Field performance of switchgrass plants engineered for reduced recalcitrance.

Switchgrass (Panicum virgatum L.) is a promising perennial bioenergy crop that achieves high yields with relatively low nutrient and energy inputs. Modification of cell wall composition for reduced recalcitrance can lower the costs of deconstructing biomass to fermentable sugars and other intermediates. We have engineered overexpression of OsAT10, encoding a rice BAHD acyltransferase and QsuB, encoding dehydroshikimate dehydratase from Corynebacterium glutamicum, to enhance saccharification efficiency in switchgrass. These engineering strategies demonstrated low lignin content, low ferulic acid esters, and increased saccharification yield during greenhouse studies in switchgrass and other plant species. In this work, transgenic switchgrass plants overexpressing either OsAT10 or QsuB were tested in the field in Davis, California, USA for three growing seasons. No significant differences in the content of lignin and cell wall-bound p-coumaric acid or ferulic acid were detected in transgenic OsAT10 lines compared with the untransformed Alamo control variety. However, the transgenic overexpressing QsuB lines had increased biomass yield and slightly increased biomass saccharification properties compared to the control plants. This work demonstrates good performance of engineered plants in the field, and also shows that the cell wall changes in the greenhouse were not replicated in the field, emphasizing the need to validate engineered plants under relevant field conditions.

A Guide to MethylationToActivity: A Deep Learning Framework That Reveals Promoter Activity Landscapes from DNA Methylomes in Individual Tumors.

Genome-wide DNA methylomes have contributed greatly to tumor detection and subclassification. However, interpreting the biological impact of the DNA methylome at the individual gene level remains a challenge. MethylationToActivity (M2A) is a pipeline that uses convolutional neural networks to infer H3K4me3 and H3K27ac enrichment from DNA methylomes and thus infer promoter activity. It was shown to be highly accurate and robust in revealing promoter activity landscapes in various pediatric and adult cancers. The following will present a user-friendly guide through the model pipeline.

Correction to "Expression of Dehydroshikimate Dehydratase in Sorghum Improves Biomass Yield, Accumulation of Protocatechuate, and Biorefinery Economics".

[This corrects the article DOI: 10.1021/acssuschemeng.2c01160.].

Engineering sorghum for higher 4-hydroxybenzoic acid content.

Engineering bioenergy crops to accumulate coproducts in planta can increase the value of lignocellulosic biomass and enable a sustainable bioeconomy. In this study, we engineered sorghum with a bacterial gene encoding a chorismate pyruvate-lyase (ubiC) to reroute the plastidial pool of chorismate from the shikimate pathway into the valuable compound 4-hydroxybenzoic acid (4-HBA). A gene encoding a feedback-resistant version of 3-deoxy-d-arabino-heptulonate-7-phosphate synthase (aroG) was also introduced in an attempt to increase the carbon flux through the shikimate pathway. At the full maturity and senesced stage, two independent lines that co-express ubiC and aroG produced 1.5 and 1.7 dw% of 4-HBA in biomass, which represents 36- and 40-fold increases compared to the titer measured in wildtype. The two transgenic lines showed no obvious phenotypes, growth defects, nor alteration of cell wall polysaccharide content when cultivated under controlled conditions. In the field, when harvested before grain maturity, transgenic lines contained 0.8 and 1.2 dw% of 4-HBA, which represent economically relevant titers based on recent technoeconomic analysis. Only a slight reduction (11-15%) in biomass yield was observed in transgenics grown under natural environment. This work provides the first metabolic engineering steps toward 4-HBA overproduction in the bioenergy crop sorghum to improve the economics of biorefineries by accumulating a value-added coproduct that can be recovered from biomass and provide an additional revenue stream.

Accurate genomic variant detection in single cells with primary template-directed amplification.

Improvements in whole genome amplification (WGA) would enable new types of basic and applied biomedical research, including studies of intratissue genetic diversity that require more accurate single-cell genotyping. Here, we present primary template-directed amplification (PTA), an isothermal WGA method that reproducibly captures >95% of the genomes of single cells in a more uniform and accurate manner than existing approaches, resulting in significantly improved variant calling sensitivity and precision. To illustrate the types of studies that are enabled by PTA, we developed direct measurement of environmental mutagenicity (DMEM), a tool for mapping genome-wide interactions of mutagens with single living human cells at base-pair resolution. In addition, we utilized PTA for genome-wide off-target indel and structural variant detection in cells that had undergone CRISPR-mediated genome editing, establishing the feasibility for performing single-cell evaluations of biopsies from edited tissues. The improved precision and accuracy of variant detection with PTA overcomes the current limitations of accurate WGA, which is the major obstacle to studying genetic diversity and evolution at cellular resolution.

