Targeting RNA with Next- and Third-Generation Sequencing Improves Pathogen Identification in Clinical Samples.
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ABSTRACT:
SUBMITTER: Zhao N
PROVIDER: S-EPMC8655164 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:MotivationNext generation sequencing (NGS) has provided researchers with a powerful tool to characterize metagenomic and clinical samples in research and diagnostic settings. NGS allows an open view into samples useful for pathogen detection in an unbiased fashion and without prior hypothesis about possible causative agents. However, NGS datasets for pathogen detection come with different obstacles, such as a very unfavorable ratio of pathogen to host reads. Alongside often appearing false positives and irrelevant organisms, such as contaminants, tools are often challenged by samples with low pathogen loads and might not report organisms present below a certain threshold. Furthermore, some metagenomic profiling tools are only focused on one particular set of pathogens, for example bacteria.ResultsWe present PAIPline, a bioinformatics pipeline specifically designed to address problems associated with detecting pathogens in diagnostic samples. PAIPline particularly focuses on userfriendliness and encapsulates all necessary steps from preprocessing to resolution of ambiguous reads and filtering up to visualization in a single tool. In contrast to existing tools, PAIPline is more specific while maintaining sensitivity. This is shown in a comparative evaluation where PAIPline was benchmarked along other well-known metagenomic profiling tools on previously published well-characterized datasets. Additionally, as part of an international cooperation project, PAIPline was applied to an outbreak sample of hemorrhagic fevers of then unknown etiology. The presented results show that PAIPline can serve as a robust, reliable, user-friendly, adaptable and generalizable stand-alone software for diagnostics from NGS samples and as a stepping stone for further downstream analyses.Availability and implementationPAIPline is freely available under https://gitlab.com/rki_bioinformatics/paipline.
| S-EPMC6129269 | biostudies-literature
Project description:Unbiased next-generation sequencing (NGS) approaches enable comprehensive pathogen detection in the clinical microbiology laboratory and have numerous applications for public health surveillance, outbreak investigation, and the diagnosis of infectious diseases. However, practical deployment of the technology is hindered by the bioinformatics challenge of analyzing results accurately and in a clinically relevant timeframe. Here we describe SURPI ("sequence-based ultrarapid pathogen identification"), a computational pipeline for pathogen identification from complex metagenomic NGS data generated from clinical samples, and demonstrate use of the pipeline in the analysis of 237 clinical samples comprising more than 1.1 billion sequences. Deployable on both cloud-based and standalone servers, SURPI leverages two state-of-the-art aligners for accelerated analyses, SNAP and RAPSearch, which are as accurate as existing bioinformatics tools but orders of magnitude faster in performance. In fast mode, SURPI detects viruses and bacteria by scanning data sets of 7-500 million reads in 11 min to 5 h, while in comprehensive mode, all known microorganisms are identified, followed by de novo assembly and protein homology searches for divergent viruses in 50 min to 16 h. SURPI has also directly contributed to real-time microbial diagnosis in acutely ill patients, underscoring its potential key role in the development of unbiased NGS-based clinical assays in infectious diseases that demand rapid turnaround times.
| S-EPMC4079973 | biostudies-literature
Project description:DNA N6-methyladenine (6mA) modification has been discovered as the most prevalent DNA modification in prokaryotes and eukaryotes, involving gene expression, DNA replication and repair, and host-pathogen interactions. Single-molecule real-time sequencing (SMRT-seq) can detect 6mA events in prokaryotic and eukaryotic genomes at the single-nucleotide level. However, there are no strict and economical quality control methods for high false-positive 6mA events in eukaryotic genomes. Therefore, by analyzing the distribution of 6mA in eukaryotic and prokaryotes, we proposed a method named MASQC (MeDIP-seq assists SMRT-seq for quality control in 6mA identification), which can identify 6mA events without doing the whole genome amplification (WGA) sequencing. The proposed MASQC method was assessed on two eukaryotic genomes and six bacterial genomes, our results demonstrate that MASQC performs well in quality control of false positive 6mA identification for both eukaryotic and prokaryotic genomes.
