Fungal Biol Biotechnol. 2025 Feb 13;12(1):1. doi: 10.1186/s40694-024-00192-3.

ABSTRACT

BACKGROUND: Fungal-based composites have emerged as renewable, high-performance biomaterials that are produced on lignocellulosic residual streams from forestry and agriculture. Production at an industrial scale promises to revolutionize the world humans inhabit by generating sustainable, low emission, non-toxic and biodegradable construction, packaging, textile, and other materials. The polypore Fomes fomentarius is one of the basidiomycete species used for biomaterial production, yet nothing is known about the transcriptional basis of substrate decomposition, nutrient uptake, or fungal growth during composite formation. Co-expression network analysis based on RNA-Seq profiling has enabled remarkable insights into a range of fungi, and we thus aimed to develop such resources for F. fomentarius.

RESULTS: We analysed gene expression from a wide range of laboratory cultures (n = 9) or biomaterial formation (n = 18) to determine the transcriptional landscape of F. fomentarius during substrate decomposition and to identify genes important for (i) the enzymatic degradation of lignocellulose and other plant-based substrates, (ii) the uptake of their carbon monomers, and (iii) genes guiding mycelium formation through hyphal growth and cell wall biosynthesis. Simple scripts for co-expression network construction were generated and tested, and harnessed to identify a fungal-specific transcription factor named CacA strongly co-expressed with multiple chitin and glucan biosynthetic genes or Rho GTPase encoding genes, suggesting this protein is a high-priority target for engineering adhesion and branching during composite growth. We then updated carbohydrate activated enzymes (CAZymes) encoding gene annotation, used phylogenetics to assign putative uptake systems, and applied network analysis to predict repressing/activating transcription factors for lignocellulose degradation. Finally, we identified entirely new types of co-expressed contiguous clusters not previously described in fungi, including genes predicted to encode CAZymes, hydrophobins, kinases, lipases, F-box domains, chitin synthases, amongst others.

CONCLUSION: The systems biology data generated in this study will enable us to understand the genetic basis of F. fomentarius biomaterial formation in unprecedented detail. We provided proof-of-principle for accurate network-derived predictions of gene function in F. fomentarius and generated the necessary data and scripts for analysis by any end user. Entirely new classes of contiguous co-expressed gene clusters were discovered, and multiple transcription factor encoding genes which are high-priority targets for genetic engineering were identified.

PMID:39948638 | DOI:10.1186/s40694-024-00192-3

Nat Genet. 2025 Feb 13. doi: 10.1038/s41588-025-02081-w. Online ahead of print.

ABSTRACT

Cell fate plasticity enables development, yet unlocked plasticity is a cancer hallmark. While transcription master regulators induce lineage-specific genes to restrict plasticity, it remains unclear whether plasticity is actively suppressed by lineage-specific repressors. Here we computationally predict so-called safeguard repressors for 18 cell types that block phenotypic plasticity lifelong. We validated hepatocyte-specific candidates using reprogramming, revealing that prospero homeobox protein 1 (PROX1) enhanced hepatocyte identity by direct repression of alternative fate master regulators. In mice, Prox1 was required for efficient hepatocyte regeneration after injury and was sufficient to prevent liver tumorigenesis. In line with patient data, Prox1 depletion caused hepatocyte fate loss in vivo and enabled the transition of hepatocellular carcinoma to cholangiocarcinoma. Conversely, overexpression promoted cholangiocarcinoma to hepatocellular carcinoma transdifferentiation. Our findings provide evidence for PROX1 as a hepatocyte-specific safeguard and support a model where cell-type-specific repressors actively suppress plasticity throughout life to safeguard lineage identity and thus prevent disease.

PMID:39948437 | DOI:10.1038/s41588-025-02081-w

EMBO J. 2025 Feb 13. doi: 10.1038/s44318-024-00330-y. Online ahead of print.

