Exploration of whole genome amplification generated chimeric sequences in long-read sequencing data.

MOTIVATION: Multiple displacement amplification (MDA) has become the most commonly used method of whole genome amplification, generating a vast amount of DNA with higher molecular weight and greater genome coverage. Coupling with long-read sequencing, it is possible to sequence the amplicons of over 20 kb in length. However, the formation of chimeric sequences (chimeras, expressed as structural errors in sequencing data) in MDA seriously interferes with the bioinformatics analysis but its influence on long-read sequencing data is unknown. RESULTS: We sequenced the phi29 DNA polymerase-mediated MDA amplicons on the PacBio platform and analyzed chimeras within the generated data. The 3rd-ChimeraMiner has been constructed as a pipeline for recognizing and restoring chimeras into the original structures in long-read sequencing data, improving the efficiency of using TGS data. Five long-read datasets and one high-fidelity long-read dataset with various amplification folds were analyzed. The result reveals that the mis-priming events in amplification are more frequently occurring than widely perceived, and the propor tion gradually accumulates from 42% to over 78% as the amplification continues. In total, 99.92% of recognized chimeric sequences were demonstrated to be artifacts, whose structures were wrongly formed in MDA instead of existing in original genomes. By restoring chimeras to their original structures, the vast majority of supplementary alignments that introduce false-positive structural variants are recycled, removing 97% of inversions on average and contributing to the analysis of structural variation in MDA-amplified samples. The impact of chimeras in long-read sequencing data analysis should be emphasized, and the 3rd-ChimeraMiner can help to quantify and reduce the influence of chimeras. AVAILABILITY AND IMPLEMENTATION: The 3rd-ChimeraMiner is available on GitHub, https://github.com/dulunar/3rdChimeraMiner.

Regulation of capsule spine formation in castor.

Castor (Ricinus communis L.) is a dicotyledonous oilseed crop that can have either spineless or spiny capsules. Spines are protuberant structures that differ from thorns or prickles. The developmental regulatory mechanisms governing spine formation in castor or other plants have remained largely unknown. Herein, using map-based cloning in 2 independent F2 populations, F2-LYY5/DL01 and F2-LYY9/DL01, we identified the RcMYB106 (myb domain protein 106) transcription factor as a key regulator of capsule spine development in castor. Haplotype analyses demonstrated that either a 4,353-bp deletion in the promoter or a single nucleotide polymorphism leading to a premature stop codon in the RcMYB106 gene could cause the spineless capsule phenotype in castor. Results of our experiments indicated that RcMYB106 might target the downstream gene RcWIN1 (WAX INDUCER1), which encodes an ethylene response factor known to be involved in trichome formation in Arabidopsis (Arabidopsis thaliana) to control capsule spine development in castor. This hypothesis, however, remains to be further tested. Nevertheless, our study reveals a potential molecular regulatory mechanism underlying the spine capsule trait in a nonmodel plant species.

Deep-Cloud: A Deep Neural Network-Based Approach for Analyzing Differentially Expressed Genes of RNA-seq Data.

Presently, the field of analyzing differentially expressed genes (DEGs) of RNA-seq data is still in its infancy, with new approaches constantly being proposed. Taking advantage of deep neural networks to explore gene expression information on RNA-seq data can provide a novel possibility in the biomedical field. In this study, a novel approach based on a deep learning algorithm and cloud model was developed, named Deep-Cloud. Its main advantage is not only using a convolutional neural network and long short-term memory to extract original data features and estimate gene expression of RNA-seq data but also combining the statistical method of the cloud model to quantify the uncertainty and carry out in-depth analysis of the DEGs between the disease groups and the control groups. Compared with traditional analysis software of DEGs, the Deep-cloud model further improves the sensitivity and accuracy of obtaining DEGs from RNA-seq data. Overall, the proposed new approach Deep-cloud paves a new pathway for mining RNA-seq data in the biomedical field.

Cytosine base editors (CBEs) for inducing targeted DNA base editing in Nicotiana benthamiana.

