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The proportions of carbon (C), nitrogen (N), and phosphorus (P) in surface ocean particulate matter deviate greatly from the canonical Redfield Ratio (C:N:P = 106:16:1) in space and time with significant implications for global carbon storage as this matter reaches the deep ocean. Recent work has revealed clear latitudinal patterns in C:N:P, yet the relative importance of ecological, physiological, or biochemical processes in creating these patterns is unclear. We present high-resolution, concurrent measurements of particulate C:N:P, macromolecular composition, environmental conditions, and plankton community composition from a transect spanning a subtropical-subpolar boundary, the North Pacific Transition Zone. We find that the summed contribution of macromolecules to particulate C, N, and P is consistent with, and provides interpretation for, particulate C:N:P patterns. A decline in particulate C:N from the subtropical to subpolar North Pacific largely reflects an increase in the relative contribution of protein compared to carbohydrate and lipid, whereas variation in C:P and N:P correspond to shifts in protein relative to polyphosphate, DNA, and RNA. Possible causes for the corresponding trends in C:N and macromolecular composition include physiological responses and changes in community structure of phytoplankton, which represented approximately 1/3 rd of particulate C across the transect. Comparison with culture experiments and an allocation-based model of phytoplankton macromolecular composition suggest that physiological acclimation to changing nutrient supply is the most likely explanation for the latitudinal trend in C:N, offering both a mechanistic interpretation and biochemical basis for large-scale patterns in C:N:P., Competing Interests: Competing interests statement:The authors declare no competing interest.

The mechanisms contributing to age-related deterioration of the female reproductive system are complex, however aberrant protein homeostasis is a major contributor. We elucidated exceptionally stable proteins, structures, and macromolecules that persist in mammalian ovaries and gametes across the reproductive lifespan. Ovaries exhibit localized structural and cell-type-specific enrichment of stable macromolecules in both the follicular and extrafollicular environments. Moreover, ovaries and oocytes both harbor a panel of exceptionally long-lived proteins, including cytoskeletal, mitochondrial, and oocyte-derived proteins. The exceptional persistence of these long-lived molecules suggest a critical role in lifelong maintenance and age-dependent deterioration of reproductive tissues., Competing Interests: EB, KV, LZ, CG, SE, MS, JS, FD No competing interests declared, (© 2024, Bomba-Warczak, Velez et al.)

Temporal control over self-assembly processes is a highly desirable attribute that is efficiently exhibited by biological systems, such as actin filaments. In nature, various proteins undergo enzymatically catalysed chemical reactions that kinetically govern their structural and functional properties. Consequently, any stimuli that can alter their reaction kinetics can lead to a change in their growth or decay profiles. This underscores the urgent need to investigate bioinspired, adaptable and controllable synthetic materials. Herein we intend to develop a general strategy for controlling the growth and decay of self-assembled systems via enzymatically coupled reactions. We achieve this by the coupling of enzymes phosphokinase/phosphatase with a bolaamphiphilic cationic chromophore (PDI) which selectively self-assembles with ATP and disassembles upon its enzymatic hydrolysis. The aggregation process is efficiently regulated by the controlled in situ generation of ATP, through enzymatic reactions. By carefully managing the ATP generating components, we realize precise control over the self-assembly process. Moreover, we also show self-assembled structures with programmed temporal decay profiles through coupled enzymatic reactions of ATP generation and hydrolysis, essentially rendering the process dissipative. This work introduces a novel strategy to generate a reaction-coupled one-dimensional nanostructure with controlled dimensions inspired by biological systems.

Purpose: The J-difference edited γ-aminobutyric acid (GABA) signal is contaminated by other co-edited signals-the largest of which originates from co-edited macromolecules (MMs)-and is consequently often reported as "GABA+." MM signals are broader and less well-characterized than the metabolites, and are commonly approximated using a Gaussian model parameterization. Experimentally measured MM signals are a consensus-recommended alternative to parameterized modeling; however, they are relatively under-studied in the context of edited MRS., Methods: To address this limitation in the literature, we have acquired GABA-edited MEGA-PRESS data with pre-inversion to null metabolite signals in 13 healthy controls. An experimental MM basis function was derived from the mean across subjects. We further derived a new parameterization of the MM signals from the experimental data, using multiple Gaussians to accurately represent their observed asymmetry. The previous single-Gaussian parameterization, mean experimental MM spectrum and new multi-Gaussian parameterization were compared in a three-way analysis of a public MEGA-PRESS dataset of 61 healthy participants., Results: Both the experimental MMs and the multi-Gaussian parameterization exhibited reduced fit residuals compared to the single-Gaussian approach (p = 0.034 and p = 0.031, respectively), suggesting they better represent the underlying data than the single-Gaussian parameterization. Furthermore, both experimentally derived models estimated larger MM fractional contribution to the GABA+ signal for the experimental MMs (58%) and multi-Gaussian parameterization (58%), compared to the single-Gaussian approach (50%)., Conclusions: Our results indicate that single-Gaussian parameterization of edited MM signals is insufficient and that both experimentally derived GABA+ spectra and their parameterized replicas improve the modeling of GABA+ spectra., (© 2024 International Society for Magnetic Resonance in Medicine.)

