Next-Generation Sequencing (NGS) Platforms-Introduction, Principle, Types, Test Requirements, Procedure, Result-Interpretation, Application, and Keynotes

Introduction of Next-Generation Sequencing (NGS) Platforms

Next-Generation Sequencing (NGS) has transformed the field of genomics and our understanding of the intricacies of the genome. Here’s a brief introduction to the topic:

What is Next-Generation Sequencing (NGS)?

Next-Generation Sequencing (NGS), also known as high-throughput sequencing, is a collective term for several modern sequencing technologies that allow for the sequencing of DNA and RNA much more quickly and cheaply than traditional Sanger sequencing. NGS platforms can generate millions or even billions of sequences concurrently.

Key Features of NGS:

  1. High-throughput: Capable of producing an enormous amount of data in a single sequencing run.
  2. Cost-effective: Decreases the cost per base of sequencing significantly as compared to Sanger sequencing.
  3. Scalability: Suitable for a wide range of applications from targeted gene sequencing to whole-genome sequencing and even metagenomic sequencing.
  4. Precision: Generates very accurate sequence data, especially when there’s enough depth (number of reads covering a specific region).

Major NGS Platforms:

  1. Illumina (Solexa): One of the most popular platforms, it uses a sequencing by synthesis approach. The technology uses reversible dye-terminators and can generate gigabases of DNA sequence per run.
  2. Ion Torrent (Life Technologies): Uses semiconductor sequencing. Here, as the nucleotides are incorporated into the growing DNA chain, a hydrogen ion is released, leading to a change in pH that is detected by the machine.
  3. Roche 454: Was the first commercially available next-gen sequencing platform. It uses pyrosequencing, where nucleotide incorporation leads to the release of a light signal.
  4. PacBio (Pacific Biosciences): Employs single-molecule real-time (SMRT) sequencing. This allows for the generation of much longer reads than other NGS platforms but has a higher error rate.
  5. Oxford Nanopore Technologies: Uses nanopore sequencing, where individual DNA or RNA molecules pass through tiny nanopores. As they pass through, changes in the electrical current are used to determine the sequence.

Applications of NGS:

  1. Whole Genome Sequencing: Provides a comprehensive view of the entire genome.
  2. Exome Sequencing: Targets only the coding regions or exons of genes.
  3. RNA-Seq: Analyzes the transcriptome to look at gene expression levels and to detect novel transcripts.
  4. ChIP-Seq: Studies protein-DNA interactions.
  5. Metagenomics: Studies microbial communities by sequencing DNA from environmental samples.

Future Perspectives:

With continuous advances in NGS platforms, we are moving towards more rapid, efficient, and cheaper sequencing methods. This has broadened the applications from research to clinical diagnostics. The integration of NGS with other platforms, big data analysis, and artificial intelligence will play a significant role in the era of personalized medicine, understanding complex diseases, and biodiversity studies.

Principle of Next-Generation Sequencing (NGS) Platforms

Next-Generation Sequencing (NGS) encompasses a range of modern sequencing technologies. While each platform has its nuances, there are some general principles that underlie their operation. Here’s an overview of the basic principles behind NGS:

1. Library Preparation:

Before sequencing can take place, DNA or RNA samples must be prepared in a format suitable for the chosen sequencing platform. This often involves:

  • Fragmentation: The DNA/RNA is broken down into smaller pieces.
  • Adapter Ligation: Specific sequences (adapters) are attached to these fragments. These adapters are crucial for the sequencing process as they help the fragments attach to the sequencing platform and often contain indices for sample identification.

2. Amplification:

Many NGS techniques require an amplification step to increase the number of DNA fragments:

  • PCR (Polymerase Chain Reaction): This is a common method where short sequences (primers) bind to the DNA, and enzymes create additional copies.
  • Bridge Amplification: Specific to some platforms like Illumina, this involves DNA fragments bending over and attaching to a nearby primer, creating a “bridge”. This structure is then amplified on the surface of a flow cell.

