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At least 55 records · Page 3

Divergence in the ABA gene regulatory network underlies differential growth control

The phytohormone abscisic acid (ABA) is a central regulator of acclimation to environmental stress; however, its contribution to differences in stress tolerance between species is unclear. To establish a comparative framework for understanding how stress hormone signalling pathways diverge across species, we studied the growth response of four Brassicaceae species to ABA treatment and generated transcriptomic and DNA affinity purification and sequencing datasets to construct a cross-species gene regulatory network (GRN) for ABA. In this work, comparison of genes bound directly by ABA-responsive element binding factors suggests that cis-factors are most important for determining the target loci represented in the ABA GRN of a particular species. Using this GRN, we reveal how rewiring of growth hormone subnetworks contributes to stark differences in the response to ABA in the extremophyte Schrenkiella parvula. Our study provides a model for understanding how divergence in gene regulation can lead to species-specific physiological outcomes in response to hormonal cues.

59 BASIC BIOLOGICAL SCIENCES↗

A divergent synthetic route to functional copolymer libraries via modular polymers

High-throughput polymer synthesis enables rapid exploration of chemical space but remains limited by batch-to-batch inconsistencies that can obscure structure–property relationship trends. To address this challenge, we developed a synthetic approach to produce multifunctional copolymers using post-polymerization modification of activated ester modular polymers with commercially available amines. Easily derivitized parent polymers—poly(tetrafluorophenyl acrylate) and poly(tetrafluorophenyl styrene sulfonate)—were synthesized by RAFT polymerization to yield single polymer batches containing highly reactive tetrafluorophenyl esters or sulfonate esters on each repeat unit. Tuning post-polymerization modification reaction conditions enabled the addition of sub-stoichiometric amounts of amines (relative to the repeat unit) to yield partially functionalized intermediates that could then be further derivatized. Reaction monitoring by 19 F NMR spectroscopy confirmed good control over these sequential post-polymerization modifications. This synthetic route produced a variety of copolymers with defined comonomer ratios while preserving the underlying polymer structure (degree of polymerization, dispersity, tacticity) for both the acrylate and styrene sulfonate backbones. We further applied this approach in a divergent manner to create a small library of structurally distinct copolymers from a single parent batch in three synthetic steps. This modular, divergent synthesis demonstrates a general route to structurally consistent copolymer libraries that enable systematic studies of structure–property relationships and can accelerate functional materials discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computational design of closely related proteins that adopt two well-defined but structurally divergent folds

The plasticity of naturally occurring protein structures, which can change shape considerably in response to changes in environmental conditions, is critical to biological function. While computational methods have been used for de novo design of proteins that fold to a single state with a deep free-energy minimum [P.-S. Huang, S. E. Boyken, D. Baker, Nature 537, 320–327 (2016)], and to reengineer natural proteins to alter their dynamics [J. A. Davey, A. M. Damry, N. K. Goto, R. A. Chica, Nat. Chem. Biol.13, 1280–1285 (2017)] or fold [P. A. Alexander, Y. He, Y. Chen, J. Orban, P. N. Bryan, Proc. Natl. Acad. Sci. U.S.A. 106, 21149–21154 (2009)], the de novo design of closely related sequences which adopt well-defined but structurally divergent structures remains an outstanding challenge. We designed closely related sequences (over 94% identity) that can adopt two very different homotrimeric helical bundle conformations—one short (~66 Å height) and the other long (~100 Å height)—reminiscent of the conformational transition of viral fusion proteins. Crystallographic and NMR spectroscopic characterization shows that both the short- and long-state sequences fold as designed. We sought to design bistable sequences for which both states are accessible, and obtained a single designed protein sequence that populates either the short state or the long state depending on the measurement conditions. The design of sequences which are poised to adopt two very different conformations sets the stage for creating large-scale conformational switches between structurally divergent forms.

