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).

A hybrid pathway for self-sustained luminescence.

The fungal bioluminescence pathway can be reconstituted in other organisms allowing luminescence imaging without exogenously supplied substrate. The pathway starts from hispidin biosynthesis-a step catalyzed by a large fungal polyketide synthase that requires a posttranslational modification for activity. Here, we report identification of alternative compact hispidin synthases encoded by a phylogenetically diverse group of plants. A hybrid bioluminescence pathway that combines plant and fungal genes is more compact, not dependent on availability of machinery for posttranslational modifications, and confers autonomous bioluminescence in yeast, mammalian, and plant hosts. The compact size of plant hispidin synthases enables additional modes of delivery of autoluminescence, such as delivery with viral vectors.

Mesenchymal stem cells-derived extracellular vesicles for therapeutics of renal tuberculosis.

Extrapulmonary tuberculosis with a renal involvement can be a manifestation of a disseminated infection that requires therapeutic intervention, particularly with a decrease in efficacy of conventional regimens. In the present study, we investigated the therapeutic potency of mesenchymal stem cell-derived extracellular vesicles (MSC-EVs) in the complex anti-tuberculosis treatment (ATT). A rabbit model of renal tuberculosis (rTB) was constructed by injecting of the standard strain Mycobacterium tuberculosis H37Rv into the cortical layer of the kidney parenchyma. Isolated rabbit MSC-EVs were intravenously administered once as an addition to standard ATT (isoniazid, pyrazinamide, and ethambutol). The therapeutic efficacy was assessed by analyzing changes of blood biochemical biomarkers and levels of anti- and pro-inflammatory cytokines as well as by renal computed tomography with subsequent histological and morphometric examination. The therapeutic effect of therapy with MSC-EVs was shown by ELISA method that confirmed a statistically significant increase of the anti-inflammatory and decrease of pro-inflammatory cytokines as compared to conventional treatment. In addition, there is a positive trend in increase of ALP level, animal weigh, and normalization of ADA activity that can indicate an improvement of kidney state. A significant reduction of the area of specific and interstitial inflammation indicated positive affect of MSC-EVs that suggests a shorter duration of ATT. The number of MSC-EVs proteins (as identified by mass-spectometry analysis) with anti-microbial, anti-inflammatory and immunoregulatory functions reduced the level of the inflammatory response and the severity of kidney damage (further proved by morphometric analysis). In conclusion, MSC-EVs can be a promising tool for the complex treatment of various infectious diseases, in particularly rTB.

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.

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.

Machine Learning Methods for Pregnancy and Childbirth Risk Management.

Machine learning methods enable medical systems to automatically generate data-driven decision support models using real-world data inputs, eliminating the need for explicit rule design. In this research, we investigated the application of machine learning methods in healthcare, specifically focusing on pregnancy and childbirth risks. The timely identification of risk factors during early pregnancy, along with risk management, mitigation, prevention, and adherence management, can significantly reduce adverse perinatal outcomes and complications for both mother and child. Given the existing burden on medical professionals, clinical decision support systems (CDSSs) can play a role in risk management. However, these systems require high-quality decision support models based on validated medical data that are also clinically interpretable. To develop models for predicting childbirth risks and due dates, we conducted a retrospective analysis of electronic health records from the perinatal Center of the Almazov Specialized Medical Center in Saint-Petersburg, Russia. The dataset, which was exported from the medical information system, consisted of structured and semi-structured data, encompassing a total of 73,115 lines for 12,989 female patients. Our proposed approach, which includes a detailed analysis of predictive model performance and interpretability, offers numerous opportunities for decision support in perinatal care provision. The high predictive performance achieved by our models ensures precise support for both individual patient care and overall health organization management.

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.

Study of the User Behaviour Caused by Automatic Recommendation Systems Call to Action.

