Safe and effective in vivo delivery of DNA and RNA using proteolipid vehicles.

Genetic medicines show promise for treating various diseases, yet clinical success has been limited by tolerability, scalability, and immunogenicity issues of current delivery platforms. To overcome these, we developed a proteolipid vehicle (PLV) by combining features from viral and non-viral approaches. PLVs incorporate fusion-associated small transmembrane (FAST) proteins isolated from fusogenic orthoreoviruses into a well-tolerated lipid formulation, using scalable microfluidic mixing. Screening a FAST protein library, we identified a chimeric FAST protein with enhanced membrane fusion activity that improved gene expression from an optimized lipid formulation. Systemically administered FAST-PLVs showed broad biodistribution and effective mRNA and DNA delivery in mouse and non-human primate models. FAST-PLVs show low immunogenicity and maintain activity upon repeat dosing. Systemic administration of follistatin DNA gene therapy with FAST-PLVs raised circulating follistatin levels and significantly increased muscle mass and grip strength. These results demonstrate the promising potential of FAST-PLVs for redosable gene therapies and genetic medicines.

The Genetics of Nitrogen Use Efficiency in Crop Plants.

In the past 50 years, the application of synthetic nitrogen (N) fertilizer to farmland resulted in a dramatic increase in crop yields but with considerable negative impacts on the environment. New solutions are therefore needed to simultaneously increase yields while maintaining, or preferably decreasing, applied N to maximize the nitrogen use efficiency (NUE) of crops. In this review, we outline the definition of NUE, the selection and development of NUE crops, and the factors that interact with NUE. In particular, we emphasize the challenges of developing crop plants with enhanced NUE, using more classical genetic approaches based on utilizing existing allelic variation for NUE traits. The challenges of phenotyping, mapping quantitative trait loci (QTLs), and selecting candidate genes for NUE improvement are described. In addition, we highlight the importance of different factors that lead to changes in the NUE components of nitrogen uptake efficiency (NUpE) and nitrogen utilization efficiency (NUtE).

Antibody titrations are critical for microflow cytometric analysis of extracellular vesicles.

Optimization of flow cytometry assays for extracellular vesicles (EVs) often fail to include appropriate reagent titrations - the most critically antibody titration is either not performed or is incomplete. Using nonoptimal antibody concentration is one of the main sources of error leading to a lack of reproducible data. Antibody titration for the analysis of antigens on the surface of EVs is challenging for a variety of technical reasons. Using platelets as surrogates for cells and platelet-derived particles as surrogates for EV populations, we demonstrate our process for antibody titration, highlighting some of the key analysis parameters that may confound and surprise new researchers moving into the field of EV research. Additional care must be exercised to ensure instrument and reagent controls are utilized appropriately. Complete graphical analysis of positive and negative signal intensities, concentration, and separation or stain index data is highly beneficial when paired with visual analysis of the cytometry data. Using analytical flow cytometry procedures optimized for cells for EV analysis can lead to misleading and nonreproducible results.

Fertilizing nature: a tragedy of excess in the commons.

Globally, we are applying excessive nitrogen (N) fertilizers to our agricultural crops, which ultimately causes nitrogen pollution to our ecosphere. The atmosphere is polluted by N2O and NO(x) gases that directly and indirectly increase atmospheric warming and climate change. Nitrogen is also leached from agricultural lands as the water-soluble form NO3⁻, which increases nutrient overload in rivers, lakes, and oceans, causing "dead zones", reducing property values and the diversity of aquatic life, and damaging our drinking water and aquatic-associated industries such as fishing and tourism. Why do some countries show reductions in fertilizer use while others show increasing use? What N fertilizer application reductions could occur, without compromising crop yields? And what are the economic and environmental benefits of using directed nutrient management strategies?

Development of an effective predictive screening tool for prostate cancer using the ClarityDX machine learning platform.

