Complex-dependent histone acetyltransferase activity of KAT8 determines its role in transcription and cellular homeostasis.

Acetylation of lysine 16 on histone H4 (H4K16ac) is catalyzed by histone acetyltransferase KAT8 and can prevent chromatin compaction in vitro. Although extensively studied in Drosophila, the functions of H4K16ac and two KAT8-containing protein complexes (NSL and MSL) are not well understood in mammals. Here, we demonstrate a surprising complex-dependent activity of KAT8: it catalyzes H4K5ac and H4K8ac as part of the NSL complex, whereas it catalyzes the bulk of H4K16ac as part of the MSL complex. Furthermore, we show that MSL complex proteins and H4K16ac are not required for cell proliferation and chromatin accessibility, whereas the NSL complex is essential for cell survival, as it stimulates transcription initiation at the promoters of housekeeping genes. In summary, we show that KAT8 switches catalytic activity and function depending on its associated proteins and that, when in the NSL complex, it catalyzes H4K5ac and H4K8ac required for the expression of essential genes.

Henlea earthworm bioluminescence comprises violet-blue BRET from tryptophan 2-carboxylate to deazaflavin cofactor.

We recently identified the deazaflavin cofactor as a light emitter in novel bioluminescence (BL) system from Siberian earthworms Henlea sp. (Petushkov et al., 2023, Org. Biomol. Chem. 21:415-427). In the present communication we compared in vitro BL spectra in the absence and in the presence of the cofactor and found a wavelength shift from 420 to 476 nm. This violet-blue BRET to deazaflavin cofactor (acceptor of photonless transfer) masks the actual oxyluciferin as an emitter (BRET donor) in the novel BL system. The best candidate for that masked chromophore is tryptophan 2-carboxylate (T2C) found previously as a building block in some natural products isolated from Henlea sp. (Dubinnyi et al., 2020, ChemSelect 5:13155-13159). We synthesized T2C and acetyl-T2C, verified their presence in earthworms by nanoflow-HRMS, explored spectral properties of excitation and emission spectra and found a chain of excitation/emission maxima with a perfect potential for BRET: 300 nm (excitation of T2C) - 420 nm (emission of T2C) - 420 nm (excitation of deazaflavin) - 476 nm (emission of deazaflavin, BL). An array of natural products with T2C chromophore are present in BL earthworms as candidates for novel oxyluciferin. We demonstrated for the Henlea BL that the energy of the excited state of the T2C chromophore is transferred by the Förster mechanism and then emitted by deazaflavin (BRET), similarly to known examples: aequorin-GFP in Aequorea victoria and antenna proteins in bacterial BL systems (lumazine from Photobacterium and yellow fluorescent protein from Vibrio fischeri strain Y1).

Structure elucidation of Keroplatus (Diptera:Keroplatidae) fungus gnat oxyluciferin.

Bioluminescence of insects is a well-known natural phenomenon in the focus of interest of scientific research. While the mechanisms of bioluminescence in Coleoptera have been extensively studied, there is a lack of information about the chemistry of light emission in Diptera species. Here we report the Keroplatus spp. oxyluciferin structure elucidation and identification as 3-hydroxykynurenic acid. Additionally, the present study provides the first direct evidence of the relationship between the bioluminescent systems of Orfelia and Keroplatus. However, the properties of the putative Orfelia oxyluciferin suggest that the light emission mechanisms are not identical.

Translation initiation downstream from annotated start codons in human mRNAs coevolves with the Kozak context.

