A practical guide to DNA metabarcoding for entomological ecologists

1. DNA metabarcoding is a cost-effective species identification approach with great potential to assist entomological ecologists. This review presents a practical guide to help entomological ecologists design their own DNA metabarcoding studies and ensure that sound ecological conclusions can be obtained. 2. The review considers approaches to field sampling, laboratory work, and bioinformatic analyses, with the aim of providing the background knowledge needed to make decisions at each step of a DNA metabarcoding workflow. 3. Although most conventional sampling methods can be adapted to DNA metabarcoding, this review highlights techniques that will ensure suitable DNA preservation during field sampling and laboratory storage. The review also calls for a greater understanding of the occurrence, transportation, and deposition of environmental DNA when applying DNA metabarcoding approaches for different ecosystems. 4. Accurate species detection with DNA metabarcoding needs to consider biases introduced during DNA extraction and PCR amplification, cross-contamination resulting from inappropriate amplicon library preparation, and downstream bioinformatic analyses. Quantifying species abundance with DNA metabarcoding is in its infancy, yet recent studies demonstrate promise for estimating relative species abundance from DNA sequencing reads. 5. Given that bioinformatics is one of the biggest hurdles for researchers new to DNA metabarcoding, several useful graphical user interface programs are recommended for sequence data processing, and the application of emerging sequencing technologies is discussed.     

Discovery of selective farnesoid X receptor agonists for the treatment of hyperlipidemia from traditional Chinese medicine based on virtual screening and in vitro validation

Abstract

Farnesoid X receptor (FXR), a bile acid receptor, has important roles in maintaining bile acid and cholesterol homeostasis, which is an attractive target for hyperlipidemia. Present study aimed to discover potential selective FXR agonists over G-protein coupled bile acid receptor 1 (GPBAR1, TGR5) from traditional Chinese medicine (TCM) by using virtual screening, in vitro studies and molecular dynamics simulation (MD). Ligand-based pharmacophore model for FXR was firstly built to screen FXR agonists from the Traditional Chinese Medicine Database (TCMD). Then, 21 FXR crystal structures were clustered in two types and two representative structures (PDB ID: 3OMM and 3P89) were, respectively, used to carry out molecular docking to refine the screened result. Moreover, the pharmacophore model for GPBAR1 was built to screen selective FXR agonists with no activity on GPBAR1. A set of 24 candidate selective FXR agonists which fitvalue of FXR pharmacophore model and docking score of 3OMM and 3P89 were in the top 100 and cannot match the pharmacophore model for GPBAR1 were obtained. By the lipid-lowering activity test in HepG2 cell lines, Arctigenin was identified to be potential selective FXR agonist with the activity of 20?μmol·L^?1. After down-regulating FXR, Arctigenin could increase the mRNA of FXR while exerted no effect on the mRNA of GPBAR1. MD was further used to interpret the mechanism of Arctigenin with the representative structures. This research provided a new screening procedure for finding selective candidate compounds and appropriate docking models of a target by considering the structure diversity of PDB structures, which was applied to discovery novel selective FXR agonists to treat hyperlipidemia.

Communicated by Ramaswamy H. Sarma     

In silico identification of novel lncRNAs with a potential role in diagnosis of gastric cancer

Abstract

Gastric cancer (GC) is the second leading cause of cancer-related deaths in the world. Due to the shortage of adequate symptoms in the early stages, it is diagnosed when the tumor has spread to distant organs. Early recognition of GC enhances the chance of successful treatment. Molecular mechanisms of GC are still poorly understood. LncRNAs are emerging as new players in cancer in both oncogene and tumor suppressor roles. High-throughput technologies such as RNA-Seq, have revealed thousands of lncRNAs which are dysregulated in GC. In this study, we retrieved lncRNAs obtained by High-throughput technologies from OncoLnc database. Consequently, retrieved lncRNAs were compared in literature-based databases including PubMed. As a result, two lists, including experimentally validated lncRNAs and predicted lncRNAs were provided. We found 43 predicted lncRNAs that had not been experimentally validated in GC, so far. Further Bioinformatics analyses were performed to obtain the expression profile of predicted lncRNAs in tumor and normal tissues. Also, the roles and targets of predicted lncRNAs in GC were identified by related databases. Finally, using the GEPIA database was reviewed the significant relationship of predicted lncRNAs with the survival of GC patients. By recognizing the lncRNAs involved in initiation and progression of GC, they may be considered as potential biomarkers in the GC early diagnosis or targeted treatment and lead to novel therapeutic strategies.

