Hemocyanin facilitates lignocellulose digestion by wood-boring marine crustaceans

Woody (lignocellulosic) plant biomass is an abundant renewable feedstock, rich in polysaccharides that are bound into an insoluble fiber composite with lignin. Marine crustacean woodborers of the genus Limnoria are among the few animals that can survive on a diet of this recalcitrant material without relying on gut resident microbiota. Analysis of fecal pellets revealed that Limnoria targets hexose-containing polysaccharides (mainly cellulose, and also glucomannans), corresponding with the abundance of cellulases in their digestive system, but xylans and lignin are largely unconsumed. We show that the limnoriid respiratory protein, hemocyanin, is abundant in the hindgut where wood is digested, that incubation of wood with hemocyanin markedly enhances its digestibility by cellulases, and that it modifies lignin. We propose that this activity of hemocyanins is instrumental to the ability of Limnoria to feed on wood in the absence of gut symbionts. These findings may hold potential for innovations in lignocellulose biorefining

The PREDICTS database: a global database of how local terrestrial biodiversity responds to human impacts

Biodiversity continues to decline in the face of increasing anthropogenic pressures such as habitat destruction, exploitation, pollution and introduction of alien species. Existing global databases of species’ threat status or population time series are dominated by charismatic species. The collation of datasets with broad taxonomic and biogeographic extents, and that support computation of a range of biodiversity indicators, is necessary to enable better understanding of historical declines and to project – and avert – future declines. We describe and assess a new database of more than 1.6 million samples from 78 countries representing over 28,000 species, collated from existing spatial comparisons of local-scale biodiversity exposed to different intensities and types of anthropogenic pressures, from terrestrial sites around the world. The database contains measurements taken in 208 (of 814) ecoregions, 13 (of 14) biomes, 25 (of 35) biodiversity hotspots and 16 (of 17) megadiverse countries. The database contains more than 1% of the total number of all species described, and more than 1% of the described species within many taxonomic groups – including flowering plants, gymnosperms, birds, mammals, reptiles, amphibians, beetles, lepidopterans and hymenopterans. The dataset, which is still being added to, is therefore already considerably larger and more representative than those used by previous quantitative models of biodiversity trends and responses. The database is being assembled as part of the PREDICTS project (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems – www.predicts.org.uk). We make site-level summary data available alongside this article. The full database will be publicly available in 2015

Optimization of Multimodal Nanoparticles Internalization Process in Mesenchymal Stem Cells for Cell Therapy Studies

Considering there are several difficulties and limitations in labeling stem cells using multifunctional nanoparticles (MFNP), the purpose of this study was to determine the optimal conditions for labeling human bone marrow mesenchymal stem cells (hBM-MSC), aiming to monitor these cells in vivo. Thus, this study provides information on hBM-MSC direct labeling using multimodal nanoparticles in terms of concentration, magnetic field, and period of incubation while maintaining these cells’ viability and the homing ability for in vivo experiments. The cell labeling process was assessed using 10, 30, and 50 µg Fe/mL of MFNP, with periods of incubation ranging from 4 to 24 h, with or without a magnetic field, using optical microscopy, near-infrared fluorescence (NIRF), and inductively coupled plasma mass spectrometry (ICP-MS). After the determination of optimal labeling conditions, these cells were applied in vivo 24 h after stroke induction, intending to evaluate cell homing and improve NIRF signal detection. In the presence of a magnetic field and utilizing the maximal concentration of MFNP during cell labeling, the iron load assessed by NIRF and ICP-MS was four times higher than what was achieved before. In addition, considering cell viability higher than 98%, the recommended incubation time was 9 h, which corresponded to a 25.4 pg Fe/cell iron load (86% of the iron load internalized in 24 h). The optimization of cellular labeling for application in the in vivo study promoted an increase in the NIRF signal by 215% at 1 h and 201% at 7 h due to the use of a magnetized field during the cellular labeling process. In the case of BLI, the signal does not depend on cell labeling showing no significant differences between unlabeled or labeled cells (with or without a magnetic field). Therefore, the in vitro cellular optimized labeling process using magnetic fields resulted in a shorter period of incubation with efficient iron load internalization using higher MFNP concentration (50 μgFe/mL), leading to significant improvement in cell detection by NIRF technique without compromising cellular viability in the stroke model