Eukaryotic translation initiation involves preinitiation ribosomal complex 5'-to-3' directional probing of mRNA for codons suitable for starting protein synthesis. The recognition of codons as starts depends on the codon identity and on its immediate nucleotide context known as Kozak context. When the context is weak (i.e., nonoptimal), leaky scanning takes place during which a fraction of ribosomes continues the mRNA probing. We explored the relationship between the context of AUG codons annotated as starts of protein-coding sequences and the next AUG codon occurrence. We found that AUG codons downstream from weak starts occur in the same frame more frequently than downstream from strong starts. We suggest that evolutionary selection on in-frame AUGs downstream from weak start codons is driven by the advantage of the reduction of wasteful out-of-frame product synthesis and also by the advantage of producing multiple proteoforms from certain mRNAs. We confirmed translation initiation downstream from weak start codons using ribosome profiling data. We also tested translation of alternative start codons in 10 specific human genes using reporter constructs. In all tested cases, initiation at downstream start codons was more productive than at the annotated ones. In most cases, optimization of Kozak context did not completely abolish downstream initiation, and in the specific example of CMPK1 mRNA, the optimized start remained unproductive. Collectively, our work reveals previously uncharacterized forces shaping the evolution of protein-coding genes and points to the plurality of translation initiation and the existence of sequence features influencing start codon selection, other than Kozak context.

Silencing of ceramide synthase 2 in hepatocytes modulates plasma ceramide biomarkers predictive of cardiovascular death.

Emerging clinical data show that three ceramide molecules, Cer d18:1/16:0, Cer d18:1/24:1, and Cer d18:1/24:0, are biomarkers of a fatal outcome in patients with cardiovascular disease. This finding raises basic questions about their metabolic origin, their contribution to disease pathogenesis, and the utility of targeting the underlying enzymatic machinery for treatment of cardiometabolic disorders. Here, we outline the development of a potent N-acetylgalactosamine-conjugated antisense oligonucleotide engineered to silence ceramide synthase 2 specifically in hepatocytes in vivo. We demonstrate that this compound reduces the ceramide synthase 2 mRNA level and that this translates into efficient lowering of protein expression and activity as well as Cer d18:1/24:1 and Cer d18:1/24:0 levels in liver. Intriguingly, we discover that the hepatocyte-specific antisense oligonucleotide also triggers a parallel modulation of blood plasma ceramides, revealing that the biomarkers predictive of cardiovascular death are governed by ceramide biosynthesis in hepatocytes. Our work showcases a generic therapeutic framework for targeting components of the ceramide enzymatic machinery to disentangle their roles in disease causality and to explore their utility for treatment of cardiometabolic disorders.

A vast pool of lineage-specific microproteins encoded by long non-coding RNAs in plants.

Pervasive transcription of eukaryotic genomes results in expression of long non-coding RNAs (lncRNAs) most of which are poorly conserved in evolution and appear to be non-functional. However, some lncRNAs have been shown to perform specific functions, in particular, transcription regulation. Thousands of small open reading frames (smORFs, <100 codons) located on lncRNAs potentially might be translated into peptides or microproteins. We report a comprehensive analysis of the conservation and evolutionary trajectories of lncRNAs-smORFs from the moss Physcomitrium patens across transcriptomes of 479 plant species. Although thousands of smORFs are subject to substantial purifying selection, the majority of the smORFs appear to be evolutionary young and could represent a major pool for functional innovation. Using nanopore RNA sequencing, we show that, on average, the transcriptional level of conserved smORFs is higher than that of non-conserved smORFs. Proteomic analysis confirmed translation of 82 novel species-specific smORFs. Numerous conserved smORFs containing low complexity regions (LCRs) or transmembrane domains were identified, the biological functions of a selected LCR-smORF were demonstrated experimentally. Thus, microproteins encoded by smORFs are a major, functionally diverse component of the plant proteome.

Unusually efficient CUG initiation of an overlapping reading frame in POLG mRNA yields novel protein POLGARF.

While near-cognate codons are frequently used for translation initiation in eukaryotes, their efficiencies are usually low (<10% compared to an AUG in optimal context). Here, we describe a rare case of highly efficient near-cognate initiation. A CUG triplet located in the 5' leader of POLG messenger RNA (mRNA) initiates almost as efficiently (∼60 to 70%) as an AUG in optimal context. This CUG directs translation of a conserved 260-triplet-long overlapping open reading frame (ORF), which we call POLGARF (POLG Alternative Reading Frame). Translation of a short upstream ORF 5' of this CUG governs the ratio between POLG (the catalytic subunit of mitochondrial DNA polymerase) and POLGARF synthesized from a single POLG mRNA. Functional investigation of POLGARF suggests a role in extracellular signaling. While unprocessed POLGARF localizes to the nucleoli together with its interacting partner C1QBP, serum stimulation results in rapid cleavage and secretion of a POLGARF C-terminal fragment. Phylogenetic analysis shows that POLGARF evolved ∼160 million y ago due to a mammalian-wide interspersed repeat (MIR) transposition into the 5' leader sequence of the mammalian POLG gene, which became fixed in placental mammals. This discovery of POLGARF unveils a previously undescribed mechanism of de novo protein-coding gene evolution.

