Morphogene-assisted transformation of Sorghum bicolor allows more efficient genome editing.

Sorghum bicolor (L.) Moench, the fifth most important cereal worldwide, is a multi-use crop for feed, food, forage and fuel. To enhance the sorghum and other important crop plants, establishing gene function is essential for their improvement. For sorghum, identifying genes associated with its notable abiotic stress tolerances requires a detailed molecular understanding of the genes associated with those traits. The limits of this knowledge became evident from our earlier in-depth sorghum transcriptome study showing that over 40% of its transcriptome had not been annotated. Here, we describe a full spectrum of tools to engineer, edit, annotate and characterize sorghum's genes. Efforts to develop those tools began with a morphogene-assisted transformation (MAT) method that led to accelerated transformation times, nearly half the time required with classical callus-based, non-MAT approaches. These efforts also led to expanded numbers of amenable genotypes, including several not previously transformed or historically recalcitrant. Another transformation advance, termed altruistic, involved introducing a gene of interest in a separate Agrobacterium strain from the one with morphogenes, leading to plants with the gene of interest but without morphogenes. The MAT approach was also successfully used to edit a target exemplary gene, phytoene desaturase. To identify single-copy transformed plants, we adapted a high-throughput technique and also developed a novel method to determine transgene independent integration. These efforts led to an efficient method to determine gene function, expediting research in numerous genotypes of this widely grown, multi-use crop.

Isolation of Histone from Sorghum Leaf Tissue for Top Down Mass Spectrometry Profiling of Potential Epigenetic Markers.

Histones belong to a family of highly conserved proteins in eukaryotes. They pack DNA into nucleosomes as functional units of chromatin. Post-translational modifications (PTMs) of histones, which are highly dynamic and can be added or removed by enzymes, play critical roles in regulating gene expression. In plants, epigenetic factors, including histone PTMs, are related to their adaptive responses to the environment. Understanding the molecular mechanisms of epigenetic control can bring unprecedented opportunities for innovative bioengineering solutions. Herein, we describe a protocol to isolate the nuclei and purify histones from sorghum leaf tissue. The extracted histones can be analyzed in their intact forms by top-down mass spectrometry (MS) coupled with online reversed-phase (RP) liquid chromatography (LC). Combinations and stoichiometry of multiple PTMs on the same histone proteoform can be readily identified. In addition, histone tail clipping can be detected using the top-down LC-MS workflow, thus, yielding the global PTM profile of core histones (H4, H2A, H2B, H3). We have applied this protocol previously to profile histone PTMs from sorghum leaf tissue collected from a large-scale field study, aimed at identifying epigenetic markers of drought resistance. The protocol could potentially be adapted and optimized for chromatin immunoprecipitation-sequencing (ChIP-seq), or for studying histone PTMs in similar plants.

Application of ddPCR for detection of Enterococcus spp. in coastal water quality monitoring.

Droplet digital polymerase chain reaction (ddPCR) was evaluated for the detection of fecal indicator bacteria (FIB), Enterococcus spp., in San Diego County beach water samples collected under diverse conditions, from multiple pollution sources, as part of regulatory monitoring activities over 20 months. Two US EPA-approved methods, qPCR (EPA 1609.1) and Enterolert (SM9230D), were used as reference comparator methods. A total of 361 samples were assayed by both ddPCR and qPCR and yielded an acceptable Index of Agreement (IA) of 0.89, based on EPA Site-Specific analysis guidelines. A Pearson's correlation coefficient of r = 0.87 (p < 0.001), further indicated a strong relationship between the methods results. From the 361 samples, 185 split samples with ddPCR and Enterolert values within the limits of quantification, were used as a 'training' data set to derive an intrinsic copy number equation (ICE) for scaling ddPCR gene copy number to Enterolert most probable number (MPN). Of the 1993 samples that comprised the complete 'test' data set assayed by ddPCR and Enterolert, 1086 generated results that fell within the limits of quantification for Enterolert and yielded an overall IA of 0.64. Re-analysis using median as a measure of central tendency to account for significant skewing of Enterolert data yielded an IA of 0.72. Beach grouping-specific IA values ranged from 0.63 to 0.93. Pearson's correlation coefficient, r, ranged from 0.13 to 0.94 within beach groupings and generated a combined value of 0.60 for all groupings. Using the ICE, a ddPCR advisory threshold of 1413 DNA copy number/100 mL was empirically determined to be the equivalent to the California Enterolert beach action threshold of 104 MPN/100 mL, based on comparison with all 1993 paired ddPCR and Enterolert results. Using the 1413 DNA copy number/100 mL as a beach action threshold for ddPCR resulted in a 90.4% agreement with Enterolert (6.0% false negative and 3.7% false positive). Together these findings support the conclusion that ddPCR readouts align closely with Enterolert MPN for identifying FIB exceedance levels of Enterococcus spp. in coastal waters of San Diego, CA.