59 BASIC BIOLOGICAL SCIENCES↗

Structural basis for divergent and convergent evolution of catalytic machineries in plant aromatic amino acid decarboxylase proteins

Radiation of the plant pyridoxal 5'-phosphate (PLP)-dependent aromatic L -amino acid decarboxylase (AAAD) family has yielded an array of paralogous enzymes exhibiting divergent substrate preferences and catalytic mechanisms. Plant AAADs catalyze either the decarboxylation or decarboxylation-dependent oxidative deamination of aromatic L -amino acids to produce aromatic monoamines or aromatic acetaldehydes, respectively. These compounds serve as key precursors for the biosynthesis of several important classes of plant natural products, including indole alkaloids, benzylisoquinoline alkaloids, hydroxycinnamic acid amides, phenylacetaldehyde-derived floral volatiles, and tyrosol derivatives. In this paper, we present the crystal structures of four functionally distinct plant AAAD paralogs. Through structural and functional analyses, we identify variable structural features of the substrate-binding pocket that underlie the divergent evolution of substrate selectivity toward indole, phenyl, or hydroxyphenyl amino acids in plant AAADs. Moreover, we describe two mechanistic classes of independently arising mutations in AAAD paralogs leading to the convergent evolution of the derived aldehyde synthase activity. Applying knowledge learned from this study, we successfully engineered a shortened benzylisoquinoline alkaloid pathway to produce (S)-norcoclaurine in yeast. This work highlights the pliability of the AAAD fold that allows change of substrate selectivity and access to alternative catalytic mechanisms with only a few mutations.

59 BASIC BIOLOGICAL SCIENCES↗

Divergent evolution of extreme production of variant plant monounsaturated fatty acids

Metabolic extremes provide opportunities to understand enzymatic and metabolic plasticity and biotechnological tools for novel biomaterial production. We discovered that seed oils of many Thunbergia species contain up to 92% of the unusual monounsaturated petroselinic acid (18:1Δ6), one of the highest reported levels for a single fatty acid in plants. Supporting the biosynthetic origin of petroselinic acid, we identified a Δ6-stearoyl-acyl carrier protein (18:0-ACP) desaturase from Thunbergia laurifolia , closely related to a previously identified Δ6-palmitoyl-ACP desaturase that produces sapienic acid (16:1Δ6)-rich oils in Thunbergia alata seeds. Guided by a T. laurifolia desaturase crystal structure obtained in this study, enzyme mutagenesis identified key amino acids for functional divergence of Δ6 desaturases from the archetypal Δ9-18:0-ACP desaturase and mutations that result in nonnative enzyme regiospecificity. Furthermore, we demonstrate the utility of the T. laurifolia desaturase for the production of unusual monounsaturated fatty acids in engineered plant and bacterial hosts. Through stepwise metabolic engineering, we provide evidence that divergent evolution of extreme petroselinic acid and sapienic acid production arises from biosynthetic and metabolic functional specialization and enhanced expression of specific enzymes to accommodate metabolism of atypical substrates.

59 BASIC BIOLOGICAL SCIENCES↗

Divergent urban land trajectories under alternative population projections within the Shared Socioeconomic Pathways

Population change is a main driver behind global environmental change, including urban land expansion. In future scenario modeling, assumptions regarding how populations will change locally, despite identical global constraints of Shared Socioeconomic Pathways (SSPs), can have dramatic effects on subsequent regional urbanization. Using a spatial modeling experiment at high resolution (1 km), this study compared how two alternative US population projections, varying in the spatially explicit nature of demographic patterns and migration, affect urban land dynamics simulated by the Spatially Explicit, Long-term, Empirical City development (SELECT) model for SSP2, SSP3, and SSP5. The population projections included: (1) newer downscaled state-specific population (SP) projections inclusive of updated international and domestic migration estimates, and (2) prevailing downscaled national-level projections (NP) agnostic to localized demographic processes. Our work shows that alternative population inputs, even those under the same SSP, can lead to dramatic and complex differences in urban land outcomes. Under the SP projection, urbanization displays more of an extensification pattern compared to the NP projection. This suggests that recent demographic information supports more extreme urban extensification and land pressures on existing rural areas in the US than previously anticipated. Urban land outcomes to population inputs were spatially variable where areas in close spatial proximity showed divergent patterns, reflective of the spatially complex urbanization processes that can be accommodated in SELECT. Although different population projections and assumptions led to divergent outcomes, urban land development is not a linear product of population change but the result of complex relationships between population, dynamic urbanization processes, stages of urban development maturity, and feedback mechanisms. These findings highlight the importance of accounting for spatial variations in the population projections, but also urbanization process to accurately project long-term urban land patterns.

54 ENVIRONMENTAL SCIENCES↗

Long-term patterns of post-fire harvest diverge among ownerships in the Pacific West, U.S.A.

