Biomolecular Condensates: Structure, Functions, Methods of Research.

The term "biomolecular condensates" is used to describe membraneless compartments in eukaryotic cells, accumulating proteins and nucleic acids. Biomolecular condensates are formed as a result of liquid-liquid phase separation (LLPS). Often, they demonstrate properties of liquid-like droplets or gel-like aggregates; however, some of them may appear to have a more complex structure and high-order organization. Membraneless microcompartments are involved in diverse processes both in cytoplasm and in nucleus, among them ribosome biogenesis, regulation of gene expression, cell signaling, and stress response. Condensates properties and structure could be highly dynamic and are affected by various internal and external factors, e.g., concentration and interactions of components, solution temperature, pH, osmolarity, etc. In this review, we discuss variety of biomolecular condensates and their functions in live cells, describe their structure variants, highlight domain and primary sequence organization of the constituent proteins and nucleic acids. Finally, we describe current advances in methods that characterize structure, properties, morphology, and dynamics of biomolecular condensates in vitro and in vivo.

In-Person Visits Before Initiation of Telemedicine for Mental Illness.

This cross-sectional study examines how often patients had an in-person visit before initiating telemedicine for mental illness between 2019 and 2022.

Maturation and Conformational Switching of a De Novo Designed Phase-Separating Polypeptide.

Cellular compartments formed by biomolecular condensation are widespread features of cell biology. These organelle-like assemblies compartmentalize macromolecules dynamically within the crowded intracellular environment. However, the intermolecular interactions that produce condensed droplets may also create arrested states and potentially pathological assemblies such as fibers, aggregates, and gels through droplet maturation. Protein liquid-liquid phase separation is a metastable process, so maturation may be an intrinsic property of phase-separating proteins, where nucleation of different phases or states arises in supersaturated condensates. Here, we describe the formation of both phase-separated droplets and proteinaceous fibers driven by a de novo designed polypeptide. We characterize the formation of supramolecular fibers in vitro and in bacterial cells. We show that client proteins can be targeted to the fibers in cells using a droplet-forming construct. Finally, we explore the interplay between phase separation and fiber formation of the de novo polypeptide, showing that the droplets mature with a post-translational switch to largely ß conformations, analogous to models of pathological phase separation.

Grow now, pay later: When should a bacterium go into debt?

Microbes grow in a wide variety of environments and must balance growth and stress resistance. Despite the prevalence of such trade-offs, understanding of their role in nonsteady environments is limited. In this study, we introduce a mathematical model of "growth debt," where microbes grow rapidly initially, paying later with slower growth or heightened mortality. We first compare our model to a classical chemostat experiment, validating our proposed dynamics and quantifying Escherichia coli's stress resistance dynamics. Extending the chemostat theory to include serial-dilution cultures, we derive phase diagrams for the persistence of "debtor" microbes. We find that debtors cannot coexist with nondebtors if "payment" is increased mortality but can coexist if it lowers enzyme affinity. Surprisingly, weak noise considerably extends the persistence of resistance elements, pertinent for antibiotic resistance management. Our microbial debt theory, broadly applicable across many environments, bridges the gap between chemostat and serial dilution systems.

Phototrophic Fe(II) oxidation benefits from light/dark cycles.

