Complex systems that exhibit emergent behaviors arise as a result of nonlinear interdependencies among multiple components. Characterizing how such whole system dynamics are sustained through multivariate interaction remains an open question. In this study, we propose an information flow‐based framework to investigate how the present state of any component arises as a result of the past interactions among interdependent variables, which is termed as causal history. Using a partitioning time lag, we divide this into immediate and distant causal history components and then characterize the information flow‐based interactions within these as self‐ and cross‐feedbacks. Such a partition allows us to characterize the information flow from the two feedbacks in both histories by using partial information decomposition as unique, synergistic, or redundant interactions. We employ this casual history analysis approach to investigate the information flows in a short‐memory coupled logistic model and a long‐memory observed stream chemistry dynamics. While the dynamics of the short‐memory system are mainly maintained by its recent historical states, the current state of each stream solute is sustained by self‐feedback‐dominated recent dynamics and cross‐dependency‐dominated earlier dynamics. The analysis suggests that the observed 1/
- Award ID(s):
- 1735095
- NSF-PAR ID:
- 10294321
- Date Published:
- Journal Name:
- Proceedings of the National Academy of Sciences
- Volume:
- 118
- Issue:
- 12
- ISSN:
- 0027-8424
- Page Range / eLocation ID:
- e2022598118
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
more » « less
Abstract f signature of each solute is a result of the interactions with other variables in the stream. Based on high‐density data streams, the approach developed here for investigating multivariate evolutionary dynamics provides an effective way to understand how components of dynamical system interact to create emergent whole system behavioral patterns such as long‐memory dependency. -
Cellular fates are determined by genes interacting across large, complex biological networks. A critical question is how to identify causal relationships spanning distinct signaling pathways and underlying organismal phenotypes. Here, we address this question by constructing a Boolean model of a well-studied developmental network and analyzing information flows through the system. Depending on environmental signals Caenorhabditis elegans develop normally to sexual maturity or enter a reproductively delayed, developmentally quiescent ‘dauer’ state, progressing to maturity when the environment changes. The developmental network that starts with environmental signal and ends in the dauer/no dauer fate involves genes across 4 signaling pathways including cyclic GMP, Insulin/IGF-1, TGF- β and steroid hormone synthesis. We identified three stable motifs leading to normal development, each composed of genes interacting across the Insulin/IGF-1, TGF- β and steroid hormone synthesis pathways. Three genes known to influence dauer fate, daf-2 , daf-7 and hsf-1 , acted as driver nodes in the system. Using causal logic analysis, we identified a five gene cyclic subgraph integrating the information flow from environmental signal to dauer fate. Perturbation analysis showed that a multifactorial insulin profile determined the stable motifs the system entered and interacted with daf-12 as the switchpoint driving the dauer/no dauer fate. Our results show that complex organismal systems can be distilled into abstract representations that permit full characterization of the causal relationships driving developmental fates. Analyzing organismal systems from this perspective of logic and function has important implications for studies examining the evolution and conservation of signaling pathways.more » « less
-
more » « less
Abstract The molecular machinery for protein synthesis is profoundly similar between plants and other eukaryotes. Mechanisms of translational gene regulation are embedded into the broader network of RNA‐level processes including RNA quality control and RNA turnover. However, over eons of their separate history, plants acquired new components, dropped others, and generally evolved an alternate way of making the parts list of protein synthesis work. Research over the past 5 years has unveiled how plants utilize translational control to defend themselves against viruses, regulate translation in response to metabolites, and reversibly adjust translation to a wide variety of environmental parameters. Moreover, during seed and pollen development plants make use of RNA granules and other translational controls to underpin developmental transitions between quiescent and metabolically active stages. The economics of resource allocation over the daily light–dark cycle also include controls over cellular protein synthesis. Important new insights into translational control on cytosolic ribosomes continue to emerge from studies of translational control mechanisms in viruses. Finally, sketches of coherent signaling pathways that connect external stimuli with a translational response are emerging, anchored in part around TOR and GCN2 kinase signaling networks. These again reveal some mechanisms that are familiar and others that are different from other eukaryotes, motivating deeper studies on translational control in plants.
