Landscape genetics of a tropical rescue pollinator

Pollination services are increasingly threatened by the loss and modification of natural habitats, posing a risk to the maintenance of both native plant biodiversity and agricultural production. In order to safeguard pollination services, it is essential to examine the impacts of habitat degradation on the population dynamics of key pollinators and identify potential “rescue pollinators” capable of persisting in these human-altered landscapes. Using a landscape genetic approach, we assessed the impact of landscape structure on genetic differentiation in the widely-distributed tropical stingless bee Trigona spinipes (Apidae: Meliponini) across agricultural landscape mosaics composed of coffee plantations and Atlantic forest fragments in southeastern Brazil. We genotyped 115 bees at 16 specific and highly polymorphic microsatellite loci, developed using next-generation sequencing. Our results reveal that T. spinipes is capable of dispersing across remarkably long distances, as we did not find genetic differentiation across a 200 km range, nor fine-scale spatial genetic structure. Furthermore, gene flow was not affected by forest cover, land cover, or elevation, indicating that reproductive individuals are able to disperse well through agricultural landscapes and across altitudinal gradients. We also found evidence of a recent population expansion, suggesting that this opportunistic stingless bee is capable of colonizing degraded habitats. Our results thus suggest that T. spinipes can persist in heavily-altered landscapes and can be regarded as a rescue pollinator, potentially compensating for the decline of other native pollinators in degraded tropical landscapes.     

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.     

Immune suppression in the tumor microenvironment: a role for dendritic cell-mediated tolerization of T cells

Immune suppression remains a consistent obstacle to successful anti-tumor immune responses. As tumors develop, they create a microenvironment that not only supports tumor growth and metastasis but also reduces potential adaptive immunity to tumor antigens. Among the many components of this tumor microenvironment is a population of dendritic cells which exert profound immune suppressive effects on T cells. In this review, we discuss our recent findings related to these tumor-associated dendritic cells and how targeting them may serve to generate more durable anti-tumor immune responses.     

Screening of binding proteins that interact with human Salvador 1 in a human fetal liver cDNA library by the yeast two-hybrid system

Salvador promotes both cell cycle exit and apoptosis through the modulation of both cyclin E and Drosophila inhibitor of apoptosis protein in Drosophila. However, the cellular function of human Salvador (hSav1) is rarely reported. To screen for novel binding proteins that interact with hSav1, the cDNA of hSav1 was cloned into a bait protein plasmid, and positive clones were screened from a human fetal liver cDNA library by the yeast two-hybrid system. hSav1 mRNA was expressed in yeast and there was no self-activation and toxicity in the yeast strain AH109. Twenty proteins were found to interact with hSav1, including HS1 (haematopoietic cell specific protein1)-associated protein X-1 (HAX-1); neural precursor cell expressed, developmentally down-regulated 9, pyruvate kinase, liver and RBC, cytochrome c oxidase subunit Vb, enoyl coenzyme A hydratase short chain 1, and NADH dehydrogenase (ubiquinone) 1 beta subcomplex, demonstrating that the yeast two-hybrid system is an efficient method for investigating protein interactions. Among the identified proteins, there were many mitochondrial proteins, indicating that hSav1 may play a role in mitochondrial function. We also confirmed the interaction of HAX-1 and hSav1 in mammalian cells. This investigation provides functional clues for further exploration of potential apoptosis-related proteins in disease biotherapy.     

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.     

Theoretical Insights into Catalytic Mechanism of Protein Arginine Methyltransferase 1

Protein arginine methyltransferase 1 (PRMT1), the major arginine asymmetric dimethylation enzyme in mammals, is emerging as a potential drug target for cancer and cardiovascular disease. Understanding the catalytic mechanism of PRMT1 will facilitate inhibitor design. However, detailed mechanisms of the methyl transfer process and substrate deprotonation of PRMT1 remain unclear. In this study, we present a theoretical study on PRMT1 catalyzed arginine dimethylation by employing molecular dynamics (MD) simulation and quantum mechanics/molecular mechanics (QM/MM) calculation. Ternary complex models, composed of PRMT1, peptide substrate, and S-adenosyl-methionine (AdoMet) as cofactor, were constructed and verified by 30-ns MD simulation. The snapshots selected from the MD trajectory were applied for the QM/MM calculation. The typical S_N2-favored transition states of the first and second methyl transfers were identified from the potential energy profile. Deprotonation of substrate arginine occurs immediately after methyl transfer, and the carboxylate group of E144 acts as proton acceptor. Furthermore, natural bond orbital analysis and electrostatic potential calculation showed that E144 facilitates the charge redistribution during the reaction and reduces the energy barrier. In this study, we propose the detailed mechanism of PRMT1-catalyzed asymmetric dimethylation, which increases insight on the small-molecule effectors design, and enables further investigations into the physiological function of this family.     

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.     

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.     

Comparing movement of four butterfly species in experimental grassland strips

In contrast to many studies on the habitat quality of road verges for butterflies in relation to management regimes, little is known about whether road verges also function as corridors linking fragmented grassland habitats. We experimentally compared movements of four model species, two small blues and two medium browns, with one habitat specialist and one habitat generalist in each size and phylogenetic category. A total of 425 individual butterflies were caught and translocated to an experimental arena with three 2 × 30 m grassland strips that approximated road verges; one with adult feeding resources, one sheltered from the wind, and one without food and shelter. Movements in grassland strips were compared to movements in continuous grassland habitat. Results indicated that (1) individuals did not use the low-quality strip, (2) only specialists used strips but not in the same way according to their size and phylogenic category, and (3) strip use could not be predicted from habitat selection. This finding supports the idea that corridors of intermediate quality are the most efficient to promote dispersal rates in fragmented landscapes. Road verges cover 250,000 ha in Sweden, which is nearly the total amount of seminatural grasslands. Our results suggest that, to benefit butterfly dispersal among grassland patches, road verges should be managed to create a more favourable microclimate (e.g. sheltered from wind, high temperatures).