| S-EPMC7109398 | biostudies-literature
Project description:BackgroundAccurate identification of primary pathogens in foot infections remains challenging due to the diverse microbiome. Conventional culture may show false-positive or false-negative growth, leading to ineffective postoperative antibiotic treatment. Next-generation sequencing (NGS) has been explored as an alternative to standard culture in orthopedic infections. NGS is highly sensitive and can detect an entire bacterial genome along with genes conferring antibiotic resistance in a given sample. We investigated the potential use of NGS for accurate identification and quantification of microbes in infected diabetic foot ulcer (DFU). We hypothesize that NGS will aid identification of dominant pathogen and provide a more complete profile of microorganisms in infected DFUs compared to the standard culture method.MethodsData were prospectively collected from 30 infected DFU patients who underwent operative treatment by a fellowship-trained orthopedic foot and ankle surgeon from October 2018 to September 2019. The average age of the patient was 60.4 years. Operative procedures performed were irrigation and debridement (12), toe or ray amputation (13), calcanectomies (4), and below-the-knee amputation (1). Infected bone specimens were obtained intraoperatively and processed for standard culture and NGS. Concordance between the standard culture and NGS was assessed.ResultsIn 29 of 30 patients, pathogens were identified by both NGS and culture, with a concordance rate of 70%. In standard culture, Staphylococcus aureus (58.6%) was the most common pathogen, followed by coagulase-negative Staphylococcus (24.1%), Corynebacterium striatum (17.2%), and Enterococcus faecalis (17.2%). In NGS, Finegoldia magna (44.8%) was the most common microorganism followed by S. aureus (41.4%), and Anaerococcus vaginalis (24.1%). On average, NGS revealed 5.1 (range, 1-11) pathogens in a given sample, whereas culture revealed 2.6 (range, 1-6) pathogens.ConclusionNGS is an emerging molecular diagnostic method of microbial identification in orthopedic infection. It frequently provides different profiles of microorganisms along with antibiotic-resistant gene information compared to conventional culture in polymicrobial foot infection. Clinical use of NGS for management of foot and ankle infections warrants further investigation.Level of evidenceLevel II, diagnostic study.
| S-EPMC8702686 | biostudies-literature
Project description:BackgroundThe cerebrospinal fluid (CSF) culture is a widely used method for the diagnosis of meningitis, but its detection sensitivity is low. Several new methods have been developed for pathogen detection, including metagenomic next-generation sequencing (mNGS) and pathogen-targeted NGS (ptNGS). In this study, we aimed to evaluate the performance of ptNGS in pathogen detection in CSF.MethodsCSF specimens were acquired from 38 patients with meningitis who were diagnosed at Xuanwu Hospital, Capital Medical University between October 2020 and February 2021. DNA was extracted from the CSF samples, and pathogens were identified using both ptNGS and mNGS. SPSS 22.0 software was used to compare the pathogen detection performance of ptNGS and mNGS in CSF.ResultsAmong the 38 patients with meningitis, 14 had a non-infectious disease (NID) and 24 had an infectious disease (ID). Of the 38 samples, both ptNGS and mNGS detected 9 (23.7%) positive samples, and 12 (31.6%) negative samples. Thirteen (34.2%) samples were detected to be positive by ptNGS only, and 4 (10.5%) were detected to be positive by mNGS only. The positivity rate detected by ptNGS for the ID group was higher than that detected by mNGS (P=0.080), and the positivity rates detected by ptNGS and mNGS for the NID group were comparable. The positive predictive value (PPV) and negative predictive value (NPV) of diagnosing an ID by ptNGS were 77.3% and 56.3%, respectively. While, the PPV and NPV of diagnosing an ID by mNGS were 76.9% and 44.0%, respectively. ptNGS increased the sensitivity rate by approximately 70%. The sensitivity rate of ptNGS was higher than that of mNGS (70.8% vs. 41.7%), while the specificity rate of mNGS was higher than that of ptNGS (78.6% vs. 64.3%). Additionally, ptNGS required a shorter time for pathogen diagnosis (15 vs. 24 hrs) and had lower costs than mNGS.ConclusionsptNGS has a number of advantages over mNGS, including its sensitivity, timeliness, and economy, all factors that are important considerations in clinical use.