MethylationToActivity: a deep-learning framework that reveals promoter activity landscapes from DNA methylomes in individual tumors.

Although genome-wide DNA methylomes have demonstrated their clinical value as reliable biomarkers for tumor detection, subtyping, and classification, their direct biological impacts at the individual gene level remain elusive. Here we present MethylationToActivity (M2A), a machine learning framework that uses convolutional neural networks to infer promoter activities based on H3K4me3 and H3K27ac enrichment, from DNA methylation patterns for individual genes. Using publicly available datasets in real-world test scenarios, we demonstrate that M2A is highly accurate and robust in revealing promoter activity landscapes in various pediatric and adult cancers, including both solid and hematologic malignant neoplasms.

Molecular Mechanism of Telomere Length Dynamics and Its Prognostic Value in Pediatric Cancers.

BACKGROUND: We aimed to systematically evaluate telomere dynamics across a spectrum of pediatric cancers, search for underlying molecular mechanisms, and assess potential prognostic value. METHODS: The fraction of telomeric reads was determined from whole-genome sequencing data for paired tumor and normal samples from 653 patients with 23 cancer types from the Pediatric Cancer Genome Project. Telomere dynamics were characterized as the ratio of telomere fractions between tumor and normal samples. Somatic mutations were gathered, RNA sequencing data for 330 patients were analyzed for gene expression, and Cox regression was used to assess the telomere dynamics on patient survival. RESULTS: Telomere lengthening was observed in 28.7% of solid tumors, 10.5% of brain tumors, and 4.3% of hematological cancers. Among 81 samples with telomere lengthening, 26 had somatic mutations in alpha thalassemia/mental retardation syndrome X-linked gene, corroborated by a low level of the gene expression in the subset of tumors with RNA sequencing. Telomerase reverse transcriptase gene amplification and/or activation was observed in 10 tumors with telomere lengthening, including two leukemias of the E2A-PBX1 subtype. Among hematological cancers, pathway analysis for genes with expressions most negatively correlated with telomere fractions suggests the implication of a gene ontology process of antigen presentation by Major histocompatibility complex class II. A higher ratio of telomere fractions was statistically significantly associated with poorer survival for patients with brain tumors (hazard ratio = 2.18, 95% confidence interval = 1.37 to 3.46). CONCLUSION: Because telomerase inhibitors are currently being explored as potential agents to treat pediatric cancer, these data are valuable because they identify a subpopulation of patients with reactivation of telomerase who are most likely to benefit from this novel therapeutic option.

Nucleome Dynamics during Retinal Development.

More than 8,000 genes are turned on or off as progenitor cells produce the 7 classes of retinal cell types during development. Thousands of enhancers are also active in the developing retinae, many having features of cell- and developmental stage-specific activity. We studied dynamic changes in the 3D chromatin landscape important for precisely orchestrated changes in gene expression during retinal development by ultra-deep in situ Hi-C analysis on murine retinae. We identified developmental-stage-specific changes in chromatin compartments and enhancer-promoter interactions. We developed a machine learning-based algorithm to map euchromatin and heterochromatin domains genome-wide and overlaid it with chromatin compartments identified by Hi-C. Single-cell ATAC-seq and RNA-seq were integrated with our Hi-C and previous ChIP-seq data to identify cell- and developmental-stage-specific super-enhancers (SEs). We identified a bipolar neuron-specific core regulatory circuit SE upstream of Vsx2, whose deletion in mice led to the loss of bipolar neurons.

VCF2CNA: A tool for efficiently detecting copy-number alterations in VCF genotype data and tumor purity.

VCF2CNA is a tool (Linux commandline or web-interface) for copy-number alteration (CNA) analysis and tumor purity estimation of paired tumor-normal VCF variant file formats. It operates on whole genome and whole exome datasets. To benchmark its performance, we applied it to 46 adult glioblastoma and 146 pediatric neuroblastoma samples sequenced by Illumina and Complete Genomics (CGI) platforms respectively. VCF2CNA was highly consistent with a state-of-the-art algorithm using raw sequencing data (mean F1-score = 0.994) in high-quality whole genome glioblastoma samples and was robust to uneven coverage introduced by library artifacts. In the whole genome neuroblastoma set, VCF2CNA identified MYCN high-level amplifications in 31 of 32 clinically validated samples compared to 15 found by CGI's HMM-based CNA model. Moreover, VCF2CNA achieved highly consistent CNA profiles between WGS and WXS platforms (mean F1 score 0.97 on a set of 15 rhabdomyosarcoma samples). In addition, VCF2CNA provides accurate tumor purity estimates for samples with sufficient CNAs. These results suggest that VCF2CNA is an accurate, efficient and platform-independent tool for CNA and tumor purity analyses without accessing raw sequence data.

