Plant Development, Auxin, and the Subsystem Incompleteness Theorem

Plant morphogenesis (the process whereby form develops) requires signal cross-talking among all levels of organization to coordinate the operation of metabolic and genomic subsystems operating in a larger network of subsystems. Each subsystem can be rendered as a logic circuit supervising the operation of one or more signal-activated system. This approach simplifies complex morphogenetic phenomena and allows for their aggregation into diagrams of progressively larger networks. This technique is illustrated here by rendering two logic circuits and signal-activated subsystems, one for auxin (IAA) polar/lateral intercellular transport and another for IAA-mediated cell wall loosening. For each of these phenomena, a circuit/subsystem diagram highlights missing components (either in the logic circuit or in the subsystem it supervises) that must be identified experimentally if each of these basic plant phenomena is to be fully understood. We also illustrate the “subsystem incompleteness theorem,” which states that no subsystem is operationally self-sufficient. Indeed, a whole-organism perspective is required to understand even the most simple morphogenetic process, because, when isolated, every biological signal-activated subsystem is morphogenetically ineffective

On the Interpretation of the Normalization Constant in the Scaling Equation

The scaling equation, Y1 = βYα2, has been used empirically and explored theoretically primarily to determine the numerical value and meaning of the scaling exponent, α. The mathematical interpretation of α is clear—it is the quotient of the relative rate of change of Y1 with respect to the rate of change of Y2. In contrast, the interpretation of the normalization constant, β, is obscure, so much so that some workers have rejected the idea that it has any biological importance. With the notable exception of Steven J. Gould\u27s early work, Huxley\u27s dismissal of β largely relegated the study of its biological role to that of an academic afterthought. Here, we attempt to clarify the meaning of β by using examples from plant biology to illustrate the four primary difficulties that have obscured its importance: (1) the consistency of the units of measurement and the metric being measured (e.g., meters and body length, respectively), (2) the relationship between β and α, (3) the interpretation of scaling equations, and (4) detecting if the numerical value of β has changed and if the change is biologically meaningful. Using examples, we show that β is biologically interpretable and offers a way to quantitatively consider similarities of biological form if (1) it is expressed in terms of the relative magnitudes of Y1 or Y2 for corresponding data points in a set of Y1 = βYα2 equations, (2) the units of measurements are in the same scale, and (3) the corresponding dimensionless numbers are established based on the same units of measurement. We provide examples of where the numerical value of β or differences in the values of β are important, and we propose a research agenda examining the meaning of β values in terms of trait-based ecology

On the Interpretation of the Normalization Constant in the Scaling Equation

The scaling equation, Y1 = βY2α, has been used empirically and explored theoretically primarily to determine the numerical value and meaning of the scaling exponent, α. The mathematical interpretation of α is clear—it is the quotient of the relative rate of change of Y1 with respect to the rate of change of Y2. In contrast, the interpretation of the normalization constant, β, is obscure, so much so that some workers have rejected the idea that it has any biological importance. With the notable exception of Steven J. Gould's early work, Huxley's dismissal of β largely relegated the study of its biological role to that of an academic afterthought. Here, we attempt to clarify the meaning of β by using examples from plant biology to illustrate the four primary difficulties that have obscured its importance: (1) the consistency of the units of measurement and the metric being measured (e.g., meters and body length, respectively), (2) the relationship between β and α, (3) the interpretation of scaling equations, and (4) detecting if the numerical value of β has changed and if the change is biologically meaningful. Using examples, we show that β is biologically interpretable and offers a way to quantitatively consider similarities of biological form if (1) it is expressed in terms of the relative magnitudes of Y1 or Y2 for corresponding data points in a set of Y1 = βY2α equations, (2) the units of measurements are in the same scale, and (3) the corresponding dimensionless numbers are established based on the same units of measurement. We provide examples of where the numerical value of β or differences in the values of β are important, and we propose a research agenda examining the meaning of β values in terms of trait-based ecology

Dynamical Patterning Modules, Biogeneric Materials, and the Evolution of Multicellular Plants

Comparative analyses of developmental processes across a broad spectrum of organisms are required to fully understand the mechanisms responsible for the major evolutionary transitions among eukaryotic photosynthetic lineages (defined here as the polyphyletic algae and the monophyletic land plants). The concepts of dynamical patterning modules (DPMs) and biogeneric materials provide a framework for studying developmental processes in the context of such comparative analyses. In the context of multicellularity, DPMs are defined as sets of conserved gene products and molecular networks, in conjunction with the physical morphogenetic and patterning processes they mobilize. A biogeneric material is defined as mesoscale matter with predictable morphogenetic capabilities that arise from complex cellular conglomerates. Using these concepts, we outline some of the main events and transitions in plant evolution, and describe the DPMs and biogeneric properties associated with and responsible for these transitions. We identify four primary DPMs that played critical roles in the evolution of multicellularity (i.e., the DPMs responsible for cell-to-cell adhesion, identifying the future cell wall, cell differentiation, and cell polarity). Three important conclusions emerge from a broad phyletic comparison: (1) DPMs have been achieved in different ways, even within the same clade (e.g., phycoplastic cell division in the Chlorophyta and phragmoplastic cell division in the Streptophyta), (2) DPMs had their origins in the co-option of molecular species present in the unicellular ancestors of multicellular plants, and (3) symplastic transport mediated by intercellular connections, particularly plasmodesmata, was critical for the evolution of complex multicellularity in plants

