BACKGROUND AND OBJECTIVE: Severe courses of COVID-19 disease can lead to long-term complications. The post-acute phase of COVID-19 refers to the persistent or new symptoms. This problem is becoming more relevant with the increasing number of patients who have contracted COVID-19 and the emergence of new virus variants. In this case, preventive treatment with corticosteroids can be applied. However, not everyone benefits from the treatment, moreover, it can have severe side effects. Currently, no study would analyze who benefits from the treatment. METHODS: This work introduces a novel approach to the recommendation of Corticosteroid (CS) treatment for patients in the post-acute phase. We have used a novel combination of clinical data, including blood tests, spirometry, and X-ray images from 273 patients. These are very challenging to collect, especially from patients in the post-acute phase of COVID-19. To our knowledge, no similar dataset exists in the literature. Moreover, we have proposed a unique methodology that combines machine learning and deep learning models based on Vision Transformer (ViT) and InceptionNet, preprocessing techniques, and pretraining strategies to deal with the specific characteristics of our data. RESULTS: The experiments have proved that combining clinical data with CXR images achieves 8% higher accuracy than independent analysis of CXR images. The proposed method reached 80.0% accuracy (78.7% balanced accuracy) and a ROC-AUC of 0.89. CONCLUSIONS: The introduced system for CS treatment prediction using our neural network and learning algorithm is unique in this field of research. Here, we have shown the efficiency of using mixed data and proved it on real-world data. The paper also introduces the factors that could be used to predict long-term complications. Additionally, this system was deployed to the hospital environment as a recommendation tool, which admits the clinical application of the proposed methodology.

• Klíčová slova
• Chest X-ray images, Clinical data, Image classification, Post-acute COVID-19, Treatment prediction, Vision transformer,
• Publikační typ
• časopisecké články MeSH

Molecular docking is a widely used technique in drug discovery to predict the binding mode of a given ligand to its target. However, the identification of the near-native binding pose in docking experiments still represents a challenging task as the scoring functions currently employed by docking programs are parametrized to predict the binding affinity, and, therefore, they often fail to correctly identify the ligand native binding conformation. Selecting the correct binding mode is crucial to obtaining meaningful results and to conveniently optimizing new hit compounds. Deep learning (DL) algorithms have been an area of a growing interest in this sense for their capability to extract the relevant information directly from the protein-ligand structure. Our review aims to present the recent advances regarding the development of DL-based pose selection approaches, discussing limitations and possible future directions. Moreover, a comparison between the performances of some classical scoring functions and DL-based methods concerning their ability to select the correct binding mode is reported. In this regard, two novel DL-based pose selectors developed by us are presented.

• Klíčová slova
• Artificial intelligence, Deep learning, Molecular docking, Pose selection, Scoring functions,
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH

FGF21 is an endocrine signaling protein belonging to the family of fibroblast growth factors (FGFs). It has emerged as a molecule of interest for treating various metabolic diseases due to its role in regulating glucogenesis and ketogenesis in the liver. However, FGF21 is prone to heat, proteolytic, and acid-mediated degradation, and its low molecular weight makes it susceptible to kidney clearance, significantly reducing its therapeutic potential. Protein engineering studies addressing these challenges have generally shown that increasing the thermostability of FGF21 led to improved pharmacokinetics. Here, we describe the computer-aided design and experimental characterization of FGF21 variants with enhanced melting temperature up to 15 °C, uncompromised efficacy at activation of MAPK/ERK signaling in Hep G2 cell culture, and ability to stimulate proliferation of Hep G2 and NIH 3T3 fibroblasts cells comparable with FGF21-WT. We propose that stabilizing the FGF21 molecule by rational design should be combined with other reported stabilization strategies to maximize the pharmaceutical potential of FGF21.

