Frameworks for Multivalent Macromolecular Interactions in Biological Linear Lattice Systems

Multivalent macromolecular interactions underlie dynamic regulation of diverse biological processes in ever-changing cellular states. These interactions often involve binding of multiple proteins to a linear lattice including intrinsically disordered proteins and the chromosomal DNA with many repeating recognition motifs. Quantitative understanding of such multivalent interactions on a linear lattice is crucial for exploring their unique regulatory potentials in the cellular processes. In this review, the distinctive molecular features of the linear lattice system are first discussed with a particular focus on the overlapping nature of potential protein binding sites within a lattice. Then, we introduce two general quantitative frameworks, combinatorial and conditional probability models, dealing with the overlap problem and relating the binding parameters to the experimentally measurable properties of the linear lattice-protein interactions. To this end, we present two specific examples where the quantitative models have been applied and further extended to provide biological insights into specific cellular processes. In the first case, the conditional probability model was extended to highlight the significant impact of nonspecific binding of transcription factors to the chromosomal DNA on gene-specific transcriptional activities. The second case presents the recently developed combinatorial models to unravel the complex organization of target protein binding sites within an intrinsically disordered region (IDR) of a nucleoporin. In particular, these models have suggested a unique function of IDRs as a molecular switch coupling distinct cellular processes. The quantitative models reviewed here are envisioned to further advance for dissection and functional studies of more complex systems including phase-separated biomolecular condensates.

The Delivery of Extracellular “Danger” Signals to Cytosolic Sensors in Phagocytes

Phagocytes, such as macrophages and dendritic cells, possess the ability to ingest large quantities of exogenous material into membrane-bound endocytic organelles such as macropinosomes and phagosomes. Typically, the ingested material, which consists of diverse macromolecules such as proteins and nucleic acids, is delivered to lysosomes where it is digested into smaller molecules like amino acids and nucleosides. These smaller molecules can then be exported out of the lysosomes by transmembrane transporters for incorporation into the cell’s metabolic pathways or for export from the cell. There are, however, exceptional instances when undigested macromolecules escape degradation and are instead delivered across the membrane of endocytic organelles into the cytosol of the phagocyte. For example, double stranded DNA, a damage associated molecular pattern shed by necrotic tumor cells, is endocytosed by phagocytes in the tumor microenvironment and delivered to the cytosol for detection by the cytosolic “danger” sensor cGAS. Other macromolecular “danger” signals including lipopolysaccharide, intact proteins, and peptidoglycans can also be actively transferred from within endocytic organelles to the cytosol. Despite the obvious biological importance of these processes, we know relatively little of how macromolecular “danger” signals are transferred across endocytic organelle membranes for detection by cytosolic sensors. Here we review the emerging evidence for the active cytosolic transfer of diverse macromolecular “danger” signals across endocytic organelle membranes. We will highlight developing trends and discuss the potential molecular mechanisms driving this emerging phenomenon.

Macromolecular background signal and non-Gaussian metabolite diffusion determined in human brain using ultra-high diffusion weighting

Purpose

Definition of a macromolecular MR spectrum based on diffusion properties rather than relaxation time differences and characterization of non‐Gaussian diffusion of brain metabolites with strongly diffusion‐weighted MR spectroscopy.

Methods

Short echo time MRS with strong diffusion‐weighting with b‐values up to 25 ms/μm² at two diffusion times was implemented on a Connectom system and applied in combination with simultaneous spectral and diffusion decay modeling. Motion‐compensation was performed with a combined method based on the simultaneously acquired water and a macromolecular signal.

Results

The motion compensation scheme prevented spurious signal decay reflected in very small apparent diffusion constants for macromolecular signal. Macromolecular background signal patterns were determined using multiple fit strategies. Signal decay corresponding to non‐Gaussian metabolite diffusion was represented by biexponential fit models yielding parameter estimates for human gray matter that are in line with published rodent data. The optimal fit strategies used constraints for the signal decay of metabolites with limited signal contributions to the overall spectrum.

