Search Results (138)

Early diagnosis of lung cancer is crucial for improving patient prognosis. In this study, we developed a diagnostic model for lung cancer based on serum proteomic data from the GSE168198 dataset using four machine learning algorithms (nnet, glmnet, svm, and XGBoost). The model’s performance was validated on datasets that included normal controls, disease controls, and lung cancer data containing both. Furthermore, the model’s diagnostic capability was further validated on an independent external dataset. Our analysis identified SLC16A4 as a key protein in the model, which was significantly downregulated in lung cancer serum samples compared to normal controls. The expression of SLC16A4 was closely associated with clinical pathological features such as gender, tumor stage, lymph node metastasis, and smoking history. Functional assays revealed that overexpression of SLC16A4 significantly inhibited lung cancer cell proliferation and induced cellular senescence, suggesting its potential role in lung cancer development. Additionally, correlation analyses showed that SLC16A4 expression was linked to immune cell infiltration and the expression of immune checkpoint genes, indicating its potential involvement in immune escape mechanisms. Based on multi-omics data from the TCGA database, we further discovered that the low expression of SLC16A4 in lung cancer may be regulated by DNA copy number variations and DNA methylation. In conclusion, this study not only established an efficient diagnostic model for lung cancer but also identified SLC16A4 as a promising biomarker with potential applications in early diagnosis and immunotherapy. Full article

Research on structural variations in the field of crop genetics has expanded with the rapid development of genome sequencing technologies. As an important aspect of genomic variations, structural variations have a profound impact on the genetic characteristics of crops and significantly affect their key agronomic traits, such as yield, quality, and disease and stress resistance—by changing the gene arrangement order, copy number, and the positions of regulatory elements. Compared with single-nucleotide polymorphisms, structural variations present a diverse range of types, including deletions, duplications, inversions, and translocations, and their impacts are more extensive and profound. However, research on structural variations in crops still faces many challenges, for example those relating to different ploidy levels, genome repetitiveness, and their associations with phenotypes. Nevertheless, breakthroughs in long-read sequencing technologies and the integration of multi-omics data offer hope for solving these problems. A deep understanding of the impact of structural variations on crops is of great significance for accurately analyzing the evolutionary history of crops and guiding modern crop breeding, and is expected to provide strong support for global food security and the sustainable development of agriculture. Full article

The increasing rate of atmospheric nitrogen (N) deposition caused by human activities is a global concern. A rise in N deposition can alter the soil microbial community, as demonstrated by most long-term N addition experiments. Nevertheless, it remains unknown how short-term N addition influences the early succession of the soil microbial community in forests. In this study, the responses of the soil microbial community to multi-level and short-term (one-year) N addition in the soil of Larix gmelinii var. principis-rupprechtii (Mayr) Pilg. plantations in the Yanshan Mountains were explored. We used high-throughput sequencing technology to analyze the 16S rRNA of bacteria, the ITS gene of fungi, and the nifH functional gene of N-fixing bacteria. The results revealed a decrease in N-fixing functional gene abundance (such as nifH) and a slight rise in fungal and bacterial copy number due to N addition. N addition influenced the N-fixing bacterial community but had no influence on the fungal and bacterial communities in general. It drastically decreased the diversity of N-fixing microbial communities while having little impact on the diversity of fungi and bacteria. The NO₃⁻-N concentration exhibited a negative connection with the Shannon–Wiener index of the N-fixing microbial community when it exceeded a specific limit. Actinomycetes and N-fixing bacteria were significantly negatively correlated. The changes in soil NO₃⁻-N concentration and abundance of actinomycetes were the main reasons for the decrease in N-fixing microbial community diversity. The results of this study set the groundwork for exploring the initial succession mechanisms of soil microorganisms after N addition. This study offers a scientific theoretical basis for precise management of plantations under N deposition. Full article