ABSTRACT

Although inflammation has been widely associated with cancer development, how it affects the outcomes of immunotherapy and chemotherapy remains incompletely understood. Here, we show that CKLF-like MARVEL transmembrane domain-containing member 4 (CMTM4) is highly expressed in multiple human and murine cancer types including Lewis lung carcinoma, triple-negative mammary cancer and melanoma. In lung carcinoma, loss of CMTM4 significantly reduces tumor growth and impairs NF-κB, mTOR, and PI3K/Akt pathway activation. Furthermore, we demonstrate that CMTM4 can regulate epidermal growth factor (EGF) signaling post-translationally by promoting EGFR recycling and preventing its Rab-dependent degradation. Consequently, CMTM4 knockout sensitizes human lung tumor cells to EGFR inhibitors. In addition, CMTM4 knockout tumors stimulated with EGF show a decreased ability to produce inflammatory cytokines including granulocyte colony-stimulating factor (G-CSF), leading to decreased recruitment of polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs) and therefore establishing a less suppressive tumor immune environment in both lung and mammary cancers. We also present evidence indicating that CMTM4-targeting siRNA-loaded liposomes reduce lung tumor growth in vivo and prolong animal survival. Knockout of CMTM4 enhances immune checkpoint blockade or chemotherapy to further reduce lung tumor growth. These data suggest that CMTM4 represents a novel target for the inhibition of tumor inflammation, and improvement of the immune response and tumor drug sensitivity.

PMID:39948411 | DOI:10.1038/s44318-024-00330-y

J Dairy Sci. 2025 Feb 11:S0022-0302(25)00065-7. doi: 10.3168/jds.2024-25425. Online ahead of print.

ABSTRACT

Body condition score and BW yield insights into body tissue reserves and diet, and serum biochemical measures reflect the metabolic status of cows. Associations between body composition measures and biochemistry are unclear and investigation may reveal important information on the metabolic and physiological status of cattle with varying levels of labile tissue reserves. Cohorts of 739 nonlactating, late-pregnancy, dry cows (26.9 d prepartum, SD = 12.4) and 690 peak-milk cows (58.0 DIM, SD = 14.5) were selected by stratified (parity: 1, 2, 3, >3) random sampling from 30 farms (15 pasture, 15 TMR) in this cross-sectional study. A single serum, BCS (1-5 scale), BW, and milk-production datum was collected per cow, per cohort between November 2022 and July 2023. Eleven analytes were collected, analyzed, and standardized within group (cohort/breed/farm). Mixed linear models for BCS and BW were specified, with the random effect of group. A 6-point, unordered, categorical body-group classification that combined BCS (greater, equal to, or less than group median; as high, median or low BCS) and BW (greater or less than group median; as high or low BW) was analyzed by polytomous logistic regression. Effect sizes are listed for a 1 SD increase in the specified analyte, keeping other covariables at their mean value. Dry BCS was positively associated with albumin (0.075 BCS ± 0.014 SE), urea (0.038 BCS ± 0.014 SE) and glucose (0.052 BCS ± 0.014 SE), and negatively with the interaction between cholesterol and days precalving. Dry BW positively associated with albumin (11.03 kg ± 2.48 SE) and negatively with cholesterol (-8.47 kg ± 2.57 SE). Peak-milk BCS was positively associated with albumin (0.47 BCS ± 0.015 SE), BHB (0.048 BCS ± 0.015 SE) and glucose (0.051 BCS ± 0.015 SE). Peak-milk BW was positively associated with albumin (6.94 kg ± 2.35 SE) and negatively with Ca (-7.02 kg ± 2.33 SE). Increasing BW and decreasing BCS was associated with increasing parity, except in dry second-parity cows that had low BCS. The dry polytomous model associated a 1 SD increase in albumin with a 4.89% ± 1.56 SE decreased risk of being low BCS and low BW and 5.87% ± 1.46 SE increased risk of high BCS and high BW. Risk change associated with 1 SD of glucose was -5.61% ± 1.58 SE for low BCS and high BW and 3.17% ± 1.58 SE for high BCS and high BW. For the peak-milk cohort, change in risk was associated with albumin for low BCS and low BW -3.67% ± 1.56 SE, low BCS and high BW -3.22% ± 1.53 SE. Risk change with 1 SD of BHB was -3.36% ± 1.47 SE for median BCS and low BW, 2.86% ± 1.44 SE for high BCS and low BW, and 2.69% ± 1.37 SE for high BCS and high BW. Risk of low BCS and low BW was greatest in second-parity cows, and high BCS and high BW was greatest in dry cows with greater than third parity and third-parity cows in peak milk. There were no interactions between parity and analytes. Albumin was consistently associated with BCS and BW, potentially reflecting innate differences in protein metabolism of cows.

PMID:39947600 | DOI:10.3168/jds.2024-25425

Lancet Infect Dis. 2025 Feb 10:S1473-3099(24)00769-2. doi: 10.1016/S1473-3099(24)00769-2. Online ahead of print.