3. Sequencing:

The manner of sequence determination varies between platforms:

  • Sequencing by Synthesis (Illumina): This involves synthesizing the complementary strand of the DNA fragment one base at a time. Each of the four nucleotide types (A, T, C, G) is labeled with a unique fluorescent dye. As they are incorporated, a camera captures the emitted fluorescence, identifying the base.
  • Pyrosequencing (Roche 454): As nucleotides are incorporated into the DNA strand, a pyrophosphate is released. This leads to a series of enzymatic reactions that produce visible light, which is then detected and recorded.
  • Ion Semiconductor Sequencing (Ion Torrent): Here, as nucleotides are incorporated, a hydrogen ion is released. This leads to a change in pH, which can be detected by a semiconductor sensor.
  • Single-Molecule Real-Time Sequencing (PacBio): This monitors the activity of DNA polymerase on a single DNA molecule in real-time. As nucleotides are incorporated, they emit fluorescence which is detected.
  • Nanopore Sequencing (Oxford Nanopore): An electric current flows through nanopores situated in a membrane. As DNA strands pass through these pores, they cause characteristic disruptions in the current, which can be used to identify the sequence.

4. Data Analysis:

The raw output from NGS platforms are short DNA sequences called “reads.” These reads need extensive computational analysis:

  • Base Calling: Transforming the raw signals (like fluorescent signals or ionic current changes) into sequences of bases.
  • Quality Control: Assessing the quality of the generated sequences.
  • Alignment/Mapping: The reads are often aligned to a reference genome to determine their origin.
  • Variant Calling: Identifying differences between the sequenced DNA and the reference genome.

5. Further Analysis:

Depending on the goal of the sequencing project, there might be additional analyses like gene expression quantification, metagenomic classification, or functional annotation.

Types of Next-Generation Sequencing (NGS) Platforms

Next-Generation Sequencing (NGS) encompasses a range of platforms that have been developed to provide faster, more efficient, and cost-effective sequencing solutions compared to traditional methods like Sanger sequencing. Here’s a brief overview of the main types of NGS platforms:

1. Illumina (previously Solexa)

  • Technology: Sequencing by Synthesis (SBS).
  • Principle: DNA fragments are amplified on a flow cell to create clusters. Each base incorporation during synthesis releases a specific fluorescence that is captured by imaging systems.
  • Applications: Whole genome sequencing, RNA-Seq, ChIP-Seq, metagenomics, and more.
  • Key Advantage: High throughput and accuracy. The platform dominates the NGS market.

2. Ion Torrent (by Thermo Fisher Scientific)

  • Technology: Semiconductor sequencing.
  • Principle: DNA is synthesized on a microchip. When a nucleotide is incorporated, a hydrogen ion is released, changing the pH. This change is detected by sensors, determining the base sequence.
  • Applications: Genome sequencing, targeted sequencing.
  • Key Advantage: No need for optical systems; it directly translates chemical signals into digital information.

3. Roche 454

  • Technology: Pyrosequencing.
  • Principle: Sequencing is based on the detection of pyrophosphate release on nucleotide incorporation, producing a light signal that is then detected and measured.
  • Applications: Genome sequencing, metagenomics, amplicon sequencing.
  • Key Advantage: Earlier NGS platform with longer read lengths compared to initial Illumina systems. However, it was discontinued due to higher costs and lower throughput compared to newer platforms.

4. PacBio (Pacific Biosciences)

  • Technology: Single-Molecule Real-Time (SMRT) Sequencing.
  • Principle: Observes DNA polymerase as it synthesizes a complementary DNA strand in real-time. Fluorescently labeled nucleotides are incorporated and detected.
  • Applications: De novo genome assembly, detection of structural variations, full-length transcriptome sequencing.
  • Key Advantage: Extremely long reads, allowing for better genome assembly and detection of complex variants.

5. Oxford Nanopore Technologies (ONT)

  • Technology: Nanopore sequencing.
  • Principle: DNA strands are pulled through nanopores. As each base passes through, it causes a characteristic disruption in an electric current, which is used to determine the sequence.
  • Applications: De novo genome assembly, real-time sequencing, direct RNA sequencing, field-based sequencing.
  • Key Advantage: Portable devices, real-time data output, and potential for extremely long reads.

6. BGI Genomics (previously Complete Genomics)

  • Technology: DNA nanoball sequencing.
  • Principle: DNA is amplified and arranged into nanoballs which are then sequenced using a combinatorial probe-anchor synthesis.
  • Applications: Whole genome sequencing, exome sequencing.
  • Key Advantage: High throughput at a competitive price.