Background: Vietnam has made significant strides in reducing the prevalence of HIV infection and achievements in its antiretroviral treatment program. However, the COVID-19 pandemic and financial challenges in the healthcare system have posed significant obstacles to maintaining effective HIV treatment and monitoring, particularly among vulnerable populations. This study aims to evaluate the situation of HIV drug resistance among patients who have experienced treatment failure in the Mekong Delta region and to compare data from 2019 to 2022. Methods: The study material was blood plasma samples from HIV-infected individuals with ART failure: 316 collected in 2019 and 326 collected in 2022. HIV-1 genotyping and mutation detection were performed based on an analysis of the nucleotide sequences of the Pol gene region. A total of 116 HIV-infected individuals with virological failure in 2019 and 2022 were assessed for HIV drug resistance. Results: The study revealed a high proportion of participants with viral loads exceeding 1000 copies/mL, significantly increasing from 12.0% in 2019 to 23.9% in 2022 (OR = 2.3; p = 0.0001). HIV drug resistance mutations were detected in 84.21% of cases in 2019 and 92.59% in 2022. The prevalence of concurrent resistance to NRTIs and NNRTIs was 37.5% and 30.13% in 2019 and 2022, respectively. There was a statistically significant decrease in NNRTI resistance (OR = 0.32, χ² = 5.43, p < 0.05). In contrast, multi-drug resistance to protease inhibitors rose from 18.52% to 45.21% (φ* = 0.00403, p < 0.05). Triple-class resistance was identified only in 2022 (17.81%). The most common mutations included M184I/V, D67N, K103N, Y181C, and V82A/S/T, with D67N rising significantly from 3.13% to 21.92%. The predominant subtype was CRF01_AE. Conclusion: A high prevalence of viral non-suppression and HIV drug resistance was observed among patients in the Mekong Delta region, particularly after the onset of the COVID-19 pandemic. Our study highlights the ongoing challenges that the HIV/AIDS treatment program in Vietnam must address in the post-pandemic period to sustain its success and achieve the goals of the country’s HIV prevention strategies. Full article

Copy number variations (CNVs), as an important structural variant in genomes, are widely present in plants, affecting their phenotype and adaptability. In recent years, CNV research has not only focused on changes in gene copy numbers but has also been linked to complex mechanisms such as genome rearrangements, transposon activity, and environmental adaptation. The advancement in sequencing technologies has made the detection and analysis of CNVs more efficient, not only revealing their crucial roles in plant disease resistance, adaptability, and growth development, but also demonstrating broad application potential in crop improvement, particularly in selective breeding and genomic selection. By studying CNV changes during the domestication process, researchers have gradually recognized the important role of CNVs in plant domestication and evolution. This article reviews the formation mechanisms of CNVs in plants, methods for their detection, their relationship with plant traits, and their applications in crop improvement. It emphasizes future research directions involving the integration of multi-omics to provide new perspectives on the structure and function of plant genomes. Full article

The identification of cancer prognostic biomarkers is crucial for predicting disease progression, optimizing personalized therapies, and improving patient survival. Molecular biomarkers are increasingly being identified for cancer prognosis estimation. However, existing studies and databases often focus on single-type molecular biomarkers, deficient in comprehensive multi-omics data integration, which constrains the comprehensive exploration of biomarkers and underlying mechanisms. To fill this gap, we conducted a systematic prognostic analysis using over 10,000 samples across 33 cancer types from The Cancer Genome Atlas (TCGA). Our study integrated nine types of molecular biomarker-related data: single-nucleotide polymorphism (SNP), copy number variation (CNV), alternative splicing (AS), alternative polyadenylation (APA), coding gene expression, DNA methylation, lncRNA expression, miRNA expression, and protein expression. Using log-rank tests, univariate Cox regression (uni-Cox), and multivariate Cox regression (multi-Cox), we evaluated potential biomarkers associated with four clinical outcome endpoints: overall survival (OS), disease-specific survival (DSS), disease-free interval (DFI), and progression-free interval (PFI). As a result, we identified 4,498,523 molecular biomarkers significantly associated with cancer prognosis. Finally, we developed SurvDB, an interactive online database for data retrieval, visualization, and download, providing a comprehensive resource for biomarker discovery and precision oncology research. Full article

Combination antiretroviral therapy (ART) suppresses detectible HIV-1 replication, but latent reservoirs and persistent immune activation contribute to residual viral-associated morbidities and potential viral reactivation. youth with HIV (YWH) virally suppressed on ART early in infection before CD4 T cell decline with fewer comorbidities compared to adults represent a critical population for identifying markers associated with viral control and predictors of viral breakthrough. This study employed a multi-omics approach to evaluate plasma biomarkers and cellular gene expression profiles in 52 participants, including 27 YWH on ART for 144 weeks and 25 youth with no infection (NI) (ages 18–24). Among the 27 YWH, 19 were virally suppressed (VS; <50 RNA copies/mL), while eight were non-suppressed (VNS; >50 RNA copies/mL). VS YWH displayed unique bioprofiles distinct from either VNS or NI. Early viral suppression mitigates inflammatory pathways and normalizes key biomarkers associated with HIV-related comorbidities. Genes upregulated in pathways linked to cellular homeostasis such as DNA repair, RNA processing, and transcription regulation may diminish viral breakthrough and maintain sustained HIV control on ART. Candidate markers and putative molecular mechanisms were identified, offering potential therapeutic targets to limit viral persistence, enhance HIV treatment strategies, and pave the way for improved clinical outcomes. Full article