The current prostate cancer (PCa) screen test, prostate-specific antigen (PSA), has a high sensitivity for PCa but low specificity for high-risk, clinically significant PCa (csPCa), resulting in overdiagnosis and overtreatment of non-csPCa. Early identification of csPCa while avoiding unnecessary biopsies in men with non-csPCa is challenging. We built an optimized machine learning platform (ClarityDX) and showed its utility in generating models predicting csPCa. Integrating the ClarityDX platform with blood-based biomarkers for clinically significant PCa and clinical biomarker data from a 3448-patient cohort, we developed a test to stratify patients' risk of csPCa; called ClarityDX Prostate. When predicting high risk cancer in the validation cohort, ClarityDX Prostate showed 95% sensitivity, 35% specificity, 54% positive predictive value, and 91% negative predictive value, at a ≥ 25% threshold. Using ClarityDX Prostate at this threshold could avoid up to 35% of unnecessary prostate biopsies. ClarityDX Prostate showed higher accuracy for predicting the risk of csPCa than PSA alone and the tested model-based risk calculators. Using this test as a reflex test in men with elevated PSA levels may help patients and their healthcare providers decide if a prostate biopsy is necessary.

The APETALA-2-like transcription factor OsAP2-39 controls key interactions between abscisic acid and gibberellin in rice.

The interaction between phytohormones is an important mechanism which controls growth and developmental processes in plants. Deciphering these interactions is a crucial step in helping to develop crops with enhanced yield and resistance to environmental stresses. Controlling the expression level of OsAP2-39 which includes an APETALA 2 (AP2) domain leads to phenotypic changes in rice. Overexpression of OsAP2-39 leads to a reduction in yield by decreasing the biomass and the number of seeds in the transgenic rice lines. Global transcriptome analysis of the OsAP2-39 overexpression transgenic rice revealed the upregulation of a key abscisic acid (ABA) biosynthetic gene OsNCED-I which codes for 9-cis-epoxycarotenoid dioxygenase and leads to an increase in the endogenous ABA level. In addition to OsNCED-1, the gene expression analysis revealed the upregulation of a gene that codes for the Elongation of Upper most Internode (EUI) protein, an enzyme that catalyzes 16α, 17-epoxidation of non-13-hydroxylated GAs, which has been shown to deactivate gibberellins (GAs) in rice. The exogenous application of GA restores the wild-type phenotype in the transgenic line and ABA application induces the expression of EUI and suppresses the expression of OsAP2-39 in the wild-type line. These observations clarify the antagonistic relationship between ABA and GA and illustrate a mechanism that leads to homeostasis of these hormones. In vivo and in vitro analysis showed that the expression of both OsNCED-1 and EUI are directly controlled by OsAP2-39. Together, these results reveal a novel mechanism for the control of the ABA/GA balance in rice which is regulated by OsAP2-39 that in turn regulates plant growth and seed production.

Clinical analysis of EV-Fingerprint to predict grade group 3 and above prostate cancer and avoid prostate biopsy.

BACKGROUND: There is an unmet clinical need for minimally invasive diagnostic tests to improve the detection of grade group (GG) ≥3 prostate cancer relative to prostate antigen-specific risk calculators. We determined the accuracy of the blood-based extracellular vesicle (EV) biomarker assay (EV Fingerprint test) at the point of a prostate biopsy decision to predict GG ≥3 from GG ≤2 and avoid unnecessary biopsies. METHODS: This study analyzed 415 men referred to urology clinics and scheduled for a prostate biopsy, were recruited to the APCaRI 01 prospective cohort study. The EV machine learning analysis platform was used to generate predictive EV models from microflow data. Logistic regression was then used to analyze the combined EV models and patient clinical data and generate the patients' risk score for GG ≥3 prostate cancer. RESULTS: The EV-Fingerprint test was evaluated using the area under the curve (AUC) in discrimination of GG ≥3 from GG ≤2 and benign disease on initial biopsy. EV-Fingerprint identified GG ≥3 cancer patients with high accuracy (0.81 AUC) at 95% sensitivity and 97% negative predictive value. Using a 7.85% probability cutoff, 95% of men with GG ≥3 would have been recommended a biopsy while avoiding 144 unnecessary biopsies (35%) and missing four GG ≥3 cancers (5%). Conversely, a 5% cutoff would have avoided 31 unnecessary biopsies (7%), missing no GG ≥3 cancers (0%). CONCLUSIONS: EV-Fingerprint accurately predicted GG ≥3 prostate cancer and would have significantly reduced unnecessary prostate biopsies.

Engineering nitrogen use efficient crop plants: the current status.