Each platform offers its unique advantages and limitations, making them suitable for specific applications. The choice of platform depends on the project’s requirements, such as read length, throughput, accuracy, and cost.

Test Requirements for Next-Generation Sequencing (NGS) Platforms

For a successful Next-Generation Sequencing (NGS) run, several test requirements must be met. Meeting these requirements ensures the accuracy and quality of the generated data. Here’s a breakdown of the typical test requirements for an NGS run:

1. Sample Quality & Quantity:

  • DNA/RNA Integrity: The quality of the nucleic acid (either DNA or RNA) is crucial. Measures like the DNA Integrity Number (DIN) or RNA Integrity Number (RIN) provide insights into the quality. Gel electrophoresis or Bioanalyzer/TapeStation systems can be used for assessment.
  • Concentration: The quantity of the nucleic acid is essential to ensure there’s enough material for library preparation. Spectrophotometry (like NanoDrop) or fluorometry (like Qubit) can be used.

2. Library Preparation:

  • Library Quality: After preparing sequencing libraries, it’s important to check their quality. This ensures adapter ligation and PCR amplification were successful. Gel electrophoresis, Bioanalyzer, or TapeStation systems can be used.
  • Library Quantification: Accurate quantification ensures that the correct amount is loaded onto the sequencer. Library quantification can be done using qPCR or digital PCR.

3. Sequencing Platform Calibration & Maintenance:

  • Platform Calibration: Regular calibration of the sequencing instruments ensures they operate accurately. Platforms like Illumina often have specific calibration routines.
  • Instrument Maintenance: Regular maintenance checks and cleaning are necessary for optimal performance.

4. Control Samples:

  • Positive Control: Including a known control sample helps in benchmarking the performance and assessing the success of the sequencing run.
  • Negative Control: A no-template control (NTC) can help identify any contamination issues.

5. Cluster Density (specific to platforms like Illumina):

  • Optimal Clustering: The DNA fragments are amplified on a flow cell to create clusters. The density of these clusters affects the quality of the sequencing run. Too few or too many can lead to suboptimal results. Monitoring the cluster density ensures that the library has been loaded at an appropriate concentration.

6. Sequencing Quality Metrics:

Once the run has started or completed:

  • Q-Score Distribution: This represents the quality of the base calls. A high percentage of bases with Q30 scores (indicating a 1 in 1000 error rate) or above is generally desirable.
  • Phasing/Prephasing: For platforms like Illumina, these metrics indicate how many clusters are staying synchronized during the sequencing-by-synthesis process.
  • Error Rates: Monitoring the error rate, often given as a percentage, ensures the accuracy of the run.

7. Run Mode & Parameters:

  • Read Length: Depending on the application, different read lengths (e.g., 50bp, 150bp, 300bp) might be chosen. Ensuring the right read length selection is essential.
  • Single-end vs. Paired-end: Some applications benefit from paired-end reads, while others might only require single-end reads.

Ensuring that these test requirements are met will aid in producing high-quality, accurate sequencing data. Regular quality checks, equipment maintenance, and proper training are crucial for optimal NGS performance.

Procedure of Next-Generation Sequencing (NGS) Platforms

The procedure for running a Next-Generation Sequencing (NGS) experiment can be broadly divided into several steps. While the specifics might vary depending on the platform and the application, the general workflow remains consistent. Here’s an outline of the typical procedure for an NGS run:

1. Sample Preparation:

  • Extraction: Extract DNA or RNA from the sample source (e.g., blood, tissue, bacteria).
  • Quality Check: Assess the quality and quantity of the extracted nucleic acids using techniques like spectrophotometry or fluorometry.

2. Library Preparation:

  • Fragmentation: Break DNA or RNA into smaller pieces either mechanically (sonication) or enzymatically.
  • End Repair: Create blunt ends for DNA fragments.
  • Adapter Ligation: Attach platform-specific adapter sequences to the fragment ends. These adapters are essential for the sequencing process and often include unique molecular identifiers (UMIs) or barcodes for sample identification.
  • (Optional) Enrichment or Amplification: Amplify the library, often using PCR, to generate enough material for sequencing. Some applications, like exome sequencing, involve enrichment of specific genomic regions.
  • Quality and Quantity Assessment: Verify the library’s size distribution and concentration, often using qPCR, Bioanalyzer, or TapeStation systems.