We explored the rationale for treating glioblastoma (GBM) with regorafenib. In 103 newly diagnosed GBM patients, we assessed mutations, copy number variants (CNVs), fusions, and overexpression in 46 genes encoding protein kinases (PKs) potentially targeted by regorafenib or its metabolites and performed a functional enrichment analysis to assess their implications in angiogenesis. We analyzed regorafenib’s binding inhibitory activity and target affinity for these 46 PKs and focused on a subset of 18 genes inhibited by regorafenib at clinically achievable concentrations and on 19 genes involved in angiogenesis. Putative oncogenic alterations were defined as oncogenic/likely oncogenic mutations, oncogenic fusions, CNVs > 5, and/or gene overexpression. Regorafenib did not target all 46 PKs. For the 46-gene set, 40 genes (86.9%) and 73 patients (70.8%) harbored at least one alteration in genes encoding targetable PKs, but putative oncogenic alterations were present in only 34 patients (33%). In the 18-gene set, 18 genes (100%) and 48 patients (46.6%) harbored alterations, but putative oncogenic alterations were detected in only 26 patients (25.2%). Thirty patients (29.1%) had oncogenic alterations in the 18-gene set and/or in angiogenesis-related genes. Around 33% of patients had oncogenic alterations in any of the 46 potential targets. Additionally, the suboptimal dosing of regorafenib, due to its poor penetration of the blood–brain barrier, may reduce the likelihood of effectively targeting certain PKs. Future use of multi-target drugs must be guided by a thorough understanding of target presence, effective inhibition, and the drug’s ability to reach brain tumors at adequate concentrations. Full article

Endometrial cancer (EC), a prevalent gynecological malignancy, presents significant challenges due to its genetic complexity and heterogeneity. The genomic landscape of EC is underpinned by genetic alterations, such as mutations in PTEN, PIK3CA, and ARID1A, and chromosomal abnormalities. The identification of molecular subtypes—POLE ultramutated, microsatellite instability (MSI), copy number low, and copy number high—illustrates the diverse genetic profiles within EC and underscores the need for subtype-specific therapeutic strategies. The integration of multi-omics technologies such as single-cell genomics and spatial transcriptomics has revolutionized our understanding and approach to studying EC and offers a holistic perspective that enhances the ability to identify novel biomarkers and therapeutic targets. The translation of these multi-omics findings into personalized medicine and precision oncology is increasingly feasible in clinical practice. Targeted therapies such as PI3K/AKT/mTOR inhibitors have demonstrated the potential for improved treatment efficacy tailored to specific genetic alterations. Despite these advancements, challenges persist in terms of variability in patient responses, the integration of genomic data into clinical workflows, and ethical considerations. This review explores the genomic underpinnings of EC, from genes to clinical practice. It highlights the ongoing need for multidisciplinary research and collaboration to address the complexities of EC and improve diagnosis, treatment, and patient outcomes. Full article

