The Communication Factor EDF and the Toxin–Antitoxin Module mazEF Determine the Mode of Action of Antibiotics

It was recently reported that the production of Reactive Oxygen Species (ROS) is a common mechanism of cell death induced by bactericidal antibiotics. Here we show that triggering the Escherichia coli chromosomal toxin–antitoxin system mazEF is an additional determinant in the mode of action of some antibiotics. We treated E. coli cultures by antibiotics belonging to one of two groups: (i) Inhibitors of transcription and/or translation, and (ii) DNA damaging. We found that antibiotics of both groups caused: (i) mazEF-mediated cell death, and (ii) the production of ROS through MazF action. However, only antibiotics of the first group caused mazEF-mediated cell death that is ROS-dependent, whereas those of the second group caused mazEF-mediated cell death by an ROS-independent pathway. Furthermore, our results showed that the mode of action of antibiotics was determined by the ability of E. coli cells to communicate through the signaling molecule Extracellular Death Factor (EDF) participating in mazEF induction

Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice

The JNK-Like MAPK KGB-1 of Caenorhabditis Elegans Promotes Reproduction, Lifespan, and Gene Expressions for Protein Biosynthesis and Germline Homeostasis but Interferes with Hyperosmotic Stress Tolerance

Aims: This study focused on the role of the JNK-like MAPK (mitogen-activated protein kinase) KGB-1 (kinase, GLH-binding 1) for osmoprotection and other vital functions. Methods: We mapped KGB-1 expression patterns and determined lifespan, reproduction and survival rates as well as changes in body volume, motility, and GPDH (glycerol-3-phosphate dehydrogenase) activity for glycerol production in wildtype (WT), different signaling mutants (including a kgb-1 deletion mutant, kgb-1∆) and RNAi-treated worms under control and hyperosmotic conditions. KGB-1-mediated gene expressions were studied, for instance, by RNA Sequencing, with the resulting transcriptome data analyzed using orthology-based approaches. Results: Surprisingly, mutation/RNAi of kgb-1 and fos-1 (gene for an AP-1, activator protein 1, element) significantly promoted hyperosmotic resistance, even though hyperosmotic GPDH activity was higher in WT than in kgb-1∆. KGB-1 and moderate hyperosmolarity promoted and severe hyperosmolarity repressed kgb-1, fos-1, and jun-1 (gene for another AP-1 element) expression. Transcriptome profiling revealed, for instance, down-regulated genes for protein biosynthesis and up-regulated genes for membrane transporters in kgb-1∆ and up-regulated genes for GPDH-1 or detoxification in WT, with the latter indicating cellular damage and less effective osmoprotection in WT. Conclusion: KGB-1 promotes reproduction and lifespan and fosters gene expressions for AP-1 elements, protein biosynthesis, and balanced gametogenesis, but inhibits expressions for membrane transporters perhaps in order to control energy consumption. Reduced protein biosyntheses and enhanced membrane transports in kgb-1∆ most likely contribute to the high hyperosmotic tolerance of the mutant by easing the burden of the existing chaperone machinery and promoting regulatory volume increases upon hyperosmotic stress

Robust discriminative keyword spotting for emotionally colored spontaneous speech using bidirectional lstm networks

In this paper we propose a new technique for robust keyword spotting that uses bidirectional Long Short-Term Memory (BLSTM) recurrent neural nets to incorporate contextual information in speech decoding. Our approach overcomes the drawbacks of generative HMM modeling by applying a discriminative learning procedure that non-linearly maps speech features into an abstract vector space. By incorporating the outputs of a BLSTM network into the speech features, it is able to make use of past and future context for phoneme predictions. The robustness of the approach is evaluated on a keyword spotting task using the HUMAINE Sensitive Artificial Listener (SAL) database, which contains accented, spontaneous, and emotionally colored speech. The test is particularly stringent because the system is not trained on the SAL database, but only on the TIMIT corpus of read speech. We show that our method prevails over a discriminative keyword spotter without BLSTM-enhanced feature functions, which in turn has been proven to outperform HMM-based techniques

Guidelines for publishing papers containing theory and modeling

The use of quantitative approaches in cell biology, including modeling and theory, has been increasing steadily in the past decade. A number of seminal works that combine experiments and modeling have made a significant impact on the field (see Hill and Kirschner, 1982; Peskin et al., 1993; Barkai and Leibler, 1997, to name but a few). Mathematical modeling can help when our intuition fails or misleads us. It can provide a precise language for understanding complex cell biological phenomena. Modeling represents a new addition to our repertoire of strategies to understand biological systems

Quantificational subordination as anaphora to a function

In [11], a semantics for cross-sentential and donkey anaphora is presented that is inspired by approaches using dependent types but couched in simple type theory with parametric polymorphism. In this paper, the approach is extended to cover quantificational subordination. It is argued that the approach enjoys advantages over existing accounts in type-theoretical semantics