-
The Clinical Respiratory Journal Jun 2024
Allergic Bronchopulmonary Aspergillosis (ABPA) With Colonized Aspergillus fumigatus Detected by Metagenomic Next-Generation Sequencing on Tissue Samples: A Distinct Subset of ABPA With a Higher Risk of Exacerbation.
Topics: Humans; Aspergillosis, Allergic Bronchopulmonary; Aspergillus fumigatus; Male; High-Throughput Nucleotide Sequencing; Female; Middle Aged; Metagenomics; Adult; Disease Progression; Aged
PubMed: 38886877
DOI: 10.1111/crj.13794 -
Genome Biology Jun 2024The advent of single-cell RNA-sequencing (scRNA-seq) has driven significant computational methods development for all steps in the scRNA-seq data analysis pipeline,...
BACKGROUND
The advent of single-cell RNA-sequencing (scRNA-seq) has driven significant computational methods development for all steps in the scRNA-seq data analysis pipeline, including filtering, normalization, and clustering. The large number of methods and their resulting parameter combinations has created a combinatorial set of possible pipelines to analyze scRNA-seq data, which leads to the obvious question: which is best? Several benchmarking studies compare methods but frequently find variable performance depending on dataset and pipeline characteristics. Alternatively, the large number of scRNA-seq datasets along with advances in supervised machine learning raise a tantalizing possibility: could the optimal pipeline be predicted for a given dataset?
RESULTS
Here, we begin to answer this question by applying 288 scRNA-seq analysis pipelines to 86 datasets and quantifying pipeline success via a range of measures evaluating cluster purity and biological plausibility. We build supervised machine learning models to predict pipeline success given a range of dataset and pipeline characteristics. We find that prediction performance is significantly better than random and that in many cases pipelines predicted to perform well provide clustering outputs similar to expert-annotated cell type labels. We identify characteristics of datasets that correlate with strong prediction performance that could guide when such prediction models may be useful.
CONCLUSIONS
Supervised machine learning models have utility for recommending analysis pipelines and therefore the potential to alleviate the burden of choosing from the near-infinite number of possibilities. Different aspects of datasets influence the predictive performance of such models which will further guide users.
Topics: Single-Cell Analysis; Benchmarking; RNA-Seq; Humans; Supervised Machine Learning; Sequence Analysis, RNA; Cluster Analysis; Computational Biology; Machine Learning; Animals; Single-Cell Gene Expression Analysis
PubMed: 38886757
DOI: 10.1186/s13059-024-03304-9 -
BMC Infectious Diseases Jun 2024Q fever, caused by the zoonotic pathogen Coxiella burnetii, exhibits a worldwide prevalence. In China, Q fever is not recognized as a notifiable disease, and the disease...
BACKGROUND
Q fever, caused by the zoonotic pathogen Coxiella burnetii, exhibits a worldwide prevalence. In China, Q fever is not recognized as a notifiable disease, and the disease is overlooked and underestimated in clinical practice, leading to diagnostic challenges.
CASE PRESENTATION
We present a case series of three patients diagnosed with persistent Q fever between 2022 and 2023. The average age of our three cases was 63.33 years old, consisting of two males and one female. The medical history of the individuals included previous valve replacement, aneurysm followed by aortic stent-graft placement and prosthetic hip joint replacement. At the onset of the disease, only one case exhibited acute fever, while the remaining two cases were devoid of any acute symptoms. The etiology was initially overlooked until metagenomic next-generation sequencing test identified Coxiella burnetii from the blood or biopsy samples. Delayed diagnosis was noted, with a duration ranging from three months to one year between the onset of the disease and its confirmation. The epidemiological history uncovered that none of the three cases had direct exposure to domestic animals or consumption of unpasteurized dairy products. Case 1 and 2 resided in urban areas, while Case 3 was a rural resident engaged in farming. All patients received combination therapy of doxycycline and hydroxychloroquine, and no recurrence of the disease was observed during the follow-up period.
CONCLUSION
Q fever is rarely diagnosed and reported in clinical practice in our country. We should be aware of persistent Q fever in high-risk population, even with unremarkable exposure history. Metagenomic next-generation sequencing holds great potential as a diagnostic tool for identifying rare and fastidious pathogens such as Coxiella burnetii.
Topics: Q Fever; Humans; Male; Middle Aged; Female; China; Coxiella burnetii; Aged; Delayed Diagnosis; Anti-Bacterial Agents; Doxycycline; High-Throughput Nucleotide Sequencing
PubMed: 38886677
DOI: 10.1186/s12879-024-09484-w -
BMC Genomic Data Jun 2024As a traditional Chinese medicine, Lepidium apetalum is commonly used for purging the lung, relieving dyspnea, alleviating edema, and has the significant pharmacological...
