Search

Alternative splicing enables a gene translating into different isoforms and into the corresponding proteoforms, which actually accomplish various biological functions of a living body. Isoform-isoform interactions (IIIs) provide a higher resolution interactome to explore the cellular processes and disease mechanisms than the canonically studied protein-protein interactions (PPIs), which are often recorded at the coarse gene level. The knowledge of IIIs is critical to map pathways, understand protein complexity and functional diversity, but the known IIIs are very scanty. In this paper, we propose a deep learning based method called DeepIII to systematically predict genome-wide IIIs by integrating diverse data sources, including RNA-seq datasets of different human tissues, exon array data, domain-domain interactions (DDIs) of proteins, nucleotide sequences and amino acid sequences. Particularly, DeepIII fuses these data to learn the representation of isoform pairs with a four-layer deep neural networks, and then performs binary classification on the learnt representation to achieve the prediction of IIIs. Experimental results show that DeepIII achieves a superior prediction performance to the state-of-the-art solutions and the III network constructed by DeepIII gives more accurate isoform function prediction. Case studies further confirm that DeepIII can differentiate the individual interaction partners of different isoforms spliced from the same gene. The code and datasets of DeepIII are available at http://mlda.swu.edu.cn/codes.php?name=DeepIII.

Discovering driver pathways is an essential task to understand the pathogenesis of cancer and to design precise treatments for cancer patients. Increasing evidences have been indicating that multiple pathways often function cooperatively in carcinogenesis. In this study, we propose an approach called CDPath to discover cooperative driver pathways. CDPath first uses Integer Linear Programming to explore driver core modules from mutation profiles by enforcing co-occurrence and functional interaction relations between modules, and by maximizing the mutual exclusivity and coverage within modules. Next, to enforce cooperation of pathways and help the follow-up exact cooperative driver pathways discovery, it performs Markov clustering on pathway-pathway interaction network to cluster pathways. After that, it identifies pathways in different modules but in the same clusters as cooperative driver pathways. We apply CDPath on two TCGA datasets: breast cancer (BRCA) and endometrial cancer (UCEC). The results show that CDPath can identify known (i.e., TP53) and potential driver genes (i.e., SPTBN2). In addition, the identified cooperative driver pathways are related with the target cancer, and they are involved with carcinogenesis and several key biological processes. CDPath can uncover more potential biological associations between pathways (over 100 percent) and more cooperative driver pathways (over 200 percent) than competitive approaches. The demo codes of CDPath are available at http://mlda.swu.edu.cn/codes.php?name=CDPath .

Copy number variation (CNV) is the most prevalent type of genetic structural variation that has been recognized as an important source of phenotypic variation in humans, animals and plants. However, the mechanisms underlying the evolution of CNVs and their function in natural or artificial selection remain unknown. Here, we generated CNV region (CNVR) datasets which were diverged or shared among cattle, goat, and sheep, including 886 individuals from 171 diverse populations. Using 9 environmental factors for genome-wide association study (GWAS), we identified a series of candidate CNVRs, including genes relating to immunity, tick resistance, multi-drug resistance, and muscle development. The number of CNVRs shared between species is significantly higher than expected (P

Agglomeration of therapeutic nanoparticles in response to tumor microenvironments is a promising approach to enhance drug accumulation and improve therapeutic efficacy. Cytosine-rich DNA sequences ...

Summary We utilize polymer micelle to precisely control indocyanine green (ICG) J-aggregation in a fast and highly efficient way. In addition to simple encapsulation, the polymer micelle plays a role as a host template to drive ICG J-aggregation by the synergy of electrostatic and hydrophobic attractions. We further demonstrate that, due to the robust host-guest interaction, the intact of ICG J-aggregate will be secured by the polymer encapsulation during the intracellular and in vivo incubation. These features make this hierarchical assembly between ICG J-aggregate and the micelle polymer a promising biomedicine for cancer phototheranostics. Therefore the complex micelles are further modified by introduction of doxorubicin for chemotherapy and DNA aptamer for tumor targeting, and the final multi-functional micellar medicine shows high therapeutic efficacy for tumor, i.e., the tumor can be completely eliminated with no local reoccurrence and without long-term toxicity or side effects during a 24-day period after the treatment., Graphical Abstract, Highlights • J-aggregation of ICG is facilitated by polymer micelle • Proper host-guest interactions are very critical • The aggregation significantly improves the capability of ICG in phototheranostics • The hierarchical assembly exhibits excellent photo/bio-stability, Medical Imaging; Organic Chemistry; Materials Science

