Rapid profiling of the preterm infant gut microbiota using nanopore sequencing aids pathogen diagnostics

ABSTRACTThe Oxford Nanopore MinION sequencing platform offers near real time analysis of DNA reads as they are generated, which makes the device attractive for in-field or clinical deployment, e.g. rapid diagnostics. We used the MinION platform for shotgun metagenomic sequencing and analysis of gut-associated microbial communities; firstly, we used a 20-species human microbiota mock community to demonstrate how Nanopore metagenomic sequence data can be reliably and rapidly classified. Secondly, we profiled faecal microbiomes from preterm infants at increased risk of necrotising enterocolitis and sepsis. In single patient time course, we captured the diversity of the immature gut microbiota and observed how its complexity changes over time in response to interventions, i.e. probiotic, antibiotics and episodes of suspected sepsis. Finally, we performed ‘real-time’ runs from sample to analysis using faecal samples of critically ill infants and of healthy infants receiving probiotic supplementation. Real-time analysis was facilitated by our new NanoOK RT software package which analysed sequences as they were generated. We reliably identified potentially pathogenic taxa (i.e. Klebsiella pneumoniae and Enterobacter cloacae) and their corresponding antimicrobial resistance (AMR) gene profiles within as little as one hour of sequencing. Antibiotic treatment decisions may be rapidly modified in response to these AMR profiles, which we validated using pathogen isolation, whole genome sequencing and antibiotic susceptibility testing. Our results demonstrate that our pipeline can process clinical samples to a rich dataset able to inform tailored patient antimicrobial treatment in less than 5 hours.

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Real-time analysis of nanopore-based metagenomic sequencing from orthopaedic device infection

10.1101/220616 ◽

2017 ◽

Cited By ~ 2

Author(s):

Nicholas D Sanderson ◽

Teresa L Street ◽

Dona Foster ◽

Jeremy Swann ◽

Bridget L. Atkins ◽

...

Keyword(s):

Real Time ◽

Sequence Data ◽

Metagenomic Sequencing ◽

Nanopore Sequencing ◽

Time Analysis ◽

Real Time Analysis ◽

Joint Infections ◽

Prosthetic Joint ◽

Device Infection ◽

Prosthetic Joint Infections

AbstractProsthetic joint infections are clinically difficult to diagnose and treat. Previously, we demonstrated metagenomic sequencing on an Illumina MiSeq replicates the findings of current gold standard microbiological diagnostic techniques. Nanopore sequencing offers advantages in speed of detection over MiSeq. Here, we compare direct-from-clinical-sample metagenomic Illumina sequencing with Nanopore sequencing, and report a real-time analytical pathway for Nanopore sequence data, designed for detecting bacterial composition of prosthetic joint infections.DNA was extracted from the sonication fluids of seven explanted orthopaedic devices, and additionally from two culture negative controls, and was sequenced on the Oxford Nanopore Technologies MinION platform. A specific analysis pipeline was assembled to overcome the challenges of identifying the true infecting pathogen, given high levels of host contamination and unavoidable background lab and kit contamination.The majority of DNA classified (>90%) was host contamination and discarded. Using negative control filtering thresholds, the species identified corresponded with both routine microbiological diagnosis and MiSeq results. By analysing sequences in real time, causes of infection were robustly detected within minutes from initiation of sequencing.We demonstrate initial proof of concept that metagenomic MinION sequencing can provide rapid, accurate diagnosis for prosthetic joint infections. We demonstrate a novel, scalable pipeline for real-time analysis of MinION sequence data. The high proportion of human DNA in extracts prevents full genome analysis from complete coverage, and methods to reduce this could increase genome depth and allow antimicrobial resistance profiling.

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Near-Real time analysis of seismic data of active volcanoes: Software implementations of time sequence data analysis

Natural Hazards and Earth System Science ◽

10.5194/nhess-8-789-2008 ◽

2008 ◽

Vol 8 (4) ◽

pp. 789-794 ◽

Cited By ~ 2

Author(s):

J. Vila ◽

R. Ortiz ◽

M. Tárraga ◽

R. Macià ◽

A. García ◽

...

Keyword(s):

Quality Control ◽

Real Time ◽

Seismic Data ◽

Sequence Data ◽

Volcanic Complex ◽

Time Analysis ◽

Continuous Analysis ◽

Seismic Waveforms ◽

Real Time Analysis ◽

Software Implementations

Abstract. This paper presents the development and applications of a software-based quality control system that monitors volcano activity in near-real time. On the premise that external seismic manifestations provide information directly related to the internal status of a volcano, here we analyzed variations in background seismic noise. By continuous analysis of variations in seismic waveforms, we detected clear indications of changes in the internal status. The application of this method to data recorded in Villarrica (Chile) and Tungurahua (Ecuador) volcanoes demonstrates that it is suitable to be used as a forecasting tool. A recent application of this developed software-based quality control to the real-time monitoring of Teide – Pico Viejo volcanic complex (Spain) anticipated external episodes of volcanic activity, thus corroborating the advantages and capacity of the methodology when implemented as an automatic real-time procedure.

