Deciphering the molecular basis of tissue-specific gene expression in plants: Can synthetic biology help?

Gene expression differences between distinct cell types are orchestrated by specific sets of transcription factors and epigenetic regulators acting upon the genome. In plants, the mechanisms underlying tissue-specific gene activity remain largely unexplored. Although transcriptional and epigenetic profiling of individual organs, tissues, and more recently, of single cells can easily detect the molecular signatures of different biological samples, how these unique cell identities are established at the mechanistic level is only beginning to be decoded. Computational methods, including machine learning, used in combination with experimental approaches, enable the identification and validation of candidate cis-regulatory elements driving cell-specific expression. Synthetic biology shows great promise not only as a means of testing candidate DNA motifs but also for establishing the general rules of nature driving promoter architecture and for the rational design of genetic circuits in research and agriculture to confer tissue-specific expression to genes or molecular pathways of interest.

Transcription factor FOXF1 identifies compartmentally distinct mesenchymal cells with a role in lung allograft fibrogenesis.

In this study, we demonstrate that forkhead box F1 (FOXF1), a mesenchymal transcriptional factor essential for lung development, was retained in a topographically distinct mesenchymal stromal cell population along the bronchovascular space in an adult lung and identify this distinct subset of collagen-expressing cells as key players in lung allograft remodeling and fibrosis. Using Foxf1-tdTomato BAC (Foxf1-tdTomato) and Foxf1-tdTomato Col1a1-GFP mice, we show that Lin-Foxf1+ cells encompassed the stem cell antigen 1+CD34+ (Sca1+CD34+) subset of collagen 1-expressing mesenchymal cells (MCs) with a capacity to generate CFU and lung epithelial organoids. Histologically, FOXF1-expressing MCs formed a 3D network along the conducting airways; FOXF1 was noted to be conspicuously absent in MCs in the alveolar compartment. Bulk and single-cell RNA-Seq confirmed distinct transcriptional signatures of Foxf1+ and Foxf1- MCs, with Foxf1-expressing cells delineated by their high expression of the transcription factor glioma-associated oncogene 1 (Gli1) and low expression of integrin α8 (Itga), versus other collagen-expressing MCs. FOXF1+Gli1+ MCs showed proximity to Sonic hedgehog-expressing (Shh-expressing) bronchial epithelium, and mesenchymal expression of Foxf1 and Gli1 was found to be dependent on paracrine Shh signaling in epithelial organoids. Using a murine lung transplant model, we show dysregulation of epithelial-mesenchymal SHH/GLI1/FOXF1 crosstalk and expansion of this specific peribronchial MC population in chronically rejecting fibrotic lung allografts.

Auxin Interactions with Other Hormones in Plant Development.

Auxin is a crucial growth regulator that governs plant development and responses to environmental perturbations. It functions at the heart of many developmental processes, from embryogenesis to organ senescence, and is key to plant interactions with the environment, including responses to biotic and abiotic stimuli. As remarkable as auxin is, it does not act alone, but rather solicits the help of, or is solicited by, other endogenous signals, including the plant hormones abscisic acid, brassinosteroids, cytokinins, ethylene, gibberellic acid, jasmonates, salicylic acid, and strigolactones. The interactions between auxin and other hormones occur at multiple levels: hormones regulate one another's synthesis, transport, and/or response; hormone-specific transcriptional regulators for different pathways physically interact and/or converge on common target genes; etc. However, our understanding of this crosstalk is still fragmentary, with only a few pieces of the gigantic puzzle firmly established. In this review, we provide a glimpse into the complexity of hormone interactions that involve auxin, underscoring how patchy our current understanding is.

Loss of FOXF1 expression promotes human lung-resident mesenchymal stromal cell migration via ATX/LPA/LPA1 signaling axis.