Nano-blocking technology has become a key to overcoming a prominent bottleneck in shale gas development. In this paper, poly(ST-VS-B-E) was synthesized by Michael addition reaction using styrene, vinyl sodium sulfonate, ethyl methacrylate, and butyl acrylate. Poly(ST-VS-B-E) was characterized by infrared spectroscopy analysis, laser scattering analysis, and thermogravimetric analysis. The rheological properties of drilling fluid with poly(ST-VS-B-E) were studied by testing the drilling fluid’s properties. The results showed that the median particle size of poly(ST-VS-B-E) was 79.15 nm and it resisted a 359.25 °C high temperature. The yield point of the water-based drilling fluid with 2.5 wt% poly(ST-VS-B-E) added was 27 Pa, and the fluid loss was 3.1 mL, with good drilling fluid performance. Further test results from simulated mud cake filtration and the simulated core penetration showed that when the mass concentration of poly(ST-VS-B-E) was 2.5 wt%, the blocking rates were 66.67% and 93.33%, respectively, and the blocking performance increased gradually with the addition of poly(ST-VS-B-E). Poly(ST-VS-B-E) can be squeezed into the nano-pores of a shale formation under the action of pressure difference, so as to block the formation and prevent the entry of water-based drilling fluid filtrate. Poly(ST-VS-B-E) can serve as a potential nano-blocking material in water-based drilling fluids.

Minimal invasive phototherapy utilising near-infrared (NIR) laser to generate local reactive oxygen species (ROS) and heat has few associated side effects and is a precise treatment in cancer therapy. However, high-efficiency and safe phototherapeutic tumour agents still need developing. The application of iron hydroxide/oxide immobilised on reduced graphene oxide (FeOxH–rGO) nanocomposites as a therapeutic agent in integration photodynamic cancer therapy (PDT) and photothermal cancer therapy (PTT) was discussed. Under 808 nm NIR irradiation, FeOxH–rGO offers a high ROS generation and light-to-heat conversion efficiency because of its strong NIR absorption. These phototherapeutic effects lead to irreversible damage in FeOxH–rGO-treated T47D cells. Using a tumour-bearing mouse model, NIR ablated the breast tumour effectively in the presence of FeOxH–rGO. The tumour treatment response was evaluated to be 100%. We integrated PDT and PTT into a single nanodevice to facilitate effective cancer therapy. Our FeOxH–rGO, which integrates the merits of FeOxH and rGO, displays an outstanding tumoricidal capacity, suggesting the utilization of this nanocomposites in future medical applications.

Polymerization of small interfering RNA (siRNA) has been demonstrated as a promising strategy to improve siRNA delivery, which will change the low-charge and rigid properties of single siRNA and enhance its electrostatic interactions with cationic polymers. For such polymerization strategy, a major breakthrough is still needed to fully eliminate chemical processes and further improve the nanocomplex-forming ability of polymerized siRNAs. Herein, the extremely strong interaction between the DNA product of rolling circle amplification (RCA) and linear poly(ether imide) (PEI) has been disclosed; accordingly, a stable nanocomplex is formed just at its charge neutralization point, which benefits from the high molecular weight of the RCA product (3 000 000 Da). In addition, as the sequence of the RCA product is determined by the cyclic template, the programmable nature of DNA can simplify the optimization process and maximize the hybridization efficiency between RCA and sticky siRNAs, realizing a superior siRNA polymerization efficiency. Depending on these two effects, the RCA DNA is utilized as a cocarrier material to organize siRNA polymerization and substantially reduce the usage amount of PEI, which greatly improves RNAi efficiency of PEI/RCA-siRNA polyplex both

Rolling circle amplification (RCA) is an isothermal enzymatic amplification reaction, which is used to massively produce periodic long-single-stranded DNA/RNA with predesigned sequences and functions. The RCA technique not only shows unparalleled advantages in constructing functional DNA assemblies; and the RCA products can also serve as high-performance scaffolds to interact with or accommodate foreign moieties, i.e., therapeutic nucleic acids, proteins, lipids, cationic polymers, and metal nanoparticles (NPs), etc. to fabricate multifunctional and bioresponsive materials with various sizes and morphologies. The RCA product is also a kind of high-molecular-weight polyanion with strong inter/intra-molecular interactions, which provides great opportunities for regulating the condensation states of DNA nanomedicines and bulk materials. Based on all these good properties, the RCA-based materials have shown more and more practical potentials in biomedical fields. In this review, we summarize the recent development of RCA-based origami structures, NPs, hydrogels, and metallization, for which the fabrication methods, their biomedical applications, and future prospects are carefully discussed.