BACKGROUND: The base editors can introduce point mutations accurately without causing double-stranded DNA breaks or requiring donor DNA templates. Previously, cytosine base editors (CBEs) containing different deaminases are reported for precise and accurate base editing in plants. However, the knowledge of CBEs in polyploid plants is inadequate and needs further exploration. RESULTS: In the present study, we constructed three polycistronic tRNA-gRNA expression cassettes CBEs containing A3A, A3A (Y130F), and rAPOBEC1(R33A) to compare their base editing efficiency in allotetraploid N. benthamiana (n = 4x). We used 14 target sites to compare their editing efficiency using transient transformation in tobacco plants. The sanger sequencing and deep sequencing results showed that A3A-CBE was the most efficient base editor. In addition, the results showed that A3A-CBE provided most comprehensive editing window (C1 ~ C17 could be edited) and had a better editing efficiency under the base background of TC. The target sites (T2 and T6) analysis in transformed N. benthamiana showed that only A3A-CBE can have C-to-T editing events and the editing efficiency of T2 was higher than T6. Additionally, no off-target events were found in transformed N. benthamiana. CONCLUSIONS: All in all, we conclude that A3A-CBE is the most suitable vector for specific C to T conversion in N. benthamiana. Current findings will provide valuable insights into selecting an appropriate base editor for breeding polyploid plants.

2D Covalent Organic Frameworks with Kagome Lattice: Synthesis and Applications.

2D covalent organic frameworks with Kagome (kgm) topology are a promising class of crystalline frameworks that possess both triangular and hexagonal pores. These dual-pore structures enable kgm COFs to exhibit unique advantages in selective separation, mass transfer, and targeted drug release. However, the synthesis of 2D kgm COFs has been hindered by the reliance on empirical methods. This review systematically summarizes the conventional macrocycle-to-framework strategy, typical [4+2] co-polymerization synthetic strategy, and bifunctional molecules self-condensation approach for constructing 2D kgm COFs. Factors influencing the formation of kgm lattice are surveyed, such as monomer type, solvent polarity, substrate concentration, etc., and highlight the representative examples on targeted synthesis. Additionally, applications of 2D kgm COFs and relationships between structure and performances are summarized. Finally, key fundamental perspectives are proposed to accelerate the further development of this intriguing material.

A case of limb shaking transient ischaemic attack due to internal carotid artery dissection: an unusual presentation of fibromuscular dysplasia.

BACKGROUND: Fibromuscular dysplasia (FMD) has a high prevalence of associated nontraumatic carotid artery dissection, which could further result in transient ischaemic attack (TIA) or stroke. Limb shaking TIA is an unusual form of TIA that is commonly discribed in elderly patients with atherosclerotic backgrounds, while there are limited data about it in patients with FMD. Furthermore, discussions of limb shaking TIA in nonelderly patients are scarce. CASE PRESENTATION: An Asian 47-year-old female presented with intermittent involuntary movement of the left upper limb accompanied by neck torsion. The episode stopped soon after changing to the supine position. On native source images of time-of-flight magnetic resonance angiography (TOF-MRA), the right internal carotid artery showed a "dual lumen sign" with an intimal flap. On contrast-enhanced magnetic resonance angiography and sagittal black-blood T1WI, an intravascular haematoma with irregular lumen stenosis was observed, which overall indicated right internal carotid artery dissection. Digital subtraction angiography showed the characteristic "string-of-beads" appearance in the left internal carotid artery, and the presence of this sign pointed to the diagnosis of FMD. The patient was finally diagnosed with limb shaking TIA due to internal carotid dissection with fibromuscular dysplasia. The patient was prescribed dual anti-platelet therapy. The limb shaking vanished soon after admission with no reoccurrence in the three-month follow-up. CONCLUSIONS: This case demonstrates that limb shaking TIA can present in patients with FMD. Limb shaking TIA in nonelderly patients can be caused by multiple diseases, and more detailed patient guidance is required in clinical practice.

Impact of metacognition on attitudes toward epilepsy in medical students.

