Cellular clarity: a logistic regression approach to identify root epidermal regulators of iron deficiency response.

BACKGROUND: Plants respond to stress through highly tuned regulatory networks. While prior works identified master regulators of iron deficiency responses in A. thaliana from whole-root data, identifying regulators that act at the cellular level is critical to a more comprehensive understanding of iron homeostasis. Within the root epidermis complex molecular mechanisms that facilitate iron reduction and uptake from the rhizosphere are known to be regulated by bHLH transcriptional regulators. However, many questions remain about the regulatory mechanisms that control these responses, and how they may integrate with developmental processes within the epidermis. Here, we use transcriptional profiling to gain insight into root epidermis-specific regulatory processes. RESULTS: Set comparisons of differentially expressed genes (DEGs) between whole root and epidermis transcript measurements identified differences in magnitude and timing of organ-level vs. epidermis-specific responses. Utilizing a unique sampling method combined with a mutual information metric across time-lagged and non-time-lagged windows, we identified relationships between clusters of functionally relevant differentially expressed genes suggesting that developmental regulatory processes may act upstream of well-known Fe-specific responses. By integrating static data (DNA motif information) with time-series transcriptomic data and employing machine learning approaches, specifically logistic regression models with LASSO, we also identified putative motifs that served as crucial features for predicting differentially expressed genes. Twenty-eight transcription factors (TFs) known to bind to these motifs were not differentially expressed, indicating that these TFs may be regulated post-transcriptionally or post-translationally. Notably, many of these TFs also play a role in root development and general stress response. CONCLUSIONS: This work uncovered key differences in -Fe response identified using whole root data vs. cell-specific root epidermal data. Machine learning approaches combined with additional static data identified putative regulators of -Fe response that would not have been identified solely through transcriptomic profiles and reveal how developmental and general stress responses within the epidermis may act upstream of more specialized -Fe responses for Fe uptake.

POPEYE intercellular localization mediates cell-specific iron deficiency responses.

Plants must tightly regulate iron (Fe) sensing, acquisition, transport, mobilization, and storage to ensure sufficient levels of this essential micronutrient. POPEYE (PYE) is an iron responsive transcription factor that positively regulates the iron deficiency response, while also repressing genes essential for maintaining iron homeostasis. However, little is known about how PYE plays such contradictory roles. Under iron-deficient conditions, pPYE:GFP accumulates in the root pericycle while pPYE:PYE-GFP is localized to the nucleus in all Arabidopsis (Arabidopsis thaliana) root cells, suggesting that PYE may have cell-specific dynamics and functions. Using scanning fluorescence correlation spectroscopy and cell-specific promoters, we found that PYE-GFP moves between different cells and that the tendency for movement corresponds with transcript abundance. While localization to the cortex, endodermis, and vasculature is required to manage changes in iron availability, vasculature and endodermis localization of PYE-GFP protein exacerbated pye-1 defects and elicited a host of transcriptional changes that are detrimental to iron mobilization. Our findings indicate that PYE acts as a positive regulator of iron deficiency response by regulating iron bioavailability differentially across cells, which may trigger iron uptake from the surrounding rhizosphere and impact root energy metabolism.

E3 ligase BRUTUS Is a Negative Regulator for the Cellular Energy Level and the Expression of Energy Metabolism-Related Genes Encoded by Two Organellar Genomes in Leaf Tissues.

E3 ligase BRUTUS (BTS), a putative iron sensor, is expressed in both root and shoot tissues in seedlings of Arabidopsis thaliana. The role of BTS in root tissues has been well established. However, its role in shoot tissues has been scarcely studied. Comparative transcriptome analysis with shoot and root tissues revealed that BTS is involved in regulating energy metabolism by modulating expression of mitochondrial and chloroplast genes in shoot tissues. Moreover, in shoot tissues of bts-1 plants, levels of ADP and ATP and the ratio of ADP/ATP were greatly increased with a concomitant decrease in levels of soluble sugar and starch. The decreased starch level in bts-1 shoot tissues was restored to the level of shoot tissues of wild-type plants upon vanadate treatment. Through this study, we expand the role of BTS to regulation of energy metabolism in the shoot in addition to its role of iron deficiency response in roots.