ABSTRACT

There are no approved treatments for post-COVID-19 condition (also known as long COVID), a debilitating disease state following SARS-CoV-2 infection that is estimated to affect tens of millions of people. A growing body of evidence shows that SARS-CoV-2 can persist for months or years following COVID-19 in a subset of individuals, with this reservoir potentially driving long-COVID symptoms or sequelae. There is, therefore, an urgent need for clinical trials targeting persistent SARS-CoV-2, and several trials of antivirals or monoclonal antibodies for long COVID are underway. However, because mechanisms of SARS-CoV-2 persistence are not yet fully understood, such studies require important considerations related to the mechanism of action of candidate therapeutics, participant selection, duration of treatment, standardisation of reservoir-associated biomarkers and measurables, optimal outcome assessments, and potential combination approaches. In addition, patient subgroups might respond to some interventions or combinations of interventions, making post-hoc analyses crucial. Here, we outline these and other key considerations, with the goal of informing the design, implementation, and interpretation of trials in this rapidly growing field. Our recommendations are informed by knowledge gained from trials targeting the HIV reservoir, hepatitis C, and other RNA viruses, as well as precision oncology, which share many of the same hurdles facing long-COVID trials.

PMID:39947217 | DOI:10.1016/S1473-3099(24)00769-2

Int Immunopharmacol. 2025 Feb 12;150:114197. doi: 10.1016/j.intimp.2025.114197. Online ahead of print.

ABSTRACT

INTRODUCTION: Sulfur mustard (SM) is a substance that causes blisters and has been repeatedly used by Iraq in chemical warfare against more than 100,000 Iranians. The main issue for these people is various pulmonary problems similar to chronic obstructive pulmonary disease (COPD).

MATERIALS AND METHODS: Our study analyzed the total RNA profile extracted using the RNA-seq technique from peripheral blood mononuclear cells (PBMCs) isolated from Mustard Lung (ML) patients of all three groups (Severe, Moderate, and Mild) in terms of disease in healthy control (HC) subjects on the BGISEQ platform (Paired-end, 7 GB data, and rRNA depletion). However, given the severe group's importance in clinical problems, we prioritized studying this group. Differentially expressed genes (DEGs) of the severe group versus HC were obtained using the limma package. DEGs were analyzed through bioinformatics tools, and their gene ontology (GO) and enrichment analysis (EA) were evaluated. Then, String-db and Cytoscape tools were used to search for the most important functional genes.

RESULTS: We identified SERPINA1, MAPK3, MMP9, FOXO3, SLC4A1, FCGR3B, CXCR2, PTGS2, HBA2, GPX1, IL1RN, IFNG, RPS29, CXCL1, FPR1, and RPS9 genes using hub and bottleneck criteria. Based on the analysis of important genes, several biological pathways were identified, including innate immunity, inflammatory response, and activation of neutrophils, cellular response to cytokines, and cellular response to oxidative stress, lipoxygenase pathway, and macrophage differentiation.

CONCLUSION: Innate immunity and neutrophils play a crucial role in the pathogenesis of these individuals. The signaling pathways of interleukins 4, 10, and 13 stimulate the differentiation of lung macrophages (MQs) into M2, essential for repair, remodeling, and inflammation. Additionally, reactive oxygen species (ROS) activate Protein kinase B (PKB), also known as AKT, through Phosphoinositide 3-kinases (PI3K) and increase the activity of nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB), which results in decreased histone deacetylase 2 (HDAC2) being one of the important pathways of pathophysiology in these patients.

PMID:39946765 | DOI:10.1016/j.intimp.2025.114197

Plant Mol Biol. 2025 Feb 13;115(2):31. doi: 10.1007/s11103-025-01554-0.

ABSTRACT

Folates are vital one carbon donors and acceptors for a whole range of key biochemical reactions, including the biosynthesis of DNA building blocks. Plants use one carbon metabolism as a jack of all trades in their growth and development. Depletion of folates impedes root growth in Arabidopsis thaliana, but the mechanistic basis behind this function is still obscure. A global transcriptomic study hinted that folate depletion may cause misregulation of cell cycle progression. However, investigations on a direct connection thereof are scarce. We confirmed the effect of methotrexate (MTX), a folate biosynthesis inhibitor, on the expression of cell cycle genes. Subsequently, we determined the effect of MTX on root morphology and cell cycle progression through phase-specific cell cycle reporter analyses. Our study reveals that folate depletion affects the expression of cell cycle regulatory genes in roots, thereby suppressing cell cycle progression. We confirmed, through DNA labelling by EdU, that MTX treatment leads to arrest in the S phase of meristematic cells, likely due to the lack of DNA precursors. Further, we noted an accumulation of the A-type CYCA3;1 cyclin at the root tip, suggesting a possible link with the observed loss of apical dominance. Overall, our study shows that the restricted cell division and cell cycle progression is one of the reasons behind the loss of primary root growth upon folate depletion.