Phototrophic Fe(II)-oxidizers use Fe(II) as electron donor for CO2 fixation thus linking Fe(II) oxidation, ATP formation, and growth directly to the availability of sunlight. We compared the effect of short (10 h light/14 h dark) and long (2-3 days light/2-3 days dark) light/dark cycles to constant light conditions for the phototrophic Fe(II)-oxidizer Chlorobium ferrooxidans KoFox. Fe(II) oxidation was completed first in the setup with constant light (9 mM Fe(II) oxidised within 8.9 days) compared to the light/dark cycles but both short and long light/dark cycles showed faster maximum Fe(II) oxidation rates. In the short and long cycle, Fe(II) oxidation rates reached 3.5 ± 1.0 and 2.6 ± 0.3 mM/d, respectively, compared to 2.1 ± 0.3 mM/d in the constant light setup. Maximum Fe(II) oxidation was significantly faster in the short cycle compared to the constant light setup. Cell growth reached roughly equivalent cell numbers across all three light conditions (from 0.2-2.0 × 106 cells/mL to 1.1-1.4 × 108 cells/mL) and took place in both the light and dark phases of incubation. SEM images showed different mineral structures independent of the light setup and 57 Fe Mössbauer spectroscopy confirmed the formation of poorly crystalline Fe(III) oxyhydroxides (such as ferrihydrite) in all three setups. Our results suggest that periods of darkness have a significant impact on phototrophic Fe(II)-oxidizers and significantly influence rates of Fe(II) oxidation.

Not Only Metabolic Complications of Childhood Obesity.

The increasing incidence of obesity in the pediatric population requires attention to its serious complications. It turns out that in addition to typical, well-known metabolic complications, obesity as a systemic disease carries the risk of equally serious, although less obvious, non-metabolic complications, such as cardiovascular diseases, polycystic ovary syndrome, chronic kidney disease, asthma, thyroid dysfunction, immunologic and dermatologic conditions, and mental health problems. They can affect almost all systems of the young body and also leave their mark in adulthood. In addition, obesity also contributes to the exacerbation of existing childhood diseases. As a result, children suffering from obesity may have a reduced quality of life, both physically and mentally, and their life expectancy may be shortened. It also turns out that, in the case of obese pregnant girls, the complications of obesity may also affect their unborn children. Therefore, it is extremely important to take all necessary actions to prevent the growing epidemic of obesity in the pediatric population, as well as to treat existing complications of obesity and detect them at an early stage. In summary, physicians treating a child with a systemic disease such as obesity must adopt a holistic approach to treatment.

Multimodal mass spectrometry imaging identifies cell-type-specific metabolic and lipidomic variation in the mammalian liver.

Spatial single-cell omics provides a readout of biochemical processes. It is challenging to capture the transient lipidome/metabolome from cells in a native tissue environment. We employed water gas cluster ion beam secondary ion mass spectrometry imaging ([H2O]n>28K-GCIB-SIMS) at ≤3 µm resolution using a cryogenic imaging workflow. This allowed multiple biomolecular imaging modes on the near-native-state liver at single-cell resolution. Our workflow utilizes desorption electrospray ionization (DESI) to build a reference map of metabolic heterogeneity and zonation across liver functional units at tissue level. Cryogenic dual-SIMS integrated metabolomics, lipidomics, and proteomics in the same liver lobules at single-cell level, characterizing the cellular landscape and metabolic states in different cell types. Lipids and metabolites classified liver metabolic zones, cell types and subtypes, highlighting the power of spatial multi-omics at high spatial resolution for understanding celluar and biomolecular organizations in the mammalian liver.

PAF1c links S-phase progression to immune evasion and MYC function in pancreatic carcinoma.

In pancreatic ductal adenocarcinoma (PDAC), endogenous MYC is required for S-phase progression and escape from immune surveillance. Here we show that MYC in PDAC cells is needed for the recruitment of the PAF1c transcription elongation complex to RNA polymerase and that depletion of CTR9, a PAF1c subunit, enables long-term survival of PDAC-bearing mice. PAF1c is largely dispensable for normal proliferation and regulation of MYC target genes. Instead, PAF1c limits DNA damage associated with S-phase progression by being essential for the expression of long genes involved in replication and DNA repair. Surprisingly, the survival benefit conferred by CTR9 depletion is not due to DNA damage, but to T-cell activation and restoration of immune surveillance. This is because CTR9 depletion releases RNA polymerase and elongation factors from the body of long genes and promotes the transcription of short genes, including MHC class I genes. The data argue that functionally distinct gene sets compete for elongation factors and directly link MYC-driven S-phase progression to tumor immune evasion.