Solving the puzzle of Fe homeostasis by integrating molecular, mathematical, and societal models.

To ensure optimal utilization and bioavailability, iron uptake, transport, subcellular localization, and assimilation are tightly regulated in plants. Herein, we examine recent advances in our understanding of cellular responses to Fe deficiency. We then use intracellular mechanisms of Fe homeostasis to discuss how formalizing cell biology knowledge via a mathematical model can advance discovery even when quantitative data is limited. Using simulation-based inference to identify plausible systems mechanisms that conform to known emergent phenotypes can yield novel, testable hypotheses to guide targeted experiments. However, this approach relies on the accurate encoding of domain-expert knowledge in exploratory mathematical models. We argue that this would be facilitated by fostering more "systems thinking" life scientists and that diversifying your research team may be a practical path to achieve that goal.

Broadening the impact of plant science through innovative, integrative, and inclusive outreach.

Population growth and climate change will impact food security and potentially exacerbate the environmental toll that agriculture has taken on our planet. These existential concerns demand that a passionate, interdisciplinary, and diverse community of plant science professionals is trained during the 21st century. Furthermore, societal trends that question the importance of science and expert knowledge highlight the need to better communicate the value of rigorous fundamental scientific exploration. Engaging students and the general public in the wonder of plants, and science in general, requires renewed efforts that take advantage of advances in technology and new models of funding and knowledge dissemination. In November 2018, funded by the National Science Foundation through the Arabidopsis Research and Training for the 21st century (ART 21) research coordination network, a symposium and workshop were held that included a diverse panel of students, scientists, educators, and administrators from across the US. The purpose of the workshop was to re-envision how outreach programs are funded, evaluated, acknowledged, and shared within the plant science community. One key objective was to generate a roadmap for future efforts. We hope that this document will serve as such, by providing a comprehensive resource for students and young faculty interested in developing effective outreach programs. We also anticipate that this document will guide the formation of community partnerships to scale up currently successful outreach programs, and lead to the design of future programs that effectively engage with a more diverse student body and citizenry.

A hybrid model connecting regulatory interactions with stem cell divisions in the root.

Stem cells give rise to the entirety of cells within an organ. Maintaining stem cell identity and coordinately regulating stem cell divisions is crucial for proper development. In plants, mobile proteins, such as WUSCHEL-RELATED HOMEOBOX 5 (WOX5) and SHORTROOT (SHR), regulate divisions in the root stem cell niche. However, how these proteins coordinately function to establish systemic behaviour is not well understood. We propose a non-cell autonomous role for WOX5 in the cortex endodermis initial (CEI) and identify a regulator, ANGUSTIFOLIA (AN3)/GRF-INTERACTING FACTOR 1, that coordinates CEI divisions. Here, we show with a multi-scale hybrid model integrating ordinary differential equations (ODEs) and agent-based modeling that quiescent center (QC) and CEI divisions have different dynamics. Specifically, by combining continuous models to describe regulatory networks and agent-based rules, we model systemic behaviour, which led us to predict cell-type-specific expression dynamics of SHR, SCARECROW, WOX5, AN3 and CYCLIND6;1, and experimentally validate CEI cell divisions. Conclusively, our results show an interdependency between CEI and QC divisions.

MAGIC: Live imaging of cellular division in plant seedlings using lightsheet microscopy.

Imaging technologies have been used to understand plant genetic and developmental processes, from the dynamics of gene expression to tissue and organ morphogenesis. Although the field has advanced incredibly in recent years, gaps remain in identifying fine and dynamic spatiotemporal intervals of target processes, such as changes to gene expression in response to abiotic stresses. Lightsheet microscopy is a valuable tool for such studies due to its ability to perform long-term imaging at fine intervals of time and at low photo-toxicity of live vertically oriented seedlings. In this chapter, we describe a detailed method for preparing and imaging Arabidopsis thaliana seedlings for lightsheet microscopy via a Multi-Sample Imaging Growth Chamber (MAGIC), which allows simultaneous imaging of at least four samples. This method opens new avenues for acquiring imaging data at a high temporal resolution, which can be eventually probed to identify key regulatory time points and any spatial dependencies of target developmental processes.