Forkhead box F1 (FOXF1) is a lung embryonic mesenchyme-associated transcription factor that demonstrates persistent expression into adulthood in mesenchymal stromal cells. However, its biologic function in human adult lung-resident mesenchymal stromal cells (LR-MSCs) remain to be elucidated. Here, we demonstrate that FOXF1 expression acts as a restraint on the migratory function of LR-MSCs via its role as a novel transcriptional repressor of autocrine motility-stimulating factor Autotaxin (ATX). Fibrotic human LR-MSCs demonstrated lower expression of FOXF1 mRNA and protein, compared to non-fibrotic controls. RNAi-mediated FOXF1 silencing in LR-MSCs was associated with upregulation of key genes regulating proliferation, migration, and inflammatory responses and significantly higher migration were confirmed in FOXF1-silenced LR-MSCs by Boyden chamber. ATX is a secreted lysophospholipase D largely responsible for extracellular lysophosphatidic acid (LPA) production, and was among the top ten upregulated genes upon Affymetrix analysis. FOXF1-silenced LR-MSCs demonstrated increased ATX activity, while mFoxf1 overexpression diminished ATX expression and activity. The FOXF1 silencing-induced increase in LR-MSC migration was abrogated by genetic and pharmacologic targeting of ATX and LPA1 receptor. Chromatin immunoprecipitation analyses identified three putative FOXF1 binding sites in the 1.5 kb ATX promoter which demonstrated transcriptional repression of ATX expression. Together these findings identify FOXF1 as a novel transcriptional repressor of ATX and demonstrate that loss of FOXF1 promotes LR-MSC migration via the ATX/LPA/LPA1 signaling axis.

RiboStreamR: a web application for quality control, analysis, and visualization of Ribo-seq data.

BACKGROUND: Ribo-seq is a popular technique for studying translation and its regulation. A Ribo-seq experiment produces a snap-shot of the location and abundance of actively translating ribosomes within a cell's transcriptome. In practice, Ribo-seq data analysis can be sensitive to quality issues such as read length variation, low read periodicities, and contaminations with ribosomal and transfer RNA. Various software tools for data preprocessing, quality assessment, analysis, and visualization of Ribo-seq data have been developed. However, many of these tools require considerable practical knowledge of software applications, and often multiple different tools have to be used in combination with each other. RESULTS: We present riboStreamR, a comprehensive Ribo-seq quality control (QC) platform in the form of an R Shiny web application. RiboStreamR provides visualization and analysis tools for various Ribo-seq QC metrics, including read length distribution, read periodicity, and translational efficiency. Our platform is focused on providing a user-friendly experience, and includes various options for graphical customization, report generation, and anomaly detection within Ribo-seq datasets. CONCLUSIONS: RiboStreamR takes advantage of the vast resources provided by the R and Bioconductor environments, and utilizes the Shiny R package to ensure a high level of usability. Our goal is to develop a tool which facilitates in-depth quality assessment of Ribo-seq data by providing reference datasets and automatically highlighting quality issues and anomalies within datasets.

A Plant Biologist's Toolbox to Study Translation.

Across a broad range of species and biological questions, more and more studies are incorporating translation data to better assess how gene regulation occurs at the level of protein synthesis. The inclusion of translation data improves upon, and has been shown to be more accurate than, transcriptional studies alone. However, there are many different techniques available to measure translation and it can be difficult, especially for young or aspiring scientists, to determine which methods are best applied in specific situations. We have assembled this review in order to enhance the understanding and promote the utilization of translational methods in plant biology. We cover a broad range of methods to measure changes in global translation (e.g., radiolabeling, polysome profiling, or puromycylation), translation of single genes (e.g., fluorescent reporter constructs, toeprinting, or ribosome density mapping), sequencing-based methods to uncover the entire translatome (e.g., Ribo-seq or translating ribosome affinity purification), and mass spectrometry-based methods to identify changes in the proteome (e.g., stable isotope labeling by amino acids in cell culture or bioorthogonal noncanonical amino acid tagging). The benefits and limitations of each method are discussed with a particular note of how applications from other model systems might be extended for use in plants. In order to make this burgeoning field more accessible to students and newer scientists, our review includes an extensive glossary to define key terms.