Abstract Post-fire harvest (PFH) is a forest management practice designed to salvage value from burned timber, mitigate safety hazards from dead trees, reduce long-term fuels, and prepare sites for replanting. Despite public controversy and extensive ecological research, little is known about how much PFH occurs on private and public lands in the U.S. Pacific West, or how practices changed with shifting forest policy and increasing area burned over the last three decades. We mapped PFH across 2.2M burned hectares in California, Oregon, and Washington between 1986-2017 and used time series intervention analysis to compare trends in area, rate (% of burned area harvested), and mean patch size between private (0.5M ha) and federal (1.6M ha) forest land and across a gradient of burn severity. Harvest rates varied by ownership (4.9% federal, 18.6% private, 8.0% overall), and practices evolved and diverged over the study period. PFH area and rate declined across all ownerships in the mid-1990s during a period of reduced fire activity. As area burned increased between the early 2000s and late 2010s, PFH area rebounded and surpassed late-1980s levels, while rates remained relatively low. On federal lands, PFH practices shifted in the early-to-mid 1990s towards lower rates (10.3% to 3.8%) and smaller patches (6.0 to 3.3 ha), following policy changes and increased litigation. PFH rates on federal lands decreased at all levels of burn severity, with the largest decreases (6.2% to 1.2%) in forests with low tree mortality (i.e. fire refugia). Conversely, private PFH rates and mean patch sizes more than doubled in forests burned at very low-to-moderate severity. Our results highlight how PFH practices have shifted with policy, socio-economic pressure, and increasing area burned over 31 years in the Pacific West. A similar area of post-fire harvest is now dispersed over larger fires, with practices diverging substantially between ownerships.

Zuspan, Aaron (ORCID:0000000315833710)↗

Divergent selection and climate adaptation fuel genomic differentiation between sister species of Sphagnum (peat moss)

Abstract Background and Aims New plant species can evolve through the reinforcement of reproductive isolation via local adaptation along habitat gradients. Peat mosses (Sphagnaceae) are an emerging model system for the study of evolutionary genomics and have well-documented niche differentiation among species. Recent molecular studies have demonstrated that the globally distributed species Sphagnum magellanicum is a complex of morphologically cryptic lineages that are phylogenetically and ecologically distinct. Here, we describe the architecture of genomic differentiation between two sister species in this complex known from eastern North America: the northern S. diabolicum and the largely southern S. magniae. Methods We sampled plant populations from across a latitudinal gradient in eastern North America and performed whole genome and restriction-site associated DNA sequencing. These sequencing data were then analyzed computationally. Key Results Using sliding-window population genetic analyses we find that differentiation is concentrated within ‘islands’ of the genome spanning up to 400 kb that are characterized by elevated genetic divergence, suppressed recombination, reduced nucleotide diversity and increased rates of non-synonymous substitution. Sequence variants that are significantly associated with genetic structure and bioclimatic variables occur within genes that have functional enrichment for biological processes including abiotic stress response, photoperiodism and hormone-mediated signalling. Demographic modelling demonstrates that these two species diverged no more than 225 000 generations ago with secondary contact occurring where their ranges overlap. Conclusions We suggest that this heterogeneity of genomic differentiation is a result of linked selection and reflects the role of local adaptation to contrasting climatic zones in driving speciation. This research provides insight into the process of speciation in a group of ecologically important plants and strengthens our predictive understanding of how plant populations will respond as Earth’s climate rapidly changes.

58 GEOSCIENCES↗

A Divergent Clade KAI2 Protein in the Root Parasitic Plant Orobanche minor Is a Highly Sensitive Strigolactone Receptor and Is Involved in the Perception of Sesquiterpene Lactones

Abstract Strigolactones (SLs) were initially discovered as germination inducers for root parasitic plants. In 2015, three groups independently reported the characterization of the SL receptor in the root parasitic plant Striga hermonthica, which causes significant damage to crop production, particularly in sub-Saharan Africa. The characterized receptors belong to HYPOSENSITIVE TO LIGHT/KARRIKIN INSENSITIVE2 (HTL/KAI2), which is a member of the α/β-hydrolase protein superfamily. In non-parasitic plants, HTL/KAI2 perceives the smoke-derived germination inducer karrikin and a yet-unidentified endogenous ligand. However, root parasitic plants evolved a specific clade of HTL/KAI2 that has diverged from the KAI2 clade of non-parasitic plants. The S. hermonthica SL receptors are included in this specific clade, which is called KAI2 divergent (KAI2d). Orobanche minor is an obligate root holoparasitic plant that grows completely dependent on the host for water and nutrients because of a lack of photosynthetic ability. Previous phylogenetic analysis of KAI2 proteins in O. minor has demonstrated the presence of at least five KAI2d clade genes. Here, we report that KAI2d3 and KAI2d4 in O. minor have the ability to act as the SL receptors. They directly interact with SLs in vitro, and when expressed in Arabidopsis, they rescue thermo-inhibited germination in response to the synthetic SL analog GR24. In particular, KAI2d3 showed high sensitivity to GR24 when expressed in Arabidopsis, suggesting that this receptor enables highly sensitive SL recognition in O. minor. Furthermore, we provide evidence that these KAI2d receptors are involved in the perception of sesquiterpene lactones, non-strigolactone-type germination inducers.

