Genomics-Based Identification of Microorganisms in Human Ocular Body Fluid

Kirstahler, Philipp; Bjerrum, Søren Solborg; Friis-Møller, Alice; Cour, Morten la; Aarestrup, Frank Møller; Westh, Henrik; Pamp, Sünje Johanna

doi:10.1101/176529

Cited by 19 publications

(30 citation statements)

References 48 publications

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“…As metagenomic sequencing enters clinical practice, it is important to recognize the potential of this powerful approach to reveal true signals, as well as clinically- 45 , manufacture contaminant-free extraction kits, and enrich for microbial sequences 6,8 are steps in the right direction to prepare metagenomic sequencing for routine clinical use, but much work remains to be done.…”

Section: Contaminant Sequence Identification and Computational Removamentioning

confidence: 99%

Combined use of metagenomic sequencing and host response profiling for the diagnosis of suspected sepsis

et al. 2019

Preprint

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Word count (not including title, abstract, research in context, acknowledgment, references, tables, and figure legends): 5,077 RESEARCH IN CONTEXTEvidence before this study: Our PubMed search for articles matching the terms ("metagenomic" OR "cell-free DNA") and "infect*" in the title/abstract and using the "Human" species filter from inception to September 30, 2019 yielded 463 articles. Many proof-of-concept and validation studies illustrating how metagenomic sequencing can diagnose infections have been previously reviewed. Our search identified only nine studies which applied metagenomic shotgun sequencing to blood specimens, likely because there is a relatively low signal-to-noise ratio with this specimen type in this setting. In a study of 358 febrile sepsis patients, plasma cell-free DNA sequencing detected causative agents missed by standard-of-care testing in 15% of patients, but also detected bacterial organisms adjudicated as commensals in 10% of patients.Recently, a proof-of-concept study used machine learning to integrate metagenomic sequencing and transcriptional host response profiling to differentiate pathogens from commensal organisms in respiratory specimens, albeit with only a small derivation cohort to train host response signatures.Added value of this study: Our 200-patient study assessed the clinical utility of combining both metagenomic sequencing and a previously-defined host response assay to diagnose sepsis. We developed a rigorous chart review approach to measure whether our assays' results could change a physician's diagnostic decision-making, without having to commit the assays into patient care. Metagenomic sequencing revealed previously-undetected and clinically relevant organisms in 17 of 200 patients, and host response profiling led at least two of three physician chart reviewers to change SUMMARY Background: Current diagnostic techniques are inadequate for rapid microbial diagnosis and optimal management of patients with suspected sepsis. We assessed the impact of metagenomic sequencing and host response profiling individually and in combination on microbiological diagnosis in these patients. Methods:In this cohort study of 200 consecutive patients with suspected sepsis we evaluated three molecular diagnostic methods with blood specimens: 1) direct bacterial DNA detection and characterization with metagenomic shotgun next generation sequencing and contaminant sequence removal using Bayesian inference; 2) direct viral DNA and RNA enrichment and detection with viral capture sequencing; and 3) transcript-based host response profiling with a previously-defined 18-gene qRT-PCR assay. We then evaluated changes in diagnostic decision-making among three expert physicians in a chart review by unblinding our three molecular test results in a staged fashion.Findings: Metagenomic shotgun sequencing confirmed positive blood culture results in 14 of 26 patients. In 17 of 200 patients, metagenomic sequencing and viral capture sequencing revealed organisms that were 1) not detected by conventional...

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Section: Contaminant Sequence Identification and Computational Removamentioning

confidence: 99%

Combined use of metagenomic sequencing and host response profiling for the diagnosis of suspected sepsis

et al. 2019

Preprint

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“…1a). These contaminating sequences may cause a variety of problems, including incorrect labels on sequences in metagenomic studies [3], faulty conclusions about horizontal gene transfer [4,5], or poor annotation quality of genomes [6].…”

Section: Introductionmentioning

confidence: 99%

Terminating contamination: large-scale search identifies more than 2,000,000 contaminated entries in GenBank

Steinegger

Salzberg

2020

Preprint

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Metagenomic sequencing allows researchers to investigate organisms sampled from their native environments by sequencing their DNA directly, and then quantifying the abundance and taxonomic composition of the organisms thus captured. However, these types of analyses are sensitive to contamination in public databases caused by incorrectly labeled reference sequences. Here we describe Conterminator, an efficient method to detect and remove incorrectly labelled sequences by an exhaustive all-against-all sequence comparison. Our analysis reports contamination in 114,035 sequences and 2767 species in the NCBI Reference Sequence Database (RefSeq), 2,161,746 sequences and 6795 species in the GenBank database, and 14,132 protein sequences in the NR non-redundant protein database. Conterminator uncovers contamination in sequences spanning the whole range from draft genomes to “complete” model organism genomes. Our method, which scales linearly with input size, was able to process 3.3 terabytes of genomic sequence data in 12 days on a single 32-core compute node. We believe that Conterminator can become an important tool to ensure the quality of reference databases with particular importance for downstream metagenomic analyses. Source code (GPLv3): https://github.com/martin-steinegger/conterminator

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“…(20,21). With the improvement of reference databases and bioinformatics tools, the validation is an ongoing process (22–25).…”

Section: Introductionmentioning

confidence: 99%

Library Preparation and Sequencing Platform Introduce Bias in Metagenomic-Based Characterizations of Microbiomes

Poulsen¹,

Pamp

Ct³

et al. 2019

Preprint

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15Next generation sequencing technologies have become increasingly used to describe microbial communities. 16 Metagenomics characterization of microbiomes is associated with minimal manipulation during sample 17 processing, which includes sampling, storage, DNA isolation, library preparation and sequencing, before the 18 raw data are obtained. Here we assess the effect of library preparation using a kit with a polymerase chain 19 reaction (PCR) step (Nextera) and two PCR-free kits (NEXTflex and KAPA), and the effect of sequencing 20 platform (HiSeq and NextSeq) on the description of microbial communities in pig feces and sewage. Two pig 21 fecal samples were obtained from different farms and two sewage samples were collected as inlet water at 22 a local wastewater treatment facility. Samples were processed to both perform DNA-isolation immediately 23 upon arrival in the lab and after storage for 64 hours at -80°C, DNA isolation was performed in duplicate. 24We find that both library preparation and sequencing platform had systematic effects on the microbial 25 community description. The effects were at a level that made differentiating between the two pig fecal 26 samples difficult. The sewage samples represented two very different communities and were at all times 27 distinguishable from each other. We find that library preparation and sequencing platform introduced more 28 variation than freezing the samples. The community changes did not seem associated with contamination 29 during processing and distinct patterns connected specific types of organisms with a processing method, but 30it was difficult to generalize between samples. This highlights the need for continuous validation of the effect 31 of sample processing in different types of samples and that all processing steps need to be considered when 32 comparing between studies. We believe standardization of sample processing is key to generate comparable 33data within a study and that comparisons of differently generated data, e.g. in a meta-analysis, should be 34 performed cautiously.35 36

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Genomics-Based Identification of Microorganisms in Human Ocular Body Fluid

Cited by 19 publications

References 48 publications

Combined use of metagenomic sequencing and host response profiling for the diagnosis of suspected sepsis

Combined use of metagenomic sequencing and host response profiling for the diagnosis of suspected sepsis

Terminating contamination: large-scale search identifies more than 2,000,000 contaminated entries in GenBank

Library Preparation and Sequencing Platform Introduce Bias in Metagenomic-Based Characterizations of Microbiomes

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