Diagnostics accuracy and usability of symptom checkers have been researched in several studies. Their ability to set a correct diagnosis especially in the urgent cases is questionable. There is one aspect of symptom checkers that has not been deeply studied yet. It is their ability to motivate patients to follow up after receiving a direct recommendation and to decrease a load on the health care professionals. The goal of this research is to study how patients behave after receiving a recommendation from a symptom checker and motivation of this behavior. We studied how patients react on the symptom checker recommendations and the motivation behind this behavior. In total we invited 3615 patients to have a symptom checker screening; 2374 of them agreed to run a symptom checker screening; 867 of them agreed to participate in the study. The proportion of the patients who agreed to have a symptom checker screening. So, we can clearly see that symptom checker screening doesn't result in a significant decrease of the load on healthcare professionals. This is supported by the quantitative study results. The patients emphasized the ease of use of the tool and clearness of the recommendations it gives. However, they perceived it as rather a second opinion tool or a tool that helps to prepare to the doctor's visit.

Structuring Research Directions in Medical Domain with Topic Modeling: Application for PhD Theses Synopses in Dentistry.

The study analyzed scientific texts based on a manually created database of synopses of theses in dentistry. The main goal was to structure medical texts into various topics by means of natural language processing techniques (topic modeling). Furthermore, a dynamic topic modeling showed the most popular in the field of dentistry over almost the last thirty years.

Mesenchymal stromal cell-derived extracellular vesicles afford neuroprotection by modulating PI3K/AKT pathway and calcium oscillations.

Mesenchymal stromal cells (MSC) are widely recognized as potential effectors in neuroprotective therapy. The protective properties of MSC were considered to be associated with the secretion of extracellular vesicles (MSC-EV). We explored the effects of MSC-EV in vivo on models of traumatic and hypoxia-ischemia (HI) brain injury. Neuroprotective mechanisms triggered by MSC-EV were also studied in vitro using a primary neuroglial culture. Intranasal administration of MSC-EV reduced the volume of traumatic brain damage, correlating with a recovery of sensorimotor functions. Neonatal HI-induced brain damage was mitigated by the MSC-EV administration. This therapy also promoted the recovery of sensorimotor functions, implying enhanced neuroplasticity, and MSC-EV-induced growth of neurites in vitro supports this. In the in vitro ischemic model, MSC-EV prevented cell calcium (Ca2+) overload and subsequent cell death. In mixed neuroglial culture, MSC-EV induced inositol trisphosphate (IP3) receptor-related Ca2+ oscillations in astrocytes were associated with resistance to calcium overload not only in astrocytes but also in co-cultured neurons, demonstrating intercellular positive crosstalk between neural cells. This implies that phosphatidylinositol 3-Kinase/AKT signaling is one of the main pathways in MSC-EV-mediated protection of neural cells exposed to ischemic challenge. Components of this pathway were identified among the most enriched categories in the MSC-EV proteome.

Hybrid Bayesian Network-Based Modeling: COVID-19-Pneumonia Case.

The primary goal of this paper is to develop an approach for predicting important clinical indicators, which can be used to improve treatment. Using mathematical predictive modeling algorithms, we examined the course of COVID-19-based pneumonia (CP) with inpatient treatment. Algorithms used include dynamic and ordinary Bayesian networks (OBN and DBN), popular ML algorithms, the state-of-the-art auto ML approach and our new hybrid method based on DBN and auto ML approaches. Predictive targets include treatment outcomes, length of stay, dynamics of disease severity indicators, and facts of prescribed drugs for different time intervals of observation. Models are validated using expert knowledge, current clinical recommendations, preceding research and classic predictive metrics. The characteristics of the best models are as follows: MAE of 3.6 days of predicting LOS (DBN plus FEDOT auto ML framework), 0.87 accuracy of predicting treatment outcome (OBN); 0.98 F1 score for predicting facts of prescribed drug (DBN). Moreover, the advantage of the proposed approach is Bayesian network-based interpretability, which is very important in the medical field. After the validation of other CP datasets for other hospitals, the proposed models can be used as part of the decision support systems for improving COVID-19-based pneumonia treatment. Another important finding is the significant differences between COVID-19 and non-COVID-19 pneumonia.

Molecular Basis of the Slow Growth of Mycoplasma hominis on Different Energy Sources.