PURPOSE: This study evaluated medical students' knowledge and attitudes toward epilepsy and the influence of metacognition thereon. METHOD: Valid questionnaires were administered to medical students including undergraduate, professional postgraduate, and standardized residency training students (N = 503). The questionnaire had 4 parts: demographic information, knowledge of epilepsy, attitudes toward epilepsy, and metacognitive assessment. The Chinese Public Attitudes Toward Epilepsy scale and 30-Item Metacognition Questionnaire were used to assess attitudes and metacognition, respectively. RESULTS: Almost all participants had heard of epilepsy; 38.8% had witnessed a seizure and 25% were acquainted with a person with epilepsy. The proportion of correct answers to epilepsy-related knowledge ranged from 40.6% (Putting an object into the mouth of a person experiencing an epileptic seizure) to 97% (Convulsion is a symptom of epilepsy). However, knowledge of epilepsy was not able to affect attitudes toward epilepsy. Age, years of clinical experience, having witnessed a seizure, positive belief of worry, and need to control thinking were correlated with the different domains of attitude toward epilepsy. When participants were divided into 2 groups-i.e., those with high and low knowledge of epilepsy, participants in the former group who had a positive belief of worry or had not witnessed any seizures were more likely to have negative attitudes toward epilepsy. CONCLUSION: Medical students showed good awareness of the etiology and symptoms of epilepsy. Overall, attitudes toward epilepsy were negative. A positive belief of worry was associated with a more negative attitude toward epilepsy among respondents with greater knowledge of epilepsy.

Inferring single cell expression profiles from overlapped pooling sequencing data with compressed sensing strategy.

Though single cell RNA sequencing (scRNA-seq) technologies have been well developed, the acquisition of large-scale single cell expression data may still lead to high costs. Single cell expression profile has its inherent sparse properties, which makes it compressible, thus providing opportunities for solutions. Here, by computational simulation as well as experiment of 54 single cells, we propose that expression profiles can be compressed from the dimension of samples by overlapped assigning each cell into plenty of pools. And we prove that expression profiles can be inferred from these pool expression data with overlapped pooling design and compressed sensing strategy. We also show that by combining this approach with plate-based scRNA-seq measurement, it can maintain its superiorities in gene detection sensitivity and individual identity and recover the expression profile with high precision, while saving about half of the library cost. This method can inspire novel conceptions on the measurement, storage or computation improvements for other compressible signals in many biological areas.

Genome-Wide Identification of Kiwifruit SGR Family Members and Functional Characterization of SGR2 Protein for Chlorophyll Degradation.

The STAY-GREEN (SGR) proteins play an important role in chlorophyll (Chl) degradation and are closely related to plant photosynthesis. However, the availability of inadequate studies on SGR motivated us to conduct a comprehensive study on the identification and functional dissection of SGR superfamily members in kiwifruit. Here, we identified five SGR genes for each of the kiwifruit species [Actinidia chinensis (Ac) and Actinidia eriantha (Ae)]. The phylogenetic analysis showed that the kiwifruit SGR superfamily members were divided into two subfamilies the SGR subfamily and the SGRL subfamily. The results of transcriptome data and RT-qPCR showed that the expression of the kiwifruit SGRs was closely related to light and plant developmental stages (regulated by plant growth regulators), which were further supported by the presence of light and the plant hormone-responsive cis-regulatory element in the promoter region. The subcellular localization analysis of the AcSGR2 protein confirmed its localization in the chloroplast. The Fv/Fm, SPAD value, and Chl contents were decreased in overexpressed AcSGR2, but varied in different cultivars of A. chinensis. The sequence analysis showed significant differences within AcSGR2 proteins. Our findings provide valuable insights into the characteristics and evolutionary patterns of SGR genes in kiwifruit, and shall assist kiwifruit breeders to enhance cultivar development.

Spatial Transcriptomic Analysis Reveals Regional Transcript Changes in Early and Late Stages of rd1 Model Mice with Retinitis Pigmentosa.

