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Medical Principles and Practice :... 2024The success in determining the whole genome sequence of a bacterial pathogen was first achieved in 1995 by determining the complete nucleotide sequence of Haemophilus... (Review)
Review
The success in determining the whole genome sequence of a bacterial pathogen was first achieved in 1995 by determining the complete nucleotide sequence of Haemophilus influenzae Rd using the chain-termination method established by Sanger et al. in 1977 and automated by Hood et al. in 1987. However, this technology was laborious, costly, and time-consuming. Since 2004, high-throughput next-generation sequencing technologies have been developed, which are highly efficient, require less time, and are cost-effective for whole genome sequencing (WGS) of all organisms, including bacterial pathogens. In recent years, the data obtained using WGS technologies coupled with bioinformatics analyses of the sequenced genomes have been projected to revolutionize clinical bacteriology. WGS technologies have been used in the identification of bacterial species, strains, and genotypes from cultured organisms and directly from clinical specimens. WGS has also helped in determining resistance to antibiotics by the detection of antimicrobial resistance genes and point mutations. Furthermore, WGS data have helped in the epidemiological tracking and surveillance of pathogenic bacteria in healthcare settings as well as in communities. This review focuses on the applications of WGS in clinical bacteriology.
Topics: Humans; Whole Genome Sequencing; Genome, Bacterial; Drug Resistance, Bacterial; High-Throughput Nucleotide Sequencing
PubMed: 38402870
DOI: 10.1159/000538002 -
Journal of Computational Biology : a... Dec 2023Processing large data sets has become an essential part of computational genomics. Greatly increased availability of sequence data from multiple sources has fueled... (Review)
Review
Processing large data sets has become an essential part of computational genomics. Greatly increased availability of sequence data from multiple sources has fueled breakthroughs in genomics and related fields but has led to computational challenges processing large sequencing experiments. The minimizer sketch is a popular method for sequence sketching that underlies core steps in computational genomics such as read mapping, sequence assembling, k-mer counting, and more. In most applications, minimizer sketches are constructed using one of few classical approaches. More recently, efforts have been put into building minimizer sketches with desirable properties compared with the classical constructions. In this survey, we review the history of the minimizer sketch, the theories developed around the concept, and the plethora of applications taking advantage of such sketches. We aim to provide the readers a comprehensive picture of the research landscape involving minimizer sketches, in anticipation of better fusion of theory and application in the future.
Topics: Algorithms; Sequence Analysis, DNA; Genomics; High-Throughput Nucleotide Sequencing; Software
PubMed: 37646787
DOI: 10.1089/cmb.2023.0094 -
Molecular Diagnosis & Therapy Nov 2023Highly sensitive molecular assays have been developed to detect plasma-based circulating tumor DNA (ctDNA), and emerging evidence suggests their clinical utility for...
BACKGROUND
Highly sensitive molecular assays have been developed to detect plasma-based circulating tumor DNA (ctDNA), and emerging evidence suggests their clinical utility for monitoring minimal residual disease and recurrent disease, providing prognostic information, and monitoring therapy responses in patients with solid tumors. The Invitae Personalized Cancer Monitoring assay uses a patient-specific, tumor-informed variant signature identified through whole exome sequencing to detect ctDNA in peripheral blood of patients with solid tumors.
METHODS
The assay's tumor whole exome sequencing and ctDNA detection components were analytically validated using 250 unique human specimens and nine commercial reference samples that generated 1349 whole exome sequencing and cell-free DNA (cfDNA)-derived libraries. A comparison of tumor and germline whole exome sequencing was used to identify patient-specific tumor variant signatures and generate patient-specific panels, followed by targeted next-generation sequencing of plasma-derived cfDNA using the patient-specific panels with anchored multiplex polymerase chain reaction chemistry leveraging unique molecular identifiers.
RESULTS
Whole exome sequencing resulted in overall sensitivity of 99.8% and specificity of > 99.9%. Patient-specific panels were successfully designed for all 63 samples (100%) with ≥ 20% tumor content and 24 (80%) of 30 samples with ≥ 10% tumor content. Limit of blank studies using 30 histologically normal, formalin-fixed paraffin-embedded specimens resulted in 100% expected panel design failure. The ctDNA detection component demonstrated specificity of > 99.9% and sensitivity of 96.3% for a combination of 10 ng of cfDNA input, 0.008% allele frequency, 50 variants on the patient-specific panels, and a baseline threshold. Limit of detection ranged from 0.008% allele frequency when utilizing 60 ng of cfDNA input with 18-50 variants in the patient-specific panels (> 99.9% sensitivity) with a baseline threshold, to 0.05% allele frequency when using 10 ng of cfDNA input with an 18-variant panel with a monitoring threshold (> 99.9% sensitivity).
CONCLUSIONS
The Invitae Personalized Cancer Monitoring assay, featuring a flexible patient-specific panel design with 18-50 variants, demonstrated high sensitivity and specificity for detecting ctDNA at variant allele frequencies as low as 0.008%. This assay may support patient prognostic stratification, provide real-time data on therapy responses, and enable early detection of residual/recurrent disease.
