Biology subjects

Clark, N. M.

Publications and source records attributed to Clark, N. M..

26 records · Page 2Linked to original sources

bioRxiv2021

Quantitative proteomics reveals extensive lysine ubiquitination in the Arabidopsis root proteome and uncovers novel transcription factor stability states

Protein activity, abundance, and stability can be regulated by posttranslational modification including ubiquitination. Ubiquitination is conserved among eukaryotes and plays a central role in modulating cellular function and yet we lack comprehensive catalogs of proteins that are modified by ubiquitin in plants. In this study, we describe an antibody-based approach to enrich peptides containing the di-glycine (diGly) remnant of ubiquitin and coupled that with isobaric labeling to enable quantification, from up to 16-multiplexed samples, for plant tissues. Collectively, we identified 7,130 diGly-modified lysine residues sites arising from 3,178 proteins in Arabidopsis primary roots. These data include ubiquitin proteasome dependent ubiquitination events as well as ubiquitination events associated with auxin treatment. Gene Ontology analysis indicated that ubiquitinated proteins are associated with numerous biological processes including hormone signaling, plant defense, protein homeostasis, and root morphogenesis. We determined the ubiquitinated lysine residues that directly regulate the stability of the transcription factors CRYPTOCHROME-INTERACTING BASIC-HELIX-LOOP-HELIX 1 (CIB1), CIB1 LIKE PROTEIN 2 (CIL2), and SENSITIVE TO PROTON RHIZOTOXICITY (STOP1) using site directed mutagenesis and in vivo degradation assays. These comprehensive site-level ubiquitinome profiles provide a wealth of data for future studies related to modulation of biological processes mediated by this posttranslational modification in plants.

plant biology↗

bioRxiv2020

Integrated omics networks reveal the temporal signaling events of brassinosteroid response in Arabidopsis

Brassinosteroids (BRs) are plant steroid hormones that are known to regulate cell division and stress response. We used a systems biology approach to integrate multi-omic datasets and unravel the molecular signaling events of BR response in Arabidopsis. We profiled the levels of 32,549 transcripts, 9,035 protein groups, and 26,950 phosphorylation sites from Arabidopsis seedlings treated with brassinolide (BL, most active BR) for six different lengths of time. We then constructed a network inference pipeline called Spatiotemporal Clustering and Inference of Omics Networks (SC-ION) that was able to integrate these multi-omic data into one, cohesive regulatory network. Our network illustrates the signaling cascade of BR response, starting with kinase-substrate phosphorylation and ending with transcriptional regulation. We used our network predictions to identify putative, relevant phosphorylation sites on the TF BRI1-EMS-SUPPRESSOR 1 (BES1); the importance of which we experimentally validated. Additionally, we identified an uncharacterized TF, which we named BRONTOSAURUS (BRON), that regulates cell division. Further, we show that bron mutant roots are hypersensitive to BL. Together, this work demonstrates the power of integrative network analysis applied to multiomic data and provides fundamental insights into the molecular signaling events occurring during BR response.

plant biology↗

bioRxiv2019

Stem-cell-ubiquitous genes spatiotemporally coordinate division through regulation of stem-cell-specific gene networks

Stem cells are responsible for generating all of the differentiated cells, tissues, and organs in a multicellular organism and, thus, play a crucial role in cell renewal, regeneration, and organization. A number of stem cell type-specific genes have a known role in stem cell maintenance, identity, and/or division. Yet, how genes expressed across different stem cell types, referred here as stem-cell-ubiquitous genes, contribute to stem cell regulation is less understood. Here, we find that, in the Arabidopsis root, a stem-cell-ubiquitous gene, TESMIN-LIKE CXC2 (TCX2), controls stem cell division by regulating stem cell-type specific networks. Development of a mathematical model of TCX2 expression allowed us to show that TCX2 orchestrates the coordinated division of different stem cell types. Our results highlight that genes expressed across different stem cell types ensure cross-communication among cells, allowing them to divide and develop harmonically together.

systems biology↗

bioRxiv2018

Single-copy Knock-In Loci for Defined Gene Expression in C. elegans

We have generated a single-copy knock-in loci for defined gene expression (SKI LODGE) system to insert any cDNA by CRISPR/Cas9 at defined safe harbors in the Caenorhabditis elegans genome. Utilizing a single crRNA guide, which also acts as a Co-CRISPR enrichment marker, any cDNA sequence can be introduced as a single integrated copy, regulated by different tissue-specific promoters. The SKI LODGE system provides a fast, economical and effective approach for generating single-copy non-silenced transgenes in C. elegans.

genetics↗

bioRxiv2018

Positive feedback and feedforward loops between PERIANTHIA, WUSCHEL-RELATED HOMEOBOX5 and GRF-INTERACTING FACTOR 1 modulate gene expression and function in the Arabidopsis root