Cell Biology↗

The N-terminal domains of NLR immune receptors exhibit structural and functional similarities across divergent plant lineages

Nucleotide-binding domain and leucine-rich repeat (NLR) proteins are a prominent class of intracellular immune receptors in plants. However, our understanding of plant NLR structure and function is limited to the evolutionarily young flowering plant clade. Here, we describe an extended spectrum of NLR diversity across divergent plant lineages and demonstrate the structural and functional similarities of N-terminal domains that trigger immune responses. We show that the broadly distributed coiled-coil (CC) and toll/interleukin-1 receptor (TIR) domain families of nonflowering plants retain immune-related functions through translineage activation of cell death in the angiosperm Nicotiana benthamiana. We further examined a CC subfamily specific to nonflowering lineages and uncovered an essential N-terminal MAEPL motif that is functionally comparable with motifs in resistosome-forming CC-NLRs. Consistent with a conserved role in immunity, the ectopic activation of CC MAEPL in the nonflowering liverwort Marchantia polymorpha led to profound growth inhibition, defense gene activation, and signatures of cell death. Moreover, comparative transcriptomic analyses of CC MAEPL activity delineated a common CC-mediated immune program shared across evolutionarily divergent nonflowering and flowering plants. Collectively, our findings highlight the ancestral nature of NLR-mediated immunity during plant evolution that dates its origin to at least ~500 million years ago.

59 BASIC BIOLOGICAL SCIENCES↗

Perfect spinfluid: A divergence-type approach

We present a new formulation of nondissipative relativistic spin hydrodynamics that incorporates spin degrees of freedom into the divergence-type theory framework. Due to the divergence-type structure, it is straightforward to enforce nonlinear causality and symmetric hyperbolicity of the equations of motion, ensuring local well-posedness of the initial-value problem and stability of the theory. Furthermore, in a specific realization based on spin kinetic theory, we prove that the equations of motion remain nonlinearly causal and symmetric-hyperbolic to all orders in the spin potential, provided a specific thermodynamic constraint is satisfied. Here, this framework can be applied for numerical simulations to study the dynamics of spin-polarized fluids, such as the quark-gluon plasma in heavy-ion collisions.

Chirality↗

Convergence and divergence in science and practice of urban and rural forest restoration

Forest restoration has never been higher on policymakers' agendas. Complex and multi-dimensional arrangements across the urban–rural continuum challenge restorationists and require integrative approaches to strengthen environmental protection and increase restoration outcomes. It remains unclear if urban and rural forest restoration are moving towards or away from each other in practice and research, and whether comparing research outcomes can help stakeholders to gain a clearer understanding of the interconnectedness between the two fields. This study aims to identify the challenges and opportunities for enhancing forest restoration in both urban and rural systems by reviewing the scientific evidence, engaging with key stakeholders and using an urban–rural forest restoration framework. Using the Society for Ecological Restoration's International Principles as discussion topics, we highlight aspects of convergence and divergence between the two fields to broaden our understanding of forest restoration and promote integrative management approaches to address future forest conditions. Our findings reveal that urban and rural forest restoration have convergent and divergent aspects. We emphasise the importance of tailoring goals and objectives to specific contexts and the need to design different institutions and incentives based on the social and ecological needs and goals of stakeholders in different regions. Here we discuss the challenges of achieving high levels of ecological restoration and the need to go beyond traditional ecology to plan, implement, monitor, and adaptively manage restored forests. We suggest that rivers and watersheds could serve as a common ground linking rural and urban landscapes and that forest restoration could interact with other environmental protection measures. We note the potential for expanding the creative vision associated with increasing tree-containing environments in cities to generate more diverse and resilient forest restoration outcomes in rural settings. This study underscores the value of integrative management approaches in addressing future forest conditions across the urban–rural continuum. Our framework provides valuable insights for policymakers, researchers, and decision-makers to advance the field of forest restoration and address the challenges of restoration across the urban–rural continuum. The rural–urban interface serves as a convergence point for forest restoration, and both urban and rural fields can benefit from each other's expertise.