| S-EPMC8667110 | biostudies-literature
Project description:miRNAs act as important regulators of gene expression by promoting mRNA degradation or by attenuating protein translation. Since miRNAs are stably expressed in bodily fluids, there is growing interest in profiling these miRNAs, as it is minimally invasive and cost-effective as a diagnostic matrix. A technical hurdle in studying miRNA dynamics is the ability to reliably extract miRNA as small sample volumes and low RNA abundance create challenges for extraction and downstream applications. The purpose of this study was to develop a pipeline for the recovery of miRNA using small volumes of archived serum samples. The RNA was extracted employing several widely utilized RNA isolation kits/methods with and without addition of a carrier. The small RNA library preparation was carried out using Illumina TruSeq small RNA kit and sequencing was carried out using Illumina platform. A fraction of five microliters of total RNA was used for library preparation as quantification is below the detection limit. We were able to profile miRNA levels in serum from all the methods tested. We found out that addition of nucleic acid based carrier molecules had higher numbers of processed reads but it did not enhance the mapping of any miRBase annotated sequences. However, some of the extraction procedures offer certain advantages: RNA extracted by TRIzol seemed to align to the miRBase best; extractions using TRIzol with carrier yielded higher miRNA-to-small RNA ratios. Nuclease free glycogen can be carrier of choice for miRNA sequencing. Our findings illustrate that miRNA extraction and quantification is influenced by the choice of methodologies. Addition of nucleic acid- based carrier molecules during extraction procedure is not a good choice when assaying miRNA using sequencing. The careful selection of an extraction method permits the archived serum samples to become valuable resources for high-throughput applications.
| S-EPMC5025515 | biostudies-literature
Project description:BackgroundTranscriptome sequencing using next-generation sequencing platforms will soon be competing with DNA microarray technologies for global gene expression analysis. As a preliminary evaluation of these promising technologies, we performed deep sequencing of cDNA synthesized from the Microarray Quality Control (MAQC) reference RNA samples using Roche's 454 Genome Sequencer FLX.ResultsWe generated more that 3.6 million sequence reads of average length 250 bp for the MAQC A and B samples and introduced a data analysis pipeline for translating cDNA read counts into gene expression levels. Using BLAST, 90% of the reads mapped to the human genome and 64% of the reads mapped to the RefSeq database of well annotated genes with e-values </= 10-20. We measured gene expression levels in the A and B samples by counting the numbers of reads that mapped to individual RefSeq genes in multiple sequencing runs to evaluate the MAQC quality metrics for reproducibility, sensitivity, specificity, and accuracy and compared the results with DNA microarrays and Quantitative RT-PCR (QRTPCR) from the MAQC studies. In addition, 88% of the reads were successfully aligned directly to the human genome using the AceView alignment programs with an average 90% sequence similarity to identify 137,899 unique exon junctions, including 22,193 new exon junctions not yet contained in the RefSeq database.ConclusionUsing the MAQC metrics for evaluating the performance of gene expression platforms, the ExpressSeq results for gene expression levels showed excellent reproducibility, sensitivity, and specificity that improved systematically with increasing shotgun sequencing depth, and quantitative accuracy that was comparable to DNA microarrays and QRTPCR. In addition, a careful mapping of the reads to the genome using the AceView alignment programs shed new light on the complexity of the human transcriptome including the discovery of thousands of new splice variants.