• Klíčová slova
• Fibroblast growth factor 21, Protein engineering, Protein stabilization,
• Publikační typ
• časopisecké články MeSH

Precise localization and dissection of gene promoters are key to understanding transcriptional gene regulation and to successful bioengineering applications. The core RNA polymerase II initiation machinery is highly conserved among eukaryotes, leading to a general expectation of equivalent underlying mechanisms. Still, less is known about promoters in the plant kingdom. In this study, we employed cap analysis of gene expression (CAGE) at three embryonic developmental stages in barley to accurately map, annotate, and quantify transcription initiation events. Unsupervised discovery of de novo sequence clusters grouped promoters based on characteristic initiator and position-specific core-promoter motifs. This grouping was complemented by the annotation of transcription factor binding site (TFBS) motifs. Integration with genome-wide epigenomic data sets and gene ontology (GO) enrichment analysis further delineated the chromatin environments and functional roles of genes associated with distinct promoter categories. The TATA-box presence governs all features explored, supporting the general model of two separate genomic regulatory environments. We describe the extent and implications of alternative transcription initiation events, including those that are specific to developmental stages, which can affect the protein sequence or the presence of regions that regulate translation. The generated promoterome dataset provides a valuable genomic resource for enhancing the functional annotation of the barley genome. It also offers insights into the transcriptional regulation of individual genes and presents opportunities for the informed manipulation of promoter architecture, with the aim of enhancing traits of agronomic importance.

• Klíčová slova
• Cap Analysis of Gene Expression, Core promoter, Hordeum vulgare, Initiator, Morex, TOR-signaling, Transcription regulation,
• Publikační typ
• časopisecké články MeSH

Computational models of gene regulations help to understand regulatory mechanisms and are extensively used in a wide range of areas, e.g., biotechnology or medicine, with significant benefits. Unfortunately, there are only a few computational gene regulatory models of whole genomes allowing static and dynamic analysis due to the lack of sophisticated tools for their reconstruction. Here, we describe Augusta, an open-source Python package for Gene Regulatory Network (GRN) and Boolean Network (BN) inference from the high-throughput gene expression data. Augusta can reconstruct genome-wide models suitable for static and dynamic analyses. Augusta uses a unique approach where the first estimation of a GRN inferred from expression data is further refined by predicting transcription factor binding motifs in promoters of regulated genes and by incorporating verified interactions obtained from databases. Moreover, a refined GRN is transformed into a draft BN by searching in the curated model database and setting logical rules to incoming edges of target genes, which can be further manually edited as the model is provided in the SBML file format. The approach is applicable even if information about the organism under study is not available in the databases, which is typically the case for non-model organisms including most microbes. Augusta can be operated from the command line and, thus, is easy to use for automated prediction of models for various genomes. The Augusta package is freely available at github.com/JanaMus/Augusta. Documentation and tutorials are available at augusta.readthedocs.io.

• Klíčová slova
• Databases, Gene interactions, Mutual information, Python package, Transcription factor binding motifs,
• Publikační typ
• časopisecké články MeSH

The RE1-Silencing Transcription factor (REST) is essential for neuronal differentiation. Here, we report the first 18.5-angstrom electron microscopy structure of human REST. The refined electron map suggests that REST forms a torus that can accommodate DNA double-helix in the central hole. Additionally, we quantitatively described REST binding to the canonical DNA sequence of the neuron-restrictive silencer element. We developed protocols for the expression and purification of full-length REST and the shortened variant REST-N62 produced by alternative splicing. We tested the mutual interaction of full-length REST and the splicing variant REST-N62. Revealed structure-function relationships of master neuronal repressor REST will allow finding new biological ways of prevention and treatment of neurodegenerative disorders and diseases.

• Klíčová slova
• CD, circular dichroism, CoIP, coimmunoprecipitation, DLS, dynamic light scattering, Differentiation, EM, EM, electron microscopy, Electron microscopy, IDRs, intrinsically disordered regions, NRSE, neuron-restrictive silencer element, NRSF, NRSF, neuron-restrictive silencer factor, Neuron-restrictive silencer factor, Neuronal, PCNA, proliferating cell nuclear antigen, RD1/2, repressor domain 1/2, RE1, repressor element-1, RE1-silencing transcription factor, REST, REST, RE1-silencing transcription factor, REST-FL, full-length REST, REST-N62, REST-N62, splicing isoform of REST, also known as REST4 or REST4-S3, REST4, ZF, zinc finger, aa, amino acid(s), bp, base pair(s), kDa, kilodaltons,
• Publikační typ
• časopisecké články MeSH

Crocosphaera and Cyanothece are both unicellular, nitrogen-fixing cyanobacteria that prefer different environments. Whereas Crocosphaera mainly lives in nutrient-deplete, open oceans, Cyanothece is more common in coastal, nutrient-rich regions. Despite their physiological similarities, the factors separating their niches remain elusive. Here we performed physiological experiments on clone cultures and expand upon a simple ecological model to show that their different niches can be sufficiently explained by the observed differences in their photosynthetic capacities and rates of carbon (C) consumption. Our experiments revealed that Cyanothece has overall higher photosynthesis and respiration rates than Crocosphaera. A simple growth model of these microorganisms suggests that C storage and consumption are previously under-appreciated factors when evaluating the occupation of niches by different marine nitrogen fixers.