The Clonal Evolution of Metastatic Osteosarcoma as Shaped by Cisplatin Treatment.

To investigate the genomic evolution of metastatic pediatric osteosarcoma, we performed whole-genome and targeted deep sequencing on 14 osteosarcoma metastases and two primary tumors from four patients (two to eight samples per patient). All four patients harbored ancestral (truncal) somatic variants resulting in TP53 inactivation and cell-cycle aberrations, followed by divergence into relapse-specific lineages exhibiting a cisplatin-induced mutation signature. In three of the four patients, the cisplatin signature accounted for >40% of mutations detected in the metastatic samples. Mutations potentially acquired during cisplatin treatment included NF1 missense mutations of uncertain significance in two patients and a KIT G565R activating mutation in one patient. Three of four patients demonstrated widespread ploidy differences between samples from the sample patient. Single-cell seeding of metastasis was detected in most metastatic samples. Cross-seeding between metastatic sites was observed in one patient, whereas in another patient a minor clone from the primary tumor seeded both metastases analyzed. These results reveal extensive clonal heterogeneity in metastatic osteosarcoma, much of which is likely cisplatin-induced. IMPLICATIONS: The extent and consequences of chemotherapy-induced damage in pediatric cancers is unknown. We found that cisplatin treatment can potentially double the mutational burden in osteosarcoma, which has implications for optimizing therapy for recurrent, chemotherapy-resistant disease.

The impact of lignin downregulation on alfalfa yield, chemical composition, and in vitro gas production.

BACKGROUND: Lignin is a complex, phenolic polymer found in plant cell walls that is essential for mechanical support, water and mineral transport, and defense in vascular plants. Over ten different enzymes play a role in the synthesis of lignin in plants. Suppression of any one enzyme or combinations of these enzymes may change the concentration and composition of lignin in the genetically transformed plants. Two lines of alfalfa that were downregulated for caffeoyl coenzyme A O-methyltransferase were used to assess the impact of lignin downregulation on chemical composition and fermentation rate and extent using an in vitro gas production technique. A total of 64 samples consisting of two reduced lignin (RL) and two controls (CL), four field replicates, two cutting intervals (CIs; 28 and 35 days), and two cuts (Cut-1 and Cut-3) were used. RESULTS: No differences were detected in yield, crude protein, neutral detergent fiber (aNDF), and acid detergent fiber between the lines when harvested at the 28-day CI. The acid detergent lignin (ADL) concentration in RL alfalfa lines was significantly (P < 0.001) lower than in the CL. In alfalfa harvested at the 35-day CI, the RL alfalfa resulted in lower (P < 0.001) yield than CL. RL alfalfa lines had 24% and 22% lower (P < 0.001) ADL in Cut-1 and Cut-3 respectively than CL lines. The in vitro dry matter digestibility and aNDF digestibility (both as determined by the near-infrared reflectance method) were greater (P < 0.001) in RL than in CL lines harvested at the 35-day CI. In alfalfa harvested at the 35-day CI, extent of in vitro gas production and metabolizable energy content were greater in RL than in CL alfalfa. RL lines had 3.8% indigestible aNDF per unit ADL, whereas CL had 3.4% (P < 0.01). The positive effect of lignin downregulation was more pronounced when intervals between harvests were longer (35-day CI compared with the 28-day CI). CONCLUSION: Lignin downregulation in alfalfa offers an opportunity to extend harvesting time (CI) for higher yield without compromising the nutritional quality of the alfalfa forage for dairy and livestock feeding. However, the in vitro results reported here warrant further study using in vivo methods. © 2018 Society of Chemical Industry.

CASP11--An Evaluation of a Modular BCL::Fold-Based Protein Structure Prediction Pipeline.