BioVision Tracker: A semi-automated image analysis software for spatiotemporal gene expression tracking in Arabidopsis thaliana.

Fluorescence microscopy can produce large quantities of data that reveal the spatiotemporal behavior of gene expression at the cellular level in plants. Automated or semi-automated image analysis methods are required to extract data from these images. These data are helpful in revealing spatial and/or temporal-dependent processes that influence development in the meristematic region of plant roots. Tracking spatiotemporal gene expression in the meristem requires the processing of multiple microscopy imaging channels (one channel used to image root geometry which serves as a reference for relating locations within the root, and one or more channels used to image fluorescent gene expression signals). Many automated image analysis methods rely on the staining of cell walls with fluorescent dyes to capture cellular geometry and overall root geometry. However, in long time-course imaging experiments, dyes may fade which hinders spatial assessment in image analysis. Here, we describe a procedure for analyzing 3D microscopy images to track spatiotemporal gene expression signals using the MATLAB-based BioVision Tracker software. This software requires either a fluorescence image or a brightfield image to analyze root geometry and a fluorescence image to capture and track temporal changes in gene expression.

Iron homeostasis and plant immune responses: Recent insights and translational implications.

Iron metabolism and the plant immune system are both critical for plant vigor in natural ecosystems and for reliable agricultural productivity. Mechanistic studies of plant iron home-ostasis and plant immunity have traditionally been carried out in isolation from each other; however, our growing understanding of both processes has uncovered significant connections. For example, iron plays a critical role in the generation of reactive oxygen intermediates during immunity and has been recently implicated as a critical factor for immune-initiated cell death via ferroptosis. Moreover, plant iron stress triggers immune activation, suggesting that sensing of iron depletion is a mechanism by which plants recognize a pathogen threat. The iron deficiency response engages hormone signaling sectors that are also utilized for plant immune signaling, providing a probable explanation for iron-immunity cross-talk. Finally, interference with iron acquisition by pathogens might be a critical component of the immune response. Efforts to address the global burden of iron deficiency-related anemia have focused on classical breeding and transgenic approaches to develop crops biofortified for iron content. However, our improved mechanistic understanding of plant iron metabolism suggests that such alterations could promote or impede plant immunity, depending on the nature of the alteration and the virulence strategy of the pathogen. Effects of iron biofortification on disease resistance should be evaluated while developing plants for iron biofortification.

Computational solutions for modeling and controlling plant response to abiotic stresses: a review with focus on iron deficiency.

Computational solutions enable plant scientists to model protein-mediated stress responses and characterize novel gene functions that coordinate responses to a variety of abiotic stress conditions. Recently, density functional theory was used to study proteins active sites and elucidate enzyme conversion mechanisms involved in iron deficiency responsive signaling pathways. Computational approaches for protein homology modeling and the kinetic modeling of signaling pathways have also resolved the identity and function in proteins involved in iron deficiency signaling pathways. Significant changes in gene relationships under other stress conditions, such as heat or drought stress, have been recently identified using differential network analysis, suggesting that stress tolerance is achieved through asynchronous control. Moreover, the increasing development and use of statistical modeling and systematic modeling of transcriptomic data have provided significant insight into the gene regulatory mechanisms associated with abiotic stress responses. These types of in silico approaches have facilitated the plant science community's future goals of developing multi-scale models of responses to iron deficiency stress and other abiotic stress conditions.

Automated Imaging, Tracking, and Analytics Pipeline for Differentiating Environmental Effects on Root Meristematic Cell Division.

