Quantitative phase microscopy enables precise and efficient determination of biomolecular condensate composition

Many compartments in eukaryotic cells are protein-rich biomolecular condensates demixed from the cyto- or nucleoplasm. Although much has been learned in recent years about the integral roles condensates play in many cellular processes as well as the biophysical properties of reconstituted condensates, an understanding of their most basic feature, their composition, remains elusive. Here we combined quantitative phase microscopy (QPM) and the physics of sessile droplets to develop a precise method to measure the shape and composition of individual model condensates. This technique does not rely on fluorescent dyes or tags, which we show can significantly alter protein phase behavior, and requires 1000-fold less material than traditional label-free technologies. We further show that this QPM method measures the protein concentration in condensates to a 3-fold higher precision than the next best label-free approach, and that commonly employed strategies based on fluorescence intensity dramatically underestimate these concentrations by as much as 50-fold. Interestingly, we find that condensed-phase protein concentrations can span a broad range, with PGL3, TAF15(RBD) and FUS condensates falling between 80 and 500 mg/ml under typical in vitro conditions. This points to a natural diversity in condensate composition specified by protein sequence. We were also able to measure temperature-dependent phase equilibria with QPM, an essential step towards relating phase behavior to the underlying physics and chemistry. Finally, time-resolved QPM reveals that PGL3 condensates undergo a contraction-like process during aging which leads to doubling of the internal protein concentration coupled to condensate shrinkage. We anticipate that this new approach will enable understanding the physical properties of biomolecular condensates and their function

Phenomenological models of synaptic plasticity based on spike timing

Synaptic plasticity is considered to be the biological substrate of learning and memory. In this document we review phenomenological models of short-term and long-term synaptic plasticity, in particular spike-timing dependent plasticity (STDP). The aim of the document is to provide a framework for classifying and evaluating different models of plasticity. We focus on phenomenological synaptic models that are compatible with integrate-and-fire type neuron models where each neuron is described by a small number of variables. This implies that synaptic update rules for short-term or long-term plasticity can only depend on spike timing and, potentially, on membrane potential, as well as on the value of the synaptic weight, or on low-pass filtered (temporally averaged) versions of the above variables. We examine the ability of the models to account for experimental data and to fulfill expectations derived from theoretical considerations. We further discuss their relations to teacher-based rules (supervised learning) and reward-based rules (reinforcement learning). All models discussed in this paper are suitable for large-scale network simulations

Modifiable risk factors associated with prediabetes in men and women: A cross-sectional analysis of the cohort study in primary health care on the evolution of patients with prediabetes

Background: Prediabetes is a high-risk state for diabetes development, but little is known about the factors associated with this state. The aim of the study was to identify modifiable risk factors associated with the presence of prediabetes in men and women. Methods: Cohort Study in Primary Health Care on the Evolution of Patients with Prediabetes (PREDAPS-Study) is a prospective study on a cohort of 1184 subjects with prediabetes and another cohort of 838 subjects without glucose metabolism disorders. It is being conducted by 125 general practitioners in Spain. Data for this analysis were collected during the baseline stage in 2012. The modifiable risk factors included were: smoking habit, alcohol consumption, low physical activity, inadequate diet, hypertension, dyslipidemia, and obesity. To assess independent association between each factor and prediabetes, odds ratios (ORs) were estimated using logistic regression models. Results: Abdominal obesity, low plasma levels of high-density lipoprotein cholesterol (HDL-cholesterol), and hypertension were independently associated with the presence of prediabetes in both men and women. After adjusting for all factors, the respective ORs (95% Confidence Intervals) were 1.98 (1.41-2.79), 1.88 (1.23-2.88) and 1.86 (1.39-2.51) for men, and 1.89 (1.36-2.62), 1.58 (1.12-2.23) and 1.44 (1.07-1.92) for women. Also, general obesity was a risk factor in both sexes but did not reach statistical significance among men, after adjusting for all factors. Risky alcohol consumption was a risk factor for prediabetes in men, OR 1.49 (1.00-2.24). Conclusions: Obesity, low HDL-cholesterol levels, and hypertension were modifiable risk factors independently related to the presence of prediabetes in both sexes. The magnitudes of the associations were stronger for men than women. Abdominal obesity in both men and women displayed the strongest association with prediabetes. The findings suggest that there are some differences between men and women, which should be taken into account when implementing specific recommendations to prevent or delay the onset of diabetes in adult population

Charge-density reduction promotes ribozyme activity in RNA-peptide coacervates via RNA fluidization and magnesium partitioning.

It has long been proposed that phase-separated compartments can provide a basis for the formation of cellular precursors in prebiotic environments. However, we know very little about the properties of coacervates formed from simple peptides, their compatibility with ribozymes or their functional significance. Here we assess the conditions under which functional ribozymes form coacervates with simple peptides. We find coacervation to be most robust when transitioning from long homopeptides to shorter, more pre-biologically plausible heteropeptides. We mechanistically show that these RNA-peptide coacervates display peptide-dependent material properties and cofactor concentrations. We find that the interspacing of cationic and neutral amino acids increases RNA mobility, and we use isothermal calorimetry to reveal sequence-dependent Mg2+ partitioning, two critical factors that together enable ribozyme activity. Our results establish how peptides of limited length, homogeneity and charge density facilitate the compartmentalization of active ribozymes into non-gelating, magnesium-rich coacervates, a scenario that could be applicable to cellular precursors with peptide-dependent functional phenotypes

Compartmentalised RNA catalysis in membrane-free coacervate protocells

Phase separation of mixtures of oppositely charged polymers provides a simple and direct route to compartmentalisation via complex coacervation, which may have been important for driving primitive reactions as part of the RNA world hypothesis. However, to date, RNA catalysis has not been reconciled with coacervation. Here we demonstrate that RNA catalysis is viable within coacervate microdroplets and further show that these membrane-free droplets can selectively retain longer length RNAs while permitting transfer of lower molecular weight oligonucleotides

Mechanochemical modeling of neutrophil migration based on four signaling layers, integrin dynamics, and substrate stiffness

Directional neutrophil migration during human immune responses is a highly coordinated process regulated by both biochemical and biomechanical environments. In this paper, we developed an integrative mathematical model of neutrophil migration using a lattice Boltzmann-particle method built in-house to solve the moving boundary problem with spatiotemporal regulation of biochemical components. The mechanical features of the cell cortex are modeled by a series of spring-connected nodes representing discrete cell-substrate adhesive sites. The intracellular signaling cascades responsible for cytoskeletal remodeling [e.g., small GTPases, phosphoinositide-3-kinase (PI3K), and phosphatase and tensin homolog] are built based on our previous four-layered signaling model centered on the bidirectional molecular transport mechanism and implemented as reaction-diffusion equations. Focal adhesion dynamics are determined by force-dependent integrin-ligand binding kinetics and integrin recycling and are thus integrated with cell motion. Using numerical simulations, the model reproduces the major features of cell migration in response to uniform and gradient biochemical stimuli based on the quantitative spatiotemporal regulation of signaling molecules, which agree with experimental observations. The existence of multiple types of integrins with different binding kinetics could act as an adaptation mechanism for substrate stiffness. Moreover, cells can perform reversal, U-turn, or lock-on behaviors depending on the steepness of the reversal biochemical signals received. Finally, this model is also applied to predict the responses of mutants in which PTEN is overexpressed or disrupted