Conclusion

The determined macromolecular spectrum based on diffusion properties deviates from the conventional one derived from longitudinal relaxation time differences calling for further investigation before use as experimental basis spectrum when fitting clinical MR spectra. The biexponential characterization of metabolite signal decay is the basis for investigations into pathologic alterations of microstructure.

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γ-aminobutyric acid measurement in the human brain at 7 T: Short echo-time or Mescher-Garwood editing

The purposes of the current study were to introduce a Mescher-Garwood (MEGA) semi-adiabatic spin-echo full-intensity localization (MEGA-sSPECIAL) sequence with macromolecule (MM) subtraction and to compare the test-retest reproducibility of γ-aminobutyric acid (GABA) measurements at 7 T using the sSPECIAL and MEGA-sSPECIAL sequences. The MEGA-sSPECIAL editing scheme using asymmetric adiabatic and highly selective Gaussian pulses was used to compare its GABA measurement reproducibility with that of short echo-time (TE) sSPECIAL. Proton magnetic resonance spectra were acquired in the motor cortex (M1) and medial prefrontal cortex (mPFC) using the sSPECIAL (TR/TE = 4000/16 ms) and MEGA-sSPECIAL sequences (TR/TE = 4000/80 ms). The metabolites were quantified using LCModel with unsuppressed water spectra. The concentrations are reported in institutional units. The test-retest reproducibility was evaluated by scanning each subject twice. Between-session reproducibility was assessed using coefficients of variation (CVs), Pearson's r correlation coefficients, and intraclass correlation coefficients (ICCs). Intersequence agreement was evaluated using Pearson's r correlation coefficients and Bland-Altman plots. Regarding GABA measurements by sSPECIAL, the GABA concentrations were 0.92 ± 0.31 (IU) in the M1 and 1.56 ± 0.49 (IU) in the mPFC. This demonstrated strong between-session correlation across both regions (r = 0.81, p < 0.01; ICC = 0.82). The CVs between the two scans were 21.8% in the M1 and 10.2% in the mPFC. On the other hand, the GABA measurements by MEGA-sSPECIAL were 0.52 ± 0.04 (IU) in the M1 and 1.04 ± 0.24 (IU) in the mPFC. MEGA-sSPECIAL demonstrated strong between-session correlation across the two regions (r = 0.98, p < 0.001; ICC = 0.98) and lower CVs than sSPECIAL, providing 4.1% in the M1 and 5.8% in the mPFC. The MEGA-editing method showed better reproducibility of GABA measurements in both brain regions compared with the short-TE sSPECIAL method. Thus it is a more sensitive method with which to detect small changes in areas with low GABA concentrations. In GABA-rich brain regions, GABA measurements can be achieved reproducibly using both methods.

Allogeneic Serum and Macromolecular Crowding Maintain Native Equine Tenocyte Function in Culture

The absence of a native extracellular matrix and the use of xenogeneic sera are often associated with rapid tenocyte function losses during in vitro culture. Herein, we assessed the influence of different sera (equine serum and foetal bovine serum) on equine tenocyte morphology, viability, metabolic activity, proliferation and protein synthesis as a function of tissue-specific extracellular matrix deposition (induced via macromolecular crowding), aging (passages 3, 6, 9) and time in culture (days 3, 5, 7). In comparison to cells at passage 3, at day 3, in foetal bovine serum and without macromolecular crowding (traditional equine tenocyte culture), the highest number of significantly decreased readouts were observed for cells in foetal bovine serum, at passage 3, at day 5 and day 7 and without macromolecular crowding. Again, in comparison to traditional equine tenocyte culture, the highest number of significantly increased readouts were observed for cells in equine serum, at passage 3 and passage 6, at day 7 and with macromolecular crowding. Our data advocate the use of an allogeneic serum and tissue-specific extracellular matrix for effective expansion of equine tenocytes.

