Echolocation, olfaction and fruit display: how bats find fruit of flagellichorous cucurbits

1. The relationship between plant morphology and the senses used by dispersal agents to find fruit was examined. 'Flagellichory' (fruit borne on pendulous structures), a costly morphology associated with dispersal by bats, is focused on.
2. Using Gurania spinulosa , a flagellichorous vine, and its major dispersal agent, Phyllostomus hastatus , the hypothesis was tested that flagellichory increases the conspicuousness of fruit to bats that use echolocation to find fruit.
3. The responses of wild-caught P. hastatus to various fruiting branch morphologies and fruit odour were recorded. Phyllostomus hastatus used echolocation rather than olfaction to detect fruit, and consistently chose fruit displayed on pendulous leafless branches, ignoring fruit held among leaves on horizontal branches.
4. By comparing echolocation signals with the distance between fruiting branches of G. spinulosa and surrounding vegetation, it was shown that pendulous fruiting branches present clear, clutter-free targets that can be detected by echolocating bats. This is the first demonstration of neotropical frugivorous bats using echolocation to find fruit.     

Cathepsin L expression is directed to secretory vesicles for enkephalin neuropeptide biosynthesis and secretion

Proteases within secretory vesicles are required for conversion of neuropeptide precursors into active peptide neurotransmitters and hormones. This study demonstrates the novel cellular role of the cysteine protease cathepsin L for producing the (Met)enkephalin peptide neurotransmitter from proenkephalin (PE) in the regulated secretory pathway of neuroendocrine PC12 cells. These findings were achieved by coexpression of PE and cathepsin L cDNAs in PC12 cells with analyses of PE-derived peptide products. Expression of cathepsin L resulted in highly increased cellular levels of (Met)enkephalin, resulting from the conversion of PE to enkephalin-containing intermediates of 23, 18-19, 8-9, and 4.5 kDa that were similar to those present in vivo. Furthermore, expression of cathepsin L with PE resulted in increased amounts of nicotine-induced secretion of (Met)enkephalin. These results indicate increased levels of (Met)enkephalin within secretory vesicles of the regulated secretory pathway. Importantly, cathespin L expression was directed to secretory vesicles, demonstrated by colocalization of cathepsin L-DsRed fusion protein with enkephalin and chromogranin A neuropeptides that are present in secretory vesicles. In vivo studies also showed that cathepsin L in vivo was colocalized with enkephalin. The newly defined secretory vesicle function of cathepsin L for biosynthesis of active enkephalin opioid peptide contrasts with its function in lysosomes for protein degradation. These findings demonstrate cathepsin L as a distinct cysteine protease pathway for producing the enkephalin member of neuropeptides.     

Quantifying the effects of switchgrass (Panicum virgatum) on deep organic C stocks using natural abundance 14C in three marginal soils

Perennial bioenergy crops have been shown to increase soil organic carbon (SOC) stocks, potentially offsetting anthropogenic C emissions. The effects of perennial bioenergy crops on SOC are typically assessed at shallow depths (<30 cm), but the deep root systems of these crops may also have substantial effects on SOC stocks at greater depths. We hypothesized that deep (>30 cm) SOC stocks would be greater under bioenergy crops relative to stocks under shallow‐rooted conventional crop cover. To test this, we sampled soils to between 1‐ and 3‐m depth at three sites in Oklahoma with 10‐ to 20‐year‐old switchgrass (Panicum virgatum) stands, and collected paired samples from nearby fields cultivated with shallow rooted annual crops. We measured root biomass, total organic C, ¹⁴C, ¹³C, and other soil properties in three replicate soil cores in each field and used a mixing model to estimate the proportion of recently fixed C under switchgrass based on ¹⁴C. The subsoil C stock under switchgrass (defined over 500–1500 kg/m² equivalent soil mass, approximately 30–100 cm depth) exceeded the subsoil stock in neighboring fields by 1.5 kg C/m² at a sandy loam site, 0.6 kg C/m² at a site with loam soils, and showed no significant difference at a third site with clay soils. Using the mixing model, we estimated that additional SOC introduced after switchgrass cultivation comprised 31% of the subsoil C stock at the sandy loam site, 22% at the loam site, and 0% at the clay site. These results suggest that switchgrass can contribute significantly to subsoil organic C—but also indicated that this effect varies across sites. Our analysis shows that agricultural strategies that emphasize deep‐rooted grass cultivars can increase soil C relative to conventional crops while expanding energy biomass production on marginal lands.     

