B cells discriminate HIV-1 Envelope protein affinities by sensing antigen binding association rates

HIV-1 Envelope (Env) proteins designed to induce neutralizing antibody responses allow study of the role of affinities (equilibrium dissociation constant, KD) and kinetic rates (association/dissociation rates) on B cell antigen recognition. It is unclear whether affinity discrimination during B cell activation is based solely on Env protein binding KD, and whether B cells discriminate between proteins of similar affinities but that bind with different kinetic rates. Here we used a panel of Env proteins and Ramos B cell lines expressing IgM BCRs with specificity for CD4 binding-site broadly neutralizing (bnAb) or a precursor antibody to study the role of antigen binding kinetic rates on both early (proximal/distal signaling) and late events (BCR/antigen internalization) in B cell activation. Our results support a kinetic model for B cell activation in which Env protein affinity discrimination is based not on overall KD, but on sensing of association rate and a threshold antigen-BCR half-life.

Ti(IV)-exchanged nano-ZIF-8 and nano-ZIF-67 for Enhanced Photocatalytic Oxidation of Hydroquinone

The metal centres of nano-ZIF-8(Zn) and nano-ZIF-67(Co) were partially exchanged with titanium centres to form bimetallic nZIF-8(Zn/Ti) (52% Ti4+) and nZIF-67(Co/Ti) (38% Ti4+) respectively, for enhanced photocatalytic performance. A morphological and structural analysis by SEM, EDS-Mapping and PXRD showed that the particle size, distribution, and the structural integrity of the Sodalite frameworks of the parent ZIFs were retained during the exchange process to form the new bimetallic Ti-ZIFs. FTIR confirmed that no additional chemical bonds were formed during the process. XPS binding energies confirmed the preservation of the Zn(II), Co(II) and Ti(IV) oxidation states, as well as the Ti-content, consistent with ICP-OES and EDS measurements. The Ti-exchanged ZIFs showed higher activity during the photocatalytic oxidation of hydroquinone in comparison with their parent ZIFs. Their kinetic rates were nearly five times faster than those of the parent ZIFs, with the first-order rate constants k = 0.189 min-1 for nZIF-8(Zn/Ti) and k = 0.139 min-1 for nZIF-67(Co/Ti). These catalysts are efficient, stable, and reusable for three photocatalytic cycles without a significant loss of catalytic activity.

Fast reactions with non-interacting species in stochastic reaction networks

<abstract><p>We consider stochastic reaction networks modeled by continuous-time Markov chains. Such reaction networks often contain many reactions, potentially occurring at different time scales, and have unknown parameters (kinetic rates, total amounts). This makes their analysis complex. We examine stochastic reaction networks with non-interacting species that often appear in examples of interest (e.g. in the two-substrate Michaelis Menten mechanism). Non-interacting species typically appear as intermediate (or transient) chemical complexes that are depleted at a fast rate. We embed the Markov process of the reaction network into a one-parameter family under a two time-scale approach, such that molecules of non-interacting species are degraded fast. We derive simplified reaction networks where the non-interacting species are eliminated and that approximate the scaled Markov process in the limit as the parameter becomes small. Then, we derive sufficient conditions for such reductions based on the reaction network structure for both homogeneous and time-varying stochastic settings, and study examples and properties of the reduction.</p></abstract>

A Novel Approach for Calculating Exact Forms of mRNA Distribution in Single-Cell Measurements

Gene transcription is a stochastic process manifested by fluctuations in mRNA copy numbers in individual isogenic cells. Together with mathematical models of stochastic transcription, the massive mRNA distribution data that can be used to quantify fluctuations in mRNA levels can be fitted by Pm(t), which is the probability of producing m mRNA molecules at time t in a single cell. Tremendous efforts have been made to derive analytical forms of Pm(t), which rely on solving infinite arrays of the master equations of models. However, current approaches focus on the steady-state (t→∞) or require several parameters to be zero or infinity. Here, we present an approach for calculating Pm(t) with time, where all parameters are positive and finite. Our approach was successfully implemented for the classical two-state model and the widely used three-state model and may be further developed for different models with constant kinetic rates of transcription. Furthermore, the direct computations of Pm(t) for the two-state model and three-state model showed that the different regulations of gene activation can generate discriminated dynamical bimodal features of mRNA distribution under the same kinetic rates and similar steady-state mRNA distribution.

Removal of As(V) from aqueous solutions using calcium-alginate microspheres with encapsulated iron nanoparticles

This work investigated As(V) removal from aqueous solutions using calcium alginate microspheres with encapsulated iron nanoparticles (FeNPs) in batch systems. The kinetic, equilibrium, and thermodynamic parameters of the adsorption process were evaluated. Adsorbents were characterized using Fourier Transform Infrared Spectroscopy, Scanning Electron Microscopy, and Zeta Potential techniques. The FeNPs were obtained by a simple and low-cost method and they were successfully encapsulated and uniformly dispersed over the microspheres' surface. Significantly fast adsorption kinetic rates were observed due to microspheres' particle size and FeNPs encapsulation. The chemisorption mechanism was recognized in both adsorbate-adsorbent systems. The As(V) isotherms data suggested that the process is associated with heterogeneous adsorption. Available sorption sites with different adsorption energies were related to the functional groups involved in removing As(V), such as hydroxyl and carboxyl groups. Significantly high adsorption capacities were obtained for both materials, suggesting they can be competitive compared to conventional adsorbents, even at low FeNPs concentrations. Besides FeNPs encapsulation enhancing arsenate removal, higher adsorption was obtained at slightly acidic pH values and, together with their small particle size, suggests that the microspheres have a great potential to be used as arsenate adsorbents in the water treatment for human consumption.