Brain Cancer Cell-Derived Matrices and Effects on Astrocyte Migration

Cell-derived matrices are useful tools for studying the extracellular matrix (ECM) of different cell types and testing the effects on cell migration or wound repair. These matrices typically are generated using extended culture with ascorbic acid to boost ECM production. Applying this technique to cancer cell cultures could advance the study of cancer ECM and its effects on recruitment and training of the tumor microenvironment, but ascorbic acid is potently cytotoxic to cancer cells. Macromolecular crowding (MMC) agents can also be added to increase matrix deposition based on the excluded volume principle. We report the use of MMC alone as an effective strategy to generate brain cancer cell-derived matrices for downstream analyses and cell migration studies. We cultured the mouse glioblastoma cell line GL261 for 1 week in the presence of three previously reported MMC agents (carrageenan, Ficoll 70/400, and hyaluronic acid). We measured the resulting deposition of collagens and sulfated glycosaminoglycans using quantitative assays, as well as other matrix components by immunostaining. Both carrageenan and Ficoll promoted significantly more accumulation of total collagen content, sulfated glycosaminoglycan content, and fibronectin staining. Only Ficoll, however, also demonstrated a significant increase in collagen I staining. The results were more variable in 3D spheroid culture. We focused on Ficoll MMC matrices, which were isolated using the small molecule Raptinal to induce cancer cell apoptosis and matrix decellularization. The cancer cell-derived matrix promoted significantly faster migration of human astrocytes in a scratch wound assay, which may be explained by focal adhesion morphology and an increase in cellular metabolic activity. Ultimately, these data show MMC culture is a useful technique to generate cancer cell-derived matrices and study the effects on stromal cell migration related to wound repair.

An Arabidopsis Callus Grafting Method to Test Cell-to-Cell Mobility of Proteins

A callus is a semi-disorganized tissue that can be induced to develop from diverse tissues by the addition of exogenous hormones. The fast growth and ease of propagation have made callus cultures useful for creating a wide variety of different experimental systems.Here, we describe a detailed and simple procedure by which different, non-clonal calli from transgenic and wild-type A. thaliana plants can be co-cultured such that they form symplasmic connections via plasmodesmata (PD). We show that callus cultures can be used to study both PD formation and transport of macromolecules between non-clonal cells via PD in a tissue lacking a vasculature. Further, we include a simple protocol for a method by which calli can be sectioned to image cells and PD by confocal laser scanning microscopy.

Using quantitative reconstitution to investigate multicomponent condensates

Many biomolecular condensates are thought to form via liquid-liquid phase separation (LLPS) of multivalent macromolecules. For those that form through this mechanism, our understanding has benefitted significantly from biochemical reconstitutions of key components and activities. Reconstitutions of RNA-based condensates to date have mostly been based on relatively simple collections of molecules. However, proteomics and sequencing data indicate that natural RNA-based condensates are enriched in hundreds to thousands of different components, and genetic data suggest multiple interactions can contribute to condensate formation to varying degrees. In this Perspective, we describe recent progress in understanding RNA-based condensates through different levels of biochemical reconstitutions as a means to bridge the gap between simple in vitro reconstitution and cellular analyses. Complex reconstitutions provide insight into the formation, regulation, and functions of multicomponent condensates. We focus on two RNA-protein condensate case studies: stress granules and RNA processing bodies (P bodies), and examine the evidence for cooperative interactions among multiple components promoting LLPS. An important concept emerging from these studies is that composition and stoichiometry regulate biochemical activities within condensates. Based on the lessons learned from stress granules and P bodies, we discuss forward-looking approaches to understand the thermodynamic relationships between condensate components, with the goal of developing predictive models of composition and material properties, and their effects on biochemical activities. We anticipate that quantitative reconstitutions will facilitate understanding of the complex thermodynamics and functions of diverse RNA-protein condensates.