Phytoplankton Chl:C:N:P ratios are important from both an ecological and a biogeochemical perspective. We show that these elemental ratios can be represented by a phytoplankton physiological model of low complexity that includes major cellular macromolecular pools. In particular, our model resolves time-dependent intracellular pools of chlorophyll, proteins, nucleic acids, carbohydrates/lipids, and N and P storage. Batch culture data for two diatom and two prasinophyte species are used to constrain parameters that represent specific allocation traits and strategies. A key novelty is the simultaneous estimation of physiological parameters for two phytoplankton groups of such different sizes. The number of free parameters is reduced by assuming (i) allometric scaling for maximum uptake rates, (ii) shared half-saturation constants for synthesis of functional macromolecules, (iii) shared exudation rates of functional macromolecules across the species. The rationale behind this assumption is that across the different species, the same or similar processes, enzymes, and metabolites play a role in key physiological processes. For the turnover numbers of macromolecular synthesis and storage exudation rates, differences between diatoms and prasinophytes need to be taken into account to obtain a good fit. Our model fits suggest that the parameters related to storage dynamics dominate the differences in the C:N:P ratios between the different phytoplankton groups. Since descriptions of storage dynamics are still incomplete and imprecise, predictions of C:N:P ratios by phytoplankton models likely have a large uncertainty., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Supramolecular chemistry focuses on the study of species joined by non-covalent interactions, and therefore on dynamic and relatively ill-defined structures. Despite being a well-developed field, it has to face important challenges when dealing with the selective recognition of biomolecules in highly competitive biomimetic media. However, supramolecular interactions reside at the core of chemical biology systems, since many processes in nature are governed by weak, non-covalent, strongly dynamic contacts. Therefore, there is a natural connection between these two research fields, which are not frequently related or share interests. In this feature article, I will highlight our most recent results in the molecular recognition of biologically relevant species, following different conceptual approaches from the most conventional design of elaborated receptors to the less popular dynamic combinatorial chemistry methodology. Selected illustrative examples from other groups will be also included. The discussion has been focused mainly on systems with potential biomedical applications.

Protein synthesis methods have been adapted to incorporate an ever-growing level of non-natural components. Meanwhile, design of de novo protein structure and function has rapidly emerged as a viable capability. Yet, these two exciting trends have yet to intersect in a meaningful way. The ability to perform de novo design with non-proteinogenic components requires that synthesis and computation align on common targets and applications. This perspective examines the state of the art in these areas and identifies specific, consequential applications to advance the field toward generalized macromolecule design.