54 ENVIRONMENTAL SCIENCES↗

The Transition From Rebound to Bonding in High-Velocity Metallic Microparticle Impacts: Jetting-Associated Power-Law Divergence

A metallic microparticle impacting a metallic substrate with sufficiently high velocity will adhere, assisted by the emergence of jetting—the splash-like extrusion of solid matter at the periphery of the impact. In this work, we compare real-time observations of high-velocity single-microparticle impacts to an elastic–plastic model to develop a more thorough understanding of the transition between the regimes of rebound and bonding. We first extract an effective dynamic yield strength for copper from prior experiments impacting alumina spheres onto copper substrates. We then use this dynamic yield strength to analyze impacts of copper particles on copper substrates. We find that up to moderate impact velocities, impacts and rebound velocities follow a power-law behavior well-predicted on the basis of elastic-perfectly plastic analysis and can be captured well with a single value for the dynamic strength that subsumes many details not explicitly modeled (rate and hardening effects and adiabatic heating). However, the rebound behavior diverges from the power-law at higher impact velocities approaching bonding, where jetting sets on. This divergence is associated with additional lost kinetic energy, which goes into the ejection of the material associated with jetting and into breaking incipient bonds between the particle and substrate. These results further support and develop the idea that jetting facilitates bonding where a critical amount of bond formation is required to effect permanent particle deposition and prevent the particle from rebounding.

36 MATERIALS SCIENCE↗

Necklace-structured high-harmonic generation for low-divergence, soft x-ray harmonic combs with tunable line spacing

The extreme nonlinear optical process of high-harmonic generation (HHG) makes it possible to map the properties of a laser beam onto a radiating electron wave function and, in turn, onto the emitted x-ray light. Bright HHG beams typically emerge from a longitudinal phased distribution of atomic-scale quantum antennae. Here, we form a transverse necklace-shaped phased array of linearly polarized HHG emitters, where orbital angular momentum conservation allows us to tune the line spacing and divergence properties of extreme ultraviolet and soft x-ray high-harmonic combs. The on-axis HHG emission has extremely low divergence, well below that obtained when using Gaussian driving beams, which further decreases with harmonic order. This work provides a new degree of freedom for the design of harmonic combs—particularly in the soft x-ray regime, where very limited options are available. Such harmonic beams can enable more sensitive probes of the fastest correlated charge and spin dynamics in molecules, nanoparticles, and materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Atypical Divergence of SARS-CoV-2 Orf8 from Orf7a within the Coronavirus Lineage Suggests Potential Stealthy Viral Strategies in Immune Evasion

Orf8, one of the most puzzling genes in the SARS lineage of coronaviruses, marks a unique and striking difference in genome organization between SARS-CoV-2 and SARS-CoV-1. Here, using sequence comparisons, we unequivocally reveal the distant sequence similarities between SARS-CoV-2 Orf8 with its SARS-CoV-1 counterparts and the X4-like genes of coronaviruses, including its highly divergent “paralog” gene Orf7a, whose product is a potential immune antagonist of known structure. Supervised sequence space walks unravel identity levels that drop below 10% and yet exhibit subtle conservation patterns in this novel superfamily, characterized by an immunoglobulin-like beta sandwich topology. We document the high accuracy of the sequence space walk process in detail and characterize the subgroups of the superfamily in sequence space by systematic annotation of gene and taxon groups. While SARS-CoV-1 Orf7a and Orf8 genes are most similar to bat virus sequences, their SARS-CoV-2 counterparts are closer to pangolin virus homologs, reflecting the fine structure of conservation patterns within the SARS-CoV-2 genomes. The divergence between Orf7a and Orf8 is exceptionally idiosyncratic, since Orf7a is more constrained, whereas Orf8 is subject to rampant change, a peculiar feature that may be related to hitherto-unknown viral infection strategies. Despite their common origin, the Orf7a and Orf8 protein families exhibit different modes of evolutionary trajectories within the coronavirus lineage, which might be partly attributable to their complex interactions with the mammalian host cell, reflected by a multitude of functional associations of Orf8 in SARS-CoV-2 compared to a very small number of interactions discovered for Orf7a.

