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Abstract Prostate cancer is the most commonly diagnosed malignancy and the third leading cause of cancer deaths. GWAS have identified variants associated with prostate cancer susceptibility; however, mechanistic and functional validation of these mutations is lacking. We used CRISPR‐Cas9 genome editing to introduce a missense variant identified in the ELAC2 gene, which encodes a dually localised nuclear and mitochondrial RNA processing enzyme, into the mouse Elac2 gene as well as to generate a prostate‐specific knockout of Elac2. These mutations caused enlargement and inflammation of the prostate and nodule formation. The Elac2 variant or knockout mice on the background of the transgenic adenocarcinoma of the mouse prostate (TRAMP) model show that Elac2 mutation with a secondary genetic insult exacerbated the onset and progression of prostate cancer. Multiomic profiling revealed defects in energy metabolism that activated proinflammatory and tumorigenic pathways as a consequence of impaired noncoding RNA processing and reduced protein synthesis. Our physiologically relevant models show that the ELAC2 variant is a predisposing factor for prostate cancer and identify changes that underlie the pathogenesis of this cancer.

IntroductionThe CIAO project was launched in Spring 2020 to address the need to make sense of the numerous and disparate data available on COVID-19 pathogenesis. Based on a crowdsourcing model of large-scale collaboration, the project has exploited the Adverse Outcome Pathway (AOP) knowledge management framework built to support chemical risk assessment driven by mechanistic understanding of the biological perturbations at the different organizational levels. Hence the AOPs might have real potential to integrate data produced through different approaches and from different disciplines as experienced in the context of COVID-19. In this study, we aim to address the effectiveness of the AOP framework (i) in supporting an interdisciplinary collaboration for a viral disease and (ii) in working as the conceptual mediator of a crowdsourcing model of collaboration.MethodsWe used a survey disseminated among the CIAO participants, a workshop open to all interested CIAO contributors, a series of interviews with some participants and a self-reflection on the processes.ResultsThe project has supported genuine interdisciplinarity with exchange of knowledge. The framework provided a common reference point for discussion and collaboration. The diagram used in the AOPs assisted with making explicit what are the different perspectives brought to the knowledge about the pathways. The AOP-Wiki showed up many aspects about its usability for those not already in the world of AOPs. Meanwhile their use in CIAO highlighted needed adaptations. Introduction of new Wiki elements for modulating factors was potentially the most disruptive one. Regarding how well AOPs support a crowdsourcing model of large-scale collaboration, the CIAO project showed that this is successful when there is a strong central organizational impetus and when clarity about the terms of the collaboration is brought as early as possible.DiscussionExtrapolate the successful CIAO approach and related processes to other areas of science where the AOP could foster interdisciplinary and systematic organization of the knowledge is an exciting perspective.

A subset of mitochondrial transcripts is not flanked by tRNAs and thus does not conform to the canonical mode of processing. Here, Clemente et al. demonstrate that phosphatase activity of ANGEL2 is required for correct processing of these transcripts.

The ability to alter the genomes of living cells is key to understanding how genes influence the functions of organisms and will be critical to modify living systems for useful purposes. Here, the authors use computational design to discover Cas9 enzymes with increased activity.

There are different approaches used to reduce reading skills deficits. One such approach, which belongs to the group of visual adaptations, is to change the font used in the texts. The main research goal is to assess the level of reading success in people with dyslexia (reading difficulties) by using a specialized Cyrillic font - Dyslexic FZF. The research was conducted on 24 persons with dyslexia from North Macedonia and obtained data about oral reading fluency and reading lists of meaningful and meaningless words with the Dyslexic FZF font and the font Times New Roman. The data of the two consecutive readings were compared. Results suggest that when using the new dyslexia typeface, Dyslexic FZF, participants were able to read more words per minute than with the Times New Roman font. A statistically significant difference in the results occurs in the errors made while reading.

The central role of the mitochondrion for cellular and organismal metabolism is well known, yet its functional role in evolution has rarely been featured in leading international conferences. Moreover, the contribution of mitochondrial genetics to complex disease phenotypes is particularly important, and although major advances have been made in the field of genomics, mitochondrial genomic data have in many cases been overlooked. Accumulating data and new knowledge support a major contribution of this maternally inherited genome, and its interactions with the nucleus, to both major evolutionary processes and diverse disease phenotypes. These advances encouraged us to assemble the first Mitochondrial Genomics and Evolution (MGE) meeting-an SMBE satellite and Israeli Science foundation international conference (Israel, September 2017). Here, we report the content and outcome of the MGE meeting (https://www.mge2017.com/; last accessed November 5, 2017).