Profile-based string kernels for remote homology detection and motif extraction

We introduce novel profile-based string kernels for use with support vector machines (SVMs) for the problems of protein classification and remote homology detection. These kernels use probabilistic profiles, such as those produced by the PSI-BLAST algorithm, to define position-dependent mutation neighborhoods along protein sequences for inexact matching of k-length subsequences ("k-mers") in the data. By use of an efficient data structure, the kernels are fast to compute once the profiles have been obtained. For example, the time needed to run PSI-BLAST in order to build the profiles is significantly longer than both the kernel computation time and the SVM training time. We present remote homology detection experiments based on the SCOP database where we show that profile-based string kernels used with SVM classifiers strongly outperform all recently presented supervised SVM methods. We further examine how to incorporate predicted secondary structure information into the profile kernel to obtain a small but significant performance improvement. We also show how we can use the learned SVM classifier to extract "discriminative sequence motifs"--short regions of the original profile that contribute almost all the weight of the SVM classification score--and show that these discriminative motifs correspond to meaningful structural features in the protein data. The use of PSI-BLAST profiles can be seen as a semi-supervised learning technique, since PSI-BLAST leverages unlabeled data from a large sequence database to build more informative profiles. Recently presented "cluster kernels" give general semi-supervised methods for improving SVM protein classification performance. We show that our profile kernel results also outperform cluster kernels while providing much better scalability to large datasets.     

Structure and architecture of the maize genome

Maize (Zea mays or corn) plays many varied and important roles in society. It is not only an important experimental model plant, but also a major livestock feed crop and a significant source of industrial products such as sweeteners and ethanol. In this study we report the systematic analysis of contiguous sequences of the maize genome. We selected 100 random regions averaging 144 kb in size, representing about 0.6% of the genome, and generated a high-quality dataset for sequence analysis. This sampling contains 330 annotated genes, 91% of which are supported by expressed sequence tag data from maize and other cereal species. Genes averaged 4 kb in size with five exons, although the largest was over 59 kb with 31 exons. Gene density varied over a wide range from 0.5 to 10.7 genes per 100 kb and genes did not appear to cluster significantly. The total repetitive element content we observed (66%) was slightly higher than previous whole-genome estimates (58%-63%) and consisted almost exclusively of retroelements. The vast majority of genes can be aligned to at least one sequence read derived from gene-enrichment procedures, but only about 30% are fully covered. Our results indicate that much of the increase in genome size of maize relative to rice (Oryza sativa) and Arabidopsis (Arabidopsis thaliana) is attributable to an increase in number of both repetitive elements and genes.     

In toto differentiation of human amniotic membrane towards the Schwann cell lineage

Human amniotic membrane (hAM) is a tissue containing cells with proven stem cell properties. In its decellularized form it has been successfully applied as nerve conduit biomaterial to improve peripheral nerve regeneration in injury models. We hypothesize that viable hAM without prior cell isolation can be differentiated towards the Schwann cell lineage to generate a possible alternative to commonly applied tissue engineering materials for nerve regeneration. For in vitro Schwann cell differentiation, biopsies of hAM of 8 mm diameter were incubated with a sequential order of neuronal induction and growth factors for 21 days and characterized for cellular viability and the typical glial markers glial fibrillary acidic protein (GFAP), S100β, p75 and neurotrophic tyrosine kinase receptor (NTRK) using immunohistology. The secretion of the neurotrophic factors brain-derived neurotrophic factor (BDNF) and glial cell-derived neurotrophic factor (GDNF) was quantified by ELISA. The hAM maintained high viability, especially under differentiation conditions (90.2 % ± 41.6 day 14; 80.0 % ± 44.5 day 21 compared to day 0). Both, BDNF and GDNF secretion was up-regulated upon differentiation. The fresh membrane stained positive for GFAP and p75 and NTRK, which was strongly increased after culture in differentiation conditions. Especially the epithelial layer within the membrane exhibited a change in morphology upon differentiation forming a multi-layered epithelium with intense accumulations of the marker proteins. However, S100β was expressed at equal levels and equal distribution in fresh and cultured hAM conditions. Viable hAM may be a promising alternative to present formulations used for peripheral nerve regeneration.