Omics A Journal of Integrative Biology最新文献

Phytophthora meadii is a polyphagous oomycete causing fatal diseases in economically important cash crops such as rubber, arecanut, cardamom, and other crops and plants of economic significance. Although information on the proteogenomic and proteomic analysis is available for several Phytophthora species, no information on the proteome repertoire of P. meadii is available. In the present study, a gel-free protein annotation was performed using liquid chromatography with tandem mass spectrometry analysis of the P. meadii hyphae, followed by bioinformatics analysis. The results were compared with a global Phytophthora proteome database-based search and an in-house P. meadii genome database, along with RefSeq proteome databases of other selected species of Phytophthora. A total of 7725 and 3979 proteins were exclusively matched with global and in-house databases, respectively. Basic Local Alignment Search Tool analysis showed 209 unique peptide sequences belonging to 85 proteins of P. meadii. Gene Ontology-based functional analysis of the P. meadii mycelial proteome categorized the proteins based on their role in cellular components, molecular functions, and biological processes. Kyoto Encyclopedia of Genes and Genomes pathway and protein-protein network analysis further revealed the role of these proteins in growth and development functions. In addition, proteins potentially involved in virulence, infections in the host system, and several signaling mechanisms were deduced. The current study is the first report on the P. meadii mycelial proteins under optimum growth conditions. These omics data also have socioeconomic implications since Phytophthora causes disease in a wide range of economically noteworthy crops and forest ecosystems.

The Rugose Spiraling Whitefly (RSW) (Aleurodicus rugioperculatus Martin), a pest native to Central America, infests coconut palms and has been introduced to other regions of the world including North America (e.g., Florida) and Southeast Asia. In India, RSW was first reported in 2016, and rapidly expanded to multiple states nationwide. Currently, RSW has growing global relevance as an agricultural insect pest. In addition to coconut, the RSW exhibits a broad host range, causing damage to various palms, fruit crops such as guava, vegetables, and ornamental shrubs. In this study, we present a high-quality draft genome assembly for this insect pest, generated using Pacific Bioscience long-read HiFi sequencing. The assembled genome spans 1.10 Gb, with a contig N50 value of 10.23 Mb. Approximately 521 Mb of sequences, accounting for 47.30% of the genome, were identified as repeat elements. The assembly includes 35,884 predicted coding sequences and exhibits high completeness, with 98.4% of Benchmarking Universal Single-Copy Orthologs genes recovered for the core insect gene set. The sequencing of the RSW genome offers valuable insights into the biology of one of the most significant and pervasive agricultural pests. The expansion of gene families associated with insecticide resistance may indicate this pest's ability to metabolize selective insecticides. These data have the potential to greatly enhance strategies for managing the RSW insect population size and limiting its invasive capacity for pest control. Additionally, the genome provides a foundation for comparative studies of whitefly genomes, and possibly informing the future design and development of novel insecticides.

Sickle cell disease (SCD) affects nearly 300,000 newborns annually worldwide, with 80% born in Africa. Sickle cell nephropathy (SCN) affects 5-18% of patients with SCD and contributes significantly to morbidity and mortality. Identifying SCN-associated factors would promote effective clinical management. We conducted a global systematic review in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analysis guidelines (Prospective Register of Systematic Reviews, registration number: CRD42020185763) to explore clinical and genetic correlates of SCN. We sought after cohort, case-control, and cross-sectional studies published up to December 31, 2024 that reported on clinical and/or genetic predictors of SCN in different populations globally. A total of 70 hospital-based study articles were finally included, with a leading percentage (45.7%) of the included studies performed in the United States, whereas 24.3% were from Sub-Saharan Africa. Most had a cross-sectional design (68.6%) involving children and adults. Genetic studies (17/70) identified associations with α-thalassemia, APOL1, and HMOX1 genes. The only genome-wide association study identified six suggestive variants in CRYL1, VWF, ADAMTS7, LRP1B, linc02288, and FPGT-TNNI3K/TNNI3K among adult patients. In conclusion, this systematic review (1) unpacks and highlights the role of clinical, genetic, and biochemical factors in the pathogenesis and progression of SCN and (2) reveals the consistent association of SCN with the 3.7 Kb deletion in HBA and variants in APOL1 and HMOX1 genes. This systematic review underscores the paucity of data from Africa, emphasizing the need for large-scale prospective studies on African SCN cohorts. Our findings also provide a foundation for the early identification of individuals at risk for SCN and the avenues for clinical and public health management strategies. To the best of our knowledge, this is the first systematic review summarizing risk factors for kidney dysfunction in SCD populations worldwide, which includes, specifically, a meta-analysis for APOL1 association with albuminuria.