Correlation of Pseudomonas aeruginosa Phage Resistance with the Numbers and Types of Antiphage Systems.

Phage therapeutics offer a potentially powerful approach for combating multidrug-resistant bacterial infections. However, to be effective, phage therapy must overcome existing and developing phage resistance. While phage cocktails can reduce this risk by targeting multiple receptors in a single therapeutic, bacteria have mechanisms of resistance beyond receptor modification. A rapidly growing body of knowledge describes a broad and varied arsenal of antiphage systems encoded by bacteria to counter phage infection. We sought to understand the types and frequencies of antiphage systems present in a highly diverse panel of Pseudomonas aeruginosa clinical isolates utilized to characterize novel antibacterials. Using the web-server tool PADLOC (prokaryotic antiviral defense locator), putative antiphage systems were identified in these P. aeruginosa clinical isolates based on sequence homology to a validated and curated catalog of known defense systems. Coupling this host bacterium sequence analysis with host range data for 70 phages, we observed a correlation between existing phage resistance and the presence of higher numbers of antiphage systems in bacterial genomes. We were also able to identify antiphage systems that were more prevalent in highly phage-resistant P. aeruginosa strains, suggesting their importance in conferring resistance.

Solid-State Molecular Protonics Devices of Solid-Supported Biological Membranes Reveal the Mechanism of Long-Range Lateral Proton Transport.

Lateral proton transport (PT) on the surface of biological membranes is a fundamental biochemical process in the bioenergetics of living cells, but a lack of available experimental techniques has resulted in a limited understanding of its mechanism. Here, we present a molecular protonics experimental approach to investigate lateral PT across membranes by measuring long-range (70 µm) lateral proton conduction via a few layers of lipid bilayers in a solid-state-like environment, i.e., without having bulk water surrounding the membrane. This configuration enables us to focus on lateral proton conduction across the surface of the membrane while decoupling it from bulk water. Hence, by controlling the relative humidity of the environment, we can directly explore the role of water in the lateral PT process. We show that proton conduction is dependent on the number of water molecules and their structure and on membrane composition, where we explore the role of the headgroup, the tail saturation, the membrane phase, and membrane fluidity. The measured PT as a function of temperature shows an inverse temperature dependency, which we explain by the desorption and adsorption of water molecules into the solid membrane platform. We explain our findings by discussing the role of percolating hydrogen bonding within the membrane structure in a Grotthuss-like mechanism.

The toxicity response of the electrochemical signal of the cell to the drug metabolized by the S9 system.

The electrochemical detection method of cytotoxicity using intracellular purines as biomarkers has shown great potential for in vitro drug toxicity evaluation. However, no electrochemical detection system based on an in vitro drug metabolism mechanism has been devised. In this paper, electrochemical voltammetry was used to investigate the effect of the S9 system on the electrochemical behavior of HepG2 cells, and benzo[a]pyrene, fluoranthene, and pyrene were employed to investigate the sensitivity of electrochemical signals of cells to the cytotoxicity of drugs metabolized by the S9 system. The results showed that, within 8 h of exposure to the S9 system, the electrochemical signal of HepG2 cells at 0.7 V did not alter noticeably. The levels of xanthine, guanine, hypoxanthine, and adenine in the cells were not significantly altered. Compared with the absence of S9 system metabolism, benzo[a]pyrene and fluoranthene processed by the S9 system decreased the electrochemical signal of the cells in a dose-dependent manner, while pyrene did not change it appreciably. HPLC also revealed that benzo[a]pyrene and fluoranthene metabolized by the S9 system decreased the intracellular purine levels, whereas pyrene had no effect on them before and after S9 system metabolism. The cytotoxicity results of the three drugs examined by electrochemical voltammetry and MTT assay showed a strong correlation and good agreement. The S9 system had no effect on the intracellular purine levels or the electrochemical signal of cells. When the drug was metabolized by the S9 system, variations in cytotoxicity could be precisely detected by electrochemical voltammetry.