Weak multivalent biomolecular interactions: a strength versus numbers tug of war with implications for phase partitioning

In this short Perspective, we discuss how recent dynamic live-cell imaging experiments have challenged our understanding of mechanisms driving functional molecular interactions in vivo. While we have generally considered the formation of functional biomolecular complexes as resulting from the stable assembly of two or more partner molecules, here we entertain the possibility that function may actually be maintained while molecules are rapidly exchanged within a complex. We postulate that at high effective concentrations, even very weak interactions can lead to strong binding site occupancy and thereby mediate function in a highly dynamic fashion. This new perspective in our definition of what represents a functional complex in living cells and in vivo could significantly alter how we define the nature of molecular transactions critical for mediating regulation in the cellular context. These less conventional principles also allow a broadening of the mechanistic options we should explore when interpreting essential biological processes such as gene regulation.

Extracellular Vesicles and Their Use as Vehicles of Immunogens

Healthy cells constitutively release lipid bilayered vesicles of different sizes and recognizing different biogenesis, collectively referred to as extracellular vesicles (EVs). EVs can be distinguished in exosomes and microvesicles. Biological and biomedical research on EVs is an emerging field that is rapidly growing. Many EV features including biogenesis, cell uptake, and functions still require unambiguous elucidation. Nevertheless, it has been well established that EVs are involved in communication among cells, tissues, and organs under both healthy and disease conditions by virtue of their ability to deliver macromolecules to target cells. Here, we summarize most recent findings regarding biogenesis, structure, and functions of both exosomes and microvesicles. In addition, the use of EVs as delivery tools to induce CD8⁺ T cell immunity is addressed compared to current designs exploiting enveloped viral vectors and virus-like particles. Finally, we describe a both safe and original approach conceived for the induction of strong CTL immunity against antigens uploaded in EVs constitutively released by muscle cells.

What are the distinguishing features and size requirements of biomolecular condensates and their implications for RNA-containing condensates?

Exciting recent work has highlighted that numerous cellular compartments lack encapsulating lipid bilayers (often called "membraneless organelles"), and that their structure and function are central to the regulation of key biological processes, including transcription, RNA splicing, translation, and more. These structures have been described as "biomolecular condensates" to underscore that biomolecules can be significantly concentrated in them. Many condensates, including RNA granules and processing bodies, are enriched in proteins and nucleic acids. Biomolecular condensates exhibit a range of material states from liquid- to gel-like, with the physical process of liquid-liquid phase separation implicated in driving or contributing to their formation. To date, in vitro studies of phase separation have provided mechanistic insights into the formation and function of condensates. However, the link between the often micron-sized in vitro condensates with nanometer-sized cellular correlates has not been well established. Consequently, questions have arisen as to whether cellular structures below the optical resolution limit can be considered biomolecular condensates. Similarly, the distinction between condensates and discrete dynamic hub complexes is debated. Here we discuss the key features that define biomolecular condensates to help understand behaviors of structures containing and generating RNA.

Single-Step Affinity Purification (ssAP) and Mass Spectrometry of Macromolecular Complexes in the Yeast S. cerevisiae

Cellular functions are mostly defined by the dynamic interactions of proteins within macromolecular networks. Deciphering the composition of macromolecular complexes and their dynamic rearrangements is the key to get a comprehensive picture of cellular behavior and to understand biological systems. In the past two decades, affinity purification coupled to mass spectrometry has become a powerful tool to comprehensively study interaction networks and their assemblies. To overcome initial limitations of the approach, in particular, the effect of protein and RNA degradation, loss of transient interactors, and poor overall yield of intact complexes from cell lysates, various modifications to affinity purification protocols have been devised over the years. In this chapter, we describe a rapid single-step affinity purification method for the efficient isolation of dynamic macromolecular complexes. The technique employs cell lysis by cryo-milling, which ensures nondegraded starting material in the submicron range, and magnetic beads, which allow for dense antibody-conjugation and thus rapid complex isolation, while avoiding loss of transient interactions. The method is epitope tag-independent, and overcomes many of the previous limitations to produce large interactomes with almost no contamination. The protocol as described here has been optimized for the yeast S. cerevisiae.

