Strategic mining of cyanobacterial patents from the USPTO patent database and analysis of their scope and implications

Patent analysis with the help of the strategic mining of patents from databases is important and useful within the framework of application-oriented research and its commercialization. In the analysis reported here, we have mined cyanobacterial patents from the patent database of the United States Patent and Trademark Office (USPTO). In order to make an assessment of the commercial potentials of cyanobacteria, we conducted the patent search (from 1976 to April 2006) using certain generic terms and the 84 genera of cyanobacteria as keywords. The search was performed in two major ways – searching the abstracts and claims of the patents cumulatively and searching the entire patent documents by the mode of ‘all fields’ in USPTO. In the abstract- and claims-based search, 234 patents were obtained after the removal of overlapping patents among the keywords. An additional 31 patents were added following the ‘all fields’ search; these patents were not covered in the search that was based on abstracts and claims. The entire package of 265 patents, of which 244 were related to cyanobacteria, was then analyzed. Information derived from these patents identified five major areas of cyanobacterial utilization. Cyanobacteria have been patented as a source of a wide spectrum of products, for medical, agriculture and environmental applications, for gene-based products, for methods of cultivation and for methods of control. The chronological development in granting cyanobacterial patents was also traced. This study demonstrates that such strategic mining and analysis of patent data can be used as an index for future development.     

Secretory delivery of heterologous proteins in attenuated <Emphasis Type="Italic">Vibrio anguillarum</Emphasis> for potential use in vaccine design

To synthesize and secrete heterologous proteins in an attenuated Vibrio anguillarum strain for potential multivalent live vaccine development, different antigen-delivery systems based on bacterial-originated secretion signal peptides (SPs) were designed and identified in this work. Four SPs were derived from hemolysin of Escherichia coli, RTX protein of V. cholerae, hemolysin of V. anguillarum, zinc-metalloprotease of V. anguillarum, respectively, and their abilities to support secretion of green fluorescent protein (GFP) in an attenuated V. anguillarum strain MVAV6203 were assayed. Immunodetection of GFP showed that the capability of the tested signal leaders to direct secretion of GFP varied greatly. Although all the four signal peptide-fused GFPs could be expressed correctly and trapped intracellularly in recombinant strains, only the EmpA signal peptide could confer efficient secretion to GFP. For the investigation of its potential application in live bacteria carrier vaccines, a heterologous protein EseB of Edwardsiella tarda was fused to the SP(empA) antigen-delivery system and introduced into the strain MVAV6203. Further analysis of EseB demonstrated that the constructed SP(empA) antigen-delivery system could be used to secrete foreign protein in attenuated V. anguillarum and be available for carrier vaccines development.     

Engineering bacteria toward tumor targeting for cancer treatment: current state and perspectives

One of the primary limitations of cancer therapy is lack of selectivity of therapeutic agents to tumor cells. Current efforts are focused on discovering and developing anticancer agents that selectively target only tumor cells and spare normal cells to improve the therapeutic index. The use of preferentially replicating bacteria as an oncolytic agent is one of the innovative approaches for the treatment of cancer. This is based on the observation that some obligate or facultative anaerobic bacteria are capable of multiplying selectively in tumors and inhibiting their growth. Meanwhile, bacteria have been demonstrated to colonize and destroy tumor, and have emerged as biological gene vectors to tumor microenvironment. To improve the efficacy and safety of the bacterial therapy, a further understanding of bacteria between with immune system is required. Furthermore, we want to evaluate how bacterial infection facilitates the “bystander effect” of chemotherapeutic agent and assess if it can be used for additional antitumor effect when combined with chemotherapy. This study may not only evaluate therapeutic efficacy of bacteria for the treatment of cancer but also elucidate the mechanisms underlying antitumor activities mediated by bacteria, which involve host immune responses and the cellular molecular responses.     

Selenite and ebselen supplementation attenuates <Emphasis Type="SmallCaps">d</Emphasis>-galactose-induced oxidative stress and increases expression of SELR and SEP15 in rat lens

Selenite and ebselen supplementation has been shown to possess anti-cataract potential in some experimental animal models of cataract, however, the underlying mechanisms remain unclear. The present study was designed to evaluate the anti-cataract effects and the underlying mechanisms of selenite and ebselen supplementation on galactose induced cataract in rats, a common animal model of sugar cataract. Transmission electron microscopy images of lens fiber cells (LFC) and lens epithelial cells (LEC) were observed in d-galactose-induced experimental cataractous rats treated with or without selenite and ebselen, also redox homeostasis and expression of proteins such as selenoprotein R (SELR), 15kD selenoprotein (SEP15), superoxide dismutase 1 (SOD1), catalase (CAT), β-crystallin protein, aldose reductase (AR) and glucose-regulated protein 78 (GRP78) were estimated in the lenses. The results showed that d-galactose injection injured rat lens and resulted in cataract formation; however, selenite and ebselen supplementation markedly alleviated ultrastructural injury of LFC and LEC. Moreover, selenite and ebselen supplementation could mitigate the oxidative damage in rat lens and increase the protein expressions of SELR, SEP15, SOD1, CAT and β-crystallin, as well as decrease the protein expressions of AR and GRP78. Taken together, these findings for the first time reveal the anti-cataract potential of selenite and ebselen in galactosemic cataract, and provide important new insights into the anti-cataract mechanisms of selenite and ebselen in sugar cataract.     