In silico prediction of a protein's tertiary structure remains an unsolved problem. The community-wide Critical Assessment of Protein Structure Prediction (CASP) experiment provides a double-blind study to evaluate improvements in protein structure prediction algorithms. We developed a protein structure prediction pipeline employing a three-stage approach, consisting of low-resolution topology search, high-resolution refinement, and molecular dynamics simulation to predict the tertiary structure of proteins from the primary structure alone or including distance restraints either from predicted residue-residue contacts, nuclear magnetic resonance (NMR) nuclear overhauser effect (NOE) experiments, or mass spectroscopy (MS) cross-linking (XL) data. The protein structure prediction pipeline was evaluated in the CASP11 experiment on twenty regular protein targets as well as thirty-three 'assisted' protein targets, which also had distance restraints available. Although the low-resolution topology search module was able to sample models with a global distance test total score (GDT_TS) value greater than 30% for twelve out of twenty proteins, frequently it was not possible to select the most accurate models for refinement, resulting in a general decay of model quality over the course of the prediction pipeline. In this study, we provide a detailed overall analysis, study one target protein in more detail as it travels through the protein structure prediction pipeline, and evaluate the impact of limited experimental data.

A Structural Study of CESA1 Catalytic Domain of Arabidopsis Cellulose Synthesis Complex: Evidence for CESA Trimers.

A cellulose synthesis complex with a "rosette" shape is responsible for synthesis of cellulose chains and their assembly into microfibrils within the cell walls of land plants and their charophyte algal progenitors. The number of cellulose synthase proteins in this large multisubunit transmembrane protein complex and the number of cellulose chains in a microfibril have been debated for many years. This work reports a low resolution structure of the catalytic domain of CESA1 from Arabidopsis (Arabidopsis thaliana; AtCESA1CatD) determined by small-angle scattering techniques and provides the first experimental evidence for the self-assembly of CESA into a stable trimer in solution. The catalytic domain was overexpressed in Escherichia coli, and using a two-step procedure, it was possible to isolate monomeric and trimeric forms of AtCESA1CatD. The conformation of monomeric and trimeric AtCESA1CatD proteins were studied using small-angle neutron scattering and small-angle x-ray scattering. A series of AtCESA1CatD trimer computational models were compared with the small-angle x-ray scattering trimer profile to explore the possible arrangement of the monomers in the trimers. Several candidate trimers were identified with monomers oriented such that the newly synthesized cellulose chains project toward the cell membrane. In these models, the class-specific region is found at the periphery of the complex, and the plant-conserved region forms the base of the trimer. This study strongly supports the "hexamer of trimers" model for the rosette cellulose synthesis complex that synthesizes an 18-chain cellulose microfibril as its fundamental product.

BCL::SAXS: GPU accelerated Debye method for computation of small angle X-ray scattering profiles.

Small angle X-ray scattering (SAXS) is an experimental technique used for structural characterization of macromolecules in solution. Here, we introduce BCL::SAXS--an algorithm designed to replicate SAXS profiles from rigid protein models at different levels of detail. We first show our derivation of BCL::SAXS and compare our results with the experimental scattering profile of hen egg white lysozyme. Using this protein we show how to generate SAXS profiles representing: (1) complete models, (2) models with approximated side chain coordinates, and (3) models with approximated side chain and loop region coordinates. We evaluated the ability of SAXS profiles to identify a correct protein topology from a non-redundant benchmark set of proteins. We find that complete SAXS profiles can be used to identify the correct protein by receiver operating characteristic (ROC) analysis with an area under the curve (AUC) > 99%. We show how our approximation of loop coordinates between secondary structure elements improves protein recognition by SAχS for protein models without loop regions and side chains. Agreement with SAXS data is a necessary but not sufficient condition for structure determination. We conclude that experimental SAXS data can be used as a filter to exclude protein models with large structural differences from the native.

Protein accumulation and rumen stability of wheat γ-gliadin fusion proteins in tobacco and alfalfa.

The nutritional value of various crops can be improved by engineering plants to produce high levels of proteins. For example, because methionine deficiency limits the protein quality of Medicago Sativa (alfalfa) forage, producing alfalfa plants that accumulate high levels of a methionine-rich protein could increase the nutritional value of that crop. We used three strategies in designing methionine-rich recombinant proteins that could accumulate to high levels in plants and thereby serve as candidates for improving the protein quality of alfalfa forage. In tobacco, two fusion proteins, γ-gliadin-δ-zein and γ-δ-zein, as well as δ-zein co-expressed with ß-zein, all formed protein bodies. However, the γ-gliadin-δ-zein fusion protein accumulated to the highest level, representing up to 1.5% of total soluble protein (TSP) in one transformant. In alfalfa, γ-gliadin-δ-zein accumulated to 0.2% of TSP, and in an in vitro rumen digestion assay, γ-gliadin-δ-zein was more resistant to microbial degradation than Rubisco. Additionally, although it did not form protein bodies, a γ-gliadin-GFP fusion protein accumulated to much higher levels, 7% of TSP, than a recombinant protein comprised of an ER localization signal fused to GFP in tobacco. Based on our results, we conclude that γ-gliadin-δ-zein is a potential candidate protein to use for enhancing methionine levels in plants and for improving rumen stability of forage protein. γ-gliadin fusion proteins may provide a general platform for increasing the accumulation of recombinant proteins in transgenic plants.

