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Tools for experimental and computational analyses of off-target editing by programmable nucleases
Genome editing using programmable nucleases is revolutionizing life science and medicine. Off-target editing by these nucleases remains a considerable concern, especially in therapeutic applications. Here we review tools developed for identifying potential off-target editing sites and compare the ability of these tools to properly analyze off-target effects. Recent advances in both in silico and experimental tools for off-target analysis have generated remarkably concordant results for sites with high off-target editing activity. However, no single tool is able to accurately predict low-frequency off-target editing, presenting a bottleneck in therapeutic genome editing, because even a small number of cells with off-target editing can be detrimental. Therefore, we recommend that at least one in silico tool and one experimental tool should be used together to identify potential off-target sites, and amplicon-based next-generation sequencing (NGS) should be used as the gold standard assay for assessing the true off-target effects at these candidate sites. Future work to improve off-target analysis includes expanding the true off-target editing dataset to evaluate new experimental techniques and to train machine learning algorithms; performing analysis using the particular genome of the cells in question rather than the reference genome; and applying novel NGS techniques to improve the sensitivity of amplicon-based off-target editing quantification.
Off-target effects of programmable nucleases remain a critical issue for therapeutic applications of genome editing. This review compares experimental and computational tools for off-target analysis and provides recommendations for better assessments of off-target effects.
Journal Article
Gene correction for SCID-X1 in long-term hematopoietic stem cells
Gene correction in human long-term hematopoietic stem cells (LT-HSCs) could be an effective therapy for monogenic diseases of the blood and immune system. Here we describe an approach for X-linked sSevere cCombined iImmunodeficiency (SCID-X1) using targeted integration of a cDNA into the endogenous start codon to functionally correct disease-causing mutations throughout the gene. Using a CRISPR-Cas9/AAV6 based strategy, we achieve up to 20% targeted integration frequencies in LT-HSCs. As measures of the lack of toxicity we observe no evidence of abnormal hematopoiesis following transplantation and no evidence of off-target mutations using a high-fidelity Cas9 as a ribonucleoprotein complex. We achieve high levels of targeting frequencies (median 45%) in CD34
+
HSPCs from six SCID-X1 patients and demonstrate rescue of lymphopoietic defect in a patient derived HSPC population in vitro and in vivo. In sum, our study provides specificity, toxicity and efficacy data supportive of clinical development of genome editing to treat SCID-Xl.
Gene correction in hematopoietic stem cells could be a powerful way to treat monogenic diseases of the blood and immune system. Here the authors develop a strategy using CRISPR-Cas9 and an aAdeno-Associated vVirus(AAV)-delivered IL2RG cDNA to correct X-linked sSevere Ccombined iImmunodeficiency (SCID-X1) with a high success rate.
Journal Article
DNA probes for monitoring dynamic and transient molecular encounters on live cell membranes
Cells interact with the extracellular environment through molecules expressed on the membrane. Disruption of these membrane-bound interactions (or encounters) can result in disease progression. Advances in super-resolution microscopy have allowed membrane encounters to be examined, however, these methods cannot image entire membranes and cannot provide information on the dynamic interactions between membrane-bound molecules. Here, we show a novel DNA probe that can transduce transient membrane encounter events into readable cumulative fluorescence signals. The probe, which translocates from one anchor site to another, mimicking motor proteins, is realized through a toehold-mediated DNA strand displacement reaction. Using this probe, we successfully monitored rapid encounter events of membrane lipid domains using flow cytometry and fluorescence microscopy. Our results show a preference for encounters within the same lipid domains.
A DNA probe that translocates from one anchor site to another by toehold-mediated DNA strand displacement is used to monitor transient molecular encounter events on live cell membranes.
Journal Article
Machine learning versus crop growth models: an ally, not a rival
Abstract
The rapid increases of the global population and climate change pose major challenges to a sustainable production of food to meet consumer demands. Process-based models (PBMs) have long been used in agricultural crop production for predicting yield and understanding the environmental regulation of plant physiological processes and its consequences for crop growth and development. In recent years, with the increasing use of sensor and communication technologies for data acquisition in agriculture, machine learning (ML) has become a popular tool in yield prediction (especially on a large scale) and phenotyping. Both PBMs and ML are frequently used in studies on major challenges in crop production and each has its own advantages and drawbacks. We propose to combine PBMs and ML given their intrinsic complementarity, to develop knowledge- and data-driven modelling (KDDM) with high prediction accuracy as well as good interpretability. Parallel, serial and modular structures are three main modes can be adopted to develop KDDM for agricultural applications. The KDDM approach helps to simplify model parameterization by making use of sensor data and improves the accuracy of yield prediction. Furthermore, the KDDM approach has great potential to expand the boundary of current crop models to allow upscaling towards a farm, regional or global level and downscaling to the gene-to-cell level. The KDDM approach is a promising way of combining simulation models in agriculture with the fast developments in data science while mechanisms of many genetic and physiological processes are still under investigation, especially at the nexus of increasing food production, mitigating climate change and achieving sustainability.