Synthesis of β-Peptide Standards for Use in Model Prebiotic Reactions

A one-pot method was developed for the preparation of a series of β-alanine standards of moderate size (2 to ≥12 residues) for studies concerning the prebiotic origins of peptides. The one-pot synthesis involved two sequential reactions: (1) dry-down self-condensation of β-alanine methyl ester, yielding β-alanine peptide methyl ester oligomers, and (2) subsequent hydrolysis of β-alanine peptide methyl ester oligomers, producing a series of β-alanine peptide standards. These standards were then spiked into a model prebiotic product mixture to confirm by HPLC the formation of β-alanine peptides under plausible reaction conditions. The simplicity of this approach suggests it can be used to prepare a variety of β-peptide standards for investigating differences between α- and β-peptides in the context of prebiotic chemistry.     

Integrated Artificial Intelligence Approaches for Disease Diagnostics

Mechanocomputational techniques in conjunction with artificial intelligence (AI) are revolutionizing the interpretations of the crucial information from the medical data and converting it into optimized and organized information for diagnostics. It is possible due to valuable perfection in artificial intelligence, computer aided diagnostics, virtual assistant, robotic surgery, augmented reality and genome editing (based on AI) technologies. Such techniques are serving as the products for diagnosing emerging microbial or non microbial diseases. This article represents a combinatory approach of using such approaches and providing therapeutic solutions towards utilizing these techniques in disease diagnostics.     

Possible role of ionic gradients in the apical growth of <Emphasis Type="Italic">Neurospora crassa</Emphasis>

The effects of the Ca²⁺/H⁺ exchanger A23187 and the K⁺/H⁺ exchanger nigericin on the growth of Neurospora crassa were analyzed. Both ionophores had the same effects on the fungus. They both inhibited growth in liquid media, apical extension being more affected than protein synthesis. A sudden challenge to either ionophore on solid media rapidly stopped hyphal extension. Additionally, both ionophores induced profuse mycelium branching and upward hyphal growth. Hyphae growing on nigericin-containing media also burst at the apex. Both ionophores caused a rapid inhibition in the apically-occurring synthesis of structural wall polysaccharides, but they did not affect mitochondrial energy conservation. With the use of DiBAC, a membrane-potential sensitive fluorophore, it was excluded that their effects were due to depletion of the plasma membrane potential. Considering that both ionophores exchange H⁺ for different metallic ions, we concluded that their effect was due to dissipation of a proton gradient, which is directly or indirectly involved in the apical growth of the fungus. This revised version was published online in June 2006 with corrections to the Cover Date.     

Analysis of rhamnolipid biosurfactants by methylene blue complexation

Rhamnolipids, produced by Pseudomonas aeruginosa, represent an important group of biosurfactants having various industrial, environmental, and medical applications. Current methods for rhamnolipid quantification involve the use of strong hazardous acids/chemicals, indirect measurement of the concentration of sugar moiety, or require the availability of expensive equipment (HPLC-MS). A safer, easier method that measures the whole rhamnolipid molecules would significantly enhance strain selection, metabolic engineering, and process development for economical rhamnolipid production. A semi-quantitative method was reported earlier to differentiate between the rhamnolipid-producing and non-producing strains using agar plates containing methylene blue and cetyl trimethylammonium bromide (CTAB). In this study, a rapid and simple method for rhamnolipid analysis was developed by systematically investigating the complexation of rhamnolipids and methylene blue, with and without the presence of CTAB. The method relies on measuring the absorbance (at 638 nm) of the rhamnolipid−methylene blue complex that partitions into the chloroform phase. With P. aeruginosa fermentation samples, the applicability of this method was verified by comparison of the analysis results with those obtained from the commonly used anthrone reaction technique.     

Chromogranin A and the Tumor Microenvironment

Chromogranin A (CgA) is an acidic glycoprotein belonging to a family of regulated secretory proteins stored in the dense core granules of the adrenal medulla and of many other neuroendocrine cells and neurons. This protein is frequently used as a diagnostic and prognostic serum marker for a range of neuroendocrine tumors. Circulating CgA is also increased in patients with other diseases, including subpopulations of patients with non-neuroendocrine tumors, with important prognostic implications. A growing body of evidence suggests that CgA is more than a diagnostic/prognostic marker for cancer patients. Indeed, results of in vitro experiments and in vivo studies in animal models suggest that this protein and its fragments can affect several elements of the tumor microenvironment, including fibroblasts and endothelial cells. In this article, recent findings implicating CgA as a modulator of the tumor microenvironment and suggesting that abnormal secretion of CgA could play important roles in tumor progression and response to therapy in cancer patients are reviewed and discussed.     

Differential expression analysis for sequence count data

High-throughput sequencing assays such as RNA-Seq, ChIP-Seq or barcode counting provide quantitative readouts in the form of count data. To infer differential signal in such data correctly and with good statistical power, estimation of data variability throughout the dynamic range and a suitable error model are required. We propose a method based on the negative binomial distribution, with variance and mean linked by local regression and present an implementation, DESeq, as an R/Bioconductor package.