Recent investigations reveal that lactate is not a waste product but a major energy source for cells, especially in the mitochondria, which can support cellular survival under glucose shortage. Accordingly, the new understanding of lactate prompts to target it together with glucose to pursue a more efficient cancer starvation therapy. Herein, zeolitic imidazolate framework‐8 (ZIF‐8) nanoplatforms are used to co‐deliver α‐cyano‐4‐hydroxycinnamate (CHC) and glucose oxidase (GOx) and fulfill the task of simultaneous depriving of lactate and glucose, resulting in a new nanomedicine CHC/GOx@ZIF‐8. The synthesis conditions are carefully optimized in order to yield monodisperse and uniform nanomedicines, which will ensure reliable and steady therapeutic properties. Compared with the strategies aiming at a single carbon source, improved starvation therapy efficacy is observed. Besides, more than boosting the energy shortage, CHC/GOx@ZIF‐8 can block the lactate‐fueled respiration and relieve solid tumor hypoxia, which will enhance GOx catalysis activity, depleting extra glucose, and producing more cytotoxic H2O2. By the synergistically enhanced anti‐tumor effect, both in vitro and in vivo cancer‐killing efficacies of CHC/GOx@ZIF‐8 show twice enhancements than the GOx mediated therapy. The results demonstrate that the dual‐depriving of lactate and glucose is a more advanced strategy for strengthening cancer starvation therapy., Metal‐organic‐framework nanomedicines encapsulating an inhibitor of monocarboxylate transporters 1 and glucose oxidase are developed for efficient glucose depletion while inhibiting the lactate influx. At meanwhile, inhibiting the lactate influx can improve the intracellular oxygen pressure, which subsequently promotes the catalytic activity of glucose oxidase. Cancer cells are substantially killed from ATP shortage and high ROS levels.

Understanding the evolutionary history and adaptive process depends on the knowledge that we can acquire from both ancient and modern genomic data. With the availability of a deluge of whole-genome sequencing data from ancient and modern goat samples, a user-friendly database making efficient reuse of these important resources is needed. Here, we use the genomes of 208 modern domestic goats, 24 bezoars, 46 wild ibexes, and 82 ancient goats to present a comprehensive goat genome variation database (GGVD). GGVD hosts a total of ∼41.44 million SNPs, ∼5.14 million indels, 6,193 selected loci, and 112 introgression regions. Users can freely visualize the frequency of genomic variations in geographical maps, selective sweeps in interactive tables, Manhattan plots, or line charts, as well as the heatmap patterns of the SNP genotype. Ancient data can be shown in haplotypes to track the state of genetic variants of selection and introgression events in the early, middle, and late stages. For facilitating access to sequence features, the UCSC Genome Browser, BLAT, BLAST, LiftOver, and pcadapt are also integrated into GGVD. GGVD will be a convenient tool for population genetic studies and molecular marker designing in goat breeding programs, and it is publicly available at http://animal.nwsuaf.edu.cn/GoatVar.

Copy number variation (CNV) is the most prevalent type of genetic structural variation that has been recognized as an important source of phenotypic variation in humans, animals and plants. However, the mechanisms underlying the evolution of CNVs and their function in natural or artificial selection remain unknown. Here, we generated CNV region (CNVR) datasets which were diverged or shared among cattle, goat, and sheep, including 886 individuals from 171 diverse populations. Using 9 environmental factors for genome-wide association study (GWAS), we identified a series of candidate CNVRs, including genes relating to immunity, tick resistance, multi-drug resistance, and muscle development. The number of CNVRs shared between species is significantly higher than expected (P0.00001), and these CNVRs may be more persist than the single nucleotide polymorphisms (SNPs) shared between species. We also identified genomic regions under long-term balancing selection and uncovered the potential diversity of the selected CNVRs close to the important functional genes. This study provides the evidence that balancing selection might be more common in mammals than previously considered, and might play an important role in the daily activities of these ruminant species.