Topics: Humans; Neoplasms; Circulating Tumor DNA; Cell-Free Nucleic Acids; High-Throughput Nucleotide Sequencing; Gene Frequency; Biomarkers, Tumor; Mutation
PubMed: 37632661
DOI: 10.1007/s40291-023-00670-1 -
MicrobiologyOpen Oct 2023Receiving the same results from repeated analysis of the same sample is a basic principle in science. The inability to reproduce previously published results has led to...
Receiving the same results from repeated analysis of the same sample is a basic principle in science. The inability to reproduce previously published results has led to discussions of a reproducibility crisis within science. For studies of microbial communities, the problem of reproducibility is more pronounced and has, in some fields, led to a discussion on the very existence of a constantly present microbiota. In this study, DNA from 44 bovine milk samples were extracted twice and the V3-V4 region of the 16S rRNA gene was sequenced in two separate runs. The FASTQ files from the two data sets were run through the same bioinformatics pipeline using the same settings and results from the two data sets were compared. Milk samples collected maximally 2 h apart were used as replicates and permitted comparisons to be made within the same run. Results show a significant difference in species richness between the two sequencing runs although Shannon and Simpson's diversity was the same. Multivariate analyses of all samples demonstrate that the sequencing run was a driver for variation. Direct comparison of similarity between samples and sequencing run showed an average similarity of 42%-45% depending on whether binary or abundance-based similarity indices were used. Within-run comparisons of milk samples collected maximally 2 h apart showed an average similarity of 39%-47% depending on the similarity index used and that similarity differed significantly between runs. We conclude that repeated DNA extraction and sequencing significantly can affect the results of a low microbial biomass microbiota study.
Topics: Animals; Milk; Bacteria; RNA, Ribosomal, 16S; Reproducibility of Results; High-Throughput Nucleotide Sequencing; Microbiota; DNA
PubMed: 37877657
DOI: 10.1002/mbo3.1383 -
Nature Communications Aug 2023Long-read RNA sequencing (RNA-seq) is a powerful technology for transcriptome analysis, but the relatively low throughput of current long-read sequencing platforms...
Long-read RNA sequencing (RNA-seq) is a powerful technology for transcriptome analysis, but the relatively low throughput of current long-read sequencing platforms limits transcript coverage. One strategy for overcoming this bottleneck is targeted long-read RNA-seq for preselected gene panels. We present TEQUILA-seq, a versatile, easy-to-implement, and low-cost method for targeted long-read RNA-seq utilizing isothermally linear-amplified capture probes. When performed on the Oxford nanopore platform with multiple gene panels of varying sizes, TEQUILA-seq consistently and substantially enriches transcript coverage while preserving transcript quantification. We profile full-length transcript isoforms of 468 actionable cancer genes across 40 representative breast cancer cell lines. We identify transcript isoforms enriched in specific subtypes and discover novel transcript isoforms in extensively studied cancer genes such as TP53. Among cancer genes, tumor suppressor genes (TSGs) are significantly enriched for aberrant transcript isoforms targeted for degradation via mRNA nonsense-mediated decay, revealing a common RNA-associated mechanism for TSG inactivation. TEQUILA-seq reduces the per-reaction cost of targeted capture by 2-3 orders of magnitude, as compared to a standard commercial solution. TEQUILA-seq can be broadly used for targeted sequencing of full-length transcripts in diverse biomedical research settings.
Topics: High-Throughput Nucleotide Sequencing; Gene Expression Profiling; Sequence Analysis, RNA; RNA; Protein Isoforms; Transcriptome
PubMed: 37553321
DOI: 10.1038/s41467-023-40083-6 -
Journal of Vascular and Interventional... Aug 2023The discovery of increasing numbers of actionable molecular and gene targets for cancer treatment has driven the demand for tissue sampling for next-generation... (Review)
Review
The discovery of increasing numbers of actionable molecular and gene targets for cancer treatment has driven the demand for tissue sampling for next-generation sequencing (NGS). Requirements for sequencing can be very specific, and inadequate sampling leads to delays in management and decision making. It is important that interventional radiologists are aware of NGS technologies and their common applications and be cognizant of the factors that contribute to successful sample sequencing. This review summarizes the fundamentals of cancer tissue collection and processing for NGS. It elaborates on sequencing technologies and their applications with the aim of providing readers with a working understanding that can enhance their clinical practice. It then describes imaging, tumor, biopsy, and sample collection factors that improve the chances of NGS success. Finally, it discusses future practice, highlighting the problem of undersampling in both clinical and research settings and the opportunities within interventional radiology to address this.
Topics: Humans; Neoplasms; Biopsy; High-Throughput Nucleotide Sequencing
PubMed: 36977432
DOI: 10.1016/j.jvir.2023.03.012 -
Current Oncology Reports Mar 2024Microbiome research has provided valuable insights into the associations between microbial communities and bladder cancer. However, this field faces significant... (Review)
Review
PURPOSE OF THE REVIEW
Microbiome research has provided valuable insights into the associations between microbial communities and bladder cancer. However, this field faces significant challenges that hinder the interpretation, generalization, and translation of findings into clinical practice. This review aims to elucidate these challenges and highlight the importance of addressing them for the advancement of microbiome research in bladder cancer.