Mycoplasma hominis is an opportunistic urogenital pathogen in vertebrates. It is a non-glycolytic species that produces energy via arginine degradation. Among genital mycoplasmas, M. hominis is the most commonly reported to play a role in systemic infections and can persist in the host for a long time. However, it is unclear how M. hominis proceeds under arginine limitation. The recent metabolic reconstruction of M. hominis has demonstrated its ability to catabolize deoxyribose phosphate to produce ATP. In this study, we cultivated M. hominis on two different energy sources (arginine and thymidine) and demonstrated the differences in growth rate, antibiotic sensitivity, and biofilm formation. Using label-free quantitative proteomics, we compared the proteome of M. hominis under these conditions. A total of 466 proteins were identified from M. hominis, representing approximately 85% of the predicted proteome, while the levels of 94 proteins changed significantly. As expected, we observed changes in the levels of metabolic enzymes. The energy source strongly affects the synthesis of enzymes related to RNA modifications and ribosome assembly. The translocation of lipoproteins and other membrane-associated proteins was also impaired. Our study, the first global characterization of the proteomic switching of M. hominis in arginine-deficiency media, illustrates energy source-dependent control of pathogenicity factors and can help to determine the mechanisms underlying the interaction between the growth rate and fitness of genome-reduced bacteria.

Gene Silencing through CRISPR Interference in Mycoplasmas.

Mycoplasmas are pathogenic, genome-reduced bacteria. The development of such fields of science as system and synthetic biology is closely associated with them. Despite intensive research of different representatives of this genus, genetic manipulations remain challenging in mycoplasmas. Here we demonstrate a single-plasmid transposon-based CRISPRi system for the repression of gene expression in mycoplasmas. We show that selected expression determinants provide a level of dCas9 that does not lead to a significant slow-down of mycoplasma growth. For the first time we describe the proteomic response of genome-reduced bacteria to the expression of exogenous dcas9. The functionality of the resulting vector is confirmed by targeting the three genes coding transcription factors-fur, essential spxA, whiA, and histone-like protein hup1 in Mycoplasma gallisepticum. As a result, the expression level of each gene was decreased tenfold and influenced the mRNA level of predicted targets of transcription factors. To illustrate the versatility of this vector, we performed a knockdown of metabolic genes in a representative member of another cluster of the Mycoplasma genus-Mycoplasma hominis. The developed CRISPRi system is a powerful tool to discover the functioning of genes that are essential, decipher regulatory networks and that can help to identify novel drug targets to control Mycoplasma infections.

Streptocinnamides A and B, Depsipeptides from Streptomyces sp. KMM 9044.

The bacterium Streptomyces sp. KMM 9044 from a sample of marine sediment collected in the northwestern part of the Sea of Japan produces highly chlorinated depsiheptapeptides streptocinnamides A (1) and B (2), representatives of a new structural group of antibiotics. The structures of 1 and 2 were determined using nuclear magnetic resonance and mass spectrometry studies and confirmed by a series of chemical transformations. Streptocinnamide A potently inhibits Micrococcus sp. KMM 1467, Arthrobacter sp. ATCC 21022, and Mycobacterium smegmatis MC2 155.

Distinct and diverse chromatin proteomes of ageing mouse organs reveal protein signatures that correlate with physiological functions.

Temporal molecular changes in ageing mammalian organs are of relevance to disease aetiology because many age-related diseases are linked to changes in the transcriptional and epigenetic machinery that regulate gene expression. We performed quantitative proteome analysis of chromatin-enriched protein extracts to investigate the dynamics of the chromatin proteomes of the mouse brain, heart, lung, kidney, liver, and spleen at 3, 5, 10, and 15 months of age. Each organ exhibited a distinct chromatin proteome and sets of unique proteins. The brain and spleen chromatin proteomes were the most extensive, diverse, and heterogenous among the six organs. The spleen chromatin proteome appeared static during the lifespan, presenting a young phenotype that reflects the permanent alertness state and important role of this organ in physiological defence and immunity. We identified a total of 5928 proteins, including 2472 nuclear or chromatin-associated proteins across the six mouse organs. Up to 3125 proteins were quantified in each organ, demonstrating distinct and organ-specific temporal protein expression timelines and regulation at the post-translational level. Bioinformatics meta-analysis of these chromatin proteomes revealed distinct physiological and ageing-related features for each organ. Our results demonstrate the efficiency of organelle-specific proteomics for in vivo studies of a model organism and consolidate the hypothesis that chromatin-associated proteins are involved in distinct and specific physiological functions in ageing organs.