Transcriptomic analysis of field-droughted sorghum from seedling to maturity reveals biotic and metabolic responses.

Drought is the most important environmental stress limiting crop yields. The C4 cereal sorghum [Sorghum bicolor (L.) Moench] is a critical food, forage, and emerging bioenergy crop that is notably drought-tolerant. We conducted a large-scale field experiment, imposing preflowering and postflowering drought stress on 2 genotypes of sorghum across a tightly resolved time series, from plant emergence to postanthesis, resulting in a dataset of nearly 400 transcriptomes. We observed a fast and global transcriptomic response in leaf and root tissues with clear temporal patterns, including modulation of well-known drought pathways. We also identified genotypic differences in core photosynthesis and reactive oxygen species scavenging pathways, highlighting possible mechanisms of drought tolerance and of the delayed senescence, characteristic of the stay-green phenotype. Finally, we discovered a large-scale depletion in the expression of genes critical to arbuscular mycorrhizal (AM) symbiosis, with a corresponding drop in AM fungal mass in the plants' roots.

iTRAQ-based analysis of changes in the cassava root proteome reveals pathways associated with post-harvest physiological deterioration.

The short storage life of harvested cassava roots is an important constraint that limits the full potential of cassava as a commercial food crop in developing countries. We investigated the molecular changes during physiological deterioration of cassava root after harvesting using isobaric tags for relative and absolute quantification (iTRAQ) of proteins in soluble and non-soluble fractions prepared during a 96 h post-harvest time course. Combining bioinformatic approaches to reduce information redundancy for unsequenced or partially sequenced plant species, we established a comprehensive proteome map of the cassava root and identified quantitatively regulated proteins. Up-regulation of several key proteins confirmed that physiological deterioration of cassava root after harvesting is an active process, with 67 and 170 proteins, respectively, being up-regulated early and later after harvesting. This included regulated proteins that had not previously been associated with physiological deterioration after harvesting, such as linamarase, glutamic acid-rich protein, hydroxycinnamoyl transferase, glycine-rich RNA binding protein, ß-1,3-glucanase, pectin methylesterase, maturase K, dehydroascorbate reductase, allene oxide cyclase, and proteins involved in signal pathways. To confirm the regulation of these proteins, activity assays were performed for selected enzymes. Together, our results show that physiological deterioration after harvesting is a highly regulated complex process involving proteins that are potential candidates for biotechnology approaches to reduce such deterioration.

A workflow to increase the detection rate of proteins from unsequenced organisms in high-throughput proteomics experiments.

We present and evaluate a strategy for the mass spectrometric identification of proteins from organisms for which no genome sequence information is available that incorporates cross-species information from sequenced organisms. The presented method combines spectrum quality scoring, de novo sequencing and error tolerant BLAST searches and is designed to decrease input data complexity. Spectral quality scoring reduces the number of investigated mass spectra without a loss of information. Stringent quality-based selection and the combination of different de novo sequencing methods substantially increase the catalog of significant peptide alignments. The de novo sequences passing a reliability filter are subsequently submitted to error tolerant BLAST searches and MS-BLAST hits are validated by a sampling technique. With the described workflow, we identified up to 20% more groups of homologous proteins in proteome analyses with organisms whose genome is not sequenced than by state-of-the-art database searches in an Arabidopsis thaliana database. We consider the novel data analysis workflow an excellent screening method to identify those proteins that evade detection in proteomics experiments as a result of database constraints.