3. Sequencing:

  • Cluster Generation (specific to platforms like Illumina): DNA fragments are bound to a flow cell and amplified to form dense regions of identical DNA clusters.
  • Sequencing Reaction:
    • Illumina: Utilizes sequencing-by-synthesis, where nucleotides are incorporated one at a time and identified based on their fluorescent signal.
    • Ion Torrent: DNA is synthesized on a semiconductor chip, and the release of hydrogen ions during nucleotide incorporation is detected.
    • PacBio: Observes DNA polymerase activity in real-time using fluorescently labeled nucleotides.
    • Oxford Nanopore: DNA strands pass through nanopores, causing disruptions in electrical current, which is used to identify bases.

4. Data Analysis:

  • Base Calling: Convert raw signals (e.g., fluorescence or ionic changes) into nucleotide sequences.
  • Quality Control: Check the quality of the generated reads.
  • Alignment/Mapping: Align the sequenced reads to a reference genome or assemble them de novo (without a reference).
  • Variant Calling: Identify differences (e.g., SNPs, indels) between the sequenced sample and the reference genome.

5. Post-Run Analysis:

Depending on the study’s objectives, further analysis may include:

  • Annotation: Identify the biological significance of detected variants.
  • Expression Analysis: For RNA-Seq data, determine the expression levels of genes or transcripts.
  • Comparative Analysis: Compare samples or datasets to identify patterns or significant differences.
  • Visualization: Use software tools to visually represent data, aiding in interpretation.

6. Data Storage and Sharing:

  • Storage: Due to the voluminous nature of NGS data, efficient storage solutions, often involving cloud storage or dedicated servers, are essential.
  • Sharing: For collaborative studies or public data repositories, data might be shared following proper formats and standards.

Result-Interpretation of Next-Generation Sequencing (NGS) Platforms

Interpreting results from Next-Generation Sequencing (NGS) runs involves converting massive volumes of raw sequence data into meaningful biological or clinical insights. The specifics of interpretation will vary depending on the application of the sequencing run (e.g., whole-genome sequencing, RNA-Seq, metagenomics). Here’s a general guideline for interpreting NGS results:

1. Quality Control (QC) Metrics:

Before diving into the biological or clinical interpretation, ensure that the raw data is of high quality:

  • Sequencing Quality: Look at the distribution of Q-scores across the reads. A high percentage of bases with Q30 scores or above usually indicates good quality.
  • Read Depth: For variant calling, especially, the depth of coverage is crucial. Sites with higher read depths are more confidently called.
  • GC Content and Bias: Check for biases in the GC content, which might indicate issues with library preparation or sequencing.

2. Alignment/Mapping Metrics:

If the reads are aligned to a reference:

  • Mapping Rate: The percentage of reads that align to the reference genome. A low mapping rate might indicate contamination or poor-quality data.
  • Coverage Uniformity: Check if the genome is uniformly covered or if there are regions with very low or no coverage.

3. Variant Analysis:

For genomic DNA sequencing:

  • Variants: Identified SNPs, indels, or other structural variants.
  • Variant Allele Frequency (VAF): The proportion of reads supporting the variant, important in cases like tumor sequencing.
  • Functional Annotation: Predicted impact of the variant (e.g., synonymous, non-synonymous, frameshift).
  • Population Frequency: How common the variant is in the general population, using databases like gnomAD or 1000 Genomes.
  • Clinical Relevance: For clinically-focused studies, databases like ClinVar can provide information about the clinical significance of variants.

4. Expression Analysis (for RNA-Seq):

  • Differentially Expressed Genes: Identify genes that show significant expression differences between conditions or groups.
  • Functional Enrichment: Determine if certain biological pathways or functions are enriched among differentially expressed genes using tools like GO or KEGG pathway analysis.

5. Metagenomics Analysis:

For sequencing of microbial communities:

  • Taxonomic Profiling: Identify the composition of microbial species in the sample.
  • Functional Profiling: Understand the metabolic pathways and functions prevalent in the microbial community.

6. Structural & Functional Analysis:

  • Protein Domains: For variants that occur in genes, understanding if they lie in critical protein domains or functional sites.
  • 3D Structure: Predicted impact of the variant on the protein’s three-dimensional structure.