OBJECTIVES
As a traditional Chinese medicine, Lepidium apetalum is commonly used for purging the lung, relieving dyspnea, alleviating edema, and has the significant pharmacological effects on cardiovascular disease, hyperlipidemia, etc. In addition, the seeds of L. apetalum are rich in unsaturated fatty acids, sterols, glucosinolates and have a variety of biological activity compounds. To facilitate genomics, phylogenetic and secondary metabolite biosynthesis studies of L. apetalum, we assembled the high-resolution genome of L. apetalum.
DATA DESCRIPTION
We completed chromosome-level genome assembly of the L. apetalum genome (2n = 32), using Illumina HiSeq and PacBio Sequel sequencing platform as well as high-throughput chromosome conformation capture (Hi-C) technique. The assembled genome was 296.80 Mb in size, 34.41% in GC content, and 23.89% in repeated sequence content, including 316 contigs with a contig N50 of 16.31 Mb. Hi-C scaffolding resulted in 16 chromosomes occupying 99.79% of the assembled genome sequences. A total of 46 584 genes and 105 pseudogenes were predicted, 98.37% of which can be annotated to Nr, GO, KEGG, TrEMBL, SwissPort, Pfam and KOG databases. The high-quality reference genome generated by this study will provide accurate genetic information for the molecular biology research of L. apetalum.
Topics: Plants, Medicinal; Genome, Plant; Lepidium; Molecular Sequence Annotation; Chromosomes, Plant; Genomics; High-Throughput Nucleotide Sequencing; Phylogeny
PubMed: 38886663
DOI: 10.1186/s12863-024-01243-9 -
Acta Oncologica (Stockholm, Sweden) Jun 2024Recent developments in molecular genetic testing methods (e.g. next-generation sequencing [NGS]-panels) largely accelerated the process of finding the most appropriate...
UNLABELLED
Recent developments in molecular genetic testing methods (e.g. next-generation sequencing [NGS]-panels) largely accelerated the process of finding the most appropriate targeted therapeutic intervention for cancer patients based on molecularly targetable genetic alterations. In Hungary, a centralized approval system following the recommendation of the National Molecular Tumor Board was launched for the coordination of all aspects of comprehensive genetic profiling (CGP) including patient selection and therapy reimbursement.
AIM
The study aims to evaluate the clinical benefit of CGP in our Comprehensive Cancer Center Methods and patients: CGP was introduced into our routine clinical practice in 2021. An NGS-based large (> 500 genes) gene panel was used for cases where molecular genetic testing was approved by the National Molecular Tumor Board. From 2021 until August 2023 163 cases were tested. The majority of them were ECOG 0-1 patients with advanced-stage diseases, histologically rare cancer, or cancers with unknown primary tumours.
RESULTS
Seventy-four cases (74 of 163, 45%) had clinically relevant genetic alterations. In 34 patients, the identified variants represented an indication for an approved therapy (approved by the Hungarian authorities, on-label indication), while in 40 cases the recommended therapy did not have an approved indication in Hungary for certain tumour types, but off-label indication could be recommended. Based on our CGP results, 24 patients (24/163; 14.7%) received targeted therapy. Treatment duration was between 1 and 60 months. In total 14 (14/163; 8.5% of the tested cases) patients had a positive clinical response (objective response or stable disease) and were treated for more than 16 weeks.
INTERPRETATION
NGS-based CGP was successfully introduced in our institution and a significant number of patients benefited from comprehensive genetic tests. Our preliminary results can serve as the starting point of Drug Rediscovery Protocol (DRUP) studies.
Topics: Humans; Hungary; Precision Medicine; Neoplasms; Male; Female; High-Throughput Nucleotide Sequencing; Middle Aged; Aged; Adult; Genetic Testing; Aged, 80 and over; Young Adult; Adolescent; Molecular Targeted Therapy; Biomarkers, Tumor
PubMed: 38881341
DOI: 10.2340/1651-226X.2024.39918 -
Veterinary Medicine and Science Jul 2024This study presents the case of non-purulent encephalomyelitis associated with astrovirus infection in a sheep from Eastern Anatolia, Türkiye.
BACKGROUND
This study presents the case of non-purulent encephalomyelitis associated with astrovirus infection in a sheep from Eastern Anatolia, Türkiye.