This article is categorized under:
Translation > Translation Regulation
RNA Structure and Dynamics > Influence of RNA Structure in Biological Systems
RNA Interactions with Proteins and Other Molecules > Protein‐RNA Interactions: Functional Implications
-
more » « less
Abstract Recent work has explored spatiotemporal relationships between excitatory (
E ) and inhibitory (I ) signaling within neural networks, and the effect of these relationships on network activity patterns. Data from these studies have indicated that excitation and inhibition are maintained at a similar level across long time periods and that excitatory and inhibitory currents may be tightly synchronized. Disruption of this balance—leading to an aberrantE /I ratio—is implicated in various brain pathologies. However, a thorough characterization of the relationship betweenE andI currents in experimental settings is largely impossible, due to their tight regulation at multiple cellular and network levels. Here, we use biophysical neural network models to investigate the emergence and properties of balanced states by heterogeneous mechanisms. Our results show that a network can homeostatically regulate theE /I ratio through interactions among multiple cellular and network factors, including average firing rates, synaptic weights and average neural depolarization levels in excitatory/inhibitory populations. Complex and competing interactions between firing rates and depolarization levels allow these factors to alternately dominate network dynamics in different synaptic weight regimes. This leads to the emergence of distinct mechanisms responsible for determining a balanced state and its dynamical correlate. Our analysis provides a comprehensive picture of howE /I ratio changes when manipulating specific network properties, and identifies the mechanisms regulatingE /I balance. These results provide a framework to explain the diverse, and in some cases, contradictory experimental observations on theE /I state in different brain states and conditions. -
INTRODUCTION Neurons are by far the most diverse of all cell types in animals, to the extent that “cell types” in mammalian brains are still mostly heterogeneous groups, and there is no consensus definition of the term. The Drosophila optic lobes, with approximately 200 well-defined cell types, provides a tractable system with which to address the genetic basis of neuronal type diversity. We previously characterized the distinct developmental gene expression program of each of these types using single-cell RNA sequencing (scRNA-seq), with one-to-one correspondence to the known morphological types. RATIONALE The identity of fly neurons is determined by temporal and spatial patterning mechanisms in stem cell progenitors, but it remained unclear how these cell fate decisions are implemented and maintained in postmitotic neurons. It was proposed in Caenorhabditis elegans that unique combinations of terminal selector transcription factors (TFs) that are continuously expressed in each neuron control nearly all of its type-specific gene expression. This model implies that it should be possible to engineer predictable and complete switches of identity between different neurons just by modifying these sustained TFs. We aimed to test this prediction in the Drosophila visual system. RESULTS Here, we used our developmental scRNA-seq atlases to identify the potential terminal selector genes in all optic lobe neurons. We found unique combinations of, on average, 10 differentially expressed and stably maintained (across all stages of development) TFs in each neuron. Through genetic gain- and loss-of-function experiments in postmitotic neurons, we showed that modifications of these selector codes are sufficient to induce predictable switches of identity between various cell types. Combinations of terminal selectors jointly control both developmental (e.g., morphology) and functional (e.g., neurotransmitters and their receptors) features of neurons. The closely related Transmedullary 1 (Tm1), Tm2, Tm4, and Tm6 neurons (see the figure) share a similar code of terminal selectors, but can be distinguished from each other by three TFs that are continuously and specifically expressed in one of these cell types: Drgx in Tm1, Pdm3 in Tm2, and SoxN in Tm6. We showed that the removal of each of these selectors in these cell types reprograms them to the default Tm4 fate. We validated these conversions using both morphological features and molecular markers. In addition, we performed scRNA-seq to show that ectopic expression of pdm3 in Tm4 and Tm6 neurons converts them to neurons with transcriptomes that are nearly indistinguishable from that of wild-type Tm2 neurons. We also show that Drgx expression in Tm1 neurons is regulated by Klumpfuss, a TF expressed in stem cells that instructs this fate in progenitors, establishing a link between the regulatory programs that specify neuronal fates and those that implement them. We identified an intronic enhancer in the Drgx locus whose chromatin is specifically accessible in Tm1 neurons and in which Klu motifs are enriched. Genomic deletion of this region knocked down Drgx expression specifically in Tm1 neurons, leaving it intact in the other cell types that normally express it. We further validated this concept by demonstrating that ectopic expression of Vsx (visual system homeobox) genes in Mi15 neurons not only converts them morphologically to Dm2 neurons, but also leads to the loss of their aminergic identity. Our results suggest that selector combinations can be further sculpted by receptor tyrosine kinase signaling after neurogenesis, providing a potential mechanism for postmitotic plasticity of neuronal fates. Finally, we combined our transcriptomic datasets with previously generated chromatin accessibility datasets to understand the mechanisms that control brain wiring downstream of terminal selectors. We built predictive computational models of gene regulatory networks using the Inferelator framework. Experimental validations of these networks revealed how selectors interact with ecdysone-responsive TFs to activate a large and specific repertoire of cell surface proteins and other effectors in each neuron at the onset of synapse formation. We showed that these network models can be used to identify downstream effectors that mediate specific cellular decisions during circuit formation. For instance, reduced levels of cut expression in Tm2 neurons, because of its negative regulation by pdm3 , controls the synaptic layer targeting of their axons. Knockdown of cut in Tm1 neurons is sufficient to redirect their axons to the Tm2 layer in the lobula neuropil without affecting other morphological features. CONCLUSION Our results support a model in which neuronal type identity is primarily determined by a relatively simple code of continuously expressed terminal selector TFs in each cell type throughout development. Our results provide a unified framework of how specific fates are initiated and maintained in postmitotic neurons and open new avenues to understanding synaptic specificity through gene regulatory networks. The conservation of this regulatory logic in both C. elegans and Drosophila makes it likely that the terminal selector concept will also be useful in understanding and manipulating the neuronal diversity of mammalian brains. Terminal selectors enable predictive cell fate reprogramming. Tm1, Tm2, Tm4, and Tm6 neurons of the Drosophila visual system share a core set of TFs continuously expressed by each cell type (simplified). The default Tm4 fate is overridden by the expression of a single additional terminal selector to generate Tm1 ( Drgx ), Tm2 ( pdm3 ), or Tm6 ( SoxN ) fates.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1073/pnas.2022598118