CASP10-BCL::Fold efficiently samples topologies of large proteins.

During CASP10 in summer 2012, we tested BCL::Fold for prediction of free modeling (FM) and template-based modeling (TBM) targets. BCL::Fold assembles the tertiary structure of a protein from predicted secondary structure elements (SSEs) omitting more flexible loop regions early on. This approach enables the sampling of conformational space for larger proteins with more complex topologies. In preparation of CASP11, we analyzed the quality of CASP10 models throughout the prediction pipeline to understand BCL::Fold's ability to sample the native topology, identify native-like models by scoring and/or clustering approaches, and our ability to add loop regions and side chains to initial SSE-only models. The standout observation is that BCL::Fold sampled topologies with a GDT_TS score > 33% for 12 of 18 and with a topology score > 0.8 for 11 of 18 test cases de novo. Despite the sampling success of BCL::Fold, significant challenges still exist in clustering and loop generation stages of the pipeline. The clustering approach employed for model selection often failed to identify the most native-like assembly of SSEs for further refinement and submission. It was also observed that for some ß-strand proteins model refinement failed as ß-strands were not properly aligned to form hydrogen bonds removing otherwise accurate models from the pool. Further, BCL::Fold samples frequently non-natural topologies that require loop regions to pass through the center of the protein.

Reconstruction of SAXS Profiles from Protein Structures.

Small angle X-ray scattering (SAXS) is used for low resolution structural characterization of proteins often in combination with other experimental techniques. After briefly reviewing the theory of SAXS we discuss computational methods based on 1) the Debye equation and 2) Spherical Harmonics to compute intensity profiles from a particular macromolecular structure. Further, we review how these formulas are parameterized for solvent density and hydration shell adjustment. Finally we introduce our solution to compute SAXS profiles utilizing GPU acceleration.

Exploring schizophrenia drug-gene interactions through molecular network and pathway modeling.

In this study, we retrieved 39 schizophrenia-related antipsychotic drugs from the DrugBank database. These drugs had interactions with 142 targets, whose corresponding genes were defined as drug targeted genes. To explore the complexity between these drugs and their related genes in schizophrenia, we constructed a drug-target gene network. These genes were overrepresented in several pathways including: neuroactive ligand-receptor pathways, glutamate metabolism, and glycine metabolism. Through integrating the pathway information into a drug-gene network, we revealed a few bridge genes connected the sub-networks of the drug-gene network: GRIN2A, GRIN3B, GRIN2C, GRIN2B, DRD1, and DRD2. These genes encode ionotropic glutamate receptors belonging to the NMDA receptor family and dopamine receptors. Haloperidol was the only drug to directly interact with these pathways and receptors and consequently may have a unique action at the drug-gene interaction level during the treatment of schizophrenia. This study represents the first systematic investigation of drug-gene interactions in psychosis.

Synthesis, characterization and photovoltaic properties of poly(thiophenevinylene-alt-benzobisoxazole)s.

Herein we report the synthesis of two solution processible, conjugated polymers containing the benzobisoxazole moiety. The polymers were characterized using (1)H NMR, UV-Vis and fluorescence spectroscopy. Thermal gravimetric analysis shows that the polymers do not exhibit significant weight loss until approximately 300 °C under nitrogen. Cyclic voltammetry shows that the polymers have reversible reduction waves with estimated LUMO levels at -3.02 and -3.10 eV relative to vacuum and optical bandgaps of 2.04-2.17 eV. Devices based on blends of the copolymers and [6,6]-phenyl C61 butyric acid methyl ester (PCBM) exhibited modest power conversion efficiencies. Theoretical models reveal that there is poor electron delocalization along the polymer backbone, leading to poor performance. However, the energy levels of these polymers indicate that the incorporation of benzobisoxazoles into the polymer backbone is a promising strategy for the synthesis of new materials.