Asthma is a heterogeneous respiratory disease with complex pathogenesis involving immune dysregulation, environmental triggers, and increasingly recognized to have contributions from the human microbiome. Emerging evidence from longitudinal birth cohorts and multi-omics studies reveals that early-life microbial colonization patterns in both the gastrointestinal and respiratory tracts play a crucial role in shaping immune trajectories and influencing asthma susceptibility. This expert review highlights the findings from pivotal studies that associate dysbiosis in the gut and airway microbiota with asthma development and its diverse phenotypic manifestations. Reduced abundance of immunomodulatory genera such as Bifidobacterium, Faecalibacterium, and Lachnospira in the gut has been consistently associated with increased asthma risk. In the airways, increased colonization by potentially pathogenic taxa, including Moraxella, Haemophilus, and Streptococcus, correlates with viral respiratory infections and persistent wheezing. Microbiome diversity patterns also differ between asthma phenotypes: eosinophilic asthma typically features a community profile closer to healthy individuals, while neutrophilic asthma is marked by enrichment of pro-inflammatory bacterial species. Moreover, protective genera such as Dolosigranulum and Corynebacterium in the upper airways are associated with lower risk of asthma and reduced respiratory infections. Elucidating these microbiome-mediated mechanisms holds promise for the development of targeted microbiota-based strategies for asthma prevention and phenotype-specific therapeutic interventions. The present review unpacks these localized microbial patterns and their mechanistic implications for asthma development, severity, and endotypic variation. Finally, unraveling the microbiome-asthma axis from airway and gut microbial communities also has implications for new ways of thinking personalized medicine in the future.

Cyclin-dependent kinase 12 (CDK12) is thought to play an important role in cancer biology pathogenesis and development. Novel, selective, safe, and effective CDK12 inhibitors are actively sought after in drug discovery and clinical development. We report here the structure-based discovery of two novel CDK12 inhibitors using integrated molecular docking, simulation, and molecular mechanics Poisson-Boltzmann surface area methods. We performed a virtual high-throughput screening of potential inhibitors sourced from the ZINC database, which contains ∼90,000 molecules. Various filters were applied to separate bioactive molecules using Lipinski's rule of five, Absorption, Distribution, Metabolism, Excretion, and Toxicity properties, Ghose filters, and Pan-assay interference compound filters. Furthermore, the elucidated compounds were subjected to molecular docking to evaluate their binding toward the target. Interaction analysis of the selected compounds showed favorable interactions with the active site pocket residues of CDK12 for ZINC 02096057 and ZINC 02094702. These two compounds modulate both the active and adenosine triphosphate (ATP)-binding sites of the target CDK12, inhibiting its biological activity. Moreover, flavopiridol, a known inhibitor of CDK12, was used to cross-check with the selected ligands to validate our findings. Molecular dynamics simulation was performed at 500 ns to evaluate the dynamics of each atom in the system. Finally, we suggest that ZINC 02096057 and ZINC 02094702 offer prospects as novel inhibitors of CDK12, which warrant further in vitro and in vivo studies. Cancer therapeutics specifically, and drug discovery more generally, stand to benefit from novel molecular leads for CDK12 inhibition.

Major depressive disorder (MDD) is a complex mental health condition whose causes may extend beyond purely biological explanations and are increasingly understood within wider ecological and social frameworks. Emerging research on the human gut-brain axis with the help of statistical and artificial intelligence tools aims to elucidate the links between the gut microbiota, diet, environment, and MDD. In this study, we analyzed data from the American Gut Project (AGP), including 361 control and 23 MDD samples, to find potential biomarkers associated with MDD. While alpha and beta diversity analyses revealed no significant differences except for age, multiple differential abundance tools and machine learning (ML) models (Random Forest and XGBoost), whose results were analyzed using Shapley Additive Explanations values, consistently detected a decrease in Bifidobacterium adolescentis and increases in Odoribacter, Ruminococcus, and Adlercreutzia among MDD samples. These four organisms influence inflammation, neurotransmitter balance, gut permeability, and other pathways associated with depression and thus can be recognized as potential biomarkers for MDD. This study highlights the promise of ML to decode the gut-brain axis as a first step in biomarker discovery, thus providing new possibilities for a personalized treatment approach and an improvement in diagnostic tools for MDD.

Circadian rhythm and the sleep/wake cycle can influence metabolic regulation, eating habits, hormone release, and common chronic health conditions such as obesity, depression, diabetes, and sleep disorders. Drosophila melanogaster, the fruit fly, with its conserved molecular clocks and accessible assays, has been used as an ideal model system to study biological processes, for example, circadian rhythms, sleep, neurodevelopment, genetics, and behavior. Using an integrated approach combining high-throughput locomotor activity monitoring and untargeted metabolomics, we analyzed the behavioral and metabolic effects of a chronobiotic melatonin. The behavioral activity of fruit flies was recorded using an infrared-based monitoring device, followed by data analysis with open-source data packages ShinyR-DAM and VANESSA. We found that 1 mM and 4 mM melatonin doses significantly increased Drosophila locomotor activity. Melatonin at a high concentration (4 mM) exhibited a protective effect to reduce mortality in Drosophila. Despite these changes, melatonin preserved the flies' endogenous bimodal activity pattern, maintaining circadian alignment. Metabolomics analysis using high-performance liquid chromatography-mass spectrometry identified differentially abundant metabolites after melatonin administration compared with the vehicle treatment. We discovered 20 biologically relevant metabolites altered by melatonin, including key perturbations in arginine biosynthesis, alanine/aspartate/glutamate metabolism, and pyrimidine pathways. Notably, melatonin upregulated glutamine, a potential indicator of enhanced neurotransmitter synthesis and broadly modulated amino acid and nucleotide metabolism, suggesting dual roles in neuroprotection and energy homeostasis. This high-throughput omics study uncovers melatonin-induced behavioral and metabolic perturbations in Drosophila as a model organism, revealing how melatonin modulates locomotor activity and circadian integrity through specific alterations in metabolism.

