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.

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.

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.

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.

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.

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.

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-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.

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.

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.

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.

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.

Macromolecular crowding: Sensing without a sensor.

All living cells are crowded with macromolecules. Crowding can directly modulate biochemical reactions to various degrees depending on the sizes, shapes, and binding affinities of the reactants. Here, we explore the possibility that cells can sense and adapt to changes in crowding through the widespread modulation of biochemical reactions without the need for a dedicated sensor. Additionally, we explore phase separation as a general physicochemical response to changes in crowding, and a mechanism to both transduce information and physically restore crowding homeostasis.

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.

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.

Physicochemical homeostasis in bacteria.

In living cells, the biochemical processes such as energy provision, molecule synthesis, gene expression, and cell division take place in a confined space where the internal chemical and physical conditions are different from those in dilute solutions. The concentrations of specific molecules and the specific reactions and interactions vary for different types of cells, but a number of factors are universal and kept within limits, which we refer to as physicochemical homeostasis. For instance, the internal pH of many cell types is kept within the range of 7.0 to 7.5, the fraction of macromolecules occupies 15%-20% of the cell volume (also known as macromolecular crowding) and the ionic strength is kept within limits to prevent salting-in or salting-out effects. In this article we summarize the generic physicochemical properties of the cytoplasm of bacteria, how they are connected to the energy status of the cell, and how they affect biological processes (Fig. 1). We describe how the internal pH and proton motive force are regulated, how the internal ionic strength is kept within limits, what the impact of macromolecular crowding is on the function of enzymes and the interaction between molecules, how cells regulate their volume (and turgor), and how the cytoplasm is structured. Physicochemical homeostasis is best understood in Escherichia coli, but pioneering studies have also been performed in lactic acid bacteria.

Engineered molecular sensors for quantifying cell surface crowding.

Cells mediate interactions with the extracellular environment through a crowded assembly of transmembrane proteins, glycoproteins and glycolipids on their plasma membrane. The extent to which surface crowding modulates the biophysical interactions of ligands, receptors, and other macromolecules is poorly understood due to the lack of methods to quantify surface crowding on native cell membranes. In this work, we demonstrate that physical crowding on reconstituted membranes and live cell surfaces attenuates the effective binding affinity of macromolecules such as IgG antibodies in a surface crowding-dependent manner. We combine experiment and simulation to design a crowding sensor based on this principle that provides a quantitative readout of cell surface crowding. Our measurements reveal that surface crowding decreases IgG antibody binding by 2 to 20 fold in live cells compared to a bare membrane surface. Our sensors show that sialic acid, a negatively charged monosaccharide, contributes disproportionately to red blood cell surface crowding via electrostatic repulsion, despite occupying only ~1% of the total cell membrane by mass. We also observe significant differences in surface crowding for different cell types and find that expression of single oncogenes can both increase and decrease crowding, suggesting that surface crowding may be an indicator of both cell type and state. Our high-throughput, single-cell measurement of cell surface crowding may be combined with functional assays to enable further biophysical dissection of the cell surfaceome.

Developmental and regional dependence of macromolecular proton fraction and fractional anisotropy in fixed brain tissue.

An important advantage of imaging fixed tissue is a gain in signal-to-noise ratio and in resolution due to unlimited scan time. However, the fidelity of quantitative MRI parameters in fixed brain tissue, particularly in developmental settings, requires validation. Macromolecular proton fraction (MPF) and fractional anisotropy (FA) indices are quantitative markers of myelination and axonal integrity relevant to preclinical and clinical research. The goal of this study was to assert the correspondence of MR-derived markers of brain development MPF and FA between in vivo and fixed tissue measures. MPF and FA were compared in several white and gray matter structures of the normal mouse brain at 2, 4, and 12 weeks of age. At each developmental stage, in vivo imaging was performed, followed by paraformaldehyde fixation and a second imaging session. MPF maps were acquired from three source images (magnetization transfer weighted, proton density weighted, and T1 weighted), and FA was obtained from diffusion tensor imaging. The MPF and FA values, measured in the cortex, striatum, and major fiber tracts, were compared before and after fixation using Bland-Altman plots, regression analysis, and analysis of variance. MPF values of the fixed tissue were consistently greater than those from in vivo measurements. Importantly, this bias varied significantly with brain region and the developmental stage of the tissue. At the same time, FA values were preserved after fixation, across tissue types and developmental stages. The results of this study suggest that MPF and FA in fixed brain tissue can be used as a proxy for in vivo measurements, but additional considerations should be made to correct for the bias in MPF.

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.