RNA in formation and regulation of transcriptional condensates

Macroscopic membraneless organelles containing RNA such as the nucleoli, germ granules, and the Cajal body have been known for decades. These biomolecular condensates are liquid-like bodies that can be formed by a phase transition. Recent evidence has revealed the presence of similar microscopic condensates associated with the transcription of genes. This brief article summarizes thoughts about the importance of condensates in the regulation of transcription and how RNA molecules, as components of such condensates, control the synthesis of RNA. Models and experimental data suggest that RNAs from enhancers facilitate the formation of a condensate that stabilizes the binding of transcription factors and accounts for a burst of transcription at the promoter. Termination of this burst is pictured as a nonequilibrium feedback loop where additional RNA destabilizes the condensate.

Chimeric Antigen Receptors Expand the Repertoire of Antigenic Macromolecules for Cellular Immunity

T-cell therapies have made significant improvements in cancer treatment over the last decade. One cellular therapy utilizing T-cells involves the use of a chimeric MHC-independent antigen-recognition receptor, typically referred to as a chimeric antigen receptor (CAR). CAR molecules, while mostly limited to the recognition of antigens on the surface of tumor cells, can also be utilized to exploit the diverse repertoire of macromolecules targetable by antibodies, which are incorporated into the CAR design. Leaning into this expansion of target macromolecules will enhance the diversity of antigens T-cells can target and may improve the tumor-specificity of CAR T-cell therapy. This review explores the types of macromolecules targetable by T-cells through endogenous and synthetic antigen-specific receptors.

Ensuring scientific reproducibility in bio-macromolecular modeling via extensive, automated benchmarks

Each year vast international resources are wasted on irreproducible research. The scientific community has been slow to adopt standard software engineering practices, despite the increases in high-dimensional data, complexities of workflows, and computational environments. Here we show how scientific software applications can be created in a reproducible manner when simple design goals for reproducibility are met. We describe the implementation of a test server framework and 40 scientific benchmarks, covering numerous applications in Rosetta bio-macromolecular modeling. High performance computing cluster integration allows these benchmarks to run continuously and automatically. Detailed protocol captures are useful for developers and users of Rosetta and other macromolecular modeling tools. The framework and design concepts presented here are valuable for developers and users of any type of scientific software and for the scientific community to create reproducible methods. Specific examples highlight the utility of this framework, and the comprehensive documentation illustrates the ease of adding new tests in a matter of hours.

Design of Swollen Lipidic Cubic Phase to Increase Transcutaneous Penetration of Biomacromolecules

Lipidic cubic phase (LCP) is a self-assembled system composed of lipids with interpenetrated aqueous channels, and its potential in drug delivery systems has been investigated. Although LCP was shown to improve transcutaneous penetration of hydrophilic molecules of up to 1203 Da so far, the transcutaneous delivery of larger molecules such as proteins has not been achieved. This is likely because proteins are usually larger than the aqueous channels of LCP (∼37.2 Å in diameter), which limits the molecular diffusion in LCP. In this report, we overcome this issue by adding N-octyl-β-d-glucopyranoside to glyceryl monooleate-water-based LCP to give swollen LCP (SLCP), which has larger aqueous channel diameters (∼65.6 Å). First, we systemically evaluated the effect of swelling on drug diffusion in LCP/SLCP. The release kinetics of various peptides and proteins whose sizes ranged from 9.14 to 55.28 Å in diameter were evaluated, and the diffusion coefficients (D) were calculated by the Fickian diffusion model. As expected, all peptides and proteins diffused faster in SLCP than in LCP. A more detailed analysis revealed a negative linear relationship between log D and the ratio of the radius of gyration of the proteins to the aqueous channel radius, indicating that swelling of a cubic nanostructure is an effective strategy to enhance D. Next, the skin penetration of proteins encapsulated in LCP and SLCP was evaluated. The skin penetration of ovalbumin (42.9 kDa), for example, was enhanced by SLCP but not by LCP, and a positive correlation between D and the amount of skin penetration was found. Collectively, this study provides an effective measure for designing LCP systems that enhance transcutaneous penetration of biomacromolecules.