Leaf water content contributes to global leaf trait relationships

Leaf functional traits are important indicators of plant growth and ecosystem dynamics. Despite a wealth of knowledge about leaf trait relationships, a mechanistic understanding of how biotic and abiotic factors quantitatively influence leaf trait variation and scaling is still incomplete. We propose that leaf water content (LWC) inherently affects other leaf traits, although its role has been largely neglected. Here, we present a modification of a previously validated model based on metabolic theory and use an extensive global leaf trait dataset to test it. Analyses show that mass-based photosynthetic capacity and specific leaf area increase nonlinearly with LWC, as predicted by the model. When the effects of temperature and LWC are controlled, the numerical values for the leaf area-mass scaling exponents converge onto 1.0 across plant functional groups, ecosystem types, and latitudinal zones. The data also indicate that leaf water mass is a better predictor of whole-leaf photosynthesis and leaf area than whole-leaf nitrogen and phosphorus masses. Our findings highlight a comprehensive theory that can quantitatively predict some global patterns from the leaf economics spectrum. Leaf functional traits are increasingly used as proxies for plant functions. Here, the authors show that leaf water affects other leaf traits and is a better predictor of whole-leaf photosynthesis and leaf area than leaf nitrogen or phosphorus content

Altitude patterns of seed C, N, and P concentrations and their stoichiometry in an alpine meadow on the eastern Tibetan Plateau

Understanding the altitudinal patterns of plant stoichiometry in seeds is critical for characterizing important germination and dormancy strategies, soil seed bank composition, seed predation probability, efficiency of seed dispersal and seedling performance, and to predict how biodiversity might be influenced by climate change. However, our understanding of the altitudinal patterns of seed stoichiometry is extremely limited. In this study, we measured the concentrations of carbon (C), nitrogen (N) and phosphorus (P) in the seeds of 253 herbaceous species along an altitudinal transect (2,000–4,200 m) on the eastern Tibetan Plateau, China, and further to characterize seed C:N:P stoichiometry. The geometric means of C, N, and P concentrations were 569.75 mg/g, 34.76 mg/g, and 5.03 mg/g, respectively. The C:N, C:P, and N:P ratios were 16.39, 113.31, and 6.91, respectively. The seed C, N, and P concentrations and C:N:P ratios varied widely among major plant groups and showed significant altitudinal trends. In general, C, N, and P concentrations increased, whereas seed C:N:P ratios decreased with elevation. These results inform our understanding of the altitudinal patterns of seed stoichiometry and how to model ecosystem nutrient cycling

Applying computational predictions of biorelevant solubility ratio upon self-emulsifying lipid-based formulations dispersion to predict dose number

Computational approaches are increasingly utilised in development of bio-enabling formulations, including self-emulsifying drug delivery systems (SEDDS), facilitating early indicators of success. This study investigated if in silico predictions of drug solubility gain i.e. solubility ratios (SR), after dispersion of a SEDDS in biorelevant media could be predicted from drug properties. Apparent solubility upon dispersion of two SEDDS in FaSSIF was measured for 30 structurally diverse poorly water soluble drugs. Increased drug solubility upon SEDDS dispersion was observed in all cases, with higher SRs observed for cationic and neutral versus anionic drugs at pH 6.5. Molecular descriptors and solid-state properties were used as inputs during partial least squares (PLS) modelling resulting in predictive models for SRMC (r2 = 0.81) and SRLC (r2 = 0.77). Multiple linear regression (MLR) facilitated generation of simplified SR equations with high predictivity (SRMC r2 = 0.74; SRLC r2 = 0.69), requiring only three drug properties; partition coefficient at pH 6.5 (logD6.5), melting point (Tm) and aromatic bonds as fraction of total bonds (FArom_B). Through using the equations to inform drug developability classifications (DCS) for drugs that have already been licensed as lipid based formulations, merits for development with SEDDS was predicted for 2/3 drugs

Stem Diameter (and Not Length) Limits Twig Leaf Biomass

The relationship between leaf and stem biomass as well as the relationship between leaf biomass and stem length and diameter are important to our understanding of a broad range of important plant scaling relationship because of their relationship to photosynthesis and thus growth. To understand how twig architecture (i.e., current year leaves, and stem diameter and length) affects stem diameter and length, and leaf number and biomass, we examined the twigs of 64 woody species collected from three forest types along an elevational gradient in the Wuyi Mountains, Jiangxi Province, China. We also compared the scaling relationships we observed with biomass allocation patterns reported at the whole tree level. Our results revealed isometric relationship between leaf and stem biomass on twigs despite differences in forest communities and despite changes in environmental factors along an elevational gradient. Across the 64 species, from twigs to individual trees, leaf biomass scaled approximately as the 2.0-power of stem diameter (but not for stem length or leaf number). These results help to identify a general rule that operates at two different levels of biological organization (twigs and whole trees). The scaling relationship between leaf biomass and stem diameter in twigs is insensitive to differences in species composition, elevation, or forest type. We speculate that this rule emerges because stem diameter serves as a proxy for the amount of resources supplied per unit cross section to developing leaves and for the flow of photosynthates from mature leaves to the rest of the plant body