Communicated by Ramaswamy H. Sarma     

Detection and destruction of HER2-positive cancer cells by Ultra Quenchbody-siRNA complex

Ultra Quenchbody (UQ-body) is a biosensor that utilizes the quenching behavior of the fluorescent dye linked to the antibody V region. When the corresponding antigen is bound to the UQ-body, the fluorescence is restored and allows the detection of target molecules easily and sensitively. In this paper, we constructed UQ-bodies to sensitively detect the human epidermal growth factor receptor 2 (HER2) cancer marker in solution or on cancer cells, which was further used to kill the cancer cells. A synthetic Fab fragment of anti-HER2 antibody Fab37 with many Trp residues at hypervariable region was prepared and labeled with fluorescent dyes to obtain the UQ-bodies. The UQ-body could detect HER2 in solution at concentrations as low as 20 pM with an EC₅₀ of 0.3 nM with a fourfold response. Fluorescence imaging of HER2-positive cells was successfully performed without any washing steps. To deliver small interfering RNA (siRNA) to cancer cells, a modified UQ-body with C-terminal 9R sequence was also prepared. HER2-positive cancer cells were effectively killed by polo-like kinase 1 siRNA intracellularly delivered by the UQ-body-9R. The novel approach employing siRNA-empowered UQ-body could detect and image the HER2 antigen easily and sensitively, and effectively kill the HER2-positive cancer cells.     

Downscaling screening cultures in a multifunctional bioreactor array-on-a-chip for speeding up optimization of yeast-based lactic acid bioproduction

A key challenge for bioprocess engineering is the identification of the optimum process conditions for the production of biochemical and biopharmaceutical compounds using prokaryotic as well as eukaryotic cell factories. Shake flasks and bench-scale bioreactor systems are still the golden standard in the early stage of bioprocess development, though they are known to be expensive, time-consuming, and labor-intensive as well as lacking the throughput for efficient production optimizations. To bridge the technological gap between bioprocess optimization and upscaling, we have developed a microfluidic bioreactor array to reduce time and costs, and to increase throughput compared with traditional lab-scale culture strategies. We present a multifunctional microfluidic device containing 12 individual bioreactors (V_t = 15 µl) in a 26 mm × 76 mm area with in-line biosensing of dissolved oxygen and biomass concentration. Following initial device characterization, the bioreactor lab-on-a-chip was used in a proof-of-principle study to identify the most productive cell line for lactic acid production out of two engineered yeast strains, evaluating whether it could reduce the time needed for collecting meaningful data compared with shake flasks cultures. Results of the study showed significant difference in the strains' productivity within 3 hr of operation exhibiting a 4- to 6-fold higher lactic acid production, thus pointing at the potential of microfluidic technology as effective screening tool for fast and parallelizable industrial bioprocess development.     

A mass spectrometry-based high-throughput screening method for engineering fatty acid synthases with improved production of medium-chain fatty acids

Microbial cell factories have been extensively engineered to produce free fatty acids (FFAs) as key components of crucial nutrients, soaps, industrial chemicals, and fuels. However, our ability to control the composition of microbially synthesized FFAs is still limited, particularly, for producing medium-chain fatty acids (MCFAs). This is mainly due to the lack of high-throughput approaches for FFA analysis to engineer enzymes with desirable product specificity. Here we report a mass spectrometry (MS)-based method for rapid profiling of MCFAs in Saccharomyces cerevisiae by using membrane lipids as a proxy. In particular, matrix-assisted laser desorption/ionization time-of-flight (MALDI-ToF) MS was used to detect shorter acyl chain phosphatidylcholines from membrane lipids and a higher m/z peak ratio at 730 and 758 was used as an indication for improved MCFA production. This colony-based method can be performed at a rate of ~2 s per sample, representing a substantial improvement over gas chromatography-MS (typically >30 min per sample) as the gold standard method for FFA detection. To demonstrate the power of this method, we performed site-saturation mutagenesis of the yeast fatty acid synthase and identified nine missense mutations that resulted in improved MCFA production relative to the wild-type strain. Colony-based MALDI-ToF MS screening provides an effective approach for engineering microbial fatty acid compositions in a high-throughput manner.     

