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Chemical reaction networks can undergo nonequilibrium phase transitions upon variation in external control parameters, such as the chemical potential of a species. We investigate the flux in the associated chemostats that is proportional to the entropy production and its critical fluctuations within the Schlögl model. Numerical simulations show that the corresponding diffusion coefficient diverges at the critical point as a function of system size. In the vicinity of the critical point, the diffusion coefficient follows a scaling form. We develop an analytical approach based on the chemical Langevin equation and van Kampen's system size expansion that yields the corresponding exponents in the monostable regime. In the bistable regime, we rely on a two-state approximation in order to analytically describe the critical behavior., (© 2024 Author(s). Published under an exclusive license by AIP Publishing.)

In a noisy environment, oscillations lose their coherence, which can be characterized by a quality factor. We determine this quality factor for oscillations arising from a driven Fokker-Planck dynamics along a periodic one-dimensional potential analytically in the weak-noise limit. With this expression, we can prove for this continuum model the analog of an upper bound that has been conjectured for the coherence of oscillations in discrete Markov network models. We show that our approach can also be adapted to motion along a noisy two-dimensional limit cycle. Specifically, we apply our scheme to the noisy Stuart-Landau oscillator and the thermodynamically consistent Brusselator as a simple model for a chemical clock. Our approach thus complements the fairly sophisticated extant general framework based on techniques from Hamilton-Jacobi theory with which we compare our results numerically.

Cyanobacterial blooms constitute a recognized danger to aquatic environment and public health not only due to presence of main group of cyanotoxins, such as microcystins, cylindrospermopsin or anatoxin-a, but also other emerging bioactivities. An innovative approach identifying such bioactivities is the application of cellular biosensors based on reporter genes which detect the impact of cyanobacterial cells and components on actual human cells in a physiological-like setting. In the present study biosensor cell lines detecting four different types of bioactivities (ARE - oxidative stress, NFKBRE - immunomodulatory pathogen-associated molecular patterns, AHRE - persistent organic pollutants, GRE - endocrine disruptors) were exposed to concentrated cyanobacterial cells from 21 environmental bloom samples and from eight cultures (Microcystis aeruginosa, Aphanizomenon flos-aquae, Planktothrix agardhii and Raphidiopsis raciborskii). The AHRE and GRE biosensors did not detect any relevant bioactivity. In turn, ARE biosensors were significantly activated by bloom samples from Jeziorsko (180-250%) and Sulejów (250-400%) reservoirs with the highest cyanobacterial biomass, while activation by cultures was weak/undetectable. The same biosensors were stimulated by microcystin-LR (250%) and anatoxin-a (150%). The NFKBRE biosensors were activated to varying extent (140-650%) by most bloom and culture samples, pointing to potential immunomodulatory toxic effects on humans. Lipopolysaccharide and lipoproteins were identified as responsible for NFKBRE activation (probably via pattern recognition receptors), while peptidoglycan had no bioactivity in this assay. Thus, the holistic approach to sample analysis with the application of cellular biosensors geared towards 4 separate pathways/bioactivities was validated for identification of novel bioactivities in organisms with recognized public health significance (e.g. this study is the first to describe cyanobacterial lipoproteins as potential environmental immunomodulators). Moreover, the ability of cellular biosensors to be activated by intact cyanobacterial cells from blooms provides proof of concept of their direct application for environmental monitoring, especially comparison of potential threats without need for chemical analysis and identification of toxicants., Competing Interests: Declaration of competing interest Authors declare that this research was funded by the National Science Centre, project no. UMO-2012/07/B/NZ8/03991 - “Application of reporter cell biosensors in ecotoxicology of cyanobacteria: new targets for bioactivity” and partly from EEA/Norway Grant Mechanism research grant PL0107 “Cellular biosensors for automated monitoring of environmental pollution”. 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 © 2021. Published by Elsevier B.V.)

Androgen signaling through the androgen receptor (AR) directs gene expression in both normal and prostate cancer cells. Androgen regulates multiple aspects of the AR life cycle, including its localization and post-translational modification, but understanding how modifications are read and integrated with AR activity has been difficult. Here, we show that ADP-ribosylation regulates AR through a nuclear pathway mediated by Parp7. We show that Parp7 mono-ADP-ribosylates agonist-bound AR, and that ADP-ribosyl-cysteines within the N-terminal domain mediate recruitment of the E3 ligase Dtx3L/Parp9. Molecular recognition of ADP-ribosyl-cysteine is provided by tandem macrodomains in Parp9, and Dtx3L/Parp9 modulates expression of a subset of AR-regulated genes. Parp7, ADP-ribosylation of AR, and AR-Dtx3L/Parp9 complex assembly are inhibited by Olaparib, a compound used clinically to inhibit poly-ADP-ribosyltransferases Parp1/2. Our study reveals the components of an androgen signaling axis that uses a writer and reader of ADP-ribosylation to regulate protein-protein interactions and AR activity.

An optimal finite-time process drives a given initial distribution to a given final one in a given time at the lowest cost as quantified by total entropy production. We prove that for a system with discrete states this optimal process involves nonconservative driving, i.e., a genuine driving affinity, in contrast to the case of a system with continuous states. In a multicyclic network, the optimal driving affinity is bounded by the number of states within each cycle. If the driving affects forward and backwards rates nonsymmetrically, the bound additionally depends on a structural parameter characterizing this asymmetry.