The Arabidopsis root meristem consists of populations of stem cells that surround the mitotically less active cells known as the Quiescent Center (QC). The QC maintains the stem cells in a non-cell-autonomous manner through the function of the transcription factor (TF) WUSCHEL-RELATED HOMEOBOX5 (WOX5), which is required for columella stem cell (CSC) maintenance. However, whether WOX5 has a regulatory role in any other adjacent stem cells is less understood. To this end, we identified a set of TFs downstream of WOX5 in both QC and Cortex Endodermis Initial (CEI) cells. We then utilized Gene Regulatory Network (GRN) inference to identify GRF-INTERACTING FACTOR 1 (GIF1) as a key gene involved in positive feedback and feedforward loops with WOX5 as well as another stem cell regulator, PERIANTHIA (PAN). Finally, we constructed an ordinary differential equation model based on this inferred GRN to simulate GIF1, PAN, and WOX5 expression over time, which suggests the precise temporal expression of WOX5 and GIF1 is important to sustain QC function.

plant biology↗

bioRxiv2018

Cell type-specific differences in protein complex stoichiometry and transcriptional regulation affect the timing of stem cell division

Stem cells divide and differentiate to form all the specialized cell types in a multicellular organism. In the Arabidopsis root, stem cells are maintained in an undifferentiated state by a less mitotically active population of cells called the Quiescent Center (QC). Determining how the QC regulates the surrounding stem cell initials, or what makes the QC fundamentally different from the actively dividing initials, is important for understanding how stem cell divisions are maintained. Here, we gained insight into the differences between the QC and the Cortex Endodermis Initials (CEI) by studying the mobile transcription factor SHORTROOT (SHR) and its binding partner SCARECROW (SCR). We constructed an Ordinary Differential Equation (ODE) model of SHR and SCR in the QC and CEI which incorporated the stoichiometry of the SHR-SCR complex as well as upstream transcriptional regulation of SHR and SCR. Our model prediction coupled with experimental validation showed that high levels of the SHR-SCR complex is associated with more CEI division but less QC division. Further, our model prediction allowed us to establish the timing of QC and CEI division and propose that SHR repression of QC division depends on the formation of SHR homodimer. Thus, our results support that SHR-SCR protein complex stoichiometry and regulation of SHR transcription modulate the division timing of two different specialized cell types in the root stem cell niche.

plant biology↗

bioRxiv2018

Dorsal/NF-κB exhibits a dorsal-to-ventral mobility gradient in the Drosophila embryo

Morphogen-mediated patterning is a highly dynamic developmental process. To obtain an accurate understanding of morphogen gradient formation and downstream gene expression, biophysical parameters such as protein mobilities must be quantified in vivo. The dorsal-ventral (DV) patterning of early Drosophila embryos by the NF-{kappa}B homolog Dorsal (Dl) is an excellent system for understanding morphogen gradient formation. Dl gradient formation is controlled by the inhibitor Cactus/I{kappa}B (Cact), which regulates the nuclear import and diffusion of Dl protein. However, quantitative measurements of Dl mobility and binding are currently lacking. Here, we use scanning fluorescence correlation spectroscopy to quantify the mobility of GFP-tagged Dl. We find that the DNA binding of Dl-GFP, which affects its mobility, varies along the DV axis, with highest DNA binding on the ventral side. Moreover, we also observe that the time scale for Dl-GFP to exit the nucleus is longer in the ventral and lateral regions of the embryo, which is consistent with stronger DNA binding. Using analysis of mutant alleles of dl tagged with GFP, we conclude that Dl-GFP/Cact interactions in the nuclei are responsible for the variation in Dl-GFP/DNA binding along the DV axis, which impacts our understanding of the spatial range of the Dl gradient and the robustness and precision of downstream gene expression. Thus, our results highlight the complexity of morphogen gradient dynamics and the ability of quantitative measurements of biophysical interactions to drive biological discovery.

developmental biology↗

bioRxiv2017

An Inference Approach Combines Spatial And Temporal Gene Expression Data To Predict Gene Regulatory Networks In Arabidopsis Stem Cells

Identifying the transcription factors (TFs) and associated networks involved in stem cell regulation is key for understanding the initiation and growth of plant tissues and organs. Although many TFs have been shown to have a role in the Arabidopsis root stem cells, a comprehensive view of the transcriptional signature of the stem cells is lacking. In this work, we used spatial and temporal transcriptomic data to predict interactions among the genes involved in stem cell regulation. For this, we transcriptionally profiled several stem cell populations and developed a gene regulatory network (GRN) inference algorithm that combines clustering with Dynamic Bayesian Network (DBN) inference. We leveraged the topology of our networks to infer potential key regulators. The results presented in this work show that our combination of molecular biology approaches, computational biology and mathematical modeling was key to identify candidate factors that function in the stem cells. Specifically, through experimental validation and mathematical modeling, we identified PERIANTHIA (PAN) as an important molecular regulator of quiescent center (QC) function.

plant biology↗