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The volatile plant hormone ethylene regulates many plant developmental processes and stress responses. It is therefore crucial that plants can precisely control their ethylene production levels in space and time. The ethylene biosynthesis pathway consists of two dedicated steps. In a first reaction, S-adenosyl-L-methionine (SAM) is converted into 1-aminocyclopropane-1-carboxylic acid (ACC) by ACC-synthase (ACS). In a second reaction, ACC is converted into ethylene by ACC-oxidase (ACO). Initially, it was postulated that ACS is the rate-limiting enzyme of this pathway, directing many studies to unravel the regulation of ACS protein activity, and stability. However, an increasing amount of evidence has been gathered over the years, which shows that ACO is the rate-limiting step in ethylene production during certain dedicated processes. This implies that also the ACO protein family is subjected to a stringent regulation. In this review, we give an overview about the state-of-the-art regarding ACO evolution, functionality and regulation, with an emphasis on the transcriptional, post-transcriptional, and post-translational control. We also highlight the importance of ACO being a prime target for genetic engineering and precision breeding, in order to control plant ethylene production levels.

Protein N-linked glycosylation is a post-translational modification that plays an important role in a myriad of biological processes. Computational prediction approaches serve as complementary methods for the characterization of glycosylation sites. Most of the existing predictors for N-linked glycosylation utilize the information that the glycosylation site occurs at the N-X-[S/T] sequon, where X is any amino acid except proline. Not all N-X-[S/T] sequons are glycosylated, thus the N-X-[S/T] sequon is a necessary but not sufficient determinant for protein glycosylation. In that regard, computational prediction of N-linked glycosylation sites confined to N-X-[S/T] sequons is an important problem. Here, we report DeepNGlyPred a deep learning-based approach that encodes the positive and negative sequences in the human proteome dataset (extracted from N-GlycositeAtlas) using sequence-based features (gapped-dipeptide), predicted structural features, and evolutionary information. DeepNGlyPred produces SN, SP, MCC, and ACC of 88.62%, 73.92%, 0.60, and 79.41%, respectively on N-GlyDE independent test set, which is better than the compared approaches. These results demonstrate that DeepNGlyPred is a robust computational technique to predict N-Linked glycosylation sites confined to N-X-[S/T] sequon. DeepNGlyPred will be a useful resource for the glycobiology community.

Post-translational modifications (PTMs) are fundamental to essential biological processes, exerting significant influence over gene expression, protein localization, stability, and genome replication. Sumoylation, a PTM involving the covalent addition of a chemical group to a specific protein sequence, profoundly impacts the functional diversity of proteins. Notably, identifying sumoylation sites has garnered significant attention due to their crucial roles in proteomic functions and their implications in various diseases, including Parkinson’s and Alzheimer’s. Despite the proposal of several computational models for identifying sumoylation sites, their effectiveness could be improved by the limitations associated with conventional learning methodologies. In this study, we introduce pseudo-position-specific scoring matrix (PsePSSM), a robust computational model designed for accurately predicting sumoylation sites using an optimized deep learning algorithm and efficient feature extraction techniques. Moreover, to streamline computational processes and eliminate irrelevant and noisy features, sequential forward selection using a support vector machine (SFS-SVM) is implemented to identify optimal features. The multi-layer Deep Neural Network (DNN) is a robust classifier, facilitating precise sumoylation site prediction. We meticulously assess the performance of PSSM-Sumo through a tenfold cross-validation approach, employing various statistical metrics such as the Matthews Correlation Coefficient (MCC), accuracy, sensitivity, specificity, and the Area under the ROC Curve (AUC). Comparative analyses reveal that PSSM-Sumo achieves an exceptional average prediction accuracy of 98.71%, surpassing existing models. The robustness and accuracy of the proposed model position it as a promising tool for advancing drug discovery and the diagnosis of diverse diseases linked to sumoylation sites.