We humans are at the nexus of increasing food production, mitigating climate change and achieving sustainable agriculture. Simulation models are useful tools for dealing with those challenges. Combining process-based models and machine learning to develop a knowledge- and data-driven modelling (KDDM) approach provides the opportunity of taking advantages of both modelling tools. Such a KDDM approach potentially increases the prediction accuracy of current modelling tools used in agriculture while keeping their interpretability at a good level. Parallel, serial and modular structures are three useful structures that can be adopted to develop a KDDM approach for agricultural applications.
Journal Article
Monitoring of long‐term vegetation dynamics and responses to droughts of various timescales in Inner Mongolia
The characteristics of vegetation and drought for different seasons between 1982 and 2015 in Inner Mongolia were studied based on the normalized difference vegetation index (NDVI) and the standardized precipitation evapotranspiration index (SPEI). The response of vegetation to drought over various timescales for different seasons and vegetation types was investigated using the maximum Pearson correlation, allowing a discussion about the possible causes of any changes. The results indicate that the vegetation NDVI in Inner Mongolia showed an increasing trend in different seasons, with spring vegetation NDVI (April–May) having the largest significant increasing rate, followed by the growing season (April–October), autumn (September–October), and summer (June–August). Accordingly, the proportion of stations with decreasing SPEI was, in descending order, summer, growing season, autumn, and spring. Additionally, the magnitude of the SPEI decrease was greater in eastern Inner Mongolia. NDVI and SPEI were positively correlated in most regions of Inner Mongolia, indicating that changes in vegetation in most parts of this region were affected by the spatial and temporal characteristics of drought, the correlation being them being strongest in the growing season, followed by summer, then spring and autumn. Considering the different types of vegetation, forests were less affected by drought, with broadleaf forests more affected than coniferous forests. The meadow steppes and typical steppes were more affected by 12‐month droughts in the growing season and summer, 6‐month droughts in spring, and 3‐month droughts in autumn, with desert steppes mainly affected by 3‐month droughts. The shrubs, sandy vegetation, and cropland were mostly affected by droughts in summer, and show a greater response to 3‐month droughts in autumn. Finally, the water balance was found to be the most important factor affecting the response of vegetation to drought in Inner Mongolia.
Journal Article
Effect of Huaier granule on recurrence after curative resection of HCC: a multicentre, randomised clinical trial
ObjectiveThere is little evidence that adjuvant therapy after radical surgical resection of hepatocellular carcinoma (HCC) improves recurrence-free survival (RFS) or overall survival (OS). We conducted a multicentre, randomised, controlled, phase IV trial evaluating the benefit of an aqueous extract of Trametes robinophila Murr (Huaier granule) to address this unmet need.Design and resultsA total of 1044 patients were randomised in 2:1 ratio to receive either Huaier or no further treatment (controls) for a maximum of 96 weeks. The primary endpoint was RFS. Secondary endpoints included OS and tumour extrahepatic recurrence rate (ERR). The Huaier (n=686) and control groups (n=316) had a mean RFS of 75.5 weeks and 68.5 weeks, respectively (HR 0.67; 95% CI 0.55 to 0.81). The difference in the RFS rate between Huaier and control groups was 62.39% and 49.05% (95% CI 6.74 to 19.94; p=0.0001); this led to an OS rate in the Huaier and control groups of 95.19% and 91.46%, respectively (95% CI 0.26 to 7.21; p=0.0207). The tumour ERR between Huaier and control groups was 8.60% and 13.61% (95% CI −12.59 to −2.50; p=0.0018), respectively.ConclusionsThis is the first nationwide multicentre study, involving 39 centres and 1044 patients, to prove the effectiveness of Huaier granule as adjuvant therapy for HCC after curative liver resection. It demonstrated a significant prolongation of RFS and reduced extrahepatic recurrence in Huaier group.Trial registration NCT01770431; Post-results.