PMID:39946030 | DOI:10.1007/s11103-025-01554-0

J Agric Food Chem. 2025 Feb 13. doi: 10.1021/acs.jafc.4c12651. Online ahead of print.

ABSTRACT

Bitter taste perception cautions humans against the ingestion of potentially toxic compounds. However, current knowledge about natural bitter substances and their activation of human bitter taste receptors (TAS2Rs) is biased toward substances from flowering plants, whereas other sources are underrepresented. Although numerous mushrooms taste bitter, the corresponding substances and receptors are unexplored. Three previously undescribed triterpene glucosides, named oligoporins D-F, together with the known oligoporins A and B, were isolated from Amaropostia stiptica. The structures of oligoporins D-F were determined using spectroscopic analyses. The isolated oligoporins and the bitter indolalkaloid infractopicrin from Cortinarius infractus were functionally screened with all TAS2Rs. For all compounds, at least one responding receptor was identified. Oligoporin D activated TAS2R46 already at a submicromolar concentration and thus belongs to the family of most potent bitter agonists. The addition of mushroom compounds to the list of cognate TAS2R activators lowers the existing bias of knowledge about bitter agonists.

PMID:39945763 | DOI:10.1021/acs.jafc.4c12651

Appl Environ Microbiol. 2025 Feb 13:e0150124. doi: 10.1128/aem.01501-24. Online ahead of print.

ABSTRACT

Reductive dehalogenases (RDases) are essential in the anaerobic degradation of various organohalide contaminants. This family of enzymes has broad sequence diversity, but high structural conservation. There have been few studies assessing how RDase amino acid sequences affect their substrate selectivity. Here, we focus on two chloroalkane RDases, CfrA and DcrA, which have 95% protein sequence identity but have diverged to have opposite substrate preferences. CfrA dechlorinates chloroform (CF) and 1,1,1-trichloroethane (TCA) but not 1,1-dichloroethane (DCA), while DcrA will dechlorinate 1,1-DCA but not CF or 1,1,1-TCA. We mutated several residues in the active site of CfrA to investigate a change in substrate preference and to identify which wild-type residues contribute the most to substrate specialization. We determined that no individual residue solely dictates substrate discrimination, but both Y80W and F125W mutations were needed to force CfrA to prefer 1,1-DCA as a substrate. When using 1,1,2-TCA as a substrate, CfrA predominately performs hydrogenolysis to 1,2-DCA, yet the introduction of the double mutant changed this preference to dihaloelimination (forming vinyl chloride). We use predictive protein models and substrate docking to predict what interactions are made between the enzyme and substrate to aid in selection. The residues of significance identified in this study are consistent with those identified from chloroethene RDases, suggesting residue locations with a particularly high impact on activity.IMPORTANCEReductive dehalogenases (RDases) play an integral role in the removal of chlorinated solvents from the environment. These enzymes have specificity toward different chlorinated compounds, and it is known that natural variants of highly similar RDases can have distinct activities. How specific differences in protein sequence influence activity is largely unknown. In this study, we demonstrate that mutating a few residues within the active site of CfrA-a chloroform and trichloroethane-specific dehalogenase-changes its substrate preference to dichloroethane. We determine that only two mutations are needed to disrupt the native activity, underscoring the nuances in substrate-structure relationships in RDases. Though we are still far from predicting function from the sequence, this knowledge can give some insight into engineering RDases for new target contaminants.

PMID:39945532 | DOI:10.1128/aem.01501-24

J Cell Sci. 2025 Feb 13:jcs.263674. doi: 10.1242/jcs.263674. Online ahead of print.

