Dromiack, H. | bioRxiv Science

bioRxiv2026

A Multiscale Model of Collective Decision-Making in Hybrid Aspen Tree Tissues Describes Bud-Dormancy Break

The mechanisms underlying cellular coordination within tissues remain enigmatic. Most models focus on interactions between just two levels of organization - cell and tissue - and do not leverage data across deeper hierarchies that best represent living processes, with many spatial and temporal scales interacting. Integrating many scales, from molecular to cellular to tissular to organismal to populational, may be necessary to fully elucidate tissue function, especially in cases of sparse data at each level. Here, we investigate multiscale, robust regulation of tissue-level decision-making, using experimental studies of cold induced dormancy release in terminal buds of hybrid aspen trees as our case study. We develop a network model of terminal bud meristematic tissue, incorporating expression data from a key cold induced regulator gene, FLOWERING LOCUS T (FT1), which controls bud dormancy release, combined with data on variability in cell-to-cell communication controlled by FT1 mediated regulation of plasmodesmata. The model can explain dormancy breaking under constant temperature, but not variable temperature. We introduce constraints from organismal-level data and show how the presence of coordinated cellular interactions within individual plant tissues is necessary to reproduce data of population-level statistics. Our findings demonstrate how mechanisms of tissue function may be better constrained when data are used across more scales. They also hint at potential tantalizing new insights such as how tissue function might not be solely dictated bottom-up from molecular interactions, but also top-down from constraints imposed by the organismal and population context. Both implications illustrate the critical importance of incorporating cross-scale information processing in modeling biological decision-making. Significance StatementBiological hierarchies involve decision-making mediated via nested feedback loops. Data-informed modeling of this hierarchal complexity remains challenging. Here, we leverage unique features of plant biology - stationary growth, prolonged decision-making, and physical structure - to study multiscale dynamics determining cellular mechanisms of bud dormancy breaking in aspen trees. We examine how tissue function can be driven bottom-up from gene regulatory networks and top-down from organismal population-level statistics. Modeling experimental data collected at genetic, cellular, and organismal levels, reveals how population-level data allow constraining mechanisms of cellular coordination within individual plants when cellular data are sparse. Our findings demonstrate how multiscale methods can combat data sparsity and suggest new ways to study cellular coordination within organisms could be dictated by organismal population-level constraints.

synthetic biology↗

bioRxiv2024

Revealing non-trivial information structures in aneural biological tissues via functional connectivity

A central challenge in the progression of a variety of open questions in biology, such as morphogenesis, wound healing, and development, is learning from empirical data how information is integrated to support tissue-level function and behavior. Information-theoretic approaches provide a quantitative framework for extracting patterns from data, but so far have been predominantly applied to neuronal systems at the tissue-level. Here, we demonstrate how time series of Ca2+ dynamics can be used to identify the structure and information dynamics of other biological tissues. To this end, we expressed the calcium reporter GCaMP6s in an organoid system of explanted amphibian epidermis derived from the African clawed frog Xenopus laevis, and imaged calcium activity pre- and post- a puncture injury, for six replicate organoids. We constructed functional connectivity networks by computing mutual information between cells from time series derived using medical imaging techniques to track intracellular Ca2+. We analyzed network properties including degree distribution, spatial embedding, and modular structure. We find organoid networks exhibit more connectivity than null models, with high degree hubs and mesoscale community structure with spatial clustering. Utilizing functional connectivity networks, we show the tissue retains non-random features after injury, displays long range correlations and structure, and non-trivial clustering that is not necessarily spatially dependent. Our results suggest increased integration after injury, possible cellular coordination in response to injury, and some type of generative structure of the anatomy. While we study Ca2+ in Xenopus epidermal cells, our computational approach and analyses highlight how methods developed to analyze functional connectivity in neuronal tissues can be generalized to any tissue and fluorescent signal type. Our framework therefore provides a bridge between neuroscience and more basal modes of information processing. Author summaryA central challenge in understanding several diverse processes in biology, including morphogenesis, wound healing, and development, is learning from empirical data how information is integrated to support tissue-level function and behavior. Significant progress in understanding information integration has occurred in neuroscience via the use of observable live calcium reporters throughout neural tissues. However, these same techniques have seen limited use in the non-neural tissues of multicellular organisms despite similarities in tissue communication. Here we utilize methods designed for neural tissues and modify them to work on any tissue type, demonstrating how non-neural tissues also contain non-random and potentially meaningful structures to be gleaned from information theoretic approaches. In the case of epidermal tissue derived from developing amphibians, we find non-trivial informational structure over greater spatial and temporal scales than those found in neural tissue. This hints at how more exploration into information structures within these tissue types could provide a deeper understanding into information processing within living systems beyond the nervous system.

systems biology↗