| S-EPMC2707382 | biostudies-literature
Project description:Metagenomic sequencing is a promising new method for pathogen detection. We aimed to detect pathogens from archived plasma using metagenomic sequencing in a previously well-characterized cohort of 254 predominantly HIV-infected patients with sepsis in Uganda. We used Illumina sequencing and the Chan Zuckerberg ID metagenomics platform to sequence and identify pathogens. On average, each plasma sample yielded 3,404,737 ± 2,201,997 reads (mean ± standard deviation), of which 220,032 ± 416,691 (6.3% ± 8.6%) were identified as nonhuman reads. Using a background model filter, 414 genus-specific pathogen identifications were found in the 254 samples. Nineteen pathogens were previously detected positive by quantitative PCR (qPCR), compared to sequencing, which demonstrated 30.2% sensitivity and 99.5% specificity. Sensitivity was higher for viral pathogens than nonviral pathogens (37% versus 5%). For example, HIV viremia was detected in 69% of samples using qPCR, and sequencing revealed 70% sensitivity and 92% specificity. There were 75 genus-specific potential pathogens identified by sequencing in this cohort, including hepatitis B and Epstein-Barr virus (EBV), among several others. qPCR showed a prevalence of hepatitis B and EBV viremia of 17% and 45%, respectively. In-hospital mortality was associated with a lower qPCR threshold cycle value for EBV (adjusted odds ratio, 0.85; P < .001) but not for hepatitis B or HIV. In conclusion, a broad range of potential pathogens were identified by metagenomic sequencing in patients with sepsis in Uganda. Unexpectedly high rates of hepatitis B and EBV viremia were found. Whether these viral infections in HIV patients with sepsis are clinically important requires further study. IMPORTANCE The use of next-generation sequencing (NGS) in blood samples is an emerging technology for clinical microbiology labs. In this work, we performed NGS on plasma samples from a well-characterized cohort, where all samples had been previously tested by PCR for 43 pathogens. Therefore, we could compare sequencing performance against that of PCR and identify clinical correlates. A broad range of potential pathogens were identified by metagenomic sequencing in patients with sepsis in Uganda, particularly viruses, which we confirmed by PCR. In addition to HIV viremia, unexpectedly high rates of hepatitis B and EBV viremia were found, which may have important clinical implications.
| S-EPMC9927450 | biostudies-literature
Project description:Rodentia is the most diverse order among mammals, with more than 2,000 species currently described. Most of the time, species assignation is so difficult based on morphological data solely that identifying rodents at the specific level corresponds to a real challenge. In this study, we compared the applicability of 100 bp mini-barcodes from cytochrome b and cytochrome c oxidase 1 genes to enable rodent species identification. Based on GenBank sequence datasets of 115 rodent species, a 136 bp fragment of cytochrome b was selected as the most discriminatory mini-barcode, and rodent universal primers surrounding this fragment were designed. The efficacy of this new molecular tool was assessed on 946 samples including rodent tissues, feces, museum samples and feces/pellets from predators known to ingest rodents. Utilizing next-generation sequencing technologies able to sequence mixes of DNA, 1,140 amplicons were tagged, multiplexed and sequenced together in one single 454 GS-FLX run. Our method was initially validated on a reference sample set including 265 clearly identified rodent tissues, corresponding to 103 different species. Following validation, 85.6% of 555 rodent samples from Europe, Asia and Africa whose species identity was unknown were able to be identified using the BLASTN program and GenBank reference sequences. In addition, our method proved effective even on degraded rodent DNA samples: 91.8% and 75.9% of samples from feces and museum specimens respectively were correctly identified. Finally, we succeeded in determining the diet of 66.7% of the investigated carnivores from their feces and 81.8% of owls from their pellets. Non-rodent species were also identified, suggesting that our method is sensitive enough to investigate complete predator diets. This study demonstrates how this molecular identification method combined with high-throughput sequencing can open new realms of possibilities in achieving fast, accurate and inexpensive species identification.
| S-EPMC3492341 | biostudies-literature
Project description:NGPS is a method for de-novo, full-length protein sequencing in high throughput. The method is based on cleavage of the protein at semi-random sites by microwave-assisted acid hydrolysis (MAAH), enrichment of LC-MS/MS amenable peptides from the hydrolysate by solid-phase-extraction, LC-MS/MS analysis, de-novo long peptide tag sequencing of resulting peptides and assembly of peptide tags into consensus contigs.
2017-04-03 | PXD003804 | Pride