Journal Article
Copper ions suppress abscisic acid biosynthesis to enhance defence against Phytophthora infestans in potato
Copper‐based antimicrobial compounds are widely and historically used to control plant diseases, such as late blight caused by Phytophthora infestans, which seriously affects the yield and quality of potato. We previously identified that copper ion (Cu2+) acts as an extremely sensitive elicitor to induce ethylene (ET)‐dependent immunity in Arabidopsis. Here, we found that Cu2+ induces the defence response to P. infestans in potato. Cu2+ suppresses the transcription of the abscisic acid (ABA) biosynthetic genes StABA1 and StNCED1, resulting in decreased ABA content. Treatment with ABA or inhibitor fluridone made potato more susceptible or resistance to late blight, respectively. In addition, potato with knockdown of StABA1 or StNCED1 showed greater resistance to late blight, suggesting that ABA negatively regulates potato resistance to P. infestans. Cu2+ also promotes the rapid biosynthesis of ET. Potato plants treated with 1‐aminocyclopropane‐1‐carboxylate showed enhanced resistance to late blight. Repressed expression of StEIN2 or StEIN3 resulted in enhanced transcription of StABA1 and StNCED1, accumulation of ABA and susceptibility to P. infestans. Consistently, StEIN3 directly binds to the promoter regions of StABA1 and StNCED1. Overall, we concluded that Cu2+ triggers the defence response to potato late blight by activating ET biosynthesis to inhibit the biosynthesis of ABA. Cu2+‐mediated late blight resistance activates ET signalling, subsequently suppressing ABA biosynthesis. This recalls two tips when using copper‐based antimicrobial compounds: water in advance; avoid strong sunshine and drought.
Journal Article
NDVI-Based Long-Term Vegetation Dynamics and Its Response to Climatic Change in the Mongolian Plateau
The response of vegetation to regional climate change was quantified between 1982 and 2010 in the Mongolian plateau by integrating the Advanced Very High Resolution Radiometer (AVHRR) Global Inventory Modeling and Mapping Studies (GIMMS) normalized difference vegetation index (NDVI) (1982–2006) and the Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI (2000–2010). Average NDVI values for the growing season (April–October) were extracted from the AVHRR and MODIS NDVI datasets after cross-calibrating and consistency checking the dataset, based on the overlapping period of 2000–2006. Correlations between NDVI and climatic variables (temperature and precipitation) were analyzed to understand the impact of climate change on vegetation dynamics in the plateau. The results indicate that the growing-season NDVI generally exhibited an upward trend with both temperature and precipitation before the mid- or late 1990s. However, a downward trend in the NDVI with significantly decreased precipitation has been observed since the mid- or late 1990s. This is an apparent reversal in the NDVI trend from 1982 to 2010. Pixel-based analysis further indicated that the timing of the NDVI trend reversal varied across different regions and for different vegetation types. We found that approximately 66% of the plateau showed an increasing trend before the reversal year, whereas 60% showed a decreasing trend afterwards. The vegetation decline in the last decade is mostly attributable to the recent tendency towards a hotter and drier climate and the associated widespread drought stress. Monitoring precipitation stress and associated vegetation dynamics will be important for raising the alarm and performing risk assessments for drought disasters and other related natural disasters like sandstorms.
Journal Article
Prognostic significance of neutrophil-lymphocyte ratio in hepatocellular carcinoma: a meta-analysis
Backgrounds
Neutrophil-lymphocyte ratio (NLR) has recently been reported as a predictor of Hepatocellular carcinoma (HCC). However, its prognostic value in HCC still remains controversial. In this study, we aimed to evaluate the association between NLR and clinical outcome of HCC patients by performing meta-analysis.
Methods
A comprehensive literature search for relevant studies published up to August 2013 was performed by using PubMed, Ovid, the Cochrane Library and Web of Science databases. Meta-analysis was performed using hazard ratio (HR) or odds ratio (OR) and 95% confidence intervals (95% CIs) as effect measures.
Results
A total of 15 studies encompassing 3094 patients were included in this meta-analysis. Our pooled results showed that high NLR was associated with poor overall survival (OS) and disease free survival (DFS) in HCC initially treated by liver transplantation (HR = 3.42, 95% CI:2.41-4.85,P = 0.000; HR = 5.90, 95% CI:3.99-8.70,P = 0.000, respectively) and surgical resection (HR = 3.33, 95% CI:2.23-4.98, P = 0.000; HR = 2.10, 95% CI: 2.06–2.14, respectively). High NLR was also associated with poor OS in HCC treated by radiofrequency-ablation (HR = 1.28, 95%CI: 1.10-1.48, P = 0.000), TACE (HR = 2.52, 95% CI: 1.64-3.86, P = 0.000) and mixed treatment (HR = 1.85, 95% CI: 1.40-2.44, P = 0.000), respectively. In addition, high NLR was significantly correlated with the presence of vascular invasion (OR = 2.69, 95% CI: 2.01–3.59, P = 0.000), tumor multifocality (OR = 1.74, 95% CI: 1.30–2.34, P = 0.000) and higher incidence of AFP ≥ 400 ng/ml (OR = 1.46, 95% CI: 1.01–2.09, P = 0.04).
Conclusion
Elevated NLR indicates a poor prognosis for patients with HCC. NLR may be a convenient, easily-obtained, low cost and reliable biomarker with prognostic potential for HCC.
Journal Article