7. Comparison and Integration:

For studies with multiple samples or conditions:

  • Comparative Genomics: Compare genomes across samples or species to identify shared or unique features.
  • Phylogenetics: Build evolutionary trees or relationships based on sequence data.

8. Clinical Interpretation (if applicable):

  • Pathogenicity Prediction: Use tools and databases to predict if a variant might be pathogenic or benign.
  • Drug Response: Some variants might indicate sensitivity or resistance to certain drugs.
  • Hereditary Information: For germline mutations, understand potential hereditary risks.

Interpreting NGS data is a multi-step, often complex process requiring a combination of bioinformatics tools, databases, and domain-specific knowledge. The end goal is to extract meaningful insights from the vast amount of sequence data, leading to deeper biological understanding or informed clinical decisions.

Application of Next-Generation Sequencing (NGS) Platforms

Next-Generation Sequencing (NGS) has revolutionized the field of genomics and has found applications across various areas of biology and medicine. Here are some of the prominent applications of NGS:

1. Genome Sequencing:

  • Whole-Genome Sequencing (WGS): Comprehensive sequencing of an entire genome, enabling detailed exploration of genetic variations.
  • Exome Sequencing: Focuses on sequencing the coding regions (exons) of genes, which are often associated with protein function and disease.
  • Mitochondrial DNA Sequencing: Specific sequencing of the mitochondrial genome, important in studying matrilineal inheritance and some diseases.

2. Transcriptomics:

  • RNA-Seq: Sequencing of RNA to study gene expression patterns, identify novel transcripts, alternative splicing events, and more.
  • Small RNA-Seq: Focuses on small RNA molecules like microRNAs which play crucial roles in post-transcriptional regulation.

3. Epigenomics:

  • ChIP-Seq (Chromatin Immunoprecipitation Sequencing): Investigates protein-DNA interactions, particularly the binding of specific proteins (like transcription factors) to DNA.
  • Bisulfite Sequencing: Analyses DNA methylation patterns across the genome, providing insights into epigenetic regulation.

4. Metagenomics:

  • Microbiome Analysis: Sequencing of DNA from environmental or biological samples to identify microbial communities, understand their function, and their impact on health or environmental conditions.

5. Structural Variant Analysis:

  • Mate-Pair Sequencing: Specifically designed for the identification of larger structural variations in the genome, such as deletions, insertions, and translocations.

6. Oncology:

  • Tumor Sequencing: Analyses tumor samples to identify mutations driving cancer, which can guide treatment decisions.
  • Liquid Biopsy: Sequencing DNA or RNA from body fluids (like blood) to detect cancer-associated mutations or to monitor disease progression.

7. Pharmacogenomics:

Studies genetic variations affecting individual responses to drugs, helping to guide personalized medicine approaches.

8. Agrigenomics:

  • Crop Genomics: Sequencing crop genomes to enhance breeding programs or study genetic diversity.
  • Livestock Genomics: Investigating the genomes of livestock to improve breeding and understand disease resistance.

9. Evolutionary and Ecological Studies:

  • Population Genomics: Studying genetic variations within populations to understand evolutionary patterns, migration, or selection pressures.
  • Environmental DNA (eDNA): Capturing DNA from environmental samples (like water) to detect and monitor biodiversity or invasive species.

10. Forensics:

  • Forensic Genomics: Uses NGS to enhance the resolution of forensic DNA typing beyond traditional methods.

11. Prenatal & Neonatal Screening:

  • Non-Invasive Prenatal Testing (NIPT): Sequencing cell-free fetal DNA from maternal blood to screen for chromosomal abnormalities.
  • Newborn Screening: Identifying genetic disorders early in neonates for timely intervention.

12. Functional Genomics:

  • ATAC-Seq (Assay for Transposase-Accessible Chromatin using Sequencing): Investigates chromatin accessibility, giving insights into active regulatory regions in the genome.

13. Ancient DNA Studies:

Analyzing DNA from archaeological samples to understand human evolution, migration patterns, and ancestry.

Keynotes on Next-Generation Sequencing (NGS) Platforms

Here are keynotes on Next-Generation Sequencing (NGS) Platforms:

1. Definition:

  • NGS refers to a group of modern sequencing technologies that allow rapid, high-throughput sequencing of DNA and RNA.