Exposure of plants to abiotic stresses, whether individually or in combination, triggers dynamic changes to gene regulation. These responses induce distinct changes in phenotypic characteristics, enabling the plant to adapt to changing environments. For example, iron deficiency and heat stress have been shown to alter root development by reducing primary root growth and reducing cell proliferation, respectively. Currently, identifying the dynamic temporal coordination of genetic responses to combined abiotic stresses remains a bottleneck. This is, in part, due to an inability to isolate specific intervals in developmental time where differential activity in plant stress responses plays a critical role. Here, we observed that iron deficiency, in combination with temporary heat stress, suppresses the expression of iron deficiency-responsive pPYE::LUC (POPEYE::luciferase) and pBTS::LUC (BRUTUS::luciferase) reporter genes. Moreover, root growth was suppressed less under combined iron deficiency and heat stress than under either single stress condition. To further explore the interaction between pathways, we also created a computer vision pipeline to extract, analyze, and compare high-dimensional dynamic spatial and temporal cellular data in response to heat and iron deficiency stress conditions at high temporal resolution. Specifically, we used fluorescence light sheet microscopy to image Arabidopsis thaliana roots expressing CYCB1;1:GFP, a marker for cell entry into mitosis, every 20 min for 24 h exposed to either iron sufficiency, iron deficiency, heat stress, or combined iron deficiency and heat stress. Our pipeline extracted spatiotemporal metrics from these time-course data. These metrics showed that the persistency and timing of CYCB1;1:GFP signal were uniquely different under combined iron deficiency and heat stress conditions versus the single stress conditions. These metrics also indicated that the spatiotemporal characteristics of the CYCB1;1:GFP signal under combined stress were more dissimilar to the control response than the response seen under iron deficiency for the majority of the 24-h experiment. Moreover, the combined stress response was less dissimilar to the control than the response seen under heat stress. This indicated that pathways activated when the plant is exposed to both iron deficiency and heat stress affected CYCB1;1:GFP spatiotemporal function antagonistically.

Keep talking: crosstalk between iron and sulfur networks fine-tunes growth and development to promote survival under iron limitation.

Plants are capable of synthesizing all the molecules necessary to complete their life cycle from minerals, water, and light. This plasticity, however, comes at a high energetic cost and therefore plants need to regulate their economy and allocate resources accordingly. Iron-sulfur (Fe-S) clusters are at the center of photosynthesis, respiration, amino acid, and DNA metabolism. Fe-S clusters are extraordinary catalysts, but their main components (Fe2+ and S2-) are highly reactive and potentially toxic. To prevent toxicity, plants have evolved mechanisms to regulate the uptake, storage, and assimilation of Fe and S. Recent advances have been made in understanding the cellular economy of Fe and S metabolism individually, and growing evidence suggests that there is dynamic crosstalk between Fe and S networks. In this review, we summarize and discuss recent literature on Fe sensing, allocation, use efficiency, and, when pertinent, its relationship to S metabolism. Our future perspectives include a discussion about the open questions and challenges ahead and how the plant nutrition field can come together to approach these questions in a cohesive and more efficient way.

Hemerythrin E3 Ubiquitin Ligases as Negative Regulators of Iron Homeostasis in Plants.

Iron (Fe) is an essential nutrient for plants, but at the same time its redox properties can make it a dangerous toxin inside living cells. Homeostasis between uptake, use and storage of Fe must be maintained at all times. A small family of unique hemerythrin E3 ubiquitin ligases found in green algae and plants play an important role in avoiding toxic Fe overload, acting as negative regulators of Fe homeostasis. Protein interaction data showed that they target specific transcription factors for degradation by the 26S proteasome. It is thought that the activity of the E3 ubiquitin ligases is controlled by Fe binding to the N-terminal hemerythrin motifs. Here, we discuss what we have learned so far from studies on the HRZ (Hemerythrin RING Zinc finger) proteins in rice, the homologous BTS (BRUTUS) and root-specific BTSL (BRUTUS-LIKE) in Arabidopsis. A mechanistic model is proposed to help focus future research questions towards a full understanding of the regulatory role of these proteins in Fe homeostasis in plants.

Defecatory dysfunction and other clinical variables are predictors of pessary discontinuation.

