Trypacidin, a Spore-Borne Toxin from Aspergillus fumigatus, Is Cytotoxic to Lung Cells

Inhalation of Aspergillus fumigatus conidia can cause severe aspergillosis in immunosuppressed people. A. fumigatus produces a large number of secondary metabolites, some of which are airborne by conidia and whose toxicity to the respiratory tract has not been investigated. We found that spores of A. fumigatus contain five main compounds, tryptoquivaline F, fumiquinazoline C, questin, monomethylsulochrin and trypacidin. Fractionation of culture extracts using RP-HPLC and LC-MS showed that samples containing questin, monomethylsulochrin and trypacidin were toxic to the human A549 lung cell line. These compounds were purified and their structure verified using NMR in order to compare their toxicity against A549 cells. Trypacidin was the most toxic, decreasing cell viability and triggering cell lysis, both effects occurring at an IC50 close to 7 µM. Trypacidin toxicity was also observed in the same concentration range on human bronchial epithelial cells. In the first hour of exposure, trypacidin initiates the intracellular formation of nitric oxide (NO) and hydrogen peroxide (H2O2). This oxidative stress triggers necrotic cell death in the following 24 h. The apoptosis pathway, moreover, was not involved in the cell death process as trypacidin did not induce apoptotic bodies or a decrease in mitochondrial membrane potential. This is the first time that the toxicity of trypacidin to lung cells has been reported

Engineered Single-Domain Antibodies with High Protease Resistance and Thermal Stability

The extreme pH and protease-rich environment of the upper gastrointestinal tract is a major obstacle facing orally-administered protein therapeutics, including antibodies. Through protein engineering, several Clostridium difficile toxin A-specific heavy chain antibody variable domains (VHHs) were expressed with an additional disulfide bond by introducing Ala/Gly54Cys and Ile78Cys mutations. Mutant antibodies were compared to their wild-type counterparts with respect to expression yield, non-aggregation status, affinity for toxin A, circular dichroism (CD) structural signatures, thermal stability, protease resistance, and toxin A-neutralizing capacity. The mutant VHHs were found to be well expressed, although with lower yields compared to wild-type counterparts, were non-aggregating monomers, retained low nM affinity for toxin A, albeit the majority showed somewhat reduced affinity compared to wild-type counterparts, and were capable of in vitro toxin A neutralization in cell-based assays. Far-UV and near-UV CD spectroscopy consistently showed shifts in peak intensity and selective peak minima for wild-type and mutant VHH pairs; however, the overall CD profile remained very similar. A significant increase in the thermal unfolding midpoint temperature was observed for all mutants at both neutral and acidic pH. Digestion of the VHHs with the major gastrointestinal proteases, at biologically relevant concentrations, revealed a significant increase in pepsin resistance for all mutants and an increase in chymotrypsin resistance for the majority of mutants. Mutant VHH trypsin resistance was similar to that of wild-type VHHs, although the trypsin resistance of one VHH mutant was significantly reduced. Therefore, the introduction of a second disulfide bond in the hydrophobic core not only increases VHH thermal stability at neutral pH, as previously shown, but also represents a generic strategy to increase VHH stability at low pH and impart protease resistance, with only minor perturbations in target binding affinities. These are all desirable characteristics for the design of protein-based oral therapeutics

Dendritic cells in cancer immunology and immunotherapy

Dendritic cells (DCs) are a diverse group of specialized antigen-presenting cells with key roles in the initiation and regulation of innate and adaptive immune responses. As such, there is currently much interest in modulating DC function to improve cancer immunotherapy. Many strategies have been developed to target DCs in cancer, such as the administration of antigens with immunomodulators that mobilize and activate endogenous DCs, as well as the generation of DC-based vaccines. A better understanding of the diversity and functions of DC subsets and of how these are shaped by the tumour microenvironment could lead to improved therapies for cancer. Here we will outline how different DC subsets influence immunity and tolerance in cancer settings and discuss the implications for both established cancer treatments and novel immunotherapy strategies.S.K.W. is supported by a European Molecular Biology Organization Long- Term Fellowship (grant ALTF 438– 2016) and a CNIC–International Postdoctoral Program Fellowship (grant 17230–2016). F.J.C. is the recipient of a PhD ‘La Caixa’ fellowship. Work in the D.S. laboratory is funded by the CNIC, by the European Research Council (ERC Consolidator Grant 2016 725091), by the European Commission (635122-PROCROP H2020), by the Ministerio de Ciencia, Innovación e Universidades (MCNU), Agencia Estatal de Investigación and Fondo Europeo de Desarrollo Regional (FEDER) (SAF2016-79040-R), by the Comunidad de Madrid (B2017/BMD-3733 Immunothercan- CM), by FIS- Instituto de Salud Carlos III, MCNU and FEDER (RD16/0015/0018-REEM), by Acteria Foundation, by Atresmedia (Constantes y Vitales prize) and by Fundació La Marató de TV3 (201723). The CNIC is supported by the Instituto de Salud Carlos III, the MCNU and the Pro CNIC Foundation, and is a Severo Ochoa Centre of Excellence (SEV-2015-0505).S

A Probabilistic, Distributed, Recursive Mechanism for Decision-making in the Brain

Decision formation recruits many brain regions, but the procedure they jointly execute is unknown. Here we characterize its essential composition, using as a framework a novel recursive Bayesian algorithm that makes decisions based on spike-trains with the statistics of those in sensory cortex (MT). Using it to simulate the random-dot-motion task, we demonstrate it quantitatively replicates the choice behaviour of monkeys, whilst predicting losses of otherwise usable information from MT. Its architecture maps to the recurrent cortico-basal-ganglia-thalamo-cortical loops, whose components are all implicated in decision-making. We show that the dynamics of its mapped computations match those of neural activity in the sensorimotor cortex and striatum during decisions, and forecast those of basal ganglia output and thalamus. This also predicts which aspects of neural dynamics are and are not part of inference. Our single-equation algorithm is probabilistic, distributed, recursive, and parallel. Its success at capturing anatomy, behaviour, and electrophysiology suggests that the mechanism implemented by the brain has these same characteristics