2. Advantages:

  • Enables massively parallel sequencing, generating millions to billions of sequences simultaneously.
  • Offers reduced cost per base compared to traditional Sanger sequencing.
  • Highly scalable, from targeted regions to whole genomes.

3. Core Steps:

  • Sample Preparation: Extract and quality check DNA/RNA.
  • Library Preparation: Fragment nucleic acids and ligate platform-specific adapters.
  • Sequencing: Determine the order of nucleotides in each fragment.
  • Data Analysis: Convert raw data into meaningful biological or clinical insights.

4. Major Platforms:

  • Illumina: Uses sequencing by synthesis with fluorescently labeled reversible terminators.
  • Ion Torrent: Detects pH changes caused by the release of hydrogen ions during nucleotide incorporation.
  • Roche 454: Employs pyrosequencing, detecting light emitted during nucleotide incorporation.
  • PacBio: Utilizes Single-Molecule Real-Time (SMRT) sequencing, observing DNA polymerase activity.
  • Oxford Nanopore: Relies on changes in electrical current as DNA strands pass through nanopores.

5. Applications:

  • Genomic: Whole-genome, exome, and targeted sequencing.
  • Transcriptomic: RNA-Seq for gene expression, isoform analysis, and transcript discovery.
  • Epigenomic: Investigate DNA modifications (e.g., methylation) and protein-DNA interactions (e.g., ChIP-Seq).
  • Metagenomic: Analyze microbial communities in various samples.
  • Clinical: Detect genetic mutations associated with disease, guide treatments, and more.

6. Data Challenges:

  • NGS generates vast amounts of data, necessitating robust storage, computational, and bioinformatics resources for analysis.

7. Quality Metrics:

  • It’s crucial to assess the quality of sequencing runs, typically using metrics like Q-scores, mapping rates, and coverage depth.

8. Cost and Throughput:

  • Over the years, NGS costs have decreased dramatically, following (and even surpassing) Moore’s Law, enabling broader access and diverse applications.

9. Future Outlook:

  • Continuous technological advancements are driving longer read lengths, higher accuracy, and even more reduced costs.
  • Integration with other platforms and fields, like artificial intelligence and personalized medicine, will shape the future of NGS.

Further Readings on Next-Generation Sequencing (NGS) Platforms

1. Foundational Texts:

  • “Genome Analysis: Current Procedures and Applications” by Maria S. Poptsova. This book provides an overview of modern genomic techniques, including NGS and bioinformatics tools.
  • “Next Generation Sequencing: Advances, Applications and Challenges” by Jerzy Kulski. This offers a comprehensive look into the various NGS technologies and their applications.

2. Technical Guides:

  • “Next-Generation DNA Sequencing Informatics” by Stuart M. Brown. This is a great resource for those who want to understand the informatics and data analysis side of NGS.
  • “Bioinformatics for High Throughput Sequencing” by N. Rodríguez-Ezpeleta et al. This book focuses on the bioinformatics challenges associated with NGS data analysis.

3. Specialized Applications:

  • “RNA-seq Data Analysis: A Practical Approach” by Eija Korpelainen, Jarno Tuimala, Panu Somervuo, Mikael Huss, and Garry Wong. As the title suggests, this book is focused on RNA-Seq, an application of NGS.
  • “Clinical Applications of Next-Generation Sequencing” by Urszula Demkow and Rafal Ploski. This text dives into the medical and clinical implications and applications of NGS.

4. Journals:

  • “Nature Methods” and “Nature Reviews Genetics”: Both journals frequently publish cutting-edge articles and reviews related to NGS technologies and their advancements.
  • “Genome Biology”: This open-access journal covers research articles, methodology, and software related to genomic studies, including many on NGS.

5. Online Resources:

  • Illumina’s Official Website: Offers a range of resources, white papers, and tutorials specific to their sequencing platforms.
  • NCBI Handbook: The National Center for Biotechnology Information provides a section dedicated to sequencing technologies, offering foundational insights and updates.
  • Coursera & EdX: Both online platforms offer courses on genomics, bioinformatics, and NGS, often in collaboration with top-tier universities and institutions.

6. Workshops & Conferences:

Attending workshops, webinars, or conferences focused on genomics or bioinformatics can provide hands-on experience and the latest insights. Examples include events hosted by the Cold Spring Harbor Laboratory or the European Bioinformatics Institute.

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