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.

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.

An Unsupervised Approach to Structuring and Analyzing Repetitive Semantic Structures in Free Text of Electronic Medical Records.

Electronic medical records (EMRs) include many valuable data about patients, which is, however, unstructured. Therefore, there is a lack of both labeled medical text data in Russian and tools for automatic annotation. As a result, today, it is hardly feasible for researchers to utilize text data of EMRs in training machine learning models in the biomedical domain. We present an unsupervised approach to medical data annotation. Syntactic trees are produced from initial sentences using morphological and syntactical analyses. In retrieved trees, similar subtrees are grouped using Node2Vec and Word2Vec and labeled using domain vocabularies and Wikidata categories. The usage of Wikidata categories increased the fraction of labeled sentences 5.5 times compared to labeling with domain vocabularies only. We show on a validation dataset that the proposed labeling method generates meaningful labels correctly for 92.7% of groups. Annotation with domain vocabularies and Wikidata categories covered more than 82% of sentences of the corpus, extended with timestamp and event labels 97% of sentences got covered. The obtained method can be used to label EMRs in Russian automatically. Additionally, the proposed methodology can be applied to other languages, which lack resources for automatic labeling and domain vocabulary.

Thymidine utilisation pathway is a novel phenotypic switch of Mycoplasma hominis.

Introduction. Mycoplasma hominis is a bacterium belonging to the class Mollicutes. It causes acute and chronic infections of the urogenital tract. The main features of this bacterium are an absence of cell wall and a reduced genome size (517-622 protein-encoding genes). Previously, we have isolated morphologically unknown M. hominis colonies called micro-colonies (MCs) from the serum of patients with inflammatory urogenital tract infection.Hypothesis. MCs are functionally different from the typical colonies (TCs) in terms of metabolism and cell division.Aim. To determine the physiological differences between MCs and TCs of M. hominis and elucidate the pathways of formation and growth of MCs by a comparative proteomic analysis of these two morphological forms.Methodology. LC-MS proteomic analysis of TCs and MCs using an Ultimate 3000 RSLC nanoHPLC system connected to a QExactive Plus mass spectrometer.Results. The study of the proteomic profiles of M. hominis colonies allowed us to reconstruct their energy metabolism pathways. In addition to the already known pentose phosphate and arginine deamination pathways, M. hominis can utilise ribose phosphate and deoxyribose phosphate formed by nucleoside catabolism as energy sources. Comparative proteomic HPLC-MS analysis revealed that the proteomic profiles of TCs and MCs were different. We assume that MC cells preferably utilised deoxyribonucleosides, particularly thymidine, as an energy source rather than arginine or ribonucleosides. Utilisation of deoxyribonucleosides is less efficient as compared with that of ribonucleosides and arginine in terms of energy production. Thymidine phosphorylase DeoA is one of the key enzymes of deoxyribonucleosides utilisation. We obtained a DeoA overexpressing mutant that exhibited a phenotype similar to that of MCs, which confirmed our hypothesis.Conclusion. In addition to the two known pathways for energy production (arginine deamination and the pentose phosphate pathway) M. hominis can use deoxyribonucleosides and ribonucleosides. MC cells demonstrate a reorganisation of energy metabolism: unlike TC cells, they preferably utilise deoxyribonucleosides, particularly thymidine, as an energy source rather than arginine or ribonucleosides. Thus MC cells enter a state of energy starvation, which helps them to survive under stress, and in particular, to be resistant to antibiotics.

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.