INTRODUCTION AND HYPOTHESIS: Pessaries provide first-line therapy for women with pelvic organ prolapse (POP) and stress urinary incontinence (SUI). The primary hypothesis was that defecatory dysfunction was associated with pessary discontinuation. METHODS: This was a retrospective cohort study of all women undergoing first pessary placement at one academic center from April 2014 to January 2017. Defecatory dysfunction was defined as the presence of constipation, rectal straining, rectal splinting, and/or incomplete defecation. Pessary discontinuation was defined as <1 year of pessary use and not using one at the most recent visit. Descriptive statistics; Person's chi-square, Fisher's exact, and Student's t test, and multivariate logistic regression analysis were used where appropriate. RESULTS: Charts of 1092 women were reviewed and 1071 were included. Mean age was 62 ± 15 years, mean body mass index (BMI) 28 ± 6 kg/m2, and mean parity 2 ± 1; 68% were Caucasian, 73% were menopausal, and 41% were sexually active. Reason for pessary use included POP (46%), SUI (24%), or both (30%). Overall pessary discontinuation rate was 77%; overall rate of defecatory dysfunction was 45%. In a logistic regression model, defecatory dysfunction in the form of incomplete defecation remained significantly associated with pessary discontinuation [odds ratio (OR) 3.29, 95% confidence interval (CI) 1.43-7.52]. Absence of bulge symptoms (OR 2.18, 95% CI 1.22-3.90), and younger age (OR 1.02, 95% CI 1.02-1.05) also remained significantly associated with pessary discontinuation. CONCLUSIONS: Pessary discontinuation was common, and defecatory dysfunction in the form of incomplete defecation had the strongest association with discontinuation. Understanding predictive factors of pessary discontinuation may help guide clinicians and patients when choosing treatment options for pelvic floor dysfunction.

The bHLH transcription factor ILR3 modulates multiple stress responses in Arabidopsis.

KEY MESSAGE: ILR3 and PYE function in a regulatory network that modulates GLS accumulation under iron deficiency. The molecular processes involved in the cross talk between iron (Fe) homeostasis and other metabolic processes in plants are poorly understood. In Arabidopsis thaliana the transcription factor IAA-LEUCINE RESISTANT3 (ILR3) regulates iron deficiency response, aliphatic glucosinolate (GLS) biosynthesis and pathogen response. ILR3 is also known to interact with its homolog, POPEYE (PYE), which also plays a role in Fe response. However, little is known about how ILR3 regulates such diverse processes, particularly, via its interaction with PYE. Since GLS are produced as part of a defense mechanism against wounding pathogens, we examined pILR3::ß-GLUCURONIDASE expression and found that Fe deficiency enhances the wound-induced expression of ILR3 in roots and that ILR3 is induced in response to the wounding pathogen, sugarbeet root cyst nematode (Heterodera schachtii). We also examined the expression pattern of genes involved in Fe homeostasis and aliphatic GLS biosynthesis in pye-1, ilr3-2 and pye-1xilr3-2 (pxi) mutants and found that ILR3 and PYE differentially regulate the expression of genes involved these processes under Fe deficiency. We measured GLS levels and sugarbeet root cyst nematode infection rates under varying Fe conditions, and found that long-chain GLS levels are elevated in ilr3-2 and pxi mutants. This increase in long-chain GLS accumulation is correlated with elevated nematode resistance in ilr3-2 and pxi mutants in the absence of Fe. Our findings suggest that ILR3 and PYE function in a regulatory network that controls wounding pathogen response in plant roots by modulating GLS accumulation under iron deficiency.

The E3 ligase BRUTUS facilitates degradation of VOZ1/2 transcription factors.