Pharmacological Inhibition of Wee1 Kinase Selectively Modulates the Voltage-Gated Na+ Channel 1.2 Macromolecular Complex

Voltage-gated Na+ (Nav) channels are a primary molecular determinant of the action potential (AP). Despite the canonical role of the pore-forming α subunit in conferring this function, protein-protein interactions (PPI) between the Nav channel α subunit and its auxiliary proteins are necessary to reconstitute the full physiological activity of the channel and to fine-tune neuronal excitability. In the brain, the Nav channel isoforms 1.2 (Nav1.2) and 1.6 (Nav1.6) are enriched, and their activities are differentially regulated by the Nav channel auxiliary protein fibroblast growth factor 14 (FGF14). Despite the known regulation of neuronal Nav channel activity by FGF14, less is known about cellular signaling molecules that might modulate these regulatory effects of FGF14. To that end, and building upon our previous investigations suggesting that neuronal Nav channel activity is regulated by a kinase network involving GSK3, AKT, and Wee1, we interrogate in our current investigation how pharmacological inhibition of Wee1 kinase, a serine/threonine and tyrosine kinase that is a crucial component of the G2-M cell cycle checkpoint, affects the Nav1.2 and Nav1.6 channel macromolecular complexes. Our results show that the highly selective inhibitor of Wee1 kinase, called Wee1 inhibitor II, modulates FGF14:Nav1.2 complex assembly, but does not significantly affect FGF14:Nav1.6 complex assembly. These results are functionally recapitulated, as Wee1 inhibitor II entirely alters FGF14-mediated regulation of the Nav1.2 channel, but displays no effects on the Nav1.6 channel. At the molecular level, these effects of Wee1 inhibitor II on FGF14:Nav1.2 complex assembly and FGF14-mediated regulation of Nav1.2-mediated Na+ currents are shown to be dependent upon the presence of Y158 of FGF14, a residue known to be a prominent site for phosphorylation-mediated regulation of the protein. Overall, our data suggest that pharmacological inhibition of Wee1 confers selective modulatory effects on Nav1.2 channel activity, which has important implications for unraveling cellular signaling pathways that fine-tune neuronal excitability.

Electron cryo-tomography reveals the subcellular architecture of growing axons in human brain organoids

During brain development, axons must extend over great distances in a relatively short amount of time. How the subcellular architecture of the growing axon sustains the requirements for such rapid build-up of cellular constituents has remained elusive. Human axons have been particularly poorly accessible to imaging at high resolution in a near-native context. Here, we present a method that combines cryo-correlative light microscopy and electron tomography with human cerebral organoid technology to visualize growing axon tracts. Our data reveal a wealth of structural details on the arrangement of macromolecules, cytoskeletal components, and organelles in elongating axon shafts. In particular, the intricate shape of the endoplasmic reticulum is consistent with its role in fulfilling the high demand for lipid biosynthesis to support growth. Furthermore, the scarcity of ribosomes within the growing shaft suggests limited translational competence during expansion of this compartment. These findings establish our approach as a powerful resource for investigating the ultrastructure of defined neuronal compartments.