ABSTRACT

Epithelia are vital tissues in multicellular organisms, acting as barriers between external and internal environments. Simple epithelia, such as pg those in embryos and the adult gut, have the remarkable ability to repair wounds efficiently, making them ideal for studying epithelial repair mechanisms. In these tissues, wound closure involves the coordinated action of a contractile actomyosin cable at the wound edge and collective cell movements around the wound. However, the dynamics of cell-cell interactions during this process remain poorly understood. Here, we demonstrate that Dachsous (Ds), an atypical cadherin associated with Planar Cell Polarity, is crucial for efficient epithelial repair in the Drosophila embryo. We show that the absence of Ds alters tissue mechanics and cell shape changes and rearrangements, leading to slower wound closure. Additionally, we reveal that Occluding Junctions are necessary for the proper apical localization of Ds, uncovering an unanticipated interaction between these two molecular complexes. This study identifies Ds as a novel key player in epithelial repair and highlights the need for further investigating the molecular mechanisms by which Ds modulates cell shape and tissue morphogenesis.

PMID:39945479 | DOI:10.1242/jcs.263674

Oncotarget. 2025 Feb 12;16:65-66. doi: 10.18632/oncotarget.28693.

NO ABSTRACT

PMID:39945472 | DOI:10.18632/oncotarget.28693

Anal Methods. 2025 Feb 13. doi: 10.1039/d4ay01723d. Online ahead of print.

ABSTRACT

Common methods for establishing the presence of enteric bacteria polluting water supplies, or in other samples, rely on detecting the hydrolysis of model glucuronide substrates by glucuronidases to release a phenolic product quantifiable by absorbance or fluorescence. Substrates include the β-D-glucuronides of p-nitrophenol, and umbelliferyl or quercetin derivatives. One limitation is that it may be difficult or impossible to quantify the released phenolic moiety in samples that are strongly coloured or, that contain fluorescent compounds. Exploiting the sensitivity available from the 19F nucleus to changes in chemical environment which can be detected by 19F NMR spectroscopy, and the almost complete absence of 19F from naturally-occurring samples containing organic matter, which provides background-free signals, we propose a model substrate; 4-fluorophenyl β-D-glucuronide (4FP-glucuronide). The 19F NMR chemical shift position of 4FP-glucuronide changes from -121.0 ppm upon hydrolysis to release 4-fluorophenol, at -124.9 ppm (at pH 6.8), enabling detection of β-glucuronidase activity. We illustrate the use of this substrate with environmental samples from forest soil, standing water, and mud from cattle pasture. Each of these would challenge conventional methods, owing to their opacity or the presence of coloured organic material. The technique enables detection of glucuronidases, a widely-used proxy for enteric bacteria, extending the scope of testing beyond water to include environmental and other challenging samples.

PMID:39945190 | DOI:10.1039/d4ay01723d

Front Physiol. 2025 Jan 29;15:1477070. doi: 10.3389/fphys.2024.1477070. eCollection 2024.

ABSTRACT

INTRODUCTION: Acute mountain sickness (AMS) is a common altitude illness that occurs when individuals rapidly ascend to altitudes ≥2,500 m without proper acclimatization. Genetic and genomic factors can contribute to the development of AMS or predispose individuals to susceptibility. This study aimed to investigate differential gene regulation and biological pathways to diagnose AMS from high-altitude (HA; 4,300 m) blood samples and predict AMS-susceptible (AMS+) and AMS-resistant (AMS─) individuals from sea-level (SL; 50 m) blood samples.

METHODS: Two independent cohorts were used to ensure the robustness of the findings. Blood samples were collected from participants at SL and HA. RNA sequencing was employed to profile gene expression. Differential expression analysis and pathway enrichment were performed to uncover transcriptomic signatures associated with AMS. Biomarker panels were developed for diagnostic and predictive purposes.

RESULTS: At HA, hemoglobin-related genes (HBA1, HBA2, and HBB) and phosphodiesterase 5A (PDE5A) emerged as key differentiators between AMS+ and AMS- individuals. The cAMP response element-binding protein (CREB) pathway exhibited contrasting regulatory patterns at SL and HA, reflecting potential adaptation mechanisms to hypoxic conditions. Diagnostic and predictive biomarker panels were proposed based on the identified transcriptomic signatures, demonstrating strong potential for distinguishing AMS+ from AMS- individuals.

DISCUSSION: The findings highlight the importance of hemoglobin-related genes and the CREB pathway in AMS susceptibility and adaptation to hypoxia. The differential regulation of these pathways provides novel insights into the biological mechanisms underlying AMS. The proposed biomarker panels offer promising avenues for the early diagnosis and prediction of AMS risk, which could enhance preventive and therapeutic strategies.