Proteins are known to perform an astonishing array of functions thanks to their ability to cooperate and modulate each other's properties. Inside cells, proteins can assemble into large multi-subunit complexes to carry out complex cellular functions. The correct assembly and maintenance of the functional state of macromolecular protein complexes is crucial for human health. Failure to do so leads to loss of function and potential accumulation of harmful materials, which is associated with a variety of human diseases such as neurodegeneration and cancer. Autophagy engulfs cytosolic material in autophagosomes, and therefore is best suited to eliminate intact macromolecular complexes without disassembling them, which could interfere with de novo assembly. In this review, we discuss the role of autophagy in the selective degradation of macromolecular complexes. We highlight the current state of knowledge for different macromolecular complexes and their selective autophagic degradation. We emphasize the gaps in our understanding of what it takes for these large macromolecular complexes to be degraded and point to future work that may shed light on the regulation of the selective degradation of macromolecular complexes by autophagy., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Successful in vitro culture of small-diameter tissue-engineered vascular grafts (TEVGs) requires rapid deposition of biomacromolecules secreted by vascular smooth muscle cells in a polyglycolic acid mesh scaffold's three-dimensional (3D) porous environment. However, common media have lower crowding conditions than in vivo tissue fluids. In addition, during the early stages of construction, most of the biomolecules secreted by the cells into the medium are lost, which negatively affects the TEVG culture process. In this study, we propose the use of macromolecular crowding (MMC) to enhance medium crowding to improve the deposition and self-assembly efficiency of major biomolecules in the early stages of TEVG culture. The addition of carrageenan significantly increased the degree of MMC in the culture medium without affecting cell viability, proliferation, and metabolic activity. Protein analysis demonstrated that the deposition of collagen types I and III and fibronectin increased significantly in the cell layers of two-dimensional and 3D smooth muscle cell cultures after the addition of a MMC agent. Collagen type I in the culture medium decreased significantly compared with that in the medium without a MMC agent. Scanning electron microscopy demonstrated that MMC agents considerably enhanced the formation of matrix protein structures during the early stages of 3D culture. Hence, MMC modifies the crowding degree of the culture medium, resulting in the rapid formation of numerous matrix proteins and fiber structures. Impact Statement Small-diameter tissue-engineered vascular grafts (TEVGs) are one of the most promising means of treating cardiovascular diseases; however, the in vitro construction of TEVGs has some limitations, such as slow deposition of extracellular matrix (ECM), long culture period, and poor mechanical properties. We hypothesized that macromolecular crowding can increase the crowding of the culture medium to construct a more bionic microenvironment, which enhances ECM deposition in the medium to the cell layer and reduces collagen loss, accelerating and enhancing TEVG culture and construction in vitro .

As the landscape of macromolecule therapeutics advances, drug developers are continuing to aim at intracellular targets. To activate, inhibit, or degrade these targets, the macromolecule must be delivered efficiently to intracellular compartments. Quite often, there is a discrepancy between binding affinity in biochemical assays and activity in cell-based assays. Identifying the bottleneck for cell-based activity requires robust assays that quantify total cellular uptake and/or cytosolic delivery. Recognizing this need, chemical biologists have designed a plethora of assays to make this measurement, each with distinct advantages and disadvantages. In this review, we describe the latest and most promising developments in the last 3 to 4 years., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Numerous non-cardiovascular drugs have a potential to induce life-threatening torsades de pointes (TdP) ventricular cardiac arrhythmias by blocking human ether-à-go-go-related gene (hERG) currents via binding to the channel's inner cavity. Identification of the hERG current-inhibiting properties of candidate drugs is performed focusing on binding sites in the channel pore. It has been suggested that biologicals have a low likelihood of hERG current inhibition, since their poor diffusion across the plasma membrane prevents them from reaching the binding site in the channel pore. However, biologicals could influence hERG channel function by binding to 'unconventional' noncanonical binding sites. This Opinion gives an overview on noncanonical blockers of hERG channels that might be of relevance for the assessment of the possible torsadogenic potential of macromolecular therapeutics., Competing Interests: Declaration of interests The author declares no conflicts of interest., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

In biological systems, the activities of macromolecular complexes must sometimes be turned off. Thus, a wide variety of protein inhibitors has evolved for this purpose. These inhibitors function through diverse mechanisms, including steric blocking of crucial interactions, enzymatic modification of key residues or substrates, and perturbation of post-translational modifications 1 . Anti-CRISPRs-proteins that block the activity of CRISPR-Cas systems-are one of the largest groups of inhibitors described, with more than 90 families that function through diverse mechanisms 2-4 . Here, we characterize the anti-CRISPR AcrIF25, and we show that it inhibits the type I-F CRISPR-Cas system by pulling apart the fully assembled effector complex. AcrIF25 binds to the predominant CRISPR RNA-binding components of this complex, comprising six Cas7 subunits, and strips them from the RNA. Structural and biochemical studies indicate that AcrIF25 removes one Cas7 subunit at a time, starting at one end of the complex. Notably, this feat is achieved with no apparent enzymatic activity. To our knowledge, AcrIF25 is the first example of a protein that disassembles a large and stable macromolecular complex in the absence of an external energy source. As such, AcrIF25 establishes a paradigm for macromolecular complex inhibitors that may be used for biotechnological applications., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