Allergic diseases commonly coexist, manifesting in a sequence described as the “allergic march”. Background/Objectives: This study aimed to evaluate TSLP’s and IL-1β’s potential as biomarkers in both single and multi-pediatric atopic diseases like atopic eczema, food allergy, and anaphylaxis and analyze specific SNPs in the TSLP and IL-1β genes to determine their associations with their occurrence and severity. Methods: This analysis included 109 atopic children diagnosed with atopic dermatitis, food allergy, or anaphylaxis alongside a control group of 57 non-atopic children. Recruitment was facilitated through the use of a comprehensive questionnaire. For the study population, the allergen profile was characterized at the molecular level by measuring specific IgE to purified natural or recombinant allergens, assessing serum levels of circulating TSLP and IL-1β, and identifying single-nucleotide polymorphisms in TSLP (rs2289277) and IL-1β (rs16944 C-511T). Results: The serum levels of TSLP and IL-1β were elevated in the study groups compared to the control group, highlighting their significance in the pathogenesis of the studied diseases. Carrying a higher number of the risk allele [C] in the TSLP SNP rs2289277 is associated with the greatest likelihood of having multiple concurrent allergic conditions, with the highest risk observed in individuals with all three conditions—atopic dermatitis, food allergy, and anaphylaxis, simultaneously. Moreover, children carrying the risk allele had a twofold increased risk of polysensitization, which rose to sixfold in those with two copies of the risk allele. Although no significant variations in genotype frequencies were detected for IL-1β rs16944, significant associations were observed for TSLP rs2289277, particularly with conditions such as atopic dermatitis, food allergy, anaphylaxis, and combinations of these diseases. Conclusions: Further research is required to elucidate these pathways and their role in the development of allergic diseases. Full article

Trypanosoma cruzi is the causative agent of Chagas disease, a neglected tropical disease, and one of the most important parasitic diseases worldwide. The first genome of T. cruzi was sequenced in 2005, and its complexity made assembly and annotation challenging. Nowadays, new sequencing methods have improved some strains’ genome sequence and annotation, revealing this parasite’s extensive genetic diversity and complexity. In this review, we examine the genetic diversity, the genomic structure, and the principal multi-gene families involved in the pathogenicity of T. cruzi. The T. cruzi genome sequence is divided into two compartments: the core (conserved) and the disruptive (variable in length and multicopy gene families among strains). The disruptive region has also been described as genome plasticity and plays a key role in the parasite survival and infection process. This region comprises several multi-gene families, including trans-sialidases, mucins, and mucin-associated surface proteins (MASPs). Trans-sialidases are the most prevalent genes in the genome with a key role in the infection process, while mucins and MASPs are also significant glycosylated proteins expressed on the parasite surface, essential for its biological functions, as host–parasite interaction, host cell invasion or protection against the host immune system, in both insect and mammalian stages. Collectively, in this review, some of the most recent advances in the structure and composition of the T. cruzi genome are reviewed. Full article

Precision fermentation processes, especially when using edited microorganisms, demand accuracy in the bioengineering process to maximize the desired outcome and to avoid adverse effects. The selection of target sites to edit using CRISPR/Cas9 can be complex, resulting in non-controlled consequences. Therefore, the use of multi-omics strategies can help in the design, selection and efficiency of genetic editing. In this study, we present a multi-omics approach based on targeted metabolite analysis and transcriptomics for the designing of CRISPR/Cas9 in baker’s yeast as a more efficient strategy to select editing regions. Multi-omics shows potential to reveal new metabolic bottlenecks and to elucidate new metabolic fluxes, which could be a key factor in minimizing the metabolic burden in edited microorganisms. In our model, we focus our attention on the isoprenoid synthesis due to their industrial interest. Targeted metabolite detection combined with a transcriptomic analysis revealed hydroxymethylglutaryl-CoA reductases (HMGs) as the best target gene to induce an increase in isoprenoid synthesis. Thus, an extra copy of HMG1 was introduced using, for the first time, the synthetic UADH1 promoter. The multi-omics analysis of the recombinant strain results in an accurate assessment of yeast behavior during the most important growth phases, highlighting the metabolic burden, Crabtree effect or the diauxic shift during culture. Full article