PMID:39944919 | PMC:PMC11813865 | DOI:10.3389/fphys.2024.1477070

Vavilovskii Zhurnal Genet Selektsii. 2024 Dec;28(8):904-917. doi: 10.18699/vjgb-24-98.

ABSTRACT

Drought is a critical factor limiting the productivity of bread wheat (Triticum aestivum L.), one of the key agricultural crops. Wheat adaptation to water deficit is ensured by complex molecular genetic mechanisms, including the coordinated work of multiple genes regulated by transcription factors and signaling non-coding RNAs, particularly microRNAs (miRNAs). miRNA-mediated regulation of gene expression is considered one of the main mechanisms of plant resistance to abiotic stresses. Studying these mechanisms necessitates computational systems biology methods. This work aims to reconstruct and analyze the gene network associated with miRNA regulation of wheat adaptation to drought. Using the ANDSystem software and the specialized Smart crop knowledge base adapted for wheat genetics and breeding, we reconstructed a wheat gene network responding to water deficit, comprising 144 genes, 1,017 proteins, and 21 wheat miRNAs. Analysis revealed that miRNAs primarily regulate genes controlling the morphogenesis of shoots and roots, crucial for morphological adaptation to drought. The key network components regulated by miRNAs are the MYBa and WRKY41 family transcription factors, heat-shock protein HSP90, and the RPM1 protein. These proteins are associated with phytohormone signaling pathways and calcium-dependent protein kinases significant in plant water deficit adaptation. Several miRNAs (MIR7757, MIR9653a, MIR9671 and MIR9672b) were identified that had not been previously discussed in wheat drought adaptation. These miRNAs regulate many network nodes and are promising candidates for experimental studies to enhance wheat resistance to water deficiency. The results obtained can find application in breeding for the development of new wheat varieties with increased resistance to water deficit, which is of substantial importance for agriculture in the context of climate change.

PMID:39944815 | PMC:PMC11811492 | DOI:10.18699/vjgb-24-98

Vavilovskii Zhurnal Genet Selektsii. 2024 Dec;28(8):940-949. doi: 10.18699/vjgb-24-101.

ABSTRACT

To systematize and effectively use the huge volume of experimental data accumulated in the field of bioinformatics and biomedicine, new approaches based on ontologies are needed, including automated methods for semantic integration of heterogeneous experimental data, methods for creating large knowledge bases and self-interpreting methods for analyzing large heterogeneous data based on deep learning. The article briefly presents the features of the subject area (bioinformatics, systems biology, biomedicine), formal definitions of the concept of ontology and knowledge graphs, as well as examples of using ontologies for semantic integration of heterogeneous data and creating large knowledge bases, as well as interpreting the results of deep learning on big data. As an example of a successful project, the Gene Ontology knowledge base is described, which not only includes terminological knowledge and gene ontology annotations (GOA), but also causal influence models (GO-CAM). This makes it useful not only for genomic biology, but also for systems biology, as well as for interpreting large-scale experimental data. An approach to building large ontologies using design patterns is discussed, using the ontology of biological attributes (OBA) as an example. Here, most of the classification is automatically computed based on previously created reference ontologies using automated inference, except for a small number of high-level concepts. One of the main problems of deep learning is the lack of interpretability, since neural networks often function as "black boxes" unable to explain their decisions. This paper describes approaches to creating methods for interpreting deep learning models and presents two examples of self-explanatory ontology-based deep learning models: (1) Deep GONet, which integrates Gene Ontology into a hierarchical neural network architecture, where each neuron represents a biological function. Experiments on cancer diagnostic datasets show that Deep GONet is easily interpretable and has high performance in distinguishing cancerous and non-cancerous samples. (2) ONN4MST, which uses biome ontologies to trace microbial sources of samples whose niches were previously poorly studied or unknown, detecting microbial contaminants. ONN4MST can distinguish samples from ontologically similar biomes, thus offering a quantitative way to characterize the evolution of the human gut microbial community. Both examples demonstrate high performance and interpretability, making them valuable tools for analyzing and interpreting big data in biology.

PMID:39944813 | PMC:PMC11813802 | DOI:10.18699/vjgb-24-101

Vavilovskii Zhurnal Genet Selektsii. 2024 Dec;28(8):982-992. doi: 10.18699/vjgb-24-105.