Bioaugmentation retting with the specialized pectinolytic and xylanolytic microorganisms can accelerate the removal of non-cellulosic macromolecules around plant fibers, thus shortening retting time and facilitating fiber quality. Currently, few specialized microorganisms have been explored for the retting of sisal fibers. The present study excavated the retting fungi including Aspergillus micronesiensis HD 3-6, Penicillium citrinum HD 3-12-3, and Cladosporium sp. HD 4-13 from the region-specific soil samples of planting sisal, and investigated their bioaugmentation retting effects on raw sisal leaves. Results showed that combination of the three fungi achieved the most excellent degumming efficiency (13.69 % of residual gum in sisal fibers) and the highest fiber yield (4.47 %). Furthermore, this fungi combination had the ideal enzymatic hydrolysis features with high activities of pectinase, xylanase and mannanase whereas a low activity of cellulase during the whole retting process, thus endowing the prepared sisal fibers with the lowest mass percentage of non-cellulosic macromolecules (9.76 wt%) and the highest cellulose content (89.23 wt%). SEM and FT-IR analysis further verified that the non-cellulosic substances around sisal fibers were efficiently removed. In summary, the consortia of the three fungi achieved ideal degumming-related enzymes for the removal of non-cellulosic macromolecules, thus acquiring the efficient preparation of sisal fibers., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Osmotic stress conditions occur at multiple stages of plant life. Changes in water availability caused by osmotic stress induce alterations in the mechanical properties of the plasma membrane, its interaction with the cell wall, and the concentration of macromolecules in the cytoplasm. We summarize the reported players involved in the sensing mechanisms of osmotic stress in plants. We discuss how changes in macromolecular crowding are perceived intracellularly by intrinsically disordered regions (IDRs) in proteins. Finally, we review methods for dynamically monitoring macromolecular crowding in living cells and discuss why their implementation is required for the discovery of new plant osmosensors. Elucidating the osmosensing mechanisms will be essential for designing strategies to improve plant productivity in the face of climate change., Competing Interests: Declaration of interests None declared., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

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.

Nature employs sophisticated mechanisms to precisely regulate self-assembly and functions within biological systems, exemplified by the formation of cytoskeletal filaments. Various enzymatic reactions and auxiliary proteins couple with the self-assembly process, meticulously regulating the length and functions of resulting macromolecular structures. In this context, we present a bioinspired, reaction-coupled approach for the controlled supramolecular polymerization in synthetic systems. To achieve this, we employ an enzymatic reaction that interfaces with the adenosine triphosphate (ATP)-templated supramolecular polymerization of naphthalene diimide monomers ( NSG ). Notably, the enzymatic production of ATP (template) plays a pivotal role in facilitating reaction-controlled, cooperative growth of the NSG monomers. This growth process, in turn, provides positive feedback to the enzymatic production of ATP, creating an ideal reaction-coupled assembly process. The success of this approach is further evident in the living-growth characteristic observed during seeding experiments, marking this method as the pioneering instance where reaction-coupled self-assembly precisely controls the growth kinetics and structural aspects of supramolecular polymers in a predictive manner, akin to biological systems.

Controlled manipulation of cultured cells by delivery of exogenous macromolecules is a cornerstone of experimental biology. Here we describe a platform that uses nanopipettes to deliver defined numbers of macromolecules into cultured cell lines and primary cells at single molecule resolution. In the nanoinjection platform, the nanopipette is used as both a scanning ion conductance microscope (SICM) probe and an injection probe. The SICM is used to position the nanopipette above the cell surface before the nanopipette is inserted into the cell into a defined location and to a predefined depth. We demonstrate that the nanoinjection platform enables the quantitative delivery of DNA, globular proteins, and protein fibrils into cells with single molecule resolution and that delivery results in a phenotypic change in the cell that depends on the identity of the molecules introduced. Using experiments and computational modeling, we also show that macromolecular crowding in the cell increases the signal-to-noise ratio for the detection of translocation events, thus the cell itself enhances the detection of the molecules delivered., (© 2024. The Author(s).)

Due to the high concentration of proteins, nucleic acids, and other macromolecules, the bacterial cytoplasm is typically described as a crowded environment. However, the extent to which each of these macromolecules individually affects the mobility of macromolecular complexes, and how this depends on growth conditions, is presently unclear. In this study, we sought to quantify the crowding experienced by an exogenous 40 nm fluorescent particle in the cytoplasm of E. coli under different growth conditions. By performing single-particle tracking measurements in cells selectively depleted of DNA and/or mRNA, we determined the contribution to crowding of mRNA, DNA, and remaining cellular components, i.e., mostly proteins and ribosomes. To estimate this contribution to crowding, we quantified the difference of the particle's diffusion coefficient in conditions with and without those macromolecules. We found that the contributions of the three classes of components were of comparable magnitude, being largest in the case of proteins and ribosomes. We further found that the contributions of mRNA and DNA to crowding were significantly larger than expected based on their volumetric fractions alone. Finally, we found that the crowding contributions change only slightly with the growth conditions. These results reveal how various cellular components partake in crowding of the cytoplasm and the consequences this has for the mobility of large macromolecular complexes., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 Biophysical Society. Published by Elsevier Inc. All rights reserved.)