Retinitis pigmentosa (RP) is the leading cause of inherited blindness with a genetically heterogeneous disorder. Currently, there is no effective treatment that can protect vision for those with RP. In recent decades, the rd1 mouse has been used to study the pathological mechanisms of RP. Molecular biological studies using rd1 mice have clarified the mechanism of the apoptosis of photoreceptor cells in the early stage of RP. However, the pathological changes in RP over time remain unclear. The unknown pathology mechanism of RP over time and the difficulty of clinical treatment make it urgent to perform more refined and spatially informed molecular biology studies of RP. In this study, spatial transcriptomic analysis is used to study the changes in different retinal layers of rd1 mice at different ages. The results demonstrate the pattern of photoreceptor apoptosis between rd1 mice and the control group. Not only was oxidative stress enhanced in the late stage of RP, but it was accompanied by an up-regulation of the VEGF pathway. Analysis of temporal kinetic trends has further identified patterns of changes in the key pathways of the early and late stages, to help understand the important pathogenesis of RP. Overall, the application of spatial transcriptomics to rd1 mice can help to elucidate the important pathogenesis of RP involving photoreceptor apoptosis and retinal remodeling.

Increased angiopoietin-like 4 expression ameliorates inflammatory bowel diseases via suppressing CD8+ T cell activities.

Angiopoietin-like 4 (ANGPTL4) is involved in inflammation-associated diseases, such as rheumatoid arthritis, type 2 diabetes, atherosclerosis, and chronic obstructive pulmonary disease. The role of ANGPTL4 in the pathogenesis of inflammatory bowel disease (IBD) remains unknown. Here, the plasma ANGPTL4 levels peaked on days 3 and 5, and expression of ANGPTL4 of inflamed colons peaked on days 5 and 7 in mice with dextran sulfate sodium (DSS)-induced colitis. Simultaneously, CD8+T cells in the inflamed colons peaked at day 5 but declined at day 7. However, the ANGPTL4-/- mice treated with DSS exhibited exacerbated colitis with more CD8+T cells and macrophages infiltrating the colons. The exogenous ANGPTL4 protein protected the mice against DSS-induced colitis with less CD8+T cell and macrophage recruitment in the colons. In addition, recombinant ANGPTL4 directly downregulated the IFN-γ and NKG2D expression of CD8+T cells but had no effects on the CD86 expression and TNF-α secretion of macrophages ex vivo. Adding ANGPTL4 protein into ANGPTL4-/- mice almost blocked the onset of DSS-induced colitis. In parallel, the plasma ANGPTL4 levels were elevated in patients with Crohn's disease and ulcerative colitis at mild/moderate stage and restored to normal levels in IBD patients at a severe stage. The higher ANGPTL4 expression in the inflamed colons of patients with IBD was correlated with lower CD8+ cell infiltration, whereas no associations with macrophages. Our results demonstrated the compensatory protective effect of ANGPTL4 on IBD development at least via the downregulation of CD8+T cell activities. Adding the ANGPTL4 protein would have beneficial effects to retard the progression of IBD.

Solid-state nanopore analysis on the conformation change of DNA polymerase I induced by a DNA substrate.

Proteins with a changeable conformation, such as polymerases, play a very important role in various life activities. Their conformational changes can be reflected in their structural size and flexibility, which may influence their transport kinetics. Recently, solid-state nanopore sensors have been widely applied to characterize the conformation of proteins and other complex structures as sensitive and high throughput single-molecule detectors. In this work, we used a SiN nanopore sensor to study the conformational changes between the Klenow fragment (KF) and its monomer complex with a DNA substrate (KF-DNA). By calculating their hydrodynamic radii, pore volume, the duration of translocation events, drift velocity, and molecular dynamics simulations, we found that the KF-DNA monomer complex has a tighter structure and transports slower. The study performed here can be potentially used to identify single polymerases in real time and may ultimately reveal conformation changes and the interaction between polymerases and their substrates.

dCITI-Seq: droplet combinational indexed transposon insertion sequencing.

The rapid development of high-throughput parallel sequencing poses new challenges for large-scale barcoding and sequencing library construction. Here, we present droplet combinational indexed transposon insertion sequencing (dCITI-Seq), in which samples are indexed by the direct insertion of index-containing adaptors through transposition. The random combination of two sets of adaptors with known barcodes and massively parallel transposition was realized via a robust droplet pairing and merging platform. This strategy potentially enlarges the indexing capacity and decreases index crosstalk. Also, dCITI-Seq exhibited a lower GC base preference than conventional in-tube transposition library preparation. With a custom bioinformatic processing, it could be further applied to large-scale single-cell sequencing.

A molecular dynamics investigation of Taq DNA polymerase and its complex with a DNA substrate using a solid-state nanopore biosensor.