In the last 40 years the amount of synthetic nitrogen (N) applied to crops has risen drastically, resulting in significant increases in yield but with considerable impacts on the environment. A requirement for crops that require decreased N fertilizer levels has been recognized in the call for a 'Second Green Revolution' and research in the field of nitrogen use efficiency (NUE) has continued to grow. This has prompted a search to identify genes that improve the NUE of crop plants, with candidate NUE genes existing in pathways relating to N uptake, assimilation, amino acid biosynthesis, C/N storage and metabolism, signalling and regulation of N metabolism and translocation, remobilization and senescence. Herein is a review of the approaches taken to determine possible NUE candidate genes, an overview of experimental study of these genes as effectors of NUE in both cereal and non-cereal plants and the processes of commercialization of enhanced NUE crop plants. Patents issued regarding increased NUE in plants as well as gene pyramiding studies are also discussed as well as future directions of NUE research.

Molecular Targeting of the Most Functionally Complex Gene in Precision Oncology: p53.

While chemotherapy is a key treatment strategy for many solid tumors, it is rarely curative, and most tumor cells eventually become resistant. Because of this, there is an unmet need to develop systemic treatments that capitalize on the unique mutational landscape of each patient's tumor. The most frequently mutated protein in cancer, p53, has a role in nearly all cancer subtypes and tumorigenesis stages and therefore is one of the most promising molecular targets for cancer treatment. Unfortunately, drugs targeting p53 have seen little clinical success despite promising preclinical data. Most of these drug compounds target specific aspects of p53 inactivation, such as through inhibiting negative regulation by the mouse double minute (MDM) family of proteins. These treatment strategies fail to address cancer cells' adaptation mechanisms and ignore the impact that p53 loss has on the entire p53 network. However, recent gene therapy successes show that targeting the p53 network and cellular dysfunction caused by p53 inactivation is now possible and may soon translate into successful clinical responses. In this review, we discuss p53 signaling complexities in cancer that have hindered the development and use of p53-targeted drugs. We also describe several current therapeutics reporting promising preclinical and clinical results.

Discovery of Metastatic Regulators using a Rapid and Quantitative Intravital Chick Chorioallantoic Membrane Model.

Recent advances in cancer research has illustrated the highly complex nature of cancer metastasis. Multiple genes or genes networks have been found to be involved in differentially regulating cancer metastatic cascade genes and gene products dependent on the cancer type, tissue, and individual patient characteristics. These represent potentially important targets for genetic therapeutics and personalized medicine approaches. The development of rapid screening platforms is essential for the identification of these genetic targets. The chick chorioallantoic membrane (CAM) is a highly vascularized, collagen rich membrane located under the eggshell that allows for gas exchange in the developing embryo. Due to the location and vascularization of the CAM, we developed it as an intravital human cancer metastasis model that allows for robust human cancer cell xenografting and real-time imaging of cancer cell interactions with the collagen rich matrix and vasculature. Using this model, a quantitative screening platform was designed for the identification of novel drivers or suppressors of cancer metastasis. We transduced a pool of head and neck HEp3 cancer cells with a complete human genome shRNA gene library, then injected the cells, at low density, into the CAM vasculature. The cells proliferated and formed single-tumor cell colonies. Individual colonies that were unable to invade into the CAM tissue were visible as a compact colony phenotype and excised for identification of the transduced shRNA present in the cells. Images of individual colonies were evaluated for their invasiveness. Multiple rounds of selections were performed to decreases the rate of false positives. Individual, isolated cancer cell clones or newly engineered clones that express genes of interest were subjected to primary tumor formation assay or cancer cell vasculature co-option analysis. In summary we present a rapid screening platform that allows for anti-metastatic target identification and intravital analysis of a dynamic and complex cascade of events.

Nitrogen use efficiencies of spring barley grown under varying nitrogen conditions in the field and growth chamber.

