Mitochondria produce reactive oxygen species (mROS) as a natural by-product of electron transport chain activity. While initial studies focused on the damaging effects of reactive oxygen species, a recent paradigm shift has shown that mROS can act as signaling molecules to activate pro-growth responses. Cancer cells have long been observed to have increased production of ROS relative to normal cells, although the implications of this increase were not always clear. This is especially interesting considering cancer cells often also induce expression of antioxidant proteins. Here, we discuss how cancer-associated mutations and microenvironments can increase production of mROS, which can lead to activation of tumorigenic signaling and metabolic reprogramming. This tumorigenic signaling also increases expression of antioxidant proteins to balance the high production of ROS to maintain redox homeostasis. We also discuss how cancer-specific modifications to ROS and antioxidants may be targeted for therapy.

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Mitochondrial reactive oxygen species and cancer

Progress in corneal wound healing

The potential for ischemic preconditioning to reduce infarct size was first recognized more than 30 years ago. Despite extension of the concept to ischemic postconditioning and remote ischemic conditioning and literally thousands of experimental studies in various species and models which identified a multitude of signaling steps, so far there is only a single and very recent study, which has unequivocally translated cardioprotection to improved clinical outcome as the primary endpoint in patients. Many potential reasons for this disappointing lack of clinical translation of cardioprotection have been proposed, including lack of rigor and reproducibility in preclinical studies, and poor design and conduct of clinical trials. There is, however, universal agreement that robust preclinical data are a mandatory prerequisite to initiate a meaningful clinical trial. In this context, it is disconcerting that the CAESAR consortium (Consortium for preclinicAl assESsment of cARdioprotective therapies) in a highly standardized multi-center approach of preclinical studies identified only ischemic preconditioning, but not nitrite or sildenafil, when given as adjunct to reperfusion, to reduce infarct size. However, ischemic preconditioning—due to its very nature—can only be used in elective interventions, and not in acute myocardial infarction. Therefore, better strategies to identify robust and reproducible strategies of cardioprotection, which can subsequently be tested in clinical trials must be developed. We refer to the recent guidelines for experimental models of myocardial ischemia and infarction, and aim to provide now practical guidelines to ensure rigor and reproducibility in preclinical and clinical studies on cardioprotection. In line with the above guideline, we define rigor as standardized state-of-the-art design, conduct and reporting of a study, which is then a prerequisite for reproducibility, i.e. replication of results by another laboratory when performing exactly the same experiment.

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Practical guidelines for rigor and reproducibility in preclinical and clinical studies on cardioprotection.

The concept of cell signaling in the context of nonenzyme-assisted protein modifications by reactive electrophilic and oxidative species, broadly known as redox signaling, is a uniquely complex topic that has been approached from numerous different and multidisciplinary angles. Our Review reflects on five aspects critical for understanding how nature harnesses these noncanonical post-translational modifications to coordinate distinct cellular activities: (1) specific players and their generation, (2) physicochemical properties, (3) mechanisms of action, (4) methods of interrogation, and (5) functional roles in health and disease. Emphasis is primarily placed on the latest progress in the field, but several aspects of classical work likely forgotten/lost are also recollected. For researchers with interests in getting into the field, our Review is anticipated to function as a primer. For the expert, we aim to stimulate thought and discussion about fundamentals of redox signaling mechanisms and nuances of sp...

Redox Signaling by Reactive Electrophiles and Oxidants

Endoplasmic reticulum (ER) is a dynamic organelle orchestrating the folding and post-translational maturation of almost all membrane proteins and most secreted proteins. These proteins synthesized in the ER, need to form disulfide bridge to acquire specific three-dimensional structures for function. The formation of disulfide bridge is mediated via protein disulfide isomerase (PDI) family and other oxidoreductases, which contribute to reactive oxygen species (ROS) generation and consumption in the ER. Therefore, redox regulation of ER is delicate and sensitive to perturbation. Deregulation in ER homeostasis, usually called ER stress, can provoke unfolded protein response (UPR) pathways with an aim to initially restore homeostasis by activating genes involved in protein folding and antioxidative machinery. Over time, however, activated UPR involves a variety of cellular signaling pathways which determine the state and fate of cell in large part (like autophagy, apoptosis, ferroptosis, inflammation, senescence, stemness, and cell cycle, etc.). This review will describe the regulation of UPR from the redox perspective in controlling the cell survival or death, emphasizing the redox modifications of UPR sensors/transducers in the ER.

