The conjugation of antitumor drugs to targeting reagents such as antibodies is a promising method that can increase the efficacy of chemotherapy and reduce their overall toxicity. In this paper, we covalently link an antitumor agent doxorubicin (Dox) to the DNA aptamer sgc8c, which was selected by the cell-SELEX method. In doing so, we expected that this sgc8c-Dox conjugate would specifically kill the target CCRF-CEM (T-cell Acute Lymphoblastic Leukemia, T-cell ALL) cells, but with minimal toxicity towards non-target cells. The results demonstrated that sgc8c-Dox conjugate possesses many of the properties of the sgc8c aptamer, including high binding affinity (K d = 2.0 ± 0.2 nM), and the capability to be efficiently internalized by target cells. Moreover, due to the specific conjugation method, the acid-labile linkage connecting the sgc8c-Dox conjugate can be cleaved inside the acidic endosomal environment. Cell viability tests demonstrate that the sgc8c-Dox conjugates not only possess potency similar to the unconjugated Dox, but also have the required molecular specificity which is lacking in most current targeted drug delivery strategies. Furthermore, we found that nonspecific uptake of membrane-permeable Dox to non-target cell lines could also be inhibited by linking the drug with the aptamer, thus, it makes the conjugates selective to the cells which express higher amounts of target proteins. Compared to the less effective reported Dox-immunoconjugates, this sgc8c-Dox conjugates make targeted chemotherapy more feasible with drugs having various potencies. When combined with the large number of recently created DNA aptamers that specifically target a wide variety of cancer cells, this drug-aptoconjugation method will have broad implications for targeted drug delivery.

A near-infrared light-responsive drug delivery platform based on Au-Ag-nanorods (Au-Ag NRs) coated with DNA-crosslinked polymeric shells was constructed. DNA complementarity has been applied to develop a polyacrylamide-based sol-gel transition system to encapsulate anticancer drugs into the gel scaffold. The Au-Ag NR based nanogels can also be readily functionalized with targeting moieties, such as aptamers, for specific recognition of tumor cells. When exposed to NIR irradiation, the photothermal effect of the Au-Ag NRs leads to a rapid rise in the temperature of the surrounding gel, resulting in the fast release of the encapsulated payload with high controllability. In vitro study confirmed that aptamer functionalized nanogels can be used as drug carriers feasible for targeted drug delivery with remote control capability by NIR light with high spatial/temporal resolution.

Complex cell behaviors are usually triggered by multivalent ligands that first bind to membrane receptors and then promote receptor clustering, thus altering intracellular signal transduction. While it is possible to produce such altered signal transduction by synthetic means, the development of chemically defined multivalent ligands of effectors is sometimes difficult and tedious. Specifically, the average spacing between two binding sites within an antibody and the average distance between receptors on the cell membrane are usually larger than most organic molecules. In this study, we directly address these challenges by demonstrating how gold nanoparticles (AuNPs) of precisely controlled mean diameters can be easily synthesized and surface-modified with dinitrophenyl (DNP) at an equally well-controlled ligand density, or spacing. We found that both nanoparticle size and surface ligand density play key regulatory roles in the process of membrane antibody-receptor (IgEFcεRI) binding and cross-linking, which, in turn, leads to degranulation and consequent release of chemical mediators on rat basophilic leukemia cells. In addition, by adjusting DNP-AuNP architecture we discovered that our conjugates could either promote or inhibit cellular activation.Thus, these results demonstrate that nanoparticles not only serve as simple platforms for multivalent binding, but also as mediators for key biological functions. As such, the findings we report here may provide insight into the use of nanoparticles as a comprehensive tool for use in detailed receptor/ ligand interaction studies and in the design of nanoscale delivery and therapeutic systems.

Poor sensitivity and low specificity of current molecular imaging probes limit their application in clinical settings. To address these challenges, we used a process known as cell‐SELEX to develop unique molecular probes termed aptamers with the high binding affinity, sensitivity, and specificity needed for in vivo molecular imaging inside living animals. Importantly, aptamers can be selected by cell‐SELEX to recognize target cells, or even surface membrane proteins, without requiring prior molecular signature information. As a result, we are able to present the first report of aptamers molecularly engineered with signaling molecules and optimized for the fluorescence imaging of specific tumor cells inside a mouse. Using a Cy5‐labeled aptamer TD05 (Cy5‐TD05) as the probe, the in vivo efficacy of aptamer‐based molecular imaging in Ramos (B‐cell lymphoma) xenograft nude mice was tested. After intravenous injection of Cy5‐TD05 into mice bearing grafted tumors, noninvasive, whole‐body fluorescence imaging then allowed the spatial and temporal distribution to be directly monitored. Our results demonstrate that the aptamers could effectively recognize tumors with high sensitivity and specificity, thus establishing the efficacy of these fluorescent aptamers for diagnostic applications and in vivo studies requiring real‐time molecular imaging.

