Molecular and physiological basis of Saccharomyces cerevisiae tolerance to adverse lignocellulose-based process conditions

Lignocellulose-based biorefineries have been gaining increasing attention to substitute current petroleum-based refineries. Biomass processing requires a pretreatment step to break lignocellulosic biomass recalcitrant structure, which results in the release of a broad range of microbial inhibitors, mainly weak acids, furans, and phenolic compounds. Saccharomyces cerevisiae is the most commonly used organism for ethanol production; however, it can be severely distressed by these lignocellulose-derived inhibitors, in addition to other challenging conditions, such as pentose sugar utilization and the high temperatures required for an efficient simultaneous saccharification and fermentation step. Therefore, a better understanding of the yeast response and adaptation towards the presence of these multiple stresses is of crucial importance to design strategies to improve yeast robustness and bioconversion capacity from lignocellulosic biomass. This review includes an overview of the main inhibitors derived from diverse raw material resultants from different biomass pretreatments, and describes the main mechanisms of yeast response to their presence, as well as to the presence of stresses imposed by xylose utilization and high-temperature conditions, with a special emphasis on the synergistic effect of multiple inhibitors/stressors. Furthermore, successful cases of tolerance improvement of S. cerevisiae are highlighted, in particular those associated with other process-related physiologically relevant conditions. Decoding the overall yeast response mechanisms will pave the way for the integrated development of sustainable yeast cell--based biorefineries.This study was supported by the Portuguese Foundation for Science and Technology (FCT) by the strategic funding of UID/BIO/04469/2013 unit, MIT Portugal Program (Ph.D. grant PD/BD/128247/ 2016 to Joana T. Cunha), Ph.D. grant SFRH/BD/130739/2017 to Carlos E. Costa, COMPETE 2020 (POCI-01-0145-FEDER-006684), BioTecNorte operation (NORTE-01-0145-FEDER-000004), YeasTempTation (ERA-IB-2-6/0001/2014), and MultiBiorefinery project (POCI-01-0145-FEDER-016403). Funding by the Institute for Bioengineering and Biosciences (IBB) from FCT (UID/BIO/04565/2013) and from Programa Operacional Regional de Lisboa 2020 (Project N. 007317) was also receiveinfo:eu-repo/semantics/publishedVersio

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency–Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research