Proteins have a small volume difference by the diversity of amino acids, which make protein detection and identification a great challenge. Solid-state nanopore as label-free biosensors has attracted attention with high sensitivity. In this work, we investigated the Taq DNA polymerase before and after combining it with a DNA substrate on a solid-state nanopore through molecular dynamics. In simulation, we analyzed the contribution source of nanopore current blockage. In addition to considering the traditional physical exclusion volume model, the non-covalent interaction between the protein molecules and the pore wall also showed to affect the current blockage in the nanopore. When choosing pores of comparable size to protein molecules, the two states of Taq DNA polymerase produce differentiated non-covalent interactions with the pore wall, which enhanced the amplitude difference in current blockage. As a result, the two DNA polymerases can be distinguished through the distinct current blockage. However, when applying additional pulling force or increasing the pore size of the nanopore, the differences between the current blockages are not significant enough to distinguish. The introduction of the non-covalent interaction makes it clear to understand the current blockage differences, which guide the mechanism between molecules with similar structures or volumes.

Genome-Wide Identification of the LHC Gene Family in Kiwifruit and Regulatory Role of AcLhcb3.1/3.2 for Chlorophyll a Content.

Light-harvesting chlorophyll a/b-binding (LHC) protein is a superfamily that plays a vital role in photosynthesis. However, the reported knowledge of LHCs in kiwifruit is inadequate and poorly understood. In this study, we identified 42 and 45 LHC genes in Actinidia chinensis (Ac) and A. eriantha (Ae) genomes. Phylogenetic analysis showed that the kiwifruit LHCs of both species were grouped into four subfamilies (Lhc, Lil, PsbS, and FCII). Expression profiles and qRT-PCR results revealed expression levels of LHC genes closely related to the light, temperature fluctuations, color changes during fruit ripening, and kiwifruit responses to Pseudomonas syringae pv. actinidiae (Psa). Subcellular localization analysis showed that AcLhcb1.5/3.1/3.2 were localized in the chloroplast while transient overexpression of AcLhcb3.1/3.2 in tobacco leaves confirmed a significantly increased content of chlorophyll a. Our findings provide evidence of the characters and evolution patterns of kiwifruit LHCs genes in kiwifruit and verify the AcLhcb3.1/3.2 genes controlling the chlorophyll a content.

Prediction of Time-Series Transcriptomic Gene Expression Based on Long Short-Term Memory with Empirical Mode Decomposition.

RNA degradation can significantly affect the results of gene expression profiling, with subsequent analysis failing to faithfully represent the initial gene expression level. It is urgent to have an artificial intelligence approach to better utilize the limited data to obtain meaningful and reliable analysis results in the case of data with missing destination time. In this study, we propose a method based on the signal decomposition technique and deep learning, named Multi-LSTM. It is divided into two main modules: One decomposes the collected gene expression data by an empirical mode decomposition (EMD) algorithm to obtain a series of sub-modules with different frequencies to improve data stability and reduce modeling complexity. The other is based on long short-term memory (LSTM) as the core predictor, aiming to deeply explore the temporal nonlinear relationships embedded in the sub-modules. Finally, the prediction results of sub-modules are reconstructed to obtain the final prediction results of time-series transcriptomic gene expression. The results show that EMD can efficiently reduce the nonlinearity of the original data, which provides reliable theoretical support to reduce the complexity and improve the robustness of LSTM models. Overall, the decomposition-combination prediction framework can effectively predict gene expression levels at unknown time points.

EasyNanopore: A Ready-to-Use Processing Software for Translocation Events in Nanopore Translocation Experiments.

We developed EasyNanopore which is a ready-to-use software to select the events of a nanopore molecular translocation experiment. The software is released as an executable file with a graphical user interface and provides several versions suitable for different operating systems without installing any running environment to execute it. We use the adaptive threshold which adapts to the low-frequency variation of the baseline to detect events and uses a multiprocess method to accelerate the process of event detection. After the event is identified, its duration and amplitude information will be extracted and a resulting txt file will be generated for further analysis. Our software runs fast and can effectively extract the data from data of large-scale nanopore molecular translocation experiments.