The Drosophila cerebrum originates from about 100 neuroblasts per hemisphere, with each neuroblast producing a characteristic set of neurons. Neurons from a neuroblast are often so diverse that many neuron types remain unexplored. We developed new genetic tools that target neuroblasts and their diverse descendants, increasing our ability to study fly brain structure and development. Common enhancer-based drivers label neurons on the basis of terminal identities rather than origins, which provides limited labeling in the heterogeneous neuronal lineages. We successfully converted conventional drivers that are temporarily expressed in neuroblasts, into drivers expressed in all subsequent neuroblast progeny. One technique involves immortalizing GAL4 expression in neuroblasts and their descendants. Another depends on loss of the GAL4 repressor, GAL80, from neuroblasts during early neurogenesis. Furthermore, we expanded the diversity of MARCM-based reagents and established another site-specific mitotic recombination system. Our transgenic tools can be combined to map individual neurons in specific lineages of various genotypes.

As a newly-identified protein post-translational modification, malonylation is involved in a variety of biological functions. Recognizing malonylation sites in substrates represents an initial but crucial step in elucidating the molecular mechanisms underlying protein malonylation. In this study, we constructed a deep learning (DL) network classifier based on long short-term memory (LSTM) with word embedding (LSTMWE) for the prediction of mammalian malonylation sites. LSTMWE performs better than traditional classifiers developed with common pre-defined feature encodings or a DL classifier based on LSTM with a one-hot vector. The performance of LSTMWE is sensitive to the size of the training set, but this limitation can be overcome by integration with a traditional machine learning (ML) classifier. Accordingly, an integrated approach called LEMP was developed, which includes LSTMWE and the random forest classifier with a novel encoding of enhanced amino acid content. LEMP performs not only better than the individual classifiers but also superior to the currently-available malonylation predictors. Additionally, it demonstrates a promising performance with a low false positive rate, which is highly useful in the prediction application. Overall, LEMP is a useful tool for easily identifying malonylation sites with high confidence. LEMP is available at http://www.bioinfogo.org/lemp.

N6-methyladenosine (m6A) is a prevalent RNA methylation modification involved in several biological processes. Hundreds or thousands of m6A sites identified from different species using high-throughput experiments provides a rich resource to construct in-silico approaches for identifying m6A sites. The existing m6A predictors are developed using conventional machine-learning (ML) algorithms and most are species-centric. In this paper, we develop a novel cross-species deep-learning classifier based on bidirectional Gated Recurrent Unit (BGRU) for the prediction of m6A sites. In comparison with conventional ML approaches, BGRU achieves outstanding performance for the Mammalia dataset that contains over fifty thousand m6A sites but inferior for the Saccharomyces cerevisiae dataset that covers around a thousand positives. The accuracy of BGRU is sensitive to the data size and the sensitivity is compensated by the integration of a random forest classifier with a novel encoding of enhanced nucleic acid content. The integrated approach dubbed as BGRU-based Ensemble RNA Methylation site Predictor (BERMP) has competitive performance in both cross-validation test and independent test. BERMP also outperforms existing m6A predictors for different species. Therefore, BERMP is a novel multi-species tool for identifying m6A sites with high confidence. This classifier is freely available at http://www.bioinfogo.org/bermp.

In this paper, we describe an easy procedure for the preparation of differently shaped and sized Au–Ag nanocomposites from gold nanorod (AuNR) seeds in various amino acid solutions—arginine (Arg), cysteine (Cys), glycine (Gly), glutamate (Glu), glutamine (Gln), histidine (His), lysine (Lys), and methionine (Met), respectively—at values of pH ranging from 8.0 to 11.5. Our results suggest that the pH, the nature of the amino acid, and its concentration all have significant impact on the preparation of Au–Ag nanocomposites; these factors exhibit their effects mainly through control over the reducing ability of ascorbate and/or its recognition capability, as well as through control over the surface charges of the amino acids on the AuNRs. Depending on the value of pH, we were able to prepare I-shaped, dumbbell-shaped, and/or sphere-shaped Au–Ag nanocomposites in 0.1 M solutions of Arg, Gly, Glu, Gln, Lys, and Met. In His solutions at pH 8.0 and 9.0, we obtained peanut-shaped Au–Ag nanocomposites. Corn-shaped Au–Ag nanocomposites were prepared in 0.1 M Met solutions (pH 9.0 and 10.0). By controlling the Lys concentration at pH 10.0, we synthesized pearl-necklace-shaped Au–Ag nanoparticles and Au–Ag wires. Based on the TEM images, we conclude that this simple and reproducible synthetic approach allows preparation of high-quality (>87%, beside>77% in His solutions) Au–Ag nanocomposites with various shapes and sizes under different conditions.