60 APPLIED LIFE SCIENCES↗

When Do Different Scenarios of Future Electricity Demand Start to Meaningfully Diverge?

Climate and population change are known to influence electricity demand, but what is the impact of uncertainty in climate and population projections on electricity demand in the United States (U.S.) over the next 30 years? This question has important implications for investment decisions in the energy sector, which are typically made using a 15- to 30-year time horizon. Simply put, if future climate and population scenarios do not lead to meteorological conditions and subsequent energy demands that are distinctly different within the first 30 years then, for the purposes of investment decisions, it may not matter which potential pathway we are most likely on. The Integrated, Multisector, Multiscale Modeling (IM3) project has generated a wide, yet plausible range of 21st century high-resolution climate and population scenarios for the U.S. The IM3 projections span two climate scenarios (Representative Concentration Pathways 4.5 and 8.5) and two population scenarios (Shared Socioeconomic Pathways 3 and 5). For each of the climate scenarios, we reflect a range of climate model uncertainty by using boundary conditions from a set of climate models that are hotter and colder than the multi-model mean. In total there are eight (2 x 2 x 2) IM3 scenarios. This work explores a basic question: When do future climate and energy outcomes start to meaningfully diverge across the eight scenarios? The analysis is done on both the raw meteorology time-series from each scenario as well as a time-series of projected total electricity demand generated using IM3's Total ELectricity Loads (TELL) model. We also explore the spatial heterogeneity of the divergence signal to identify regions of the country that may be more or less path dependent.

Climate Change↗

Climate-Driven Divergence in Biophysical and Economic Impacts of Agrivoltaics

Increasing global demands for food and energy necessitate innovative land-use solutions. Agrivoltaics, colocating solar photovoltaics with agriculture, shows promise, but its widespread adoption faces complex biophysical and economic trade-offs in a changing climate. Here, we develop an integrated biophysical-economic modeling framework to quantify how agrivoltaics affect biophysical and economic impacts across the Midwestern United States under both current and project climate conditions. We find strong regional divergences driven by climate gradients. In the humid eastern Midwest, solar panel shading limits photosynthesis, leading to reduced yields (maize -24%; soybean -16%) and lower farmers' profitability (maize -16%; soybean -2%) compared to conventional agriculture. Conversely, in the semiarid western region, shading alleviates heat and water stress, moderating yield reductions for maize (-12%) and even boosting soybean yields (+6%), resulting in improved economic returns (-6% for maize; +9% for soybean), for a scenario with 33% photovoltaic ground coverage ratio. Although agrivoltaics generate substantial electrical energy across all regions, high upfront installation costs challenge solar developers compared to standalone solar photovoltaics. However, our analysis identifies “win-win” opportunities where soybean-based agrivoltaics in the semiarid region produce economic benefits for both farmers and solar developers, highlighting the necessity for region-specific designs tailored to local climate conditions. Critically, future climate projections indicate eastward expansion of semiarid conditions, broadening areas where agrivoltaics can mitigate crop yield penalties (even boosting yield) and improve overall profitability, especially under high-emission scenarios. The results provide a mechanistic and economically integrated understanding essential for developing evidence-based and region-specific strategies to scale agrivoltaics in a changing climate.

14 SOLAR ENERGY↗

Kullback–Leibler Divergence of an Open-Queuing Network of a Cell-Signal-Transduction Cascade

Queuing networks (QNs) are essential models in operations research, with applications in cloud computing and healthcare systems. However, few studies have analyzed the cell’s biological signal transduction using QN theory. This study entailed the modeling of signal transduction as an open Jackson’s QN (JQN) to theoretically determine cell signal transduction, under the assumption that the signal mediator queues in the cytoplasm, and the mediator is exchanged from one signaling molecule to another through interactions between the signaling molecules. Each signaling molecule was regarded as a network node in the JQN. The JQN Kullback–Leibler divergence (KLD) was defined using the ratio of the queuing time (λ) to the exchange time (μ), λ/μ. The mitogen-activated protein kinase (MAPK) signal-cascade model was applied, and the KLD rate per signal-transduction-period was shown to be conserved when the KLD was maximized. Our experimental study on MAPK cascade supported this conclusion. This result is similar to the entropy-rate conservation of chemical kinetics and entropy coding reported in our previous studies. Thus, JQN can be used as a novel framework to analyze signal transduction.

97 MATHEMATICS AND COMPUTING↗