METHODS
A necropsy was performed on a sheep showing nervous signs. Afterwards, brain tissue samples were taken and examined with histopathological, immunohistochemical and molecular techniques.
RESULTS
Neuropathologic changes included neuronal degeneration, diffuse gliosis, multifocal perivascular cuffing, neuronophagy and neuronal necrosis in the cerebrum, the cerebellum and the cervical spinal cord. Aerobic and anaerobic bacterial culture, selective culture for Listeria monocytogenes, and PCR analysis for rabies virus, tick-borne encephalitis virus, Türkiye encephalitis virus, small ruminant lentiviruses and border disease virus were negative. However, the presence of astrovirus RNA in cerebral, cerebellar and spinal cord samples was demonstrated by a pan-astrovirus RT-PCR. Immunohistochemical examinations revealed astrovirus antigens within the neuronal cytoplasm. High-throughput sequencing techniques identified the causative agent as a member of the genotype species Mamastrovirus 13 but representing a distinct genetic lineage with similarity to ovine astrovirus 1 in the open-reading frames (ORF)1ab region and muskox astrovirus in the ORF2 region.
CONCLUSION
This report provides evidence that astroviruses are potentially encephalitis-causing pathogens in ovine populations in Türkiye, featuring an astrovirus strain distinct from those previously identified in sheep.
Topics: Animals; Sheep; Astroviridae Infections; Sheep Diseases; High-Throughput Nucleotide Sequencing; Encephalomyelitis; Sheep, Domestic; Astroviridae; Mamastrovirus; Phylogeny
PubMed: 38879881
DOI: 10.1002/vms3.1499 -
Communications Biology Jun 2024Ulcerative colitis (UC) is a significant inflammatory bowel disease caused by an abnormal immune response to gut microbes. However, there are still gaps in our...
Ulcerative colitis (UC) is a significant inflammatory bowel disease caused by an abnormal immune response to gut microbes. However, there are still gaps in our understanding of how immune and metabolic changes specifically contribute to this disease. Our research aims to address this gap by examining mouse colons after inducing ulcerative colitis-like symptoms. Employing single-cell RNA-seq and 16 s rRNA amplicon sequencing to analyze distinct cell clusters and microbiomes in the mouse colon at different time points after induction with dextran sodium sulfate. We observe a significant reduction in epithelial populations during acute colitis, indicating tissue damage, with a partial recovery observed in chronic inflammation. Analyses of cell-cell interactions demonstrate shifts in networking patterns among different cell types during disease progression. Notably, macrophage phenotypes exhibit diversity, with a pronounced polarization towards the pro-inflammatory M1 phenotype in chronic conditions, suggesting the role of macrophage heterogeneity in disease severity. Increased expression of Nampt and NOX2 complex subunits in chronic UC macrophages contributes to the inflammatory processes. The chronic UC microbiome exhibits reduced taxonomic diversity compared to healthy conditions and acute UC. The study also highlights the role of T cell differentiation in the context of dysbiosis and its implications in colitis progression, emphasizing the need for targeted interventions to modulate the inflammatory response and immune balance in colitis.
Topics: Animals; Colitis, Ulcerative; Gastrointestinal Microbiome; Macrophages; Dextran Sulfate; Mice; Single-Cell Analysis; RNA-Seq; Mice, Inbred C57BL; Disease Models, Animal; DNA Barcoding, Taxonomic; RNA, Ribosomal, 16S; Male; Single-Cell Gene Expression Analysis
PubMed: 38879692
DOI: 10.1038/s42003-024-06409-w -
Clinical Epigenetics Jun 2024As new treatment options for patients with higher-risk myelodysplastic syndromes are emerging, identification of prognostic markers for hypomethylating agent (HMA)...
BACKGROUND
As new treatment options for patients with higher-risk myelodysplastic syndromes are emerging, identification of prognostic markers for hypomethylating agent (HMA) treatment and understanding mechanisms of their delayed and short-term responses are essential. Early fetal hemoglobin (HbF) induction has been suggested as a prognostic indicator for decitabine-treated patients. Although epigenetic mechanisms are assumed, responding patients' epigenomes have not been thoroughly examined. We aimed to clarify HbF kinetics and prognostic value for azacytidine treated patients, as well as the epigenetic landscape that might influence HbF re-expression and its clinical relevance.