Dying mammalian cells emit numerous signals that interact with the host to dictate the immunological correlates of cellular stress and death. In the absence of reactive antigenic determinants (which is generally the case for healthy cells), such signals may drive inflammation but cannot engage adaptive immunity. Conversely, when cells exhibit sufficient antigenicity, as in the case of infected or malignant cells, their death can culminate with adaptive immune responses that are executed by cytotoxic T lymphocytes and elicit immunological memory. Suggesting a key role for immunogenic cell death (ICD) in immunosurveillance, both pathogens and cancer cells evolved strategies to prevent the recognition of cell death as immunogenic. Intriguingly, normal cells succumbing to conditions that promote the formation of post-translational neoantigens (for example, oxidative stress) can also drive at least some degree of antigen-specific immunity, pointing to a novel implication of ICD in the etiology of non-infectious, non-malignant disorders linked to autoreactivity.Immunogenic cell death (ICD) is central to both homeostatic and pathophysiological events. Kroemer et al. review the mechanisms of ICD and its role in therapy and disease.

Much has been learned since the early 1960s about histone post-translational modifications (PTMs) and how they affect DNA-templated processes at the molecular level. This understanding has been bolstered in the past decade by the identification of new types of histone PTM, the advent of new genome-wide mapping approaches and methods to deposit or remove PTMs in a locally and temporally controlled manner. Now, with the availability of vast amounts of data across various biological systems, the functional role of PTMs in important processes (such as transcription, recombination, replication, DNA repair and the modulation of genomic architecture) is slowly emerging. This Review explores the contribution of histone PTMs to the regulation of genome function by discussing when these modifications play a causative (or instructive) role in DNA-templated processes and when they are deposited as a consequence of such processes, to reinforce and record the event. Important advances in the field showing that histone PTMs can exert both direct and indirect effects on genome function are also presented.Histone post-translational modifications (PTMs) have been mainly regarded as instructing DNA-templated processes. In this Review, Gonzalo Millán-Zambrano and colleagues describe how histone PTMs both affect and are affected by these DNA processes and should be viewed as components of a complex genome-regulating network.

Post-translational modifications (PTMs) can occur on specific amino acids localized within regulatory domains of target proteins, which control a protein’s stability. These regions, called degrons, are often controlled by PTMs, which act as signals to expedite protein degradation (PTM-activated degrons) or to forestall degradation and stabilize a protein (PTM-inactivated degrons). We summarize current knowledge of the regulation of protein stability by various PTMs. We aim to display the variety and breadth of known mechanisms of regulation as well as highlight common themes in PTM-regulated degrons to enhance potential for identifying novel drug targets where druggable targets are currently lacking. Here the authors summarize current knowledge of the regulation of protein stability by various post-translational modifications (PTMs) including methylation and phosphorylation. PTM-regulated degrons act as signals for protein degradation or stabilization.

Lysine acetylation is a widespread and versatile protein post-translational modification. Lysine acetyltransferases and lysine deacetylases catalyse the addition or removal, respectively, of acetyl groups at both histone and non-histone targets. In this Review, we discuss several features of acetylation and deacetylation, including their diversity of targets, rapid turnover, exquisite sensitivity to the concentrations of the cofactors acetyl-CoA, acyl-CoA and NAD+, and tight interplay with metabolism. Histone acetylation and non-histone protein acetylation influence a myriad of cellular and physiological processes, including transcription, phase separation, autophagy, mitosis, differentiation and neural function. The activity of lysine acetyltransferases and lysine deacetylases can, in turn, be regulated by metabolic states, diet and specific small molecules. Histone acetylation has also recently been shown to mediate cellular memory. These features enable acetylation to integrate the cellular state with transcriptional output and cell-fate decisions.Lysine acetyltransferases and lysine deacetylases regulate gene expression and protein function by controlling acetylation and deacetylation of histones and diverse non-histone proteins. The activity of lysine acetyltransferases and lysine deacetylases is regulated by cellular metabolic states, offering the potential for therapeutic modulation through dietary and pharmacological interventions.