Domain Truncation in Hispidin Synthase Orthologs from Non-Bioluminescent Fungi Does Not Lead to Hispidin Biosynthesis.

Hispidin is a polyketide found in plants and fungi. In bioluminescent fungi, hispidin serves as a precursor of luciferin and is produced by hispidin synthases. Previous studies revealed that hispidin synthases differ in orthologous polyketide synthases from non-bioluminescent fungi by the absence of two domains with predicted ketoreductase and dehydratase activities. Here, we investigated the hypothesis that the loss of these domains in evolution led to the production of hispidin and the emergence of bioluminescence. We cloned three orthologous polyketide synthases from non-bioluminescent fungi, as well as their truncated variants, and assessed their ability to produce hispidin in a bioluminescence assay in yeast. Interestingly, expression of the full-length enzyme hsPKS resulted in dim luminescence, indicating that small amounts of hispidin are likely being produced as side products of the main reaction. Deletion of the ketoreductase and dehydratase domains resulted in no luminescence. Thus, domain truncation by itself does not appear to be a sufficient step for the emergence of efficient hispidin synthases from orthologous polyketide synthases. At the same time, the production of small amounts of hispidin or related compounds by full-length enzymes suggests that ancestral fungal species were well-positioned for the evolution of bioluminescence.

Conjugated Dienoic Acid Peroxides as Substrates in Chaetopterus Bioluminescence System.

Biochemistry of bioluminescence of the marine parchment tubeworm Chaetopterus has been in research focus for over a century; however, the results obtained by various groups contradict each other. Here, we report the isolation and structural elucidation of three compounds from Chaetomorpha linum algae, which demonstrate bioluminescence activity with Chaetopterus luciferase in the presence of Fe2+ ions. These compounds are derivatives of polyunsaturated fatty acid peroxides. We have also obtained their structural analogues and demonstrated their activity in the bioluminescence reaction, thus confirming the broad substrate specificity of the luciferase.

Three-stage intelligent support of clinical decision making for higher trust, validity, and explainability.

The paper presents a conceptual framework for building practically applicable clinical decision support systems (CDSSs) using data-driven (DD) predictive modelling. With the proposed framework we have tried to fill the gap between experimental CDSS implementations widely covered in the literature and solutions acceptable by physicians in daily practice. The framework is based on a three-stage approach where DD model definition is accomplished with practical norms referencing (scales, clinical recommendations, etc.) and explanation of the prediction results and recommendations. The approach is aimed at increasing the applicability of CDSSs based on DD models through better integration into decision context and higher explainability. The approach has been implemented in software solutions and tested within a case study in type 2 diabetes mellitus (T2DM) prediction, enabling us to improve known clinical scales (such as FINDRISK) while keeping the problem-specific reasoning interface similar to existing applications. A survey was performed to assess and investigate the acceptance level and provide insights on the influences of the introduced framework's element on physicians' behavior.

Deep Functional Profiling of Wild Animal Microbiomes Reveals Probiotic Bacillus pumilus Strains with a Common Biosynthetic Fingerprint.