RESULTS
Serial HbF measurements by high-performance liquid chromatography (n = 20) showed induction of HbF only among responders (p = 0.030). Moreover, HbF increase immediately after the first azacytidine cycle demonstrated prognostic value for progression-free survival (PFS) (p = 0.032, HR = 0.19, CI 0.24-1.63). Changes in methylation patterns were revealed with methylated DNA genome-wide sequencing analysis (n = 7) for FOG-1, RCOR-1, ZBTB7A and genes of the NuRD-complex components. Targeted pyrosequencing methodology (n = 28) revealed a strong inverse correlation between the degree of γ-globin gene (HBG2) promoter methylation and baseline HbF levels (p = 0.003, r = - 0.663). A potential epigenetic mechanism of HbF re-expression in azacytidine responders was enlightened by targeted methylation analysis, through hypomethylation of site -53 of HBG2 promoter (p = 0.039, r = - 0.504), which corresponds to MBD2-NuRD binding site, and to hypermethylation of the CpG326 island of ZBTB7A (p = 0.05, r = 0.482), a known HbF repressor. These changes were associated to blast cell clearance (p = 0.011, r = 0.480/p = 0.026, r = 0.427) and showed prognostic value for PFS (p = 0.037, HR = 1.14, CI 0.34-3.8).
CONCLUSIONS
Early HbF induction is featured as an accessible prognostic indicator for HMA treatment and the proposed potential epigenetic mechanism of HbF re-expression in azacytidine responders includes hypomethylation of the γ-globin gene promoter region and hypermethylation of the CpG326 island of ZBTB7A. The association of these methylation patterns with blast clearance and their prognostic value for PFS paves the way to discuss in-depth azacytidine epigenetic mechanism of action.
Topics: Humans; Fetal Hemoglobin; DNA Methylation; Azacitidine; Female; Male; Aged; Epigenesis, Genetic; Middle Aged; Myelodysplastic Syndromes; Prognosis; Aged, 80 and over; Leukemia, Myeloid, Acute; Antimetabolites, Antineoplastic
PubMed: 38879530
DOI: 10.1186/s13148-024-01687-x -
Briefings in Bioinformatics May 2024Neurodegenerative diseases, such as Alzheimer's disease, pose a significant global health challenge with their complex etiology and elusive biomarkers. In this study, we...
Neurodegenerative diseases, such as Alzheimer's disease, pose a significant global health challenge with their complex etiology and elusive biomarkers. In this study, we developed the Alzheimer's Identification Tool (AITeQ) using ribonucleic acid-sequencing (RNA-seq), a machine learning (ML) model based on an optimized ensemble algorithm for the identification of Alzheimer's from RNA-seq data. Analysis of RNA-seq data from several studies identified 87 differentially expressed genes. This was followed by a ML protocol involving feature selection, model training, performance evaluation, and hyperparameter tuning. The feature selection process undertaken in this study, employing a combination of four different methodologies, culminated in the identification of a compact yet impactful set of five genes. Twelve diverse ML models were trained and tested using these five genes (CNKSR1, EPHA2, CLSPN, OLFML3, and TARBP1). Performance metrics, including precision, recall, F1 score, accuracy, Matthew's correlation coefficient, and receiver operating characteristic area under the curve were assessed for the finally selected model. Overall, the ensemble model consisting of logistic regression, naive Bayes classifier, and support vector machine with optimized hyperparameters was identified as the best and was used to develop AITeQ. AITeQ is available at: https://github.com/ishtiaque-ahammad/AITeQ.
Topics: Alzheimer Disease; Humans; Machine Learning; Algorithms; Gene Expression Profiling; Transcriptome; Computational Biology; RNA-Seq
PubMed: 38877887
DOI: 10.1093/bib/bbae291 -
Briefings in Bioinformatics May 2024Single-cell sequencing has revolutionized our ability to dissect the heterogeneity within tumor populations. In this study, we present LoRA-TV (Low Rank Approximation...
Single-cell sequencing has revolutionized our ability to dissect the heterogeneity within tumor populations. In this study, we present LoRA-TV (Low Rank Approximation with Total Variation), a novel method for clustering tumor cells based on the read depth profiles derived from single-cell sequencing data. Traditional analysis pipelines process read depth profiles of each cell individually. By aggregating shared genomic signatures distributed among individual cells using low-rank optimization and robust smoothing, the proposed method enhances clustering performance. Results from analyses of both simulated and real data demonstrate its effectiveness compared with state-of-the-art alternatives, as supported by improvements in the adjusted Rand index and computational efficiency.
Topics: Single-Cell Analysis; Humans; Neoplasms; Cluster Analysis; Algorithms; Computational Biology; High-Throughput Nucleotide Sequencing; Genomics
PubMed: 38877886
DOI: 10.1093/bib/bbae277