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.     

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.     

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.     

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.     

Abnormal Pelage Color in an Isolated Population of <Emphasis Type="Italic">Alouatta guariba clamitans</Emphasis> Cabrera, 1940 in South Brazil

We located 4 brown howlers (1 adult male, 2 adult females, and 1 juvenile male) showing abnormally lighter pelage in 3 social groups comprising 5, 6, and 9 individuals in a 20 ha-forest fragment in the State of Rio Grande do Sul, Brazil. Two additional groups composed only of normally colored individuals also live in the fragment, which is isolated from nearby fragments by 267–1009 m. They were the only brown howlers with abnormal pelage color out of a total of 386 individuals belonging to 67 groups in 21 fragments in the 5876-ha study area. The isolation of the forest fragment, its high howler density (2.2 individuals⁄ha), and large group size (8.8 ± 2.4 individuals) may decrease the likelihood of successful immigration into the population, leading to an increased probability of inbreeding that may facilitate the expression of rare alleles.     

Activity dynamics and propagation of synchronous spiking in locally connected random networks

Random network models have been a popular tool for investigating cortical network dynamics. On the scale of roughly a cubic millimeter of cortex, containing about 100,000 neurons, cortical anatomy suggests a more realistic architecture. In this locally connected random network, the connection probability decreases in a Gaussian fashion with the distance between neurons. Here we present three main results from a simulation study of the activity dynamics in such networks. First, for a broad range of parameters these dynamics exhibit a stationary state of asynchronous network activity with irregular single-neuron spiking. This state can be used as a realistic model of ongoing network activity. Parametric dependence of this state and the nature of the network dynamics in other regimes are described. Second, a synchronous excitatory stimulus to a fraction of the neurons results in a strong activity response that easily dominates the network dynamics. And third, due to that activity response an embedding of a divergent-convergent feed-forward subnetwork (as in synfire chains) does not naturally lead to a stable propagation of synchronous activity in the subnetwork; this is in contrast to our earlier findings in isolated subnetworks of that type. Possible mechanisms for stabilizing the interplay of volleys of synchronous spikes and network dynamics by specific learning rules or generalizations of the subnetworks are discussed.