ABSTRACT

Neurocomputing technology is a field of interdisciplinary research and development widely applied in modern digital medicine. One of the problems of neuroimaging technology is the creation of methods for studying human brain activity in socially oriented conditions by using modern information approaches. The aim of this study is to develop a methodology for collecting and processing psychophysiological data, which makes it possible to estimate the functional states of the human brain associated with the attribution of external information to oneself or other people. Self-reference is a person's subjective assessment of information coming from the external environment as related to himself/herself. Assigning information to other people or inanimate objects is evaluating information as a message about someone else or about things. In modern neurophysiology, two approaches to the study of self-referential processing have been developed: (1) recording brain activity at rest, then questioning the participant for self-reported thoughts; (2) recording brain activity induced by self-assigned stimuli. In the presented paper, a technology was tested that combines registration and analysis of EEG with viewing facial video recordings. The novelty of our approach is the use of video recordings obtained in the first stage of the survey to induce resting states associated with recognition of information about different subjects in later stages of the survey. We have developed a software and hardware module, i. e. a set of related programs and procedures for their application consisting of blocks that allow for a full cycle of registration and processing of psychological and neurophysiological data. Using this module, brain electrical activity (EEG) indicators reflecting individual characteristics of recognition of information related to oneself and other people were compared between groups of 30 Chinese (14 men and 16 women, average age 23.2 ± 0.4 years) and 32 Russian (15 men, 17 women, average age 22.1 ± 0.4 years) participants. We tested the hypothesis that differences in brain activity in functional rest intervals between Chinese and Russian participants depend on their psychological differences in collectivism scores. It was revealed that brain functional activity depends on the subject relevance of the facial video that the participants viewed between resting-state intervals. Interethnic differences were observed in the activity of the anterior and parietal hubs of the default-mode network and depended on the subject attribution of information. In Chinese, but not Russian, participants significant positive correlations were revealed between the level of collectivism and spectral density in the anterior hub of the default-mode network in all experimental conditions for a wide range of frequencies. The developed software and hardware module is included in an integrated digital platform for conducting research in the field of systems biology and digital medicine.

PMID:39944805 | PMC:PMC11811493 | DOI:10.18699/vjgb-24-105

Vavilovskii Zhurnal Genet Selektsii. 2024 Dec;28(8):882-896. doi: 10.18699/vjgb-24-96.

ABSTRACT

The metabolomic profiles of glioblastoma and surrounding brain tissue, comprising 17 glioblastoma samples and 15 peritumoral tissue samples, were thoroughly analyzed in this investigation. The LC-MS/MS method was used to analyze over 400 metabolites, revealing significant variations in metabolite content between tumor and peritumoral tissues. Statistical analyses, including the Mann-Whitney and Cucconi tests, identified several metabolites, particularly ceramides, that showed significant differences between glioblastoma and peritumoral tissues. Pathway analysis using the KEGG database, conducted with MetaboAnalyst 6.0, revealed a statistically significant overrepresentation of sphingolipid metabolism, suggesting a critical role of these lipid molecules in glioblastoma pathogenesis. Using computational systems biology and artificial intelligence methods implemented in a cognitive platform, ANDSystem, molecular genetic regulatory pathways were reconstructed to describe potential mechanisms underlying the dysfunction of sphingolipid metabolism enzymes. These reconstructed pathways were integrated into a regulatory gene network comprising 15 genes, 329 proteins, and 389 interactions. Notably, 119 out of the 294 proteins regulating the key enzymes of sphingolipid metabolism were associated with glioblastoma. Analysis of the overrepresentation of Gene Ontology biological processes revealed the statistical significance of 184 processes, including apoptosis, the NF-kB signaling pathway, proliferation, migration, angiogenesis, and pyroptosis, many of which play an important role in oncogenesis. The findings of this study emphasize the pivotal role of sphingolipid metabolism in glioblastoma development and open new prospects for therapeutic approaches modulating this metabolism.

PMID:39944803 | PMC:PMC11811506 | DOI:10.18699/vjgb-24-96

Vavilovskii Zhurnal Genet Selektsii. 2024 Dec;28(8):927-939. doi: 10.18699/vjgb-24-100.