BACKGROUND AND AIMS: Nitrogen-use efficiency (NUE) of cereals needs to be improved by nitrogen (N) management, traditional plant breeding methods and/or biotechnology, while maintaining or, optimally, increasing crop yields. The aims of this study were to compare spring-barley genotypes grown on different nitrogen levels in field and growth-chamber conditions to determine the effects on N uptake (NUpE) and N utilization efficiency (NUtE) and ultimately, NUE. METHODS: Morphological characteristics, seed yield and metabolite levels of 12 spring barley (Hordeum vulgare) genotypes were compared when grown at high and low nitrogen levels in field conditions during the 2007 and 2008 Canadian growing seasons, and in potted and hydroponic growth-chamber conditions. Genotypic NUpE, NUtE and NUE were calculated and compared between field and growth-chamber environments. KEY RESULTS: Growth chamber and field tests generally showed consistent NUE characteristics. In the field, Vivar, Excel and Ponoka, showed high NUE phenotypes across years and N levels. Vivar also had high NUE in growth-chamber trials, showing NUE across complex to simplistic growth environments. With the high NUE genotypes grown at low N in the field, NUtE predominates over NUpE. N metabolism-associated amino acid levels were different between roots (elevated glutamine) and shoots (elevated glutamate and alanine) of hydroponically grown genotypes. In field trials, metabolite levels were different between Kasota grown at high N (elevated glutamine) and Kasota at low N plus Vivar at either N condition. CONCLUSIONS: Determining which trait(s) or gene(s) to target to improve barley NUE is important and can be facilitated using simplified growth approaches to help determine the NUE phenotype of various genotypes. The genotypes studied showed similar growth and NUE characteristics across field and growth-chamber tests demonstrating that simplified, low-variable growth environments can help pinpoint genetic targets for improving spring barley NUE.

Novel therapeutic targets for cancer metastasis.

Introduction: Metastatic cancers are extremely difficult to treat, and account for the vast majority of cancer-related deaths. The dissemination of tumor cells to distant sites is highly dynamic, asynchronous, and involves both tumor and host intrinsic factors. Effective therapeutic targets to block metastasis will need to disrupt key pathways that are required for multiple stages of metastasis.Areas covered: This review discusses the heterogeneity of cancers and metastasis, with an emphasis on motility as a key driver trait of metastasis. Recent metastatic cancer studies that identified either host or cancer cell intrinsic factors important for metastasis, using single gene-deficient animal models or 3D intravital imaging of avian embryo models, are also discussed. Potential metastatic blocking targets are listed as they relate to metastatic cancer therapy.Expert opinion: The development of metastatic disease is a complex interplay of genetic and epigenetic factors from the host and cancer cells acting in a patient-specific manner. Inhibiting key driver traits of metastasis should yield survival benefit at any stage of the disease, and we look forward to the next generation of personalized medicines for cancer therapy that target cancer cell motility for increased therapeutic efficacy.

Cohort profile: the Alberta Prostate Cancer Research Initiative (APCaRI) Registry and Biorepository facilitates technology translation to the clinic through the use of linked, longitudinal clinical and patient-reported data and biospecimens from men in Alberta, Canada.

PURPOSE: The Alberta Prostate Cancer Research Initiative (APCaRI) Registry and Biorepository was established in 2014 by the APCaRI to facilitate the collection of clinical and patient-reported data, biospecimen, to measure prostate cancer outcomes and to support the development and clinical translation of innovative technologies to better diagnose and predict outcomes for patients with prostate cancer. PARTICIPANTS: Men suspected with prostate cancer and referred to Urology centres in Alberta were enrolled in the APCaRI 01 study, while men with a prior prostate cancer diagnosis participated in the APCaRI 03 study from 1 July 2014 to 30 June 2019. The APCaRI Registry and Biorepository links biospecimens and data from a wide representation of patients drawn from an Alberta population of more than 4 million. FINDINGS TO DATE: From 1 July 2014 to 30 June 2019, total APCaRI 01 and 03 study recruitment was 3754 men; 142 (4%) of these men withdrew in full, 65 men (2%) withdrew biospecimens and 123 men (3%) died of any cause. Over this same time, 8677 patient-reported outcome measure (PROM) surveys and 7368 biospecimens were collected and are available from the registry and biorepository, respectively. The data entry error rate was 0.8% and 0.95% for critical and non-critical values, respectively, and 1.8% for patient-reported surveys. FUTURE PLANS: The APCaRI Registry and Biorepository will collect longitudinal data and PROM surveys until 2024, patient outcomes up to 25 years after recruitment and biospecimen storage for up to 25 years. The APCaRI cohorts will continue to provide data and samples to researchers conducting retrospective studies. The richness of the data and biospecimens will complement many different research questions, ultimately to improve the quality of care for men with prostate cancer.