In the indoor application environment, in order to improve the overall efficiency of the service robot in the target detection, combined with the deep learning target detection theory, the SSD target detection algorithm and a lightweight neural network mobilenetv2 are combined to design a new target detection algorithm, which improves the target detection efficiency to a certain extent. The main improvements of this paper are as follows. Firstly, using SSD for reference, multi-scale feature extraction is carried out for the target image, and different sizes of targets are detected at different scales; Secondly, in the process of matching the actual target detection region with the algorithm prediction region, the positive and negative samples are processed properly to ensure the stability of the model; Thirdly, using the idea of mobilenet for reference, the traditional convolution is replaced by the deep separable convolution, which greatly reduces the calculation of data processing and improves the processing speed of the model while ensuring the accuracy of the model. Fourthly, in view of the time-consuming and laborious situation of manually marking data sets, a method of automatically marking data sets is proposed, which improves the efficiency of data set preparation and reduces the workload of manual marking. Through the improvement of the above algorithm, the detection speed of the system model has been greatly improved compared with SSD algorithm, and the overall recognition efficiency of indoor service robot has been improved to a certain extent.

Functional nucleic acids, which can target cancer cells and realize stimuli-responsive drug delivery in tumor microenvironment, have been widely applied for anticancer chemotherapy. At present, high cost, unsatisfactory biostability, and complicated fabrication process are the main limits for the development of DNA-based drug-delivery nanocarriers. Here, a doxorubicin (Dox)-delivery nanoparticle for tumor-targeting chemotherapy is developed taking advantage of rolling circle amplification (RCA) technique, by which a high quantity of functional DNAs can be efficiently collected. Furthermore, Mg2+, a major electrolyte in human body showing superior biocompatibility, can sufficiently condense the very long sequence of an RCA product and better preserve its functions. The resultant DNA nanoparticle exhibits a high biostability, making it a safe and ideal nanomaterial for in vivo application. Through cellular and in vivo experiments, we thoroughly demonstrate that this kind of Mg2+-stabilized multifunctional D...

Apple (Malus × domestica) trees are vulnerable to freezing temperatures. However, there has been only limited success in developing cold-hardy cultivars. This lack of progress is due at least partly to lack of understanding of the molecular mechanisms of freezing tolerance in apple. In this study, we evaluated the potential roles for two R2R3 MYB transcription factors (TFs), MYB88 and the paralogous FLP (MYB124), in cold stress in apple and Arabidopsis. We found that MYB88 and MYB124 positively regulate freezing tolerance and cold-responsive gene expression in both apple and Arabidopsis. Chromatin-Immunoprecipitation-qPCR and electrophoretic mobility shift assays showed that MdMYB88/MdMYB124 act as direct regulators of the COLD SHOCK DOMAIN PROTEIN 3 (MdCSP3) and CIRCADIAN CLOCK ASSOCIATED 1 (MdCCA1) genes. Dual luciferase reporter assay indicated that MdCCA1 but not MdCSP3 activated the expression of MdCBF3 under cold stress. Moreover, MdMYB88 and MdMYB124 promoted anthocyanin accumulation and H2 O2 detoxification in response to cold. Taken together, our results suggest that MdMYB88 and MdMYB124 positively regulate cold hardiness and cold-responsive gene expression under cold stress by C-REPEAT BINDING FACTOR (CBF)-dependent and CBF-independent pathways.

The interaction between graphene oxide (GO) and DNA is very sensitive to the environment. For example, under acidic conditions, the affinity of GO for DNA is enhanced, weakening the capability of GO to distinguish DNAs with different conformations. This effect has impeded the development of sensitive pH biosensors based on GO-DNA nanosystems. In this work, we systematically studied the affinity between GO and i-motif forming oligonucleotides (IFOs) at different pH values and developed a herring sperm DNA (HSD) treatment method. Using this method, HSD occupies the surface of GO, compromising the attractive force of GO that is significantly enhanced under acidic conditions. As a result, the ability of GO to distinguish between "open" and "closed" IFOs is successfully generalized to a wider pH range. Finally, a pH-sensitive GO-IFO nanosystem was fabricated that showed excellent sensing ability both in vitro and for intracellular pH detection. Because the interaction between GO and DNA is the basis for constructing GO-DNA biosensors, the strategy developed in this work shows great potential to be applied in a variety of other GO-DNA sensing systems.

