CRISPR/Cas9-generated mutations in a sugar transporter gene reduce cassava susceptibility to bacterial blight.

Bacteria from the genus Xanthomonas are prolific phytopathogens that elicit disease in over 400 plant species. Xanthomonads carry a repertoire of specialized proteins called transcription activator-like (TAL) effectors that promote disease and pathogen virulence by inducing expression of host susceptibility (S) genes. Xanthomonas phaseoli pv. manihotis (Xpm) causes bacterial blight on the staple food crop cassava (Manihot esculenta Crantz). The Xpm effector TAL20 induces ectopic expression of the S gene Manihot esculenta Sugars Will Eventually be Exported Transporter 10a (MeSWEET10a), which encodes a sugar transporter that contributes to cassava bacterial blight susceptibility. We used CRISPR/Cas9 to generate multiple cassava lines with edits to the MeSWEET10a TAL20 effector binding site and/or coding sequence. In several of the regenerated lines, MeSWEET10a expression was no longer induced by Xpm, and in these cases, we observed reduced cassava bacterial blight (CBB) disease symptoms post Xpm infection. Because MeSWEET10a is expressed in cassava flowers, we further characterized the reproductive capability of the MeSWEET10a promoter and coding sequence mutants. Lines were crossed to themselves and to wild-type plants. The results indicated that expression of MeSWEET10a in female, but not male, flowers, is critical to produce viable F1 seed. In the case of promoter mutations that left the coding sequence intact, viable F1 progeny were recovered. Taken together, these results demonstrate that blocking MeSWEET10a induction is a viable strategy for decreasing cassava susceptibility to CBB and that ideal lines will contain promoter mutations that block TAL effector binding while leaving endogenous expression of MeSWEET10a unaltered.

Improving cassava bacterial blight resistance by editing the epigenome.

Pathogens rely on expression of host susceptibility (S) genes to promote infection and disease. As DNA methylation is an epigenetic modification that affects gene expression, blocking access to S genes through targeted methylation could increase disease resistance. Xanthomonas phaseoli pv. manihotis, the causal agent of cassava bacterial blight (CBB), uses transcription activator-like20 (TAL20) to induce expression of the S gene MeSWEET10a. In this work, we direct methylation to the TAL20 effector binding element within the MeSWEET10a promoter using a synthetic zinc-finger DNA binding domain fused to a component of the RNA-directed DNA methylation pathway. We demonstrate that this methylation prevents TAL20 binding, blocks transcriptional activation of MeSWEET10a in vivo and that these plants display decreased CBB symptoms while maintaining normal growth and development. This work therefore presents an epigenome editing approach useful for crop improvement.

A comparison of ImageJ and machine learning based image analysis methods to measure cassava bacterial blight disease severity.

BACKGROUND: Methods to accurately quantify disease severity are fundamental to plant pathogen interaction studies. Commonly used methods include visual scoring of disease symptoms, tracking pathogen growth in planta over time, and various assays that detect plant defense responses. Several image-based methods for phenotyping of plant disease symptoms have also been developed. Each of these methods has different advantages and limitations which should be carefully considered when choosing an approach and interpreting the results. RESULTS: In this paper, we developed two image analysis methods and tested their ability to quantify different aspects of disease lesions in the cassava-Xanthomonas pathosystem. The first method uses ImageJ, an open-source platform widely used in the biological sciences. The second method is a few-shot support vector machine learning tool that uses a classifier file trained with five representative infected leaf images for lesion recognition. Cassava leaves were syringe infiltrated with wildtype Xanthomonas, a Xanthomonas mutant with decreased virulence, and mock treatments. Digital images of infected leaves were captured overtime using a Raspberry Pi camera. The image analysis methods were analyzed and compared for the ability to segment the lesion from the background and accurately capture and measure differences between the treatment types. CONCLUSIONS: Both image analysis methods presented in this paper allow for accurate segmentation of disease lesions from the non-infected plant. Specifically, at 4-, 6-, and 9-days post inoculation (DPI), both methods provided quantitative differences in disease symptoms between different treatment types. Thus, either method could be applied to extract information about disease severity. Strengths and weaknesses of each approach are discussed.

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.

Improved Spirodela polyrhiza genome and proteomic analyses reveal a conserved chromosomal structure with high abundance of chloroplastic proteins favoring energy production.

Duckweeds are a monophyletic group of rapidly reproducing aquatic monocots in the Lemnaceae family. Given their clonal, exponentially fast reproduction, a key question is whether genome structure is conserved across the species in the absence of meiotic recombination. Here, we studied the genome and proteome of Spirodela polyrhiza, or greater duckweed, which has the largest body plan yet the smallest genome size in the family (1C=150 Mb). Using Oxford Nanopore sequencing combined with Hi-C scaffolding, we generated a highly contiguous, chromosome-scale assembly of S. polyrhiza line Sp7498 (Sp7498_HiC). Both the Sp7498_HiC and Sp9509 genome assemblies reveal large chromosomal misorientations relative to a recent PacBio assembly of Sp7498, highlighting the need for orthogonal long-range scaffolding techniques such as Hi-C and BioNano optical mapping. Shotgun proteomics of Sp7498 verified the expression of ~2250 proteins and revealed a high abundance of proteins involved in photosynthesis and carbohydrate metabolism among other functions. In addition, a strong increase in chloroplast proteins was observed that correlated to chloroplast density. This Sp7498_HiC genome was generated cheaply and quickly with a single Oxford Nanopore MinION flow cell and one Hi-C library in a classroom setting. Combining these data with a mass spectrometry-generated proteome illustrates the utility of duckweed as a model for genomics- and proteomics-based education.

Identification of Novel Growth Regulators in Plant Populations Expressing Random Peptides.

The use of chemical genomics approaches allows the identification of small molecules that integrate into biological systems, thereby changing discrete processes that influence growth, development, or metabolism. Libraries of chemicals are applied to living systems, and changes in phenotype are observed, potentially leading to the identification of new growth regulators. This work describes an approach that is the nexus of chemical genomics and synthetic biology. Here, each plant in an extensive population synthesizes a unique small peptide arising from a transgene composed of a randomized nucleic acid sequence core flanked by translational start, stop, and cysteine-encoding (for disulfide cyclization) sequences. Ten and 16 amino acid sequences, bearing a core of six and 12 random amino acids, have been synthesized in Arabidopsis (Arabidopsis thaliana) plants. Populations were screened for phenotypes from the seedling stage through senescence. Dozens of phenotypes were observed in over 2,000 plants analyzed. Ten conspicuous phenotypes were verified through separate transformation and analysis of multiple independent lines. The results indicate that these populations contain sequences that often influence discrete aspects of plant biology. Novel peptides that affect photosynthesis, flowering, and red light response are described. The challenge now is to identify the mechanistic integrations of these peptides into biochemical processes. These populations serve as a new tool to identify small molecules that modulate discrete plant functions that could be produced later in transgenic plants or potentially applied exogenously to impart their effects. These findings could usher in a new generation of agricultural growth regulators, herbicides, or defense compounds.