Efficient secretory production of large-size heterologous enzymes in Bacillus subtilis: A secretory partner and directed evolution

Secretory production of recombinant proteins provides a simple approach to the production and purification of target proteins in the enzyme industry. We developed a combined strategy for the secretory production of three large-size heterologous enzymes with a special focus on 83-kDa isoamylase (IA) from an archaeon Sulfolobus tokodaii in a bacterium Bacillus subtilis. First, a secretory protein of the B. subtilis family 5 glycoside hydrolase endoglucanase (Cel5) was used as a fusion partner, along with the NprB signal peptide, to facilitate secretory production of IA. This secretory partner strategy was effective for the secretion of two other large enzymes: family 9 glycoside hydrolase from Clostridium phytofermentas and cellodextrin phosphorylase from Clostridium thermocellum. Second, the secretion of Cel5-IA was improved by directed evolution with two novel double-layer Petri-dish-based high-throughput screening (HTS) methods. The high-sensitivity HTS relied on the detection of high-activity Cel5 on the carboxymethylcellulose/Congo-red assay. The second modest-sensitivity HTS focused on the detection of low-activity IA on the amylodextrin-I₂ assay. After six rounds of HTS, a secretory Cel5-IA level was increased to 234 mg/L, 155 times the wild-type IA with the NprB signal peptide only. This combinatory strategy could be useful to enhance the secretory production of large-size heterologous proteins in B. subtilis.     

Rapid screenhouse assessment of bacterial blight in cassava genotypes in Nigeria

Bacterial blight disease caused by Xanthomonas axonopodis pv. manihotis (Berthet-Bondar) Dye was assessed in 11 artificially inoculated cassava genotypes in a screenhouse. Disease progress was estimated at intervals of 3 days by measuring the length of necrotic lesions on stems and leaves, as well as estimating the average disease score and area under disease progress curve (AUDPC). Based on the average disease scores, cassava genotypes 30572, TME 1, TME 7 and TME 9 were classified as resistant to bacterial blight, genotypes 4(2)1425, TME 2, TME 4 and TME 12 were tolerant while cassava genotypes 30001, TME 3, and TME 28 were susceptible. Direct correlations, statistically significant at p < 0.05, were obtained between stem necrosis, leaf necrosis, average disease scores and AUDPC in the 11 cassava genotypes. Screenhouse experiments afford rapid assessment of resistance status of cassava genotypes to bacterial blight in Nigeria.     

Biochemical markers as a useful tool for the early identification of Fusarium oxysporum f.sp. cubense,race 1 resistance banana clones

Abstract

Panama disease of banana (Musa spp) caused by the fungus Fusarium oxysporum f. sp. Cubense (FOC), is a serious constraint both to the commercial production of banana and cultivation for subsistence agriculture. Chemical control is not economically effective and is also hazardous to the environment and human health. Breeding for disease resistance is an alternative strategy, which leads to the development of resistance clones. Field evaluation is the most reliable method of screening for disease resistance, but it is demanding in terms of cost, manpower and space requirements. Another approach of screening hybrids at the sucker's stage (planting material) through biochemical markers has been found to be effective in early identification of resistant hybrids. The resistance mechanisms involving the role of phenol, PAL, oxidative enzymes like peroxidase (PO), polyphenol oxidase (PPO), superoxide dismutase (SOD), catalase and PR-proteins like chitinase, β-1-3 glucanase were studied and they showed relatively higher activity in resistant hybrids than susceptible hybrids. Isozyme analysis of peroxidase (PO) and polyphenol oxidase (PPO) was also carried out in cultivars and hybrids, which revealed the induction of specific isoforms in the resistant hybrids upon challenge inoculation. This could be a useful tool for early identification of F. oxysporum f. sp. cubense resistance banana clones.