BRUTUS (BTS) is an iron binding E3 ligase that has been shown to bind to and influence the accumulation of target basic helix-loop-helix transcription factors through 26S proteasome-mediated degradation in Arabidopsis thaliana. Vascular Plant One-Zinc finger 1 (VOZ1) and Vascular plant One-Zinc finger 2 (VOZ2) are NAM, ATAF1/2 and CUC2 (NAC) domain transcription factors that negatively regulate drought and cold stress responses in plants and have previously been shown to be degraded via the 26S proteasome. However, the mechanism that initializes this degradation is unknown. Here, we show that BTS interacts with VOZ1 and VOZ2 and that the presence of the BTS RING domain is essential for these interactions. Through cell-free degradation and immunodetection analyses, we demonstrate that BTS facilitates the degradation of Vascular plant One-Zinc finger 1/2 (VOZ1/2) protein in the nucleus particularly under drought and cold stress conditions. In addition to its known role in controlling the iron-deficiency response in plants, here, we report that BTS may play a role in drought and possibly other abiotic stress responses by facilitating the degradation of transcription factors, VOZ1/2.

More than meets the eye: Emergent properties of transcription factors networks in Arabidopsis.

Uncovering and mathematically modeling Transcription Factor Networks (TFNs) are the first steps in engineering plants with traits that are better equipped to respond to changing environments. Although several plant TFNs are well known, the framework for systematically modeling complex characteristics such as switch-like behavior, oscillations, and homeostasis that emerge from them remain elusive. This review highlights literature that provides, in part, experimental and computational techniques for characterizing TFNs. This review also outlines methodologies that have been used to mathematically model the dynamic characteristics of TFNs. We present several examples of TFNs in plants that are involved in developmental and stress response. In several cases, advanced algorithms capture or quantify emergent properties that serve as the basis for robustness and adaptability in plant responses. Increasing the use of mathematical approaches will shed new light on these regulatory properties that control plant growth and development, leading to mathematical models that predict plant behavior. This article is part of a Special Issue entitled: Plant Gene Regulatory Mechanisms and Networks, edited by Dr. Erich Grotewold and Dr. Nathan Springer.

Further insight into BRUTUS domain composition and functionality.

BRUTUS (BTS) is a hemerythrin (HHE) domain containing E3 ligase that facilitates the degradation of POPEYE-like (PYEL) proteins in a proteasomal-dependent manner. Deletion of BTS HHE domains enhances BTS stability in the presence of iron and also complements loss of BTS function, suggesting that the HHE domains are critical for protein stability but not for enzymatic function. The RING E3 domain plays an essential role in BTS' capacity to both interact with PYEL proteins and to act as an E3 ligase. Here we show that removal of the RING domain does not complement loss of BTS function. We conclude that enzymatic activity of BTS via the RING domain is essential for response to iron deficiency in plants. Further, we analyze possible BTS domain structure evolution and predict that the combination of domains found in BTS is specific to photosynthetic organisms, potentially indicative of a role for BTS and its orthologs in mitigating the iron-related challenges presented by photosynthesis.

Clustering and Differential Alignment Algorithm: Identification of Early Stage Regulators in the Arabidopsis thaliana Iron Deficiency Response.

Time course transcriptome datasets are commonly used to predict key gene regulators associated with stress responses and to explore gene functionality. Techniques developed to extract causal relationships between genes from high throughput time course expression data are limited by low signal levels coupled with noise and sparseness in time points. We deal with these limitations by proposing the Cluster and Differential Alignment Algorithm (CDAA). This algorithm was designed to process transcriptome data by first grouping genes based on stages of activity and then using similarities in gene expression to predict influential connections between individual genes. Regulatory relationships are assigned based on pairwise alignment scores generated using the expression patterns of two genes and some inferred delay between the regulator and the observed activity of the target. We applied the CDAA to an iron deficiency time course microarray dataset to identify regulators that influence 7 target transcription factors known to participate in the Arabidopsis thaliana iron deficiency response. The algorithm predicted that 7 regulators previously unlinked to iron homeostasis influence the expression of these known transcription factors. We validated over half of predicted influential relationships using qRT-PCR expression analysis in mutant backgrounds. One predicted regulator-target relationship was shown to be a direct binding interaction according to yeast one-hybrid (Y1H) analysis. These results serve as a proof of concept emphasizing the utility of the CDAA for identifying unknown or missing nodes in regulatory cascades, providing the fundamental knowledge needed for constructing predictive gene regulatory networks. We propose that this tool can be used successfully for similar time course datasets to extract additional information and infer reliable regulatory connections for individual genes.