Amyloid fibril systems reduce, stabilize and deliver bioavailable nanosized iron

Iron-deficiency anaemia (IDA) is a major global public health problem. A sustainable and cost-effective strategy to reduce IDA is iron fortification of foods, but the most bioavailable fortificants cause adverse organoleptic changes in foods. Iron nanoparticles are a promising solution in food matrices, although their tendency to oxidize and rapidly aggregate in solution severely limits their use in fortification. Amyloid fibrils are protein aggregates initially known for their association with neurodegenerative disorders, but recently described in the context of biological functions in living organisms and emerging as unique biomaterial building blocks. Here, we show an original application for these protein fibrils as efficient carriers for iron fortification. We use biodegradable amyloid fibrils from β-lactoglobulin, an inexpensive milk protein with natural reducing effects, as anti-oxidizing nanocarriers and colloidal stabilizers for iron nanoparticles. The resulting hybrid material forms a stable protein-iron colloidal dispersion that undergoes rapid dissolution and releases iron ions during acidic and enzymatic in vitro digestion. Importantly, this hybrid shows high in vivo iron bioavailability, equivalent to ferrous sulfate in haemoglobin-repletion and stable-isotope studies in rats, but with reduced organoleptic changes in foods. Feeding the rats with these hybrid materials did not result in abnormal iron accumulation in any organs, or changes in whole blood glutathione concentrations, inferring their primary safety. Therefore, these iron-amyloid fibril hybrids emerge as novel, highly effective delivery systems for iron in both solid and liquid matrices

Uncovering disease mechanisms through network biology in the era of next generation sequencing.

Characterizing the behavior of disease genes in the context of biological networks has the potential to shed light on disease mechanisms, and to reveal both new candidate disease genes and therapeutic targets. Previous studies addressing the network properties of disease genes have produced contradictory results. Here we have explored the causes of these discrepancies and assessed the relationship between the network roles of disease genes and their tolerance to deleterious germline variants in human populations leveraging on: the abundance of interactome resources, a comprehensive catalog of disease genes and exome variation data. We found that the most salient network features of disease genes are driven by cancer genes and that genes related to different types of diseases play network roles whose centrality is inversely correlated to their tolerance to likely deleterious germline mutations. This proved to be a multiscale signature, including global, mesoscopic and local network centrality features. Cancer driver genes, the most sensitive to deleterious variants, occupy the most central positions, followed by dominant disease genes and then by recessive disease genes, which are tolerant to variants and isolated within their network modules.We received support from UBACyT (20020130100582BA) and MinCyT (PICT2014-2701), ISCIII-FEDER (PI13/00082, CP10/00524), IMI-JU under grants agreements n° 115002 (eTOX), n° 115191 (Open PHACTS)], n° 115372 (EMIF) and n° 115735 (iPiE), resources of which are composed of financial contribution from the European Union’s Seventh Framework Programme (FP7/2007-2013) and EFPIA companies’ in kind contribution, and the EU H2020 Programme 2014-2020 under grant agreements no. 634143 (MedBioinformatics) and no. 676559 (Elixir-Excelerate). The Research Programme on Biomedical Informatics (GRIB) is a node of the Spanish National Institute of Bioinformatics (INB). A.G.-P. is supported by a Ramon y Cajal scholarship funded by the Spanish Ministry of Economy. The authors would like to thank the Exome Aggregation Consortium and the groups that provided exome variant data for comparison. A full list of contributing groups can be found at http://exac.broadinstitute.org/about