Stability Analysis of Parameter Varying Genetic Toggle Switches Using Koopman Operators

The genetic toggle switch is a well known model in synthetic biology that represents the dynamic interactions between two genes that repress each other. The mathematical models for the genetic toggle switch that currently exist have been useful in describing circuit dynamics in rapidly dividing cells, assuming fixed or time-invariant kinetic rates. There is a growing interest in being able to model and extend synthetic biological function for growth conditions such as stationary phase or during nutrient starvation. As cells transition from one growth phase to another, kinetic rates become time-varying parameters. In this paper, we propose a novel class of parameter varying nonlinear models that can be used to describe the dynamics of genetic circuits, including the toggle switch, as they transition from different phases of growth. We show that there exists unique solutions for this class of systems, as well as for a class of systems that incorporates the microbial phenomena of quorum sensing. Further, we show that the domain of these systems, which is the positive orthant, is positively invariant. We also showcase a theoretical control strategy for these systems that would grant asymptotic monostability of a desired fixed point. We then take the general form of these systems and analyze their stability properties through the framework of time-varying Koopman operator theory. A necessary condition for asymptotic stability is also provided as well as a sufficient condition for instability. A Koopman control strategy for the system is also proposed, as well as an analogous discrete time-varying Koopman framework for applications with regularly sampled measurements.

Force Dependence of Proteins’ Transition State Position and the Bell–Evans Model

Single-molecule force spectroscopy has opened a new field of research in molecular biophysics and biochemistry. Pulling experiments on individual proteins permit us to monitor conformational transitions with high temporal resolution and measure their free energy landscape. The force–extension curves of single proteins often present large hysteresis, with unfolding forces that are higher than refolding ones. Therefore, the high energy of the transition state (TS) in these molecules precludes kinetic rates measurements in equilibrium hopping experiments. In irreversible pulling experiments, force-dependent kinetic rates measurements show a systematic discrepancy between the sum of the folding and unfolding TS distances derived by the kinetic Bell–Evans model and the full molecular extension predicted by elastic models. Here, we show that this discrepancy originates from the force-induced movement of TS. Specifically, we investigate the highly kinetically stable protein barnase, using pulling experiments and the Bell–Evans model to characterize the position of its kinetic barrier. Experimental results show that while the TS stays at a roughly constant distance relative to the native state, it shifts with force relative to the unfolded state. Interestingly, a conversion of the protein extension into amino acid units shows that the TS position follows the Leffler–Hammond postulate: the higher the force, the lower the number of unzipped amino acids relative to the native state. The results are compared with the quasi-reversible unfolding–folding of a short DNA hairpin.

A Stochastic Binary Model for Regulation of Gene Expression to Investigate Treatment Effects Targeting RKIP

In this manuscript we use an exactly solvable stochastic binary model for regulation of gene expression to analyse the dynamics of response to a treatment aiming to modulate the number of transcripts of RKIP gene. We demonstrate the usefulness of our method simulating three treatment scenarios aiming to reestablish RKIP gene expression dynamics towards pre-cancerous state: i. to increase the promoter&rsquo;s ON state duration; ii. to increase the mRNAs&rsquo; synthesis rate; iii. to increase both rates. We show that the pre-treatment kinetic rates of ON and OFF promoter switching speeds and mRNA synthesis and degradation will affect the heterogeneity and time for treatment response. Hence, we present a strategy for reducing drug dosage by simultaneously targeting multiple kinetic rates. That enables a reduction of treatment response time and heterogeneity which in principle diminishes the chances of emergence of resistance to treatment. This approach may be useful for inferring kinetic constants related to expression of antimetastatic genes or oncogenes and on the design of multi-drug therapeutic strategies targeting master regulatory genes.

Simulating CXCR5 Dynamics in Complex Tissue Microenvironments

To effectively navigate complex tissue microenvironments, immune cells sense molecular concentration gradients using G-protein coupled receptors. However, due to the complexity of receptor activity, and the multimodal nature of chemokine gradients in vivo, chemokine receptor activity in situ is poorly understood. To address this issue, we apply a modelling and simulation approach that permits analysis of the spatiotemporal dynamics of CXCR5 expression within an in silico B-follicle with single-cell resolution. Using this approach, we show that that in silico B-cell scanning is robust to changes in receptor numbers and changes in individual kinetic rates of receptor activity, but sensitive to global perturbations where multiple parameters are altered simultaneously. Through multi-objective optimization analysis we find that the rapid modulation of CXCR5 activity through receptor binding, desensitization and recycling is required for optimal antigen scanning rates. From these analyses we predict that chemokine receptor signaling dynamics regulate migration in complex tissue microenvironments to a greater extent than the total numbers of receptors on the cell surface.

Analysis of a High Andean River's Behavior at Loads of Organic Matter Through the Use of Mathematical Models with Experimentally Determined Kinetic Rates

Using models of organic matter degradation and dissolved oxygen consumption, the concentrations of these compounds are analyzed in two stretches of a river after a discharge of raw sewage. The analyzed river has low drafts and widths, so the velocity is high and the aeration coefficient kr calculated with the Covar method is high, this indicates a rapid recovery of oxygen from the water consumed by the organic matter degradation processes, the river has been instrumented to measure flows and organic matter at various points to calibrate the model. The hydraulic parameters of the river section are analyzed in three control points, in each one sample are taken to analyze oxygen consumption by organic matter and nitrification through laboratory tests to determine and adjust the kinetics of the processes (kd; knit). This kinetics have been used in the development of a water quality model to verify its adjustment, obtaining higher RMSE results than with kinetics from secondary sources. It is observed that the river has an excellent capacity for self-purification due to the high income of dissolved oxygen, with a kr > 9 d-1.