Mammalian mitoribosomes feature dramatically reduced ribosomal RNAs and follow mitochondria specific assembly pathways. Here the authors describe the process of human mitochondrial ribosome maturation that results in the formation of the ribosomal active site region, including the peptidyl transferase loop and the two tRNA-binding loops.

Reactive oxygen species (ROS) and reactive nitrogen species (RNS) are formed as a result of natural cellular processes, intracellular signaling, or as adverse responses associated with diseases or exposure to oxidizing chemical and non-chemical stressors. The action of ROS and RNS, collectively referred to as reactive oxygen and nitrogen species (RONS), has recently become highly relevant in a number of adverse outcome pathways (AOPs) that capture, organize, evaluate and portray causal relationships pertinent to adversity or disease progression. RONS can potentially act as a key event (KE) in the cascade of responses leading to an adverse outcome (AO) within such AOPs, but are also known to modulate responses of events along the AOP continuum without being an AOP event itself. A substantial discussion has therefore been undertaken in a series of workshops named “Mystery or ROS” to elucidate the role of RONS in disease and adverse effects associated with exposure to stressors such as nanoparticles, chemical, and ionizing and non-ionizing radiation. This review introduces the background for RONS production, reflects on the direct and indirect effects of RONS, addresses the diversity of terminology used in different fields of research, and provides guidance for developing a harmonized approach for defining a common event terminology within the AOP developer community.

Transcription of the human mitochondrial genome and correct processing of the two long polycistronic transcripts are crucial for oxidative phosphorylation. According to the tRNA punctuation model, nucleolytic processing of these large precursor transcripts occurs mainly through the excision of the tRNAs that flank most rRNAs and mRNAs. However, some mRNAs are not punctuated by tRNAs, and it remains largely unknown how these non-canonical junctions are resolved. The FASTK family proteins are emerging as key players in non-canonical RNA processing. Here, we have generated human cell lines carrying single or combined knockouts of several FASTK family members to investigate their roles in non-canonical RNA processing. The most striking phenotypes were obtained with loss of FASTKD4 and FASTKD5 and with their combined double knockout. Comprehensive mitochondrial transcriptome analyses of these cell lines revealed a defect in processing at several canonical and non-canonical RNA junctions, accompanied by an increase in specific antisense transcripts. Loss of FASTKD5 led to the most severe phenotype with marked defects in mitochondrial translation of key components of the electron transport chain complexes and in oxidative phosphorylation. We reveal that the FASTK protein family members are crucial regulators of non-canonical junction and non-coding mitochondrial RNA processing.

Eco-driving has garnered considerable research attention owing to its potential socio-economic impact, including enhanced public health and mitigated climate change effects through the reduction of greenhouse gas emissions. With an expectation of more autonomous vehicles (AVs) on the road, an eco-driving strategy in hybrid traffic networks encompassing AV and human-driven vehicles (HDVs) with the coordination of traffic lights is a challenging task. The challenge is partially due to the insufficient infrastructure for collecting, transmitting, and sharing real-time traffic data among vehicles, facilities, and traffic control centers, and the following decision-making of agents involved in traffic control. Additionally, the intricate nature of the existing traffic network, with its diverse array of vehicles and facilities, contributes to the challenge by hindering the development of a mathematical model for accurately characterizing the traffic network. In this study, we utilized the Simulation of Urban Mobility (SUMO) simulator to tackle the first challenge through computational analysis. To address the second challenge, we employed a model-free reinforcement learning (RL) algorithm, proximal policy optimization, to decide the actions of AV and traffic light signals in a traffic network. A novel eco-driving strategy was proposed by introducing different percentages of AV into the traffic flow and collaborating with traffic light signals using RL to control the overall speed of the vehicles, resulting in improved fuel consumption efficiency. Average rewards with different penetration rates of AV (5%, 10%, and 20% of total vehicles) were compared to the situation without any AV in the traffic flow (0% penetration rate). The 10% penetration rate of AV showed a minimum time of convergence to achieve average reward, leading to a significant reduction in fuel consumption and total delay of all vehicles. [ABSTRACT FROM AUTHOR]