RECENT FINDINGS
Recent findings underscore the complexities involved in microbiome research, particularly in the context of bladder cancer. Challenges include low microbial biomass in urine samples, potential contamination issues during collection and processing, variability in sequencing methods and primer selection, and the difficulty of establishing causality between microbiota and bladder cancer. Studies have shown the impact of sample storage conditions and DNA isolation kits on microbiome analysis, emphasizing the need for standardization. Additionally, variations in urine collection methods can introduce contamination and affect results. The choice of 16S rRNA gene amplicon sequencing or shotgun metagenomic sequencing introduces technical challenges, including primer selection and sequencing read length. Establishing causality between the microbiota and bladder cancer requires experimental methods like fecal microbiota transplantation and human microbiota-associated murine models, which face their own set of challenges. Translating microbiome research into therapeutic applications is hindered by methodological variability, incomplete understanding of bioactive molecules, imperfect animal models, and the inherent heterogeneity of microbiome communities among individuals. Microbiome research in bladder cancer presents significant challenges stemming from technical and conceptual complexities. Addressing these challenges through standardization, improved experimental models, and advanced analytical approaches is essential for advancing our understanding of the microbiome's role in bladder cancer and its potential clinical applications. Achieving this goal can lead to improved patient outcomes and novel therapeutic strategies in the future.
Topics: Humans; Mice; Animals; RNA, Ribosomal, 16S; Microbiota; Urinary Bladder Neoplasms; High-Throughput Nucleotide Sequencing
PubMed: 38376627
DOI: 10.1007/s11912-024-01508-7 -
Nucleic Acids Research Jul 2023Ribosome profiling provides quantitative, comprehensive, and high-resolution snapshots of cellular translation by the high-throughput sequencing of short mRNA fragments...
Ribosome profiling provides quantitative, comprehensive, and high-resolution snapshots of cellular translation by the high-throughput sequencing of short mRNA fragments that are protected by ribosomes from nucleolytic digestion. While the overall principle is simple, the workflow of ribosome profiling experiments is complex and challenging, and typically requires large amounts of sample, limiting its broad applicability. Here, we present a new protocol for ultra-rapid ribosome profiling from low-input samples. It features a robust strategy for sequencing library preparation within one day that employs solid phase purification of reaction intermediates, allowing to reduce the input to as little as 0.1 pmol of ∼30 nt RNA fragments. Hence, it is particularly suited for the analyses of small samples or targeted ribosome profiling. Its high sensitivity and its ease of implementation will foster the generation of higher quality data from small samples, which opens new opportunities in applying ribosome profiling.
Topics: High-Throughput Nucleotide Sequencing; Protein Biosynthesis; Ribosome Profiling; Ribosomes; RNA, Messenger
PubMed: 37246712
DOI: 10.1093/nar/gkad459 -
Scientific Reports Oct 2023Therapeutic antibody discovery often relies on in-vitro display methods to identify lead candidates. Assessing selected output diversity traditionally involves random...
Therapeutic antibody discovery often relies on in-vitro display methods to identify lead candidates. Assessing selected output diversity traditionally involves random colony picking and Sanger sequencing, which has limitations. Next-generation sequencing (NGS) offers a cost-effective solution with increased read depth, allowing a comprehensive understanding of diversity. Our study establishes NGS guidelines for antibody drug discovery, demonstrating its advantages in expanding the number of unique HCDR3 clusters, broadening the number of high affinity antibodies, expanding the total number of antibodies recognizing different epitopes, and improving lead prioritization. Surprisingly, our investigation into the correlation between NGS-derived frequencies of CDRs and affinity revealed a lack of association, although this limitation could be moderately mitigated by leveraging NGS clustering, enrichment and/or relative abundance across different regions to enhance lead prioritization. This study highlights NGS benefits, offering insights, recommendations, and the most effective approach to leverage NGS in therapeutic antibody discovery.
Topics: High-Throughput Nucleotide Sequencing; Antibodies; Epitopes
PubMed: 37884618
DOI: 10.1038/s41598-023-45538-w -
The Journal of Clinical Investigation Feb 2024Next-generation sequencing (NGS) applications for the diagnostics of infectious diseases has demonstrated great potential with three distinct approaches: whole-genome...
Next-generation sequencing (NGS) applications for the diagnostics of infectious diseases has demonstrated great potential with three distinct approaches: whole-genome sequencing (WGS), targeted NGS (tNGS), and metagenomic NGS (mNGS, also known as clinical metagenomics). These approaches provide several advantages over traditional microbiologic methods, though challenges still exist.
Topics: High-Throughput Nucleotide Sequencing; Metagenomics; Whole Genome Sequencing; Sensitivity and Specificity
PubMed: 38357923
DOI: 10.1172/JCI178003