Macromolecules exhibit ordered structures and complex functions in an aqueous environment with strong thermodynamic fluctuations [...].

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., Competing Interests: Competing interests statement:The authors declare no competing interest.

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., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

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., Competing Interests: Declaration of competing interest The authors declare that they have no affiliations with or involvement in any organization or entity with any financial interest in the subject matter or materials discussed in this manuscript., (Copyright © 2024 Elsevier B.V. All rights reserved.)

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., (© 2024 Federation of European Biochemical Societies.)

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.

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., (© 2023 John Wiley & Sons, Ltd.)

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., (© 2024. Springer Nature Limited.)

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 (T 1m , T 2m ), reference-specific (T 1ref , T 2ref ), and sequence-specific (T R , T E ) 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., (© 2023 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

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

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.

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.

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., (Copyright © 2024. Published by Elsevier Inc.)

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., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

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., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Optimum protein function and biochemical activity critically depends on water availability because solvent thermodynamics drive protein folding and macromolecular interactions 1 . 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 timescales 2,3 ; 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., (© 2023. The Author(s).)

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.

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.

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., (© The Author(s) 2023. Published by Oxford University Press on behalf of FEMS.)

Neurochemical concentrations determined by magnetic resonance spectroscopy (MRS) have been treated as statistically independent measurements in various clinical MRS studies. However, spectral overlap, independent of any biological effects, could lead to significant correlations between neurochemical concentrations extracted from spectral fitting of MRS data, confounding determination of correlations of biological origin. Short echo time (TE) proton MRS spectra are very crowded because of the comparatively narrow chemical shift dispersion of proton nuclear spins. In this study, the complex neurochemical correlations of spectral origin in short-TE MRS spectra were quantified. The effects of macromolecules and the background spectral baseline on metabolite-metabolite correlations were also analyzed. Our results demonstrate the importance of factoring in spectral correlations when correlating overlapping metabolite signals in short-TE spectra with clinical parameters., (Published 2023. This article is a U.S. Government work and is in the public domain in the USA.)

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 T 1 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., (© 2023 John Wiley & Sons Ltd.)

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.

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.

Macromolecules of various sizes induce crowding of the cellular environment. This crowding impacts on biochemical reactions by increasing solvent viscosity, decreasing the water-accessible volume and altering protein shape, function, and interactions. Although mitochondria represent highly protein-rich organelles, most of these proteins are somehow immobilized. Therefore, whether the mitochondrial matrix solvent exhibits macromolecular crowding is still unclear. Here, we demonstrate that fluorescent protein fusion peptides (AcGFP1 concatemers) in the mitochondrial matrix of HeLa cells display an elongated molecular structure and that their diffusion constant decreases with increasing molecular weight in a manner typical of macromolecular crowding. Chloramphenicol (CAP) treatment impaired mitochondrial function and reduced the number of cristae without triggering mitochondrial orthodox-to-condensed transition or a mitochondrial unfolded protein response. CAP-treated cells displayed progressive concatemer immobilization with increasing molecular weight and an eightfold matrix viscosity increase, compatible with increased macromolecular crowding. These results establish that the matrix solvent exhibits macromolecular crowding in functional and dysfunctional mitochondria. Therefore, changes in matrix crowding likely affect matrix biochemical reactions in a manner depending on the molecular weight of the involved crowders and reactants., (© 2023 The Authors. Published under the terms of the CC BY NC ND 4.0 license.)

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., Competing Interests: Conflict of interest statement Nothing declared., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

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., (© 2022 John Wiley & Sons Ltd.)

Standard cell cultures are performed in aqueous media with a low macromolecule concentration compared to tissue microenvironment. In macromolecular crowding (MMC) experiments, synthetic polymeric crowders are added into cell culture media to better mimic macromolecule concentrations found in vivo. However, their effect on cultured cells is incompletely understood and appears context-dependent. Here we show using human gingival fibroblasts, a cell type associated with fast and scarless wound healing, that MMC (standard medium supplemented with Ficoll 70/400) potently modulates fibroblast phenotype and extracellular matrix (ECM) composition compared to standard culture media (nMMC) over time. MMC significantly reduced cell numbers, but increased accumulation of collagen I, cellular fibronectin, and tenascin C, while suppressing level of SPARC (Secreted Protein Acidic and Cysteine Rich). Out of the 75 wound healing and ECM related genes studied, MMC significantly modulated expression of 25 genes compared to nMMC condition. MMC also suppressed myofibroblast markers and promoted deposition of basement membrane molecules collagen IV, laminin 1, and expression of LAMB3 (Laminin Subunit Beta 3) gene. In cell-derived matrices produced by a novel decellularization protocol, the altered molecular composition of MMC matrices was replicated. Thus, MMC may improve cell culture models for research and provide novel approaches for regenerative therapy., (© 2023. The Author(s).)