Transcriptome analysis of nitrogen-efficient rice over-expressing alanine aminotransferase.

Crop plants require nitrogen for key macromolecules, such as DNA, proteins and metabolites, yet they are generally inefficient at acquiring nitrogen from the soil. Crop producers compensate for this low nitrogen utilization efficiency by applying nitrogen fertilizers. However, much of this nitrogen is unavailable to the plants as a result of microbial uptake and environmental loss of nitrogen, causing air, water and soil pollution. We engineered rice over-expressing alanine aminotransferase (AlaAT) under the control of a tissue-specific promoter that showed a strong nitrogen use efficiency phenotype. In this study, we examined the transcriptome response in roots and shoots to the over-expression of AlaAT to provide insights into the nitrogen-use-efficient phenotype of these plants. Transgenic and control rice plants were grown hydroponically and the root and shoot gene expression profiles were analysed using Affymetrix Rice GeneChip microarrays. Transcriptome analysis revealed that there was little impact on the transgenic transcriptome compared with controls, with 0.11% and 0.07% differentially regulated genes in roots and shoots, respectively. The most up-regulated transcripts, a glycine-rich cell wall (GRP) gene and a gene encoding a hypothetical protein (Os8823), were expressed in roots. Another transgenic root-specific up-regulated gene was leucine rich repeat (LRR). Genes induced in the transgenic shoots included GRP, LRR, acireductone dioxygenase (OsARD), SNF2 ATP-translocase and a putative leucine zipper transcription factor. This study provides a genome-wide view of the response to AlaAT over-expression, and elucidates some of the genes that may play a role in the nitrogen-use-efficient phenotype.

Cowpea mosaic virus nanoparticles for cancer imaging and therapy.

Nanoparticle platforms are particularly attractive for theranostic applications due to their capacity for multifunctionality and multivalency. Some of the most promising nano-scale scaffold systems have been co-opted from nature including plant viruses such as cowpea mosaic virus (CPMV). The use of plant viruses like CPMV as viral nanoparticles is advantageous for many reasons; they are non-infectious and nontoxic to humans and safe for use in intravital imaging and drug delivery. The CPMV capsid icosahedral shape allows for enhanced multifunctional group display and the ability to carry specific cargoes. The native tropism of CPMV for cell-surface displayed vimentin and the enhanced permeability and retention effect allow them to preferentially extravasate from tumor neovasculature and efficiently penetrate tumors. Furthermore, CPMVs can be engineered via several straightforward chemistries to display targeting and imaging moieties on external, addressable residues and they can be loaded internally with therapeutic drug cargoes. These qualities make them highly effective as biocompatible platforms for tumor targeting, intravital imaging and cancer therapy.

PROSPeCT: A Predictive Research Online System for Prostate Cancer Tasks.

PURPOSE: An online clinical information system, called Predictive Research Online System Prostate Cancer Tasks (PROSPeCT), was developed to enable users to query the Alberta Prostate Cancer Registry database hosted by the Alberta Prostate Cancer Research Initiative. To deliver high-quality patient treatment, prostate cancer clinicians and researchers require a user-friendly system that offers an easy and efficient way to obtain relevant and accurate information about patients from a robust and expanding database. METHODS: PROSPeCT was designed and implemented to make it easy for users to query the prostate cancer patient database by creating, saving, and reusing simple and complex definitions. We describe its intuitive nature by exemplifying the creation and use of a complex definition to identify a "high-risk" patient cohort. RESULTS: PROSPeCT was made to minimize user error and to maximize efficiency without requiring the user to have programming skills. Thus, it provides tools that allow both novice and expert users to easily identify patient cohorts, manage individual patient care, perform Kaplan Meier estimates, plot aggregate PSA views, compute PSA-doubling time, and visualize results. CONCLUSION: This report provides an overview of PROSPeCT, a system that helps clinicians to identify appropriate patient treatments and researchers to develop prostate cancer hypotheses, with the overarching goal of improving the quality of life of patients with prostate cancer. We have made available the code for the PROSPeCT implementation at https://github.com/max-uhlich/e-PROSPeCT .

5S clavam biosynthetic genes are located in both the clavam and paralog gene clusters in Streptomyces clavuligerus.