Computational Evaluation of Abrogation of HBx-Bcl-xL Complex with High-Affinity Carbon Nanotubes (Fullerene) to Halt the Hepatitis B Virus Replication

Hepatitis B virus (HBV) is the world's most prevalent chronic viral infection. More than 350 million individuals are chronic carriers of the virus, with an estimated 2 billion infected persons. For instance, the role of HBx protein in attachment and infection is very obvious and consequently deemed as an important druggable target. Targeting the interface and discovering novel drugs greatly advanced the field of therapeutics development. Therefore, in the current study, HBx to Bcl-xL is abrogated on high-affinity carbon nanotubes using computational structural biology tools. Our analysis revealed that among the total 62 carbon fullerenes, only 13 compounds exhibited inhibitory activity against HBx, which was further confirmed through IFD-based rescoring. Structural dynamics investigation revealed stable binding, compactness, and hydrogen bonds reprogramming. Moreover, the binding free energy calculation results revealed that the top hits1-4 possess the total binding energy of -54.36 kcal/mol (hit1), -50.81 kcal/mol (hit2), -47.09 kcal/mol (hit3), and -45.59 kcal/mol for hit4. In addition, the predicted KD values and bioactivity scores further validated the inhibitory potential of these top hits. The identified compounds need further in vitro and in vivo validation to aid the treatment process of HBV.

A Supramolecular Antidote to Macromolecular Toxins Prepared through Coassembly of Macrocyclic Amphiphiles

Poisoning is a leading cause of admission to medical emergency departments and intensive care units. Supramolecular detoxification, which involves injecting supramolecular receptors that bind with toxins to suppress their biological activity, is an emerging strategy for poisoning treatment; it has few requirements and a broad application scope. However, it is still a formidable challenge to design supramolecular therapeutic materials as an antidote to macromolecular toxins, because the large size, flexible conformation, and presence of multiple and diverse binding sites of biomacromolecules hinder their recognition. Herein, a supramolecular antidote to macromolecular toxins is developed through the coassembly of macrocyclic amphiphiles, relying on heteromultivalent recognition between the coassembled components and toxic macromolecules. The coassembly of amphiphilic cyclodextrin and calixarene strongly and selectively captures melittin, a toxin studied herein; this imparts various therapeutic effects such as inhibiting the interactions of melittin with cell membranes, alleviating melittin cytotoxicity and hemolytic toxicity, reducing the mortality rate of melittin-poisoned mice, and mitigating damage to major organs. The use of the proposed antidote overcomes the limitation of supramolecular detoxification applicability to only small-molecular toxins. The antidote can also detoxify other macromolecular toxins as long as selective and strong binding is achieved because of the coassembling tunability.

Genesis of Neurotoxic Hybrid Nanofibers from the Coassembly of Aromatic Amino Acids

Considering the relevance of accumulation and self-assembly of metabolites and aftermath of biological consequences, it is important to know whether they undergo coassembly and what properties the resultant hybrid higher-order structures would exhibit. This work reveals the inherent tendency of aromatic amino acids to undergo a spontaneous coassembly process under physiologically mimicked conditions, which yields neurotoxic hybrid nanofibers. Resultant hybrid nanostructures resembled the β-structured conformers stabilized by H-bonds and π-π stacking interactions, which were highly toxic to human neuroblastoma cells. The hybrid nanofibers also showed strong cross-seeding potential that triggered in vitro aggregation of diverse globular proteins and brain extract components, converting the native structures into cross-β-rich amyloid aggregates. The heterogenic nature of the hybrid nanofibers seems crucial for their higher toxicity and faster cross-seeding potential as compared to the homogeneous amino acid nanofibers. Our findings reveal the importance of aromaticity-driven optimized intermolecular arrangements for the coassembly of aromatic amino acids, and the results may provide important clues to the fundamental understanding of metabolite accumulation-related complications.

Supramolecular Cylinders Target Bulge Structures in the 5' UTR of the RNA Genome of SARS-CoV-2 and Inhibit Viral Replication*

The untranslated regions (UTRs) of viral genomes contain a variety of conserved yet dynamic structures crucial for viral replication, providing drug targets for the development of broad spectrum anti-virals. We combine in vitro RNA analysis with molecular dynamics simulations to build the first 3D models of the structure and dynamics of key regions of the 5' UTR of the SARS-CoV-2 genome. Furthermore, we determine the binding of metallo-supramolecular helicates (cylinders) to this RNA structure. These nano-size agents are uniquely able to thread through RNA junctions and we identify their binding to a 3-base bulge and the central cross 4-way junction located in stem loop 5. Finally, we show these RNA-binding cylinders suppress SARS-CoV-2 replication, highlighting their potential as novel anti-viral agents.