Purpose: This study analyzes the effects of retrospective lipid suppression, a simulated macromolecular prior knowledge and different spline baseline stiffness values on 9.4T multi-slice proton FID-MRSI data spanning the whole cerebrum of human brain and the reproducibility of respective metabolite ratio to total creatine (/tCr) maps for 10 brain metabolites., Methods: Measurements were performed twice on 5 volunteers using a short TR and TE FID MRSI 2D sequence at 9.4T. The effects of retrospective lipid L2-regularization, macromolecular spectrum and different LCModel baseline flexibilities on SNR, FWHM, fitting residual, Cramér-Rao lower bound, and metabolite ratio maps were investigated. Intra-subject, inter-session coefficient of variation and the test-retest reproducibility of the mean metabolite ratios (/tCr) of each slice was calculated., Results: Transversal, sagittal, and coronal slices of many metabolite ratio maps correspond to the anatomically expected concentration relations in gray and white matter for the majority of the cerebrum when using a flexible baseline in LCModel fit. Results from the second measurements of the same subjects show that slice positioning and data quality correlate significantly to the first measurement. L2-regularization provided effective suppression of lipid-artifacts, but should be avoided if no artifacts are detected., Conclusion: Reproducible concentration ratio maps (/tCr) for 4 metabolites (total choline, N-acetylaspartate, glutamate, and myoinositol) spanning the majority of the cerebrum and 6 metabolites (N-acetylaspartylglutamate, γ-aminobutyric acid, glutathione, taurine, glutamine, and aspartate) covering 32 mm in the upper part of the brain were acquired at 9.4T using multi-slice FID MRSI with retrospective lipid suppression, a macromolecular spectrum and a flexible LCModel baseline., (© 2022 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

Secretory proteins play an important role in the tumor microenvironment and are widely distributed throughout tumor tissues. Tumor cells secrete a protein that mediates communication between tumor cells and stromal cells, thereby controlling tumor growth and affecting the success of cancer treatments in the clinic. The cancer secretome is produced by various secretory pathways and has a wide range of applications in oncoproteomics. Secretory proteins are involved in cancer development and tumor cell migration, and thus serve as biomarkers or effective therapeutic targets for a variety of cancers. Several proteomic strategies have recently been used for the analysis of cancer secretomes in order to gain a better understanding and elaborate interpretation. For instance, the development of exosome proteomics, degradomics, and tumor-host cell interaction provide clear information regarding the mechanism of cancer pathobiology. In this chapter, we emphasize the recent advances in secretory protein and the challenges in the field of secretome analysis and their clinical applications., (Copyright © 2023 Elsevier Inc. All rights reserved.)

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., (© 2022 S. Karger AG, Basel.)

Cell-free protein synthesis is an important tool for studying gene expression and harnessing it for applications. In cells, gene expression is regulated in part by the spatial organization of transcription and translation. Unfortunately, current cell-free approaches are unable to control the organization of molecular components needed for gene expression, which limits the ability to probe and utilize its effects. Here, we show, using complementary computational and experimental approaches, that macromolecular crowding can be used to control the spatial organization and translational efficiency of gene expression in cell-sized vesicles. Computer simulations and imaging experiments reveal that, as crowding is increased, DNA plasmids become localized at the inner surface of vesicles. Ribosomes, in contrast, remain uniformly distributed, demonstrating that crowding can be used to differentially organize components of gene expression. We further carried out cell-free protein synthesis reactions in cell-sized vesicles and quantified mRNA and protein abundance. At sufficiently high levels of crowding, we observed localization of mRNA near vesicle surfaces, a decrease in translational efficiency and protein abundance, and anomalous scaling of protein abundance as a function of vesicle size. These results are consistent with high levels of crowding causing altered spatial organization and slower diffusion. Our work demonstrates a straightforward way to control the organization of gene expression in cell-sized vesicles and provides insight into the spatial regulation of gene expression in cells.