Iron(II) phthalocyanine was immobilized onto amidoximated polyacrylonitrile fiber to construct a bioinspired catalytic system for oxidizing organic dyes by H2O2 activation. The amidoxime groups greatly helped to anchor Iron(II) phthalocyanine molecules onto the fiber through coordination interaction, which has been confirmed by Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy and UV-vis diffuse reflectance spectroscopy analyses. Electron spin resonance studies indicate that the catalytic process of physically anchored Iron(II) phthalocyanine performed via a hydroxyl radical pathway, while the catalyst bonded Iron(II) phthalocyanine through coordination effect could selectively catalyze the H2O2 decomposition to generate high-valent iron-oxo species. This may result from the amidoxime groups functioning as the axial fifth ligands to favor the heterolytic cleavage of the peroxide OO bond. This feature also enables the catalyst to only degrade the dyes adjacent to the catalytic active centers and enhances the efficient utilization of H2O2. In addition, this catalyst could effectively catalyze the mineralization of organic dyes and can be easily recycled without any loss of activity.

The carcinogenesis is typically involved with the cooperations of multiple pathways. Therefore, discovering cooperative driver pathways can provide more precise therapy to patients. Existing cooperative driver pathway identification methods can only identify few (or previously well-known) driver pathways, because of noisy or single type knowledge, or of the insufficient attention to pathway cooperations. To address these problems, we develop a novel approach called CoPath that leverages genomic alteration profiles and bi-clustering to discover cooperative driver pathways. Based on the mutation profiles reconstructed from somatic mutations and copy number variations, CoPath firstly uses a greedy search on the gene signaling network to identify mutually exclusive modules of genes, which have common downstream events in the network. Next, it incorporates the identified mutually exclusive modules and gene interaction network as prior knowledge, and introduces a dual regularized bi-clustering method on gene expression data to cluster cooperative mutually exclusive modules. Finally, it identifies the modules in the same cluster as cooperative driver pathways. Extensive experiments on real cancer genomics dataset (Breast from TCGA) shows that CoPath can not only detect individual driver pathways but also uncover more relations between potential driver genes and pathways than related competitive approaches.

Intracellular pH is a vital parameter which can reflect the physiological process, and the detection of intracellular pH with a high signal-to-noise ratio (SNR) remains a challenge. Compared to pH biosensors based on a single-wavelength signal, it is much easier to obtain better sensitivity and higher SNR from the biosensors by two-wavelength ratiometric signals. In this study, we used DNA-grafted graphene oxide (GO) to ratiometrically detect intracellular pH ranging from basic to acidic. A high SNR with a 35-fold difference in the ratiometric output has been achieved through careful optimization: (1) A high DNA conjugation yield of 45% has been gained through utilizing the partial double-stranded assembly strategy. (2) Herring sperm DNA (HSD) plays an important role in improving the sensitivity of the nanosystem by purifying and passivating the surface of GO; therefore, the concentration of HSD has been optimized to pursue the most sensitive ratiometric response. Apart from the ultrahigh SNR, fabricated GO-AR-Cy5/IFO-Cy3 exhibited excellent stability and biocompatibility in biological environments. Further experiments demonstrated that the nanosystem worked well in live cells in response to pH changes. It is possible to distinguish small pH differences and realize quantitative detection based on ratiometric fluorescence imaging by laser scanning confocal microscope analysis, which makes the nanosystem a promising candidate for further biological study and clinical applications.