Main-Side Chain Hydrogen Bonding-Based Self-Healable Polyurethane with Highly Stretchable, Excellent Mechanical Properties for Self-Healing Acid-Base Resistant Coating.

Developing an autonomous self-healing polyurethane (PU) elastomer with excellent mechanical properties and high ductility has attracted increasing attention. Nowadays, the synthesis of elastomers with excellent mechanical properties and rapid self-healing at room temperature faces a huge challenge. Herein, This work reports a new supramolecular PU with excellent mechanical properties and rapid self-healing at room temperature through the introduction of T-type chain extender into the supramolecular polymer chain. The introduction of T-chain extender can be used to enhance the mechanical strength of PU, and the multiple hydrogen bonds on the side-chain provide theoretical support for the rapid self-healing ability of PU. Maximum stress of the synthesized PU can reach 3.4 ± 0.15 Mpa, and maximum elongation at break can reach 3200% ± 160%. Due to flexibility and re-constructability of side-chain hydrogen bonds, PU stress repair efficiency can reach 96.7%, and can be self-healing scratches rapidly and effectively at room temperature. The mechanical properties and self-healing properties of PU can be adjusted by the content of T-type chain extender. The PU is applied to the metal surface coating, which has excellent acid-base resistance, bond strength up to 2.9 ± 0.1 Mpa, and the ability to eliminate local damage on the coating surface quickly at room temperature.

Bitter Melon Extract Yields Multiple Effects on Intestinal Epithelial Cells and Likely Contributes to Anti-diabetic Functions.

The intestines have been recognized as important tissues for metabolic regulation, including glycemic control, but their vital role in promoting the anti-diabetic effects of bitter melon, the fruit of Momordica charantia L, has seldom been characterized, nor acknowledged. Evidence suggests that bitter melon constituents can have substantial interactions with the intestinal epithelial cells before circulating to other tissues. We therefore characterized the effects of bitter melon extract (BME) on intestinal epithelial cells. BME was found to contain substantial amounts of carbohydrates, proteins, and triterpenoids. TNF-α induced insulin resistance in an enterocyte cell line of IEC-18 cells, and BME promoted glucose utilization of the insulin-resistant cells. Further analysis suggested that the increased glucose consumption was a result of the combined effects of insulin sensitizing and insulin substitution functions of BME. The functions of insulin substitution were likely generated due to the activation of AMP-activated protein kinase. Meanwhile, BME acted as a glucagon-like peptide 1 (GLP-1) secretagogue on enteroendocrine cells, which may be mediated by the activation of bitter-taste receptors. Therefore, BME possesses insulin sensitizing, insulin substitution, and GLP-1 secretagogue functions upon intestinal cells. These effects of BME on intestinal cells likely play a significant part in the anti-diabetic action of bitter melon.

Cardiac Troponin I association with critical illness and death risk in 726 seriously ill COVID-19 patients: A retrospective cohort study.

Background: For coronavirus disease 2019 (COVID-19), early identification of patients with serious symptoms at risk of critical illness and death is important for personalized treatment and balancing medical resources. Methods: Demographics, clinical characteristics, and laboratory tests data from 726 patients with serious COVID-19 at Tongji Hospital (Wuhan, China) were analyzed. Patients were classified into critical group (n = 174) and severe group (n= 552), the critical group was sub-divided into survivors (n = 47) and non-survivors (n = 127). Results: Multivariable analyses revealed the risk factors associated with critical illness in serious patients were: Advanced age, high respiratory rate (RR), high lactate dehydrogenase (LDH) level, high hypersensitive cardiac troponin I (hs-cTnI) level, and thrombocytopenia on admission. High hs-cTnI level was the independent risk factor of mortality among critically ill patients in the unadjusted and adjusted models. ROC curves demonstrated that hs-cTnI and LDH were predictive factors for critical illness in patients with serious COVID-19 whereas procalcitonin and D-Dimer with hs-cTnI and LDH were predictive parameters in mortality risk. Conclusions: Advanced age, high RR, LDH, hs-cTnI, and thrombocytopenia, constitute risk factors for critical illness among patients with serious COVID-19, and the hs-cTnI level helps predict fatal outcomes in critically ill patients.