The Streptomyces clavuligerus clavam gene cluster was examined to identify genes specifically involved in 5S clavam biosynthesis. A reduction/loss of 5S clavam production was seen in cvm2 and cvm5 gene mutants, and a clavam metabolite not previously observed, 2-carboxymethylideneclavam, accumulated in the cvm5 mutant. Disruption of additional genes from the region of the clavam cluster did not have any effect on 5S clavam production. Examination of the paralog gene cluster region for 5S clavam biosynthetic genes led to the identification of cvm6P and cvm7P, which encode a putative aminotransferase and a transcriptional regulator, respectively. Mutants defective in cvm6P and cvm7P were completely blocked in 5S clavam but not clavulanic acid production. The loss of 5S clavam production in cvm7P mutants suggests that this gene encodes a transcriptional regulator specific for 5S clavam metabolite biosynthesis.

Intravital imaging tumor screen used to identify novel metastasis-blocking therapeutic targets.

Cancer cell motility is a key driver of metastasis. Although the intravasation of cancer cells into the blood stream is highly dependent on their motility and metastatic dissemination is the primary cause of cancer related deaths, current therapeutic strategies do not target the genes and proteins that are essential for cell motility. A primary reason for this is because the identification of cell motility-related genes that are relevant in vivo requires the visualization of metastatic lesions forming in an appropriate in vivo model. The cancer research community has lacked an in vivo and intravital metastatic cancer model that could be imaged as motility developed, in real-time. To address this, we developed a novel quantitative in vivo screening platform based on intravital imaging in shell-less ex ovo chick embryos. We applied this imaging approach to screen a human genome-wide short hairpin RNA library (shRNA) versus the highly motile head and neck cancer cells (HEp3 cell line) introduced into the chorioallantoic membrane (CAM) of chick embryos and identified multiple novel in vivo cancer cell motility-associated genes. When the expression of several of the identified genes was inhibited in the HEp3 tumors, we observed a nearly total block of spontaneous cancer metastasis.

Identification of Nitrogen Use Efficiency Genes in Barley: Searching for QTLs Controlling Complex Physiological Traits.

Over the past half century, the use of nitrogen (N) fertilizers has markedly increased crop yields, but with considerable negative effects on the environment and human health. Consequently, there has been a strong push to reduce the amount of N fertilizer used by maximizing the nitrogen use efficiency (NUE) of crops. One approach would be to use classical genetics to improve the NUE of a crop plant. This involves both conventional breeding and quantitative trait loci (QTL) mapping in combination with marker-assisted selection (MAS) to track key regions of the chromosome that segregate for NUE. To achieve this goal, one of initial steps is to characterize the NUE-associated genes, then use the profiles of specific genes to combine plant physiology and genetics to improve plant performance. In this study, on the basis of genetic homology and expression analysis, barley candidate genes from a variety of families that exhibited potential roles in enhancing NUE were identified and mapped. We then performed an analysis of QTLs associated with NUE in field trials and further analyzed their map-location data to narrow the search for these candidate genes. These results provide a novel insight on the identification of NUE genes and for the future prospects, will lead to a more thorough understanding of physiological significances of the diverse gene families that may be associated with NUE in barley.

Understanding Plant Nitrogen Metabolism through Metabolomics and Computational Approaches.

A comprehensive understanding of plant metabolism could provide a direct mechanism for improving nitrogen use efficiency (NUE) in crops. One of the major barriers to achieving this outcome is our poor understanding of the complex metabolic networks, physiological factors, and signaling mechanisms that affect NUE in agricultural settings. However, an exciting collection of computational and experimental approaches has begun to elucidate whole-plant nitrogen usage and provides an avenue for connecting nitrogen-related phenotypes to genes. Herein, we describe how metabolomics, computational models of metabolism, and flux balance analysis have been harnessed to advance our understanding of plant nitrogen metabolism. We introduce a model describing the complex flow of nitrogen through crops in a real-world agricultural setting and describe how experimental metabolomics data, such as isotope labeling rates and analyses of nutrient uptake, can be used to refine these models. In summary, the metabolomics/computational approach offers an exciting mechanism for understanding NUE that may ultimately lead to more effective crop management and engineered plants with higher yields.