A beginner's guideline for low-cost 3D printing of macromolecules usable for teaching and demonstration

The structure and function of biomolecules relationship is the hallmark of biochemistry, molecular biology, and life sciences in general. Physical models of macromolecules give students the possibility to manipulate these structures in three dimensions, developing a sense of spatiality and a better understanding of key aspects such as atom size and shape, bond lengths and symmetry. Several molecular model systems were developed specifically to represent particular classes or groups of molecules and hence lack the flexibility of a universal solution. Three-dimensional printing could nevertheless provide such a universal solution, as it can be used to create physical models of biomolecular structures based on the teacher's or demonstrator's needs and requirements. Here, insulin was used as a model molecule and several depiction and printing parameters were tested in order to highlight the technical limitations of the approach. In the end, a set of settings that worked is provided which could serve as a starting point for anyone wishing to print his or her own custom macromolecular model on the cheap.

Intra-vessel heterogeneity establishes enhanced sites of macromolecular leakage downstream of laminin α5

Endothelial cells display heterogeneous properties based on location and function. How this heterogeneity influences endothelial barrier stability both between and within vessel subtypes is unexplored. In this study, we find that endothelial cells exhibit heterogeneous barrier properties on inter-organ and intra-vessel levels. Using intravital microscopy and sequential stimulation of the ear dermis with vascular endothelial growth factor-A (VEGFA) and/or histamine, we observe distinct, reappearing sites, common for both agonists, where leakage preferentially takes place. Through repetitive stimulation of the diaphragm and trachea, we find inter-organ conservation of such predetermined leakage sites. Qualitatively, predetermined sites display distinct leakage properties and enhanced barrier breakdown compared to less susceptible regions. Mechanistically, laminin α5 is reduced at predetermined sites, which is linked to reduced junctional vascular endothelial (VE)-cadherin and enhanced VEGFA-induced VE-cadherin phosphorylation. These data highlight functional intra-vessel heterogeneity that defines predetermined sites with distinct leakage properties and that may disproportionately impact pathological vascular leakage.

Synapsin Condensates Recruit alpha-Synuclein

Neurotransmission relies on the tight spatial and temporal regulation of the synaptic vesicle (SV) cycle. Nerve terminals contain hundreds of SVs that form tight clusters. These clusters represent a distinct liquid phase in which one component of the phase are SVs and the other synapsin 1, a highly abundant synaptic protein. Another major family of disordered proteins at the presynapse includes synucleins, most notably α-synuclein. The precise physiological role of α-synuclein in synaptic physiology remains elusive, albeit its role has been implicated in nearly all steps of the SV cycle. To determine the effect of α-synuclein on the synapsin phase, we employ the reconstitution approach using natively purified SVs from rat brains and the heterologous cell system to generate synapsin condensates. We demonstrate that synapsin condensates recruit α-synuclein, and while enriched into these synapsin condensates, α-synuclein still maintains its high mobility. The presence of SVs enhances the rate of synapsin/α-synuclein condensation, suggesting that SVs act as catalyzers for the formation of synapsin condensates. Notably, at physiological salt and protein concentrations, α-synuclein alone is not able to cluster isolated SVs. Excess of α-synuclein disrupts the kinetics of synapsin/SV condensate formation, indicating that the molar ratio between synapsin and α-synuclein is important in assembling the functional condensates of SVs. Understanding the molecular mechanism of α-synuclein interactions at the nerve terminals is crucial for clarifying the pathogenesis of synucleinopathies, where α-synuclein, synaptic proteins and lipid organelles all accumulate as insoluble intracellular inclusions.