• Klíčová slova
• Carbon consumption, Niche separation, UCYN-B, UCYN-C,
• Publikační typ
• časopisecké články MeSH

Polyhydroxyalkanoates (PHAs) have emerged as an environmentally friendly alternative to conventional polyesters. In this study, we present a comprehensive analysis of the genomic and phenotypic characteristics of three non-model thermophilic bacteria known for their ability to produce PHAs: Schlegelella aquatica LMG 23380T, Caldimonas thermodepolymerans DSM 15264, and C. thermodepolymerans LMG 21645 and the results were compared with the type strain C. thermodepolymerans DSM 15344T. We have assembled the first complete genomes of these three bacteria and performed the structural and functional annotation. This analysis has provided valuable insights into the biosynthesis of PHAs and has allowed us to propose a comprehensive scheme of carbohydrate metabolism in the studied bacteria. Through phylogenomic analysis, we have confirmed the synonymity between Caldimonas and Schlegelella genera, and further demonstrated that S. aquatica and S. koreensis, currently classified as orphan species, belong to the Caldimonas genus.

• Klíčová slova
• Caldimonas, DSM 15264, DSM 15344T, LMG 21645, LMG 23380T, Next-Generation Industrial Biotechnology, PHAs, Schlegelella, de novo assembly,
• Publikační typ
• časopisecké články MeSH

The fibroblast growth factors (FGF) family holds significant potential for addressing chronic diseases. Specifically, recombinant FGF18 shows promise in treating osteoarthritis by stimulating cartilage formation. However, recent phase 2 clinical trial results of sprifermin (recombinant FGF18) indicate insufficient efficacy. Leveraging our expertise in rational protein engineering, we conducted a study to enhance the stability of FGF18. As a result, we obtained a stabilized variant called FGF18-E4, which exhibited improved stability with 16 °C higher melting temperature, resistance to trypsin and a 2.5-fold increase in production yields. Moreover, the FGF18-E4 maintained mitogenic activity after 1-week incubation at 37 °C and 1-day at 50 °C. Additionally, the inserted mutations did not affect its binding to the fibroblast growth factor receptors, making FGF18-E4 a promising candidate for advancing FGF-based osteoarthritis treatment.

• Klíčová slova
• Computer-assisted stabilization, FGF-18, Fibroblast growth factor, Improved yield, Protease, Resistance to, Thermostability,
• Publikační typ
• časopisecké články MeSH

Potassium is an essential intracellular ion, and a sufficient intracellular concentration of it is crucial for many processes; therefore it is fundamental for cells to precisely regulate K+ uptake and efflux through the plasma membrane. The uniporter Trk1 is a key player in K+ acquisition in yeasts. The TRK1 gene is expressed at a low and stable level; thus the activity of the transporter needs to be regulated at a posttranslational level. S. cerevisiae Trk1 changes its activity and affinity for potassium ion quickly and according to both internal and external concentrations of K+, as well as the membrane potential. The molecular basis of these changes has not been elucidated, though phosphorylation is thought to play an important role. In this study, we examined the role of the second, short, and highly conserved intracellular hydrophilic loop of Trk1 (IL2), and identified two phosphorylable residues (Ser882 and Thr900) as very important for 1) the structure of the loop and consequently for the targeting of Trk1 to the plasma membrane, and 2) the upregulation of the transporter's activity reaching maximal affinity under low external K+ conditions. Moreover, we identified three residues (Thr155, Ser414, and Thr900) within the Trk1 protein as strong candidates for interaction with 14-3-3 regulatory proteins, and showed, in an in vitro experiment, that phosphorylated Thr900 of the IL2 indeed binds to both isoforms of yeast 14-3-3 proteins, Bmh1 and Bmh2.

• Klíčová slova
• 14–3–3 proteins, Phosphorylation, Potassium ion uptake, Saccharomyces cerevisiae, Trk1,
• Publikační typ
• časopisecké články MeSH