We demonstrate the synthesis of antibacterial carbon quantum dots (CQDs) through a one-step pyrolysis of biogenic polyamine (PA) and dopamine (DA) mixture. SPM/DA-CQDs synthesized from DA combined with spermine (SPM) exhibit effective antibacterial activity and high adhesion properties on glass and surfaces of polymeric contact lens material. The antimicrobial activity of SPM/DA-CQDs is primarily due to their ability to disrupt the bacterial membrane, and they possess wide spectrum antimicrobial activity against Gram-negative bacteria (Escherichia coli, Salmonella enterica serovar Enteritidis, and Pseudomonas aeruginosa) and Gram-positive bacteria (Staphylococcus aureus and its multidrug-resistant strain, methicillin-resistant S. aureus). The minimal inhibitory concentration (MIC) of SPM/DA-CQDs against the tested bacteria was >17-fold and >7-fold lower than those of CQDs prepared solely from spermine and dopamine, respectively. The great biocompatibility of our SPM/DA-CQDs is revealed from the in vitro cytotoxicity and hemolysis assays and in vivo evaluation of morphological and physiological changes of rabbit corneas. We further prepared SPM/DA-CQDs-coated coverslips and contact lenses, which display excellent stability and antibiofilm properties. Moreover, in vivo tests show that SPM/DA-CQDs suppress bacterial keratitis (BK) formation in a corneal-injured rabbit model. Our results indicate that SPM/DA-CQDs have great potential as a coating material for inhibition of biofilm formation on contact lenses, and broadly to protect medical devices from contamination.

A widely used approach in transcriptome analysis is the alignment of short reads to a reference genome. However, owing to the deficiencies of specially designed analytical systems, short reads unmapped to the genome sequence are usually ignored, resulting in the loss of significant biological information and insights. To fill this gap, we present Comprehensive Assembly and Functional annotation of Unmapped RNA-Seq data (CAFU), a Galaxy-based framework that can facilitate the large-scale analysis of unmapped RNA sequencing (RNA-Seq) reads from single- and mixed-species samples. By taking advantage of machine learning techniques, CAFU addresses the issue of accurately identifying the species origin of transcripts assembled using unmapped reads from mixed-species samples. CAFU also represents an innovation in that it provides a comprehensive collection of functions required for transcript confidence evaluation, coding potential calculation, sequence and expression characterization and function annotation. These functions and their dependencies have been integrated into a Galaxy framework that provides access to CAFU via a user-friendly interface, dramatically simplifying complex exploration tasks involving unmapped RNA-Seq reads. CAFU has been validated with RNA-Seq data sets from wheat and Zea mays (maize) samples. CAFU is freely available via GitHub: https://github.com/cma2015/CAFU.

Oligonucleotide-stabilized silver nanoclusters (AgNCs) show promising applications in bioimaging and bio-/chemo-sensing. However, their unsatisfactory photostability limits their practical applications. In this work, fluorescent AgNCs were synthesized in situ in a DNA hydrogel, consisting of cross-linked enzymatically amplified polymeric DNAs with cytosine-rich sequences in the presence of Ag+. The fluorescence property of the resultant AgNCs was optimized by a rational design of the DNA sequences to cover a broad spectrum with comparable green and red emissions. Under the protection of the DNA hydrogel, the AgNCs showed significantly improved photostability in an ambient oxygen environment, as well as low cytotoxicity even at a high concentration. Therefore, these properties show the rolling-circle-amplification-stabilized AgNCs to be a promising possible fluorescent probe for the detection of reactive oxygen/nitrogen species (ROS/RNS) in live cells because red-emitting species are susceptible to oxidati...

Cell direct reprogramming technology has been rapidly developed with its low risk of tumor risk and avoidance of ethical issues caused by stem cells, but it is still limited to specific cell types. Direct reprogramming from an original cell to target cell type needs the cell similarity and cell specific regulatory network. The position and function of cells in vivo, can provide some hints about the cell similarity. However, it still needs further clarification based on molecular level studies. CellSim is therefore developed to offer a solution for cell similarity calculation and a tool of bioinformatics for researchers. CellSim is a novel tool for the similarity calculation of different cells based on cell ontology and molecular networks in over 2000 different human cell types and presents sharing regulation networks of part cells. CellSim can also calculate cell types by entering a list of genes, including more than 250 human normal tissue specific cell types and 130 cancer cell types. The results are shown in both tables and spider charts which can be preserved easily and freely. CellSim aims to provide a computational strategy for cell similarity and the identification of distinct cell types. Stable CellSim releases (Windows, Linux, and Mac OS/X) are available at: www.cellsim.nwsuaflmz.com , and source code is available at: https://github.com/lileijie1992/CellSim/ .