Retinoic acid-inducible gene I (RIG-I)-like receptors (RLRs) are key sensors of virus infection, mediating the transcriptional induction of type I interferons and other genes that collectively establish an antiviral host response. Recent studies have revealed that both viral and host-derived RNAs can trigger RLR activation; this can lead to an effective antiviral response but also immunopathology if RLR activities are uncontrolled. In this Review, we discuss recent advances in our understanding of the types of RNA sensed by RLRs in the contexts of viral infection, malignancies and autoimmune diseases. We further describe how the activity of RLRs is controlled by host regulatory mechanisms, including RLR-interacting proteins, post-translational modifications and non-coding RNAs. Finally, we discuss key outstanding questions in the RLR field, including how our knowledge of RLR biology could be translated into new therapeutics.The RNA-sensing retinoic acid-inducible gene I (RIG-I)-like receptors (RLRs) are important inducers of type I interferons and other antiviral immune mediators. Here, Jan Rehwinkel and Michaela Gack explain how members of the RLR family are regulated and reflect on the importance of the RLRs in viral infection, autoimmunity and cancer.

The silent information regulator sirtuin 1 (SIRT1) protein, a highly conserved NAD + -dependent deacetylase belonging to the sirtuin family, is a post-translational regulator that plays a role in modulating inflammation. SIRT1 affects multiple biological processes by deacetylating a variety of proteins including histones and non-histone proteins. Recent studies have revealed intimate links between SIRT1 and inflammation, while alterations to SIRT1 expression and activity have been linked to inflammatory diseases. In this review, we summarize the mechanisms that regulate SIRT1 expression, including upstream activators and suppressors that operate on the transcriptional and post-transcriptional levels. We also summarize factors that influence SIRT1 activity including the NAD + /NADH ratio, SIRT1 binding partners, and post-translational modifications. Furthermore, we underscore the role of SIRT1 in the development of inflammation by commenting on the proteins that are targeted for deacetylation by SIRT1. Finally, we highlight the potential for SIRT1-based therapeutics for inflammatory diseases.

Deposition of tau aggregates is a pathological hallmark of Alzheimer's disease that is closely linked both spatially and temporally to emergence of neurodegeneration and manifestation of clinical symptoms. There is an urgent need for accurate PET, CSF, and plasma biomarkers of tau pathology to improve the diagnostic process in clinical practice and the selection of participants and monitoring of treatment effects in trials. Innovative second-generation tau-PET tracers with high affinity and selectivity to tau pathology in Alzheimer's disease have enabled detection of tau pathology in medial temporal lobe subregions that are affected in the earliest disease stages. Furthermore, novel but common tau spreading subtypes have been discovered using tau-PET, suggesting much greater interindividual differences in the distribution of tau pathology across the brain than previously assumed. In the CSF biomarker field, novel phosphorylated tau (p-tau) assays have been introduced that better reflect tau tangle load than established CSF biomarkers of tau pathology. The advent of cost-effective and accessible blood-based biomarkers for tau pathophysiology (ie, p-tau181, p-tau217, and p-tau231) might transform the Alzheimer's disease field, as these biomarkers correlate with post-mortem Alzheimer's disease pathology, differentiate Alzheimer's disease from other types of dementia, and predict future progression from normal cognition and mild cognitive impairment to Alzheimer's disease. In controlled investigational settings, improvements in tau-PET and biofluid p-tau markers have led to earlier disease detection, more accurate diagnostic methods, and refinement of prognosis. The anti-tau therapy landscape is rapidly evolving, with multiple ongoing phase 1 and 2 trials of post-translational modification of tau, tau immunotherapy, tau aggregation inhibitors, and targeting production of tau and reduction of intracellular tau levels. Neuroimaging and biofluid tau markers hold potential for optimising such clinical trials by augmenting participant selection, providing evidence of target engagement, and monitoring treatment efficacy. Major challenges to overcome are the high cost of tau-PET, partial sensitivity to detect early-stage Alzheimer's disease pathology, and off-target tracer binding. Prospective validation studies of biofluid p-tau markers are needed, and assay-related preanalytical and analytical factors need further refinement. Future studies should focus on demonstrating the diagnostic and prognostic accuracy of tau biomarkers—blood-based markers in particular—in non-tertiary settings, such as primary care, which is characterised by a diverse population with medical comorbidities. Large-scale head-to-head studies are needed across different stages of Alzheimer's disease to determine which tau biomarker is optimal in various clinical scenarios, such as early diagnosis, differential diagnosis, and prognosis, and for aspects of clinical trial design, such as proving target engagement, optimising participant selection, and refining monitoring of treatment effects.