Precision oncology aims to deliver individually tailored interventions in clinical management of cancers, which remain a global health challenge. Cancer immunotherapy is a field of precision oncology that can benefit from nanotechnology and nanomaterials. Nanotechnology, material science, and drug delivery fields have thus begun converging with precision oncology. However, advances in nanomaterials are not adequately covered in this field. The present expert review aims to address this gap in biomedical literature. Carbon quantum dots (CQDs), a new-generation nanomaterial, have attracted vast interest owing to their unique properties, including notable electrical conductivity, chemical stability, eco-friendly behavior, and strong fluorescence. Their high versatility and low-cost synthesis have replaced conventional quantum dots for about a decade. Recent advances demonstrate CQDs' potential in targeted drug delivery, bioimaging, and immunomodulation for cancer treatment. Their physicochemical properties enable precise tumor targeting while minimizing damage to healthy tissues. CQDs can be functionalized with biomolecules to enhance tumor specificity and cellular uptake, making them ideal carriers for chemotherapeutic agents. Their intrinsic photoluminescence facilitates real-time monitoring of drug distribution. Emerging evidence suggests CQDs can stimulate immune responses by modulating tumor microenvironments. Despite promising applications, challenges remain in synthesis standardization and toxicological profiling. Future studies should focus on optimizing CQD formulations and minimizing cytotoxicity to maximize their therapeutic potential, paving the way for safer, more effective, and personalized treatments for precision oncology and nanomedicine.

Idiopathic pulmonary fibrosis (IPF) and pulmonary hypertension (PH) are two chronic conditions that can coexist occasionally, resulting in high morbidity and mortality. Despite their clinical association, the underlying genetic mechanisms and therapeutic targets that might link these two chronic disorders remain poorly understood. The present study used in silico analyses and machine learning to uncover genetic features and potential therapeutic targets shared by IPF and PH. Differentially expressed genes (DEGs) were identified using RNA sequencing data from the Gene Expression Omnibus, which revealed a total of 13 common DEGs between IPF and PH. Importantly, among the identified genes, TFF3 was significantly upregulated in both diseases. TFF3 is targeted by aminoglutethimide as identified through the Drug Gene Interaction Database, and with an interaction score of 3.26. Using the Protein Contact Atlas, PROCHECK, PROSA, and ProtParam tools, the structural model of TFF3 was validated. Finally, molecular docking analysis demonstrated a binding affinity score of -6.1 kcal/mol between TFF3 and aminoglutethimide, indicating a stable and potentially effective interaction between aminoglutethimide and the target protein. Aminoglutethimide displayed favorable ADMET properties as well. In conclusion, this in silico study reports (1) potential overlapping molecular links between IPF and PH, and (2) in silico potential of aminoglutethimide and TFF3 in drug repurposing for therapeutic interventions targeting both IPF and PH. These findings also challenge the traditional paradigm of pharmaceutical innovation that has long relied on the "one drug, one disease" premise, and highlight the potentials of "one drug, polydisease" paradigm of drug discovery and development.

Network medicine considers the interconnectedness of human diseases and their underlying molecular substrates. In this context, sarcoidosis and pulmonary hypertension (PH) have long been thought of as distinct diseases, but there is growing evidence of shared molecular mechanisms. This study reports on common differentially expressed genes (DEGs), regulatory elements, and pathways between the two diseases. Publicly available transcriptomic datasets for sarcoidosis (GSE157671) and PH (GSE236251) were retrieved from the Gene Expression Omnibus database. DEGs were identified using GEO2R, followed by pathway enrichment and gene interaction analyses via GeneMANIA and STRING. Importantly, a total of 13 common DEGs were identified between sarcoidosis and PH, with 7 upregulated and 6 downregulated genes. The SMAD2/3 nuclear pathway was a shared enriched pathway, suggesting a role in fibrosis and immune regulation. There were also divergences between sarcoidosis and PH. For example, gene set enrichment analysis indicated significant associations of the IFN-gamma signaling pathway with sarcoidosis and the TNF-alpha signaling with PH. miRNA network analysis identified hsa-miR-34a-5p, hsa-let-7g-5p, and hsa-miR-19a-3p as key shared regulators linked to common genes in both sarcoidosis and PH. Finally, DGIdb analysis revealed potential therapeutic candidates targeting these genes in both diseases. This study contributes to the field of drug design and discovery from a network medicine standpoint. The shared molecular links uncovered between sarcoidosis and PH in this study point to several potential biomarkers and therapeutic targets. Further experimental validation and translational medical research are called for diagnostics and drugs, which can effectively and safely help the clinical management of both diseases.