Alzheimer’s disease (AD) is a complex neurodegenerative disorder influenced by various genetic factors. In addition to the well-established amyloid precursor protein (APP), Presenilin-1 (PSEN1), Presenilin-2 (PSEN2), and apolipoprotein E (APOE), several other genes such as Sortilin-related receptor 1 (SORL1), Phospholipid-transporting ATPase ABCA7 (ABCA7), Triggering Receptor Expressed on Myeloid Cells 2 (TREM2), Phosphatidylinositol-binding clathrin assembly protein (PICALM), and clusterin (CLU) were implicated. These genes contribute to neurodegeneration through both gain-of-function and loss-of-function mechanisms. While it was traditionally thought that heterozygosity in autosomal recessive mutations does not lead to disease, haploinsufficiency was linked to several conditions, including cancer, autism, and intellectual disabilities, indicating that a single functional gene copy may be insufficient for normal cellular functions. In AD, the haploinsufficiency of genes such as ABCA7 and SORL1 may play significant yet under-explored roles. Paradoxically, heterozygous knockouts of PSEN1 or PSEN2 can impair synaptic plasticity and alter the expression of genes involved in oxidative phosphorylation and cell adhesion. Animal studies examining haploinsufficient AD risk genes, such as vacuolar protein sorting-associated protein 35 (VPS35), sirtuin-3 (SIRT3), and PICALM, have shown that their knockout can exacerbate neurodegenerative processes by promoting amyloid production, accumulation, and inflammation. Conversely, haploinsufficiency in APOE, beta-secretase 1 (BACE1), and transmembrane protein 59 (TMEM59) was reported to confer neuroprotection by potentially slowing amyloid deposition and reducing microglial activation. Given its implications for other neurodegenerative diseases, the role of haploinsufficiency in AD requires further exploration. Modeling the mechanisms of gene knockout and monitoring their expression patterns is a promising approach to uncover AD-related pathways. However, challenges such as identifying susceptible genes, gene–environment interactions, phenotypic variability, and biomarker analysis must be addressed. Enhancing model systems through humanized animal or cell models, utilizing advanced research technologies, and integrating multi-omics data will be crucial for understanding disease pathways and developing new therapeutic strategies. Full article

The thymidylate kinase (tmk) gene is indispensable for the proliferation and survival of phytoplasma. To reveal the molecular variation and phylogeny of the tmk genes of Candidatus phytoplasma ziziphi, in this study, the tmk genes of 50 phytoplasma strains infecting different resistant and susceptible jujube cultivars from different regions in China were amplified and analyzed. Two sequence types, tmk-x and tmk-y, were identified using clone-based sequencing. The JWB phytoplasma strains were classified into three types, type-X, type-Y, and type-XY, based on the sequencing chromatograms of the tmk genes. The type-X and type-Y strains contained only tmk-x and tmk-y genes, respectively. The type-XY strain contained both tmk-x and tmk-y genes. The type-X, type-Y, and type-XY strains comprised 42%, 12%, and 46% of all the strains, respectively. The type-X and type-XY strains were identified in both susceptible and resistant jujube cultivars, while type-Y strain was only identified in susceptible cultivars. Phylogenetic analysis indicated that the tmk genes of the phytoplasmas were divided into two categories: phylo-S and phylo-M. The phylo-S tmk gene was single-copied in the genome, with an evolutionary pattern similar to the 16S rRNA gene; the phylo-M tmk gene was multi-copied, related to PMU-mediated within-genome transposition and between-genome transfer. Furthermore, the phylogenetic tree suggested that the tmk genes shuttled between the genomes of the Paulownia witches’ broom phytoplasma and JWB phytoplasma. These findings provide insights into the evolutionary and adaptive mechanisms of phytoplasmas. Full article

The accurate diagnosis and identification of Leishmania species are crucial for the therapeutic selection and effective treatment of leishmaniasis. This study aims to develop and evaluate the use of high-resolution melting curve analysis (HRM)-PCR for Leishmania species identification causing visceral leishmaniasis (VL), post-kala-azar dermal leishmaniasis (PKDL) and cutaneous leishmaniasis (CL) in the Indian subcontinent. Two multi-copy targets (ITS-1 and 7SL-RNA genes) were selected, and an HRM-PCR assay was established using L. donovani, L. major, and L. tropica standard strain DNA. The assay was applied on 93 clinical samples with confirmed Leishmania infection, including VL (n = 30), PKDL (n = 50), and CL (n = 13) cases. The ITS-1 HRM-PCR assay detected as little as 0.01 pg of template DNA for L. major and up to 0.1 pg for L. donovani and L. tropica. The detection limit for the 7SL-RNA HRM-PCR was 1 pg for L. major and 10 pg for L. donovani and L. tropica. The ITS-1 HRM-PCR identified 68 out of 93 (73.11%) leishmaniasis cases, whereas 7SL-RNA HRM-PCR could only detect 18 out of 93 (19.35%) cases. A significant correlation was observed between the kDNA-based low Ct values and ITS-1 HRM-PCR positivity in the VL (p = 0.007), PKDL (p = 0.0002), and CL (p = 0.03) samples. The ITS-1 HRM-PCR assay could identify Leishmania spp. causing different clinical forms of leishmaniasis in the Indian subcontinent, providing rapid and accurate results that can guide clinical management and treatment decisions. Full article