Extremely strong and tough hydrogels as prospective candidates for tissue repair – A review

Ideal candidates for the repair of robust biological tissues should exhibit diverse features such as biocompatibility, strength, toughness, self-healing ability and a well-defined structure. Among the available biomaterials, hydrogels, as highly hydrated 3D-crosslinked polymeric networks, are promising for Tissue Engineering purposes as result of their high resemblance with native extracellular matrix. However, these polymeric structures often exhibit a poor mechanical behavior, hampering their use in load-bearing applications. During the last years, several efforts have been made to create new strategies and concepts to fabricate strong and tough hydrogels. Although it is already possible to shape the mechanical properties of artificial hydrogels to mimic biotissues, critical issues regarding, for instance, their biocompatibility and hierarchical structure are often neglected. Therefore, this review covers the structural and mechanical characteristics of the developed methodologies to toughen hydrogels, highlighting some pioneering efforts employed to combine the aforementioned properties in natural-based hydrogels.

Growth of sulfate reducing bacteria on the methanogenic inhibitor BES

The metabolism of methanogenic archaea is inhibited by 2-bromoethanesulfonate (BES). Methane production is blocked because BES is an analog of methyl-coenzyme M and competes with this key molecule in the last step of methanogenesis. For this reason, BES is commonly used in several studies to avoid growth of acetoclastic and hydrogenotrophic methanogens [1]. Despite its effectiveness as methanogenic inhibitor, BES was found to alter microbial communities’ structure, to inhibit the metabolism of non-methanogenic microorganisms and to stimulate homoacetogenic metabolism [2,3]. Even though sulfonates have been reported as electron acceptors for sulfate- and sulfite-reducing bacteria (SRB), only one study described the reduction of BES by complex microbial communities [4]. In this work, a sulfate-reducing bacterium belonging to Desulfovibrio genus (98 % identity at the 16S rRNA gene level with Desulfovibrio aminophilus) was isolated from anaerobic sludge after several successive transfers in anaerobic medium containing BES as sole substrate. Sulfate was not supplemented to the anaerobic growth medium. This microorganism was able to grow under the following conditions: on BES plus H2/CO2 in bicarbonate buffered medium; on BES without H2/CO2 in bicarbonate buffered medium; and on BES in phosphate buffered medium. The main products of BES utilization were sulfide and acetate, the former was produced by the reduction of sulfur from the sulfonate moiety of BES and the latter likely originated from the carbon backbone of the BES molecule. BES was found, in this study, to represent not only an alternative electron acceptor but also to serve as electron donor, and sole carbon and energy source, supporting growth of a Desulfovibrio sp. obtained in pure culture. This is the first study that reports growth of SRB with BES as electron donor and electron acceptor, showing that the methanogenic inhibitor is a substrate for anaerobic growth.

A critical evaluation of methods for the reconstruction of tissue-specific models

Under the framework of constraint based modeling, genome-scale metabolic models (GSMMs) have been used for several tasks, such as metabolic engineering and phenotype prediction. More recently, their application in health related research has spanned drug discovery, biomarker identification and host-pathogen interactions, targeting diseases such as cancer, Alzheimer, obesity or diabetes. In the last years, the development of novel techniques for genome sequencing and other high-throughput methods, together with advances in Bioinformatics, allowed the reconstruction of GSMMs for human cells. Considering the diversity of cell types and tissues present in the human body, it is imperative to develop tissue-specific metabolic models. Methods to automatically generate these models, based on generic human metabolic models and a plethora of omics data, have been proposed. However, their results have not yet been adequately and critically evaluated and compared. This work presents a survey of the most important tissue or cell type specific metabolic model reconstruction methods, which use literature, transcriptomics, proteomics and metabolomics data, together with a global template model. As a case study, we analyzed the consistency between several omics data sources and reconstructed distinct metabolic models of hepatocytes using different methods and data sources as inputs. The results show that omics data sources have a poor overlapping and, in some cases, are even contradictory. Additionally, the hepatocyte metabolic models generated are in many cases not able to perform metabolic functions known to be present in the liver tissue. We conclude that reliable methods for a priori omics data integration are required to support the reconstruction of complex models of human cells.