Cytoophidia: a conserved yet promising mode of enzyme regulation in nucleotide metabolism.

Nucleotide biosynthesis encompasses both de novo and salvage synthesis pathways, each characterized by significant material and procedural distinctions. Despite these differences, cells with elevated nucleotide demands exhibit a preference for the more intricate de novo synthesis pathway, intricately linked to modes of enzyme regulation. In this study, we primarily scrutinize the biological importance of a conserved yet promising mode of enzyme regulation in nucleotide metabolism-cytoophidia. Cytoophidia, comprising cytidine triphosphate synthase or inosine monophosphate dehydrogenase, is explored across diverse biological models, including yeasts, Drosophila, mice, and human cancer cell lines. Additionally, we delineate potential biomedical applications of cytoophidia. As our understanding of cytoophidia deepens, the roles of enzyme compartmentalization and polymerization in various biochemical processes will unveil, promising profound impacts on both research and the treatment of metabolism-related diseases.

Dehydration-responsive cytoskeleton proteome of rice reveals reprograming of key molecular pathways to mediate metabolic adaptation and cell survival.

The plant cytoskeletal proteins play a key role that control cytoskeleton dynamics, contributing to crucial biological processes such as cell wall morphogenesis, stomatal conductance and abscisic acid accumulation in repercussion to water-deficit stress or dehydration. Yet, it is still completely unknown which specific biochemical processes and regulatory mechanisms the cytoskeleton uses to drive dehydration tolerance. To better understand the role of cytoskeleton, we developed the dehydration-responsive cytoskeletal proteome map of a resilient rice cultivar. Initially, four-week-old rice plants were exposed to progressive dehydration, and the magnitude of dehydration-induced compensatory physiological responses was monitored in terms of physicochemical indices. The organelle fractionation in conjunction with label-free quantitative proteome analysis led to the identification of 955 dehydration-responsive cytoskeletal proteins (DRCPs). To our knowledge, this is the first report of a stress-responsive plant cytoskeletal proteome, representing the largest inventory of cytoskeleton and cytoskeleton-associated proteins. The DRCPs were apparently involved in a wide array of intra-cellular molecules transportation, organelles positioning, cytoskeleton organization followed by different metabolic processes including amino acid metabolism. These findings presented open a unique view on global regulation of plant cytoskeletal proteome is intimately linked to cellular metabolic rewiring of adaptive responses, and potentially confer dehydration tolerance, especially in rice, and other crop species, in general.

A benchmark of optimization solvers for genome-scale metabolic modeling of organisms and communities.

Genome-scale metabolic modeling is a powerful framework for predicting metabolic phenotypes of any organism with an annotated genome. For two decades, this framework has been used for the rational design of microbial cell factories. In the last decade, the range of applications has exploded, and new frontiers have emerged, including the study of the gut microbiome and its health implications and the role of microbial communities in global ecosystems. However, all the critical steps in this framework, from model construction to simulation, require the use of powerful linear optimization solvers, with the choice often relying on commercial solvers for their well-known computational efficiency. In this work, I benchmark a total of six solvers (two commercial and four open source) and measure their performance to solve linear and mixed-integer linear problems of increasing complexity. Although commercial solvers are still the fastest, at least two open-source solvers show comparable performance. These results show that genome-scale metabolic modeling does not need to be hindered by commercial licensing schemes and can become a truly open science framework for solving urgent societal challenges.IMPORTANCEModeling the metabolism of organisms and communities allows for computational exploration of their metabolic capabilities and testing their response to genetic and environmental perturbations. This holds the potential to address multiple societal issues related to human health and the environment. One of the current limitations is the use of commercial optimization solvers with restrictive licenses for academic and non-academic use. This work compares the performance of several commercial and open-source solvers to solve some of the most complex problems in the field. Benchmarking results show that, although commercial solvers are indeed faster, some of the open-source options can also efficiently tackle the hardest problems, showing great promise for the development of open science applications.