Redox signaling and unfolded protein response coordinate cell fate decisions under ER stress.

Recent developments in high-throughput technologies have accelerated the accumulation of massive amounts of omics data from multiple sources: genome, epigenome, transcriptome, proteome, metabolome, etc. Traditionally, data from each source (e.g., genome) is analyzed in isolation using statistical and machine learning (ML) methods. Integrative analysis of multi-omics and clinical data is key to new biomedical discoveries and advancements in precision medicine. However, data integration poses new computational challenges as well as exacerbates the ones associated with single-omics studies. Specialized computational approaches are required to effectively and efficiently perform integrative analysis of biomedical data acquired from diverse modalities. In this review, we discuss state-of-the-art ML-based approaches for tackling five specific computational challenges associated with integrative analysis: curse of dimensionality, data heterogeneity, missing data, class imbalance and scalability issues.

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Machine Learning and Integrative Analysis of Biomedical Big Data.

HSPA5 Gene encoding Hsp70 chaperone BiP in the endoplasmic reticulum.

Oxidative protein folding in the endoplasmic reticulum (ER) has emerged as a potentially significant source of cellular reactive oxygen species (ROS). Recent studies suggest that levels of ROS generated as a byproduct of oxidative folding rival those produced by mitochondrial respiration. Mechanisms that protect cells against oxidant accumulation within the ER have begun to be elucidated yet many questions still remain regarding how cells prevent oxidant-induced damage from ER folding events. Here we report a new role for a central well-characterized player in ER homeostasis as a direct sensor of ER redox imbalance. Specifically we show that a conserved cysteine in the lumenal chaperone BiP is susceptible to oxidation by peroxide, and we demonstrate that oxidation of this conserved cysteine disrupts BiP's ATPase cycle. We propose that alteration of BiP activity upon oxidation helps cells cope with disruption to oxidative folding within the ER during oxidative stress.

/pdf/redox-signaling-via-the-molecular-chaperone-bip-protects-kjitkhb0g1.pdf

Redox signaling via the molecular chaperone BiP protects cells against endoplasmic reticulum-derived oxidative stress

Transcript abundance and protein abundance show modest correlation in many biological models, but how this impacts disease signature discovery in omics experiments is rarely explored. Here we report an integrated omics approach, incorporating measurements of transcript abundance, protein abundance, and protein turnover to map the landscape of proteome remodeling in a mouse model of pathological cardiac hypertrophy. Analyzing the hypertrophy signatures that are reproducibly discovered from each omics data type across six genetic strains of mice, we find that the integration of transcript abundance, protein abundance, and protein turnover data leads to 75% gain in discovered disease gene candidates. Moreover, the inclusion of protein turnover measurements allows discovery of post-transcriptional regulations across diverse pathways, and implicates distinct disease proteins not found in steady-state transcript and protein abundance data. Our results suggest that multi-omics investigations of proteome dynamics provide important insights into disease pathogenesis in vivo.

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Integrated omics dissection of proteome dynamics during cardiac remodeling

http://www.jbc.org/content/291/14/7541.full.pdf

Jie Wang

Papers

Machine Learning and Integrative Analysis of Biomedical Big Data.

HSPA5 Gene encoding Hsp70 chaperone BiP in the endoplasmic reticulum.

Redox signaling via the molecular chaperone BiP protects cells against endoplasmic reticulum-derived oxidative stress

Integrated omics dissection of proteome dynamics during cardiac remodeling

Formation and Reversibility of BiP Protein Cysteine Oxidation Facilitate Cell Survival during and post Oxidative Stress