The biodiversity of microorganisms is maintained by intricate nets of interactions between competing species. Impaired functionality of human microbiomes correlates with their reduced biodiversity originating from aseptic environmental conditions and antibiotic use. Microbiomes of wild animals are free of these selective pressures. Microbiota provides a protecting shield from invasion by pathogens in the wild, outcompeting their growth in specific ecological niches. We applied ultrahigh-throughput microfluidic technologies for functional profiling of microbiomes of wild animals, including the skin beetle, Siberian lynx, common raccoon dog, and East Siberian brown bear. Single-cell screening of the most efficient killers of the common human pathogen Staphylococcus aureus resulted in repeated isolation of Bacillus pumilus strains. While isolated strains had different phenotypes, all of them displayed a similar set of biosynthetic gene clusters (BGCs) encoding antibiotic amicoumacin, siderophore bacillibactin, and putative analogs of antimicrobials including bacilysin, surfactin, desferrioxamine, and class IId cyclical bacteriocin. Amicoumacin A (Ami) was identified as a major antibacterial metabolite of these strains mediating their antagonistic activity. Genome mining indicates that Ami BGCs with this architecture subdivide into three distinct families, characteristic of the B. pumilus, B. subtilis, and Paenibacillus species. While Ami itself displays mediocre activity against the majority of Gram-negative bacteria, isolated B. pumilus strains efficiently inhibit the growth of both Gram-positive S. aureus and Gram-negative E. coli in coculture. We believe that the expanded antagonistic activity spectrum of Ami-producing B. pumilus can be attributed to the metabolomic profile predetermined by their biosynthetic fingerprint. Ultrahigh-throughput isolation of natural probiotic strains from wild animal microbiomes, as well as their metabolic reprogramming, opens up a new avenue for pathogen control and microbiome remodeling in the food industry, agriculture, and healthcare.

Possible role of small secreted peptides (SSPs) in immune signaling in bryophytes.

Plants utilize a plethora of peptide signals to regulate their immune response. Peptide ligands and their cognate receptors involved in immune signaling share common motifs among many species of vascular plants. However, the origin and evolution of immune peptides is still poorly understood. Here, we searched for genes encoding small secreted peptides in the genomes of three bryophyte lineages-mosses, liverworts and hornworts-that occupy a critical position in the study of land plant evolution. We found that bryophytes shared common predicted small secreted peptides (SSPs) with vascular plants. The number of SSPs is higher in the genomes of mosses than in both the liverwort Marchantia polymorpha and the hornwort Anthoceros sp. The synthetic peptide elicitors-AtPEP and StPEP-specific for vascular plants, triggered ROS production in the protonema of the moss Physcomitrella patens, suggesting the possibility of recognizing peptide ligands from angiosperms by moss receptors. Mass spectrometry analysis of the moss Physcomitrella patens, both the wild type and the Δcerk mutant secretomes, revealed peptides that specifically responded to chitosan treatment, suggesting their role in immune signaling.

Prediction model for thyrotoxic atrial fibrillation: a retrospective study.

BACKGROUND: Thyrotoxic atrial fibrillation (TAF) is a recognized significant complication of hyperthyroidism. Early identification of the individuals predisposed to TAF would improve thyrotoxic patients' management. However, to our knowledge, an instrument that establishes an individual risk of the condition is unavailable. Therefore, the aim of this study is to build a TAF prediction model and rank TAF predictors in order of importance using machine learning techniques. METHODS: In this retrospective study, we have investigated 36 demographic and clinical features for 420 patients with overt hyperthyroidism, 30% of which had TAF. At first, the association of these features with TAF was evaluated by classical statistical methods. Then, we developed several TAF prediction models with eight different machine learning classifiers and compared them by performance metrics. The models included ten features that were selected based on their clinical effectuality and importance for model output. Finally, we ranked TAF predictors, elicited from the optimal final model, by the machine learning tehniques. RESULTS: The best performance metrics prediction model was built with the extreme gradient boosting classifier. It had the reasonable accuracy of 84% and AUROC of 0.89 on the test set. The model confirmed such well-known TAF risk factors as age, sex, hyperthyroidism duration, heart rate and some concomitant cardiovascular diseases (arterial hypertension and conjestive heart rate). We also identified premature atrial contraction and premature ventricular contraction as new TAF predictors. The top five TAF predictors, elicited from the model, included (in order of importance) PAC, PVC, hyperthyroidism duration, heart rate during hyperthyroidism and age. CONCLUSIONS: We developed a machine learning model for TAF prediction. It seems to be the first available analytical tool for TAF risk assessment. In addition, we defined five most important TAF predictors, including premature atrial contraction and premature ventricular contraction as the new ones. These results have contributed to TAF prediction investigation and may serve as a basis for further research focused on TAF prediction improvement and facilitation of thyrotoxic patients' management.

