Search Results (4)

Background/Objectives: Massively parallel sequencing technologies have advanced chronic lymphocytic leukemia (CLL) diagnostics and precision oncology. Illumina platforms, while offering robust performance, require substantial infrastructure investment and a large number of samples for cost-efficiency. Conversely, third-generation long-read nanopore sequencing from Oxford Nanopore Technologies (ONT) can significantly reduce sequencing costs, making it a valuable tool in resource-limited settings. However, nanopore sequencing faces challenges with lower accuracy and throughput than Illumina platforms, necessitating additional computational strategies. In this paper, we demonstrate that integrating publicly available short-read data with in-house generated ONT data, along with the application of machine learning approaches, enables the characterization of the CLL transcriptome landscape, the identification of clinically relevant molecular subtypes, and the assignment of these subtypes to nanopore-sequenced samples. Methods: Public Illumina RNA sequencing data for 608 CLL samples were obtained from the CLL-Map Portal. CLL transcriptome analysis, gene module identification, and transcriptomic subtype classification were performed using the oposSOM R package for high-dimensional data visualization with self-organizing maps. Eight CLL patients were recruited from the Hematology Center After Prof. R. Yeolyan (Yerevan, Armenia). Sequencing libraries were prepared from blood total RNA using the PCR-cDNA sequencing-barcoding kit (SQK-PCB109) following the manufacturer’s protocol and sequenced on an R9.4.1 flow cell for 24–48 h. Raw reads were converted to TPM values. These data were projected into the SOMs space using the supervised SOMs portrayal (supSOM) approach to predict the SOMs portrait of new samples using support vector machine regression. Results: The CLL transcriptomic landscape reveals disruptions in gene modules (spots) associated with T cell cytotoxicity, B and T cell activation, inflammation, cell cycle, DNA repair, proliferation, and splicing. A specific gene module contained genes associated with poor prognosis in CLL. Accordingly, CLL samples were classified into T-cell cytotoxic, immune, proliferative, splicing, and three mixed types: proliferative–immune, proliferative–splicing, and proliferative–immune–splicing. These transcriptomic subtypes were associated with survival orthogonal to gender and mutation status. Using supervised machine learning approaches, transcriptomic subtypes were assigned to patient samples sequenced with nanopore sequencing. Conclusions: This study demonstrates that the CLL transcriptome landscape can be parsed into functional modules, revealing distinct molecular subtypes based on proliferative and immune activity, with important implications for prognosis and treatment that are orthogonal to other molecular classifications. Additionally, the integration of nanopore sequencing with public datasets and machine learning offers a cost-effective approach to molecular subtyping and prognostic prediction, facilitating more accessible and personalized CLL care. Full article

The diagnosis and management of fragile X syndrome (FXS) have significantly improved in the last three decades, although the current diagnostic techniques are not yet able to precisely identify the number of repeats, methylation status, level of mosaicism, and/or the presence of AGG interruptions. A high number of repeats (>200) in the fragile X messenger ribonucleoprotein 1 gene (FMR1) results in hypermethylation of promoter and gene silencing. The actual molecular diagnosis is performed using a Southern blot, TP-PCR (Triplet-Repeat PCR), MS-PCR (Methylation-Specific PCR), and MS-MLPA (Methylation-Specific MLPA) with some limitations, with multiple assays being necessary to completely characterise a patient with FXS. The actual gold standard diagnosis uses Southern blot; however, it cannot accurately characterise all cases. Optical genome mapping is a new technology that has also been developed to approach the diagnosis of fragile X syndrome. Long-range sequencing represented by PacBio and Oxford Nanopore has the potential to replace the actual diagnosis and offers a complete characterization of molecular profiles in a single test. The new technologies have improved the diagnosis of fragile X syndrome and revealed unknown aberrations, but they are a long way from being used routinely in clinical practice. Full article

In contrast to bacteria, microbiome analyses often neglect archaea, but also eukaryotes. This is partly because they are difficult to culture due to their demanding growth requirements, or some even have to be classified as uncultured microorganisms. Consequently, little is known about the relevance of archaea in human health and diseases. Contemporary broad availability and spread of next generation sequencing techniques now enable a stronger focus on such microorganisms, whose cultivation is difficult. However, due to the enormous evolutionary distances between bacteria, archaea and eukaryotes, the implementation of sequencing strategies for smaller laboratory scales needs to be refined to achieve as a holistic view on the microbiome as possible. Here, we present a technical approach that enables simultaneous analyses of archaeal, bacterial and eukaryotic microbial communities to study their roles in development and courses of respiratory disorders. We thus applied combinatorial 16S-/18S-rDNA sequencing strategies for sequencing-library preparation. Considering the lower total microbiota density of airway surfaces, when compared with gut microbiota, we optimized the DNA purification workflow from nasopharyngeal swab specimens. As a result, we provide a protocol that allows the efficient combination of bacterial, archaeal, and eukaryotic libraries for nanopore-sequencing using Oxford Nanopore Technologies MinION devices and subsequent phylogenetic analyses. In a pilot study, this workflow allowed the identification of some environmental archaea, which were not correlated with airway microbial communities before. Moreover, we assessed the protocol’s broader applicability using a set of human stool samples. We conclude that the proposed protocol provides a versatile and adaptable tool for combinatorial studies on bacterial, archaeal, and eukaryotic microbiomes on a small laboratory scale. Full article

The scale of the ongoing SARS-CoV-2 pandemic warrants the urgent establishment of a global decentralized surveillance system to recognize local outbreaks and the emergence of novel variants of concern. Among available deep-sequencing technologies, nanopore-sequencing could be an important cornerstone, as it is mobile, scalable, and cost-effective. Therefore, streamlined nanopore-sequencing protocols need to be developed and optimized for SARS-CoV-2 variants identification. We adapted and simplified existing workflows using the ‘midnight’ 1200 bp amplicon split primer sets for PCR, which produce tiled overlapping amplicons covering almost the entire SARS-CoV-2 genome. Subsequently, we applied Oxford Nanopore Rapid Barcoding and the portable MinION Mk1C sequencer combined with the interARTIC bioinformatics pipeline. We tested a simplified and less time-consuming workflow using SARS-CoV-2-positive specimens from clinical routine and identified the CT value as a useful pre-analytical parameter, which may help to decrease sequencing failures rates. Complete pipeline duration was approx. 7 h for one specimen and approx. 11 h for 12 multiplexed barcoded specimens. The adapted protocol contains fewer processing steps and can be completely conducted within one working day. Diagnostic CT values deduced from qPCR standardization experiments can act as principal criteria for specimen selection. As a guideline, SARS-CoV-2 genome copy numbers lower than 4 × 10⁶ were associated with a coverage threshold below 20-fold and incompletely assembled SARS-CoV-2 genomes. Thus, based on the described thermocycler/chemistry combination, we recommend CT values of ~26 or lower to achieve full and high-quality SARS-CoV-2 (+)RNA genome coverage. Full article