Methods of Granulocyte Isolation from Human Blood and Labeling with Multimodal Superparamagnetic Iron Oxide Nanoparticles

This in vitro study aimed to find the best method of granulocyte isolation for subsequent labeling with multimodal nanoparticles (magnetic and fluorescent properties) to enable detection by optical and magnetic resonance imaging (MRI) techniques. The granulocytes were obtained from venous blood samples from 12 healthy volunteers. To achieve high purity and yield, four different methods of granulocyte isolation were evaluated. The isolated granulocytes were labeled with multimodal superparamagnetic iron oxide nanoparticles (M-SPIONs) coated with dextran, and the iron load was evaluated qualitatively and quantitatively by MRI, near-infrared fluorescence (NIRF) and inductively coupled plasma mass spectrometry (ICP-MS). The best method of granulocyte isolation was Percoll with Ficoll, which showed 95.92% purity and 94% viability. After labeling with M-SPIONs, the granulocytes showed 98.0% purity with a yield of 3.5 × 106 cells/mL and more than 98.6% viability. The iron-loading value in the labeled granulocytes, as obtained by MRI, was 6.40 ± 0.18 pg/cell. Similar values were found with the ICP-MS and NIRF imaging techniques. Therefore, our study shows that it is possible to isolate granulocytes with high purity and yield and labeling with M-SPIONs provides a high internalized iron load and low toxicity to cells. Therefore, these M-SPION-labeled granulocytes could be a promising candidate for future use in inflammation/infection detection by optical and MRI techniques

Cross-sectional analysis reveals autoantibody signatures associated with COVID-19 severity

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is associated with increased levels of autoantibodies targeting immunological proteins such as cytokines and chemokines. Reports further indicate that COVID-19 patients may develop a broad spectrum of autoimmune diseases due to reasons not fully understood. Even so, the landscape of autoantibodies induced by SARS-CoV-2 infection remains uncharted territory. To gain more insight, we carried out a comprehensive assessment of autoantibodies known to be linked to diverse autoimmune diseases observed in COVID-19 patients in a cohort of 231 individuals, of which 161 were COVID-19 patients (72 with mild, 61 moderate, and 28 with severe disease) and 70 were healthy controls. Dysregulated IgG and IgA autoantibody signatures, characterized mainly by elevated concentrations, occurred predominantly in patients with moderate or severe COVID-19 infection. Autoantibody levels often accompanied anti-SARS-CoV-2 antibody concentrations while stratifying COVID-19 severity as indicated by random forest and principal component analyses. Furthermore, while young versus elderly COVID-19 patients showed only slight differences in autoantibody levels, elderly patients with severe disease presented higher IgG autoantibody concentrations than young individuals with severe COVID-19. This work maps the intersection of COVID-19 and autoimmunity by demonstrating the dysregulation of multiple autoantibodies triggered during SARS-CoV-2 infection. Thus, this cross-sectional study suggests that SARS-CoV-2 infection induces autoantibody signatures associated with COVID-19 severity and several autoantibodies that can be used as biomarkers of COVID-19 severity, indicating autoantibodies as potential therapeutical targets for these patients

The database of the PREDICTS (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems) project

The PREDICTS project—Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (www.predicts.org.uk)—has collated from published studies a large, reasonably representative database of comparable samples of biodiversity from multiple sites that differ in the nature or intensity of human impacts relating to land use. We have used this evidence base to develop global and regional statistical models of how local biodiversity responds to these measures. We describe and make freely available this 2016 release of the database, containing more than 3.2 million records sampled at over 26,000 locations and representing over 47,000 species. We outline how the database can help in answering a range of questions in ecology and conservation biology. To our knowledge, this is the largest and most geographically and taxonomically representative database of spatial comparisons of biodiversity that has been collated to date; it will be useful to researchers and international efforts wishing to model and understand the global status of biodiversity