FlashPack: Fast and Simple Preparation of Ultrahigh-performance Capillary Columns for LC-MS.

Capillary ultrahigh-pressure liquid chromatography (cUHPLC) is essential for in-depth characterization of complex biomolecule mixtures by LC-MS. We developed a simple and fast method called FlashPack for custom packing of capillary columns of 50-100 cm length with sub- 2 µm sorbent particles. FlashPack uses high sorbent concentrations of 500-1,000 mg/ml for packing at relatively low pressure of 100 bar. Column blocking by sorbent aggregation is avoided during the packing by gentle mechanical tapping of the capillary proximal end by a slowly rotating magnet bar. Utilizing a standard 100-bar pressure bomb, Flashpack allows for production of 15-25 cm cUHPLC columns within a few minutes and of 50 cm cUHPLC columns in less than an hour. Columns exhibit excellent reproducibility of back-pressure, retention time, and resolution (CV 8.7%). FlashPack cUHPLC columns are inexpensive, robust and deliver performance comparable to commercially available cUHPLC columns. The FlashPack method is versatile and enables production of cUHPLC columns using a variety of sorbent materials.

Correction to: Draft genome sequences of Hirudo medicinalis and salivary transcriptome of three closely related medicinal leeches.

An amendment to this paper has been published and can be accessed via the original article.

Draft genome sequences of Hirudo medicinalis and salivary transcriptome of three closely related medicinal leeches.

BACKGROUND: Salivary cell secretion (SCS) plays a critical role in blood feeding by medicinal leeches, making them of use for certain medical purposes even today. RESULTS: We annotated the Hirudo medicinalis genome and performed RNA-seq on salivary cells isolated from three closely related leech species, H. medicinalis, Hirudo orientalis, and Hirudo verbana. Differential expression analysis verified by proteomics identified salivary cell-specific gene expression, many of which encode previously unknown salivary components. However, the genes encoding known anticoagulants have been found to be expressed not only in salivary cells. The function-related analysis of the unique salivary cell genes enabled an update of the concept of interactions between salivary proteins and components of haemostasis. CONCLUSIONS: Here we report a genome draft of Hirudo medicinalis and describe identification of novel salivary proteins and new homologs of genes encoding known anticoagulants in transcriptomes of three medicinal leech species. Our data provide new insights in genetics of blood-feeding lifestyle in leeches.

Middle-Down Proteomic Analyses with Ion Mobility Separations of Endogenous Isomeric Proteoforms.

Biological functions of many proteins are governed by post-translational modifications (PTMs). In particular, the rich PTM complement in histones controls the gene expression and chromatin structure with major health implications via a combinatoric language. Deciphering that "histone code" is the great challenge for proteomics given an astounding number of possible proteoforms, including isomers with different PTM positions. These must be disentangled on the top- or middle-down level to preserve the key PTM connectivity, which condensed-phase separations failed to achieve. We reported the capability of ion mobility spectrometry (IMS) methods to resolve such isomers for model histone tails. Here, we advance to biological samples, showing middle-down analyses of histones from mouse embryonic stem cells via online chromatography to fractionate proteoforms with distinct PTM sets, differential or field asymmetric waveform IMS (FAIMS) to resolve the isomers, and Orbitrap mass spectrometry with electron transfer dissociation to identify the resolved species.

Quantitative Proteome and Phosphoproteome Analyses of Streptomyces coelicolor Reveal Proteins and Phosphoproteins Modulating Differentiation and Secondary Metabolism.