ABSTRACT

Parkinson's disease (PD) and vascular parkinsonism (VP) are characterized by similar neurological syndromes but differ in pathogenesis, morphology, and therapeutic approaches. The molecular genetic mechanisms of these pathologies are multifactorial and involve multiple biological processes. To comprehensively analyze the pathophysiology of PD and VP, the methods of systems biology and gene network reconstruction are essential. In the current study, we performed metabolomic screening of amino acids and acylcarnitines in blood plasma of three groups of subjects: PD patients, VP patients and the control group. Comparative statistical analysis of the metabolic profiles identified significantly altered metabolites in the PD and the VP group. To identify potential mechanisms of amino acid and acylcarnitine metabolism disorders in PD and VP, regulatory gene networks were reconstructed using ANDSystem, a cognitive system. Regulatory pathways to the enzymes converting significant metabolites were found from PD-specific genetic markers, VP-specific genetic markers, and the group of genetic markers common to the two diseases. Comparative analysis of molecular genetic pathways in gene networks allowed us to identify both specific and non-specific molecular mechanisms associated with changes in the metabolomic profile in PD and VP. Regulatory pathways with potentially impaired function in these pathologies were discovered. The regulatory pathways to the enzymes ALDH2, BCAT1, AL1B1, and UD11 were found to be specific for PD, while the pathways regulating OCTC, FURIN, and S22A6 were specific for VP. The pathways regulating BCAT2, ODPB and P4HA1 were associated with genetic markers common to both diseases. The results obtained deepen the understanding of pathological processes in PD and VP and can be used for application of diagnostic systems based on the evaluation of the amino acids and acylcarnitines profile in blood plasma of patients with PD and VP.

PMID:39944797 | PMC:PMC11811507 | DOI:10.18699/vjgb-24-100

Front Mol Biosci. 2025 Jan 29;11:1490533. doi: 10.3389/fmolb.2024.1490533. eCollection 2024.

ABSTRACT

Inflammatory Bowel Disease (IBD), which includes Ulcerative Colitis (UC) and Crohn's Disease (CD), is marked by dysbiosis of the gut microbiome. Despite therapeutic interventions with biological agents like Vedolizumab, Ustekinumab, and anti-TNF agents, the variability in clinical, histological, and molecular responses remains significant due to inter-individual and inter-population differences. This study introduces a novel approach using Individual Specific Networks (ISNs) derived from faecal microbial measurements of IBD patients across multiple cohorts. These ISNs, constructed from baseline and follow-up data post-treatment, successfully predict therapeutic outcomes based on endoscopic remission criteria. Our analysis revealed that ISNs characterised by core gut microbial families, including Lachnospiraceae and Ruminococcaceae, are predictive of treatment responses. We identified significant changes in abundance levels of specific bacterial genera in response to treatment, confirming the robustness of ISNs in capturing both linear and non-linear microbiota signals. Utilising network topological metrics, we further validated these findings, demonstrating that critical microbial features identified through ISNs can differentiate responders from non-responders with respect to various therapeutic outcomes. The study highlights the potential of ISNs to provide individualised insights into microbiota-driven therapeutic responses, emphasising the need for larger cohort studies to enhance the accuracy of molecular biomarkers. This innovative methodology paves the way for more personalised and effective treatment strategies in managing IBD.

PMID:39944755 | PMC:PMC11813754 | DOI:10.3389/fmolb.2024.1490533

Front Microbiol. 2025 Jan 29;16:1472832. doi: 10.3389/fmicb.2025.1472832. eCollection 2025.

ABSTRACT

Yeast cells sometimes engage in interspecific hybridization, i.e., crosses between different species. These interspecific yeast hybrids combine phenotypes of the two parental species and can therefore allow fast adaptation to new niches. This is perhaps most evident in beer yeasts, where a cross between Saccharomyces cerevisiae and Saccharomyces eubayanus led to the emergence of the lager yeast Saccharomyces pastorianus, which combines the fermentation capacity of S. cerevisiae with the cold tolerance of S. eubayanus, making the hybrid suitable for the typical cool lager beer fermentation conditions. Interestingly, however, merging two different genomes into one cell causes genomic instability and rearrangements, ultimately leading to a reorganized but more stable hybrid genome. Here, we investigate how different parameters influence this genome stabilization trajectory and ultimately can lead to variants with different industrial phenotypes. We generated seven de novo interspecific hybrids between two S. eubayanus strains and an ale S. cerevisiae strain, subsequently exposing them to three different genome stabilization procedures. Next, we analyzed the fermentation characteristics and metabolite production of selected stabilized hybrids. Our results reveal how variation in the genome stabilization procedure leads to phenotypic variability and can generate additional diversity after the initial hybridization process. Moreover, several stabilized hybrids showed phenotypes that are interesting for industrial applications.

PMID:39944641 | PMC:PMC11813950 | DOI:10.3389/fmicb.2025.1472832