Streptomycetes are multicellular bacteria with complex developmental cycles. They are of biotechnological importance as they produce most bioactive compounds used in biomedicine, e.g. antibiotic, antitumoral and immunosupressor compounds. Streptomyces genomes encode many Ser/Thr/Tyr kinases, making this genus an outstanding model for the study of bacterial protein phosphorylation events. We used mass spectrometry based quantitative proteomics and phosphoproteomics to characterize bacterial differentiation and activation of secondary metabolism of Streptomyces coelicolor We identified and quantified 3461 proteins corresponding to 44.3% of the S. coelicolor proteome across three developmental stages: vegetative hypha (first mycelium); secondary metabolite producing hyphae (second mycelium); and sporulating hyphae. A total of 1350 proteins exhibited more than 2-fold expression changes during the bacterial differentiation process. These proteins include 136 regulators (transcriptional regulators, transducers, Ser/Thr/Tyr kinases, signaling proteins), as well as 542 putative proteins with no clear homology to known proteins which are likely to play a role in differentiation and secondary metabolism. Phosphoproteomics revealed 85 unique protein phosphorylation sites, 58 of them differentially phosphorylated during differentiation. Computational analysis suggested that these regulated protein phosphorylation events are implicated in important cellular processes, including cell division, differentiation, regulation of secondary metabolism, transcription, protein synthesis, protein folding and stress responses. We discovered a novel regulated phosphorylation site in the key bacterial cell division protein FtsZ (pSer319) that modulates sporulation and regulates actinorhodin antibiotic production. We conclude that manipulation of distinct protein phosphorylation events may improve secondary metabolite production in industrial streptomycetes, including the activation of cryptic pathways during the screening for new secondary metabolites from streptomycetes.

Protein encoded in human telomerase RNA is involved in cell protective pathways.

Several studies have described functional peptides encoded in RNA that are considered to be noncoding. Telomerase RNA together with telomerase reverse transcriptase and regulatory proteins make up the telomerase complex, the major component of the telomere length-maintaining machinery. In contrast to protein subunits, telomerase RNA is expressed constitutively in most somatic cells where telomerase reverse transcriptase is absent. We show here that the transcript of human telomerase RNA codes a 121 amino acid protein (hTERP). The existence of hTERP was shown by immunoblotting, immunofluorescence microscopy and mass spectroscopy. Gain-of-function and loss-of-function experiments showed that hTERP protects cells from drug-induced apoptosis and participates in the processing of autophagosome. We suggest that hTERP regulates crosstalk between autophagy and apoptosis and is involved in cellular adaptation under stress conditions.

Identification of risk factors for patients with diabetes: diabetic polyneuropathy case study.

BACKGROUND: Methods of data mining and analytics can be efficiently applied in medicine to develop models that use patient-specific data to predict the development of diabetic polyneuropathy. However, there is room for improvement in the accuracy of predictive models. Existing studies of diabetes polyneuropathy considered a limited number of predictors in one study to enable a comparison of efficiency of different machine learning methods with different predictors to find the most efficient one. The purpose of this study is the implementation of machine learning methods for identifying the risk of diabetes polyneuropathy based on structured electronic medical records collected in databases of medical information systems. METHODS: For the purposes of our study, we developed a structured procedure for predictive modelling, which includes data extraction and preprocessing, model adjustment and performance assessment, selection of the best models and interpretation of results. The dataset contained a total number of 238,590 laboratory records. Each record 27 laboratory tests, age, gender and presence of retinopathy or nephropathy). The records included information about 5846 patients with diabetes. Diagnosis served as a source of information about the target class values for classification. RESULTS: It was discovered that inclusion of two expressions, namely "nephropathy" and "retinopathy" allows to increase the performance, achieving up to 79.82% precision, 81.52% recall, 80.64% F1 score, 82.61% accuracy, and 89.88% AUC using the neural network classifier. Additionally, different models showed different results in terms of interpretation significance: random forest confirmed that the most important risk factor for polyneuropathy is the increased neutrophil level, meaning the presence of inflammation in the body. Linear models showed linear dependencies of the presence of polyneuropathy on blood glucose levels, which is confirmed by the clinical interpretation of the importance of blood glucose control. CONCLUSION: Depending on whether one needs to identify pathophysiological mechanisms for one's prospective study or identify early or late predictors, the choice of model will vary. In comparison with the previous studies, our research makes a comprehensive comparison of different decisions using a large and well-structured dataset applied to different decision support tasks.