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Real-time analysis of nanopore-based metagenomic sequencing from infected orthopaedic devices

BMC Genomics ◽

10.1186/s12864-018-5094-y ◽

2018 ◽

Vol 19 (1) ◽

Cited By ~ 38

Author(s):

Nicholas D Sanderson ◽

Teresa L Street ◽

Dona Foster ◽

Jeremy Swann ◽

Bridget L Atkins ◽

...

Keyword(s):

Real Time ◽

Metagenomic Sequencing ◽

Time Analysis ◽

Real Time Analysis

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657. Evaluation of Nanopore-Based 16S Ribosomal RNA (rRNA) Gene Sequencing for the Development of a Rapid Infection Intervention Clinical Service

Open Forum Infectious Diseases ◽

10.1093/ofid/ofz360.725 ◽

2019 ◽

Vol 6 (Supplement_2) ◽

pp. S302-S302

Author(s):

Rahul Batra ◽

R Baldan ◽

P Cliff ◽

Amita Patel ◽

Jonathan Edgeworth ◽

...

Keyword(s):

16S Rrna ◽

Real Time ◽

Pathogen Detection ◽

Clinical Service ◽

Clinical Samples ◽

Rrna Gene ◽

Acid Extraction ◽

Time Analysis ◽

Real Time Analysis ◽

Gene Assay

Abstract Background Rapid and accurate identification of bacteria is the basis of appropriate antibiotic treatment and effective clinical decision-making. Next-generation sequencing (NGS) platforms such as Oxford Nanopore Technologies (ONT) holds the promise of a diagnostic revolution by overcoming the limitations of culture-based identification with rapid molecular detection of bacteria. We have developed a pilot to evaluate an ONT 16S rRNA gene assay with the ability to provide real-time analysis and identification of bacterial species. Our aim was to investigate whether long-read sequencing and high-speed analysis can be combined to create a clinically useful, rapid diagnostic tool. Methods A collection of bacterial isolates representing pathogenic species received by the clinical laboratory over 1 year was assembled. Sample preparation was as described in the ONT 16S protocol and included bead beating sample disruption, MagNA Pure automated nucleic acid extraction (Roche), and PCR amplification (Thermo). Sequencing was performed on the MinION and GridION X5 platforms. Output was analyzed with ONT’s automated EPI2ME 16S pipeline which assigns reads to taxa using BLAST results and the NCBI 16S Bacterial database. Results A total of 155 clinical samples with 139 species were sequenced. 119 species were identified at the species level. For 20 samples, a species in the same genus claimed the majority of reads, with the true species being matched to 3%-41% of reads. The average proportion of reads assigned to the correct species was 62.2%, specifically 67% for non-Enterobacteriaceae and 33% for Enterobacteriaceae. 4 clinical samples (3 Bronchoalveolar lavages (BALs), positive for (1) K. pneumoniae, (2) S. pneumoniae, and (3) S. pneumoniae, S. enterica, and S. typhimurium, and 1 bone positive for P. aeruginosa) were also analyzed with sequencing results matching culture. Conclusion Early results show that 16S rRNA sequencing coupled with real-time analysis was able to accelerate pathogen detection and was able to discriminate the majority of species from a relevant clinical collection. Pipeline refinement is required and subsequent confirmatory consensus-based identification may be a helpful adjunct. Nanopore sequencing shows promise as a rapid bacterial pathogen detection platform for clinical service. Disclosures All authors: No reported disclosures.

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Real-time analysis and visualization of pathogen sequence data

10.1101/286187 ◽

2018 ◽

Author(s):

Richard A. Neher ◽

Trevor Bedford

Keyword(s):

Real Time ◽

Sequence Data ◽

Rapid Development ◽

Clinical Diagnostics ◽

Time Analysis ◽

Phenotypic Data ◽

Sequencing Technologies ◽

Real Time Analysis ◽

Routine Surveillance ◽

Recent Developments

The rapid development of sequencing technologies has to led to an explosion of pathogen sequence data that are increasingly collected as part of routine surveillance or clinical diagnostics. In public health, sequence data is used to reconstruct the evolution of pathogens, anticipate future spread, and target interventions. In clinical settings whole genome sequences identify pathogens at the strain level, can be used to predict phenotypes such as drug resistance and virulence, and inform treatment by linking to closely related cases. However, the vast majority of sequence data are only used for specific narrow applications such as typing. Comprehensive analysis of these data could provide detailed insight into outbreak dynamics, but is not routinely done since fast, robust, and interpretable analysis work-flows are not in place. Here, we review recent developments in real-time analysis of pathogen sequence data with a particular focus on visualization and integration of sequence and phenotypic data.

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An Interactive Minicomputer Program for the Indexing and Simulation of Electron Diffraction Patterns

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100092670 ◽

1976 ◽

Vol 34 ◽

pp. 542-543

Author(s):

R.P. Goehner ◽

W.T. Hatfield ◽

Prakash Rao

Keyword(s):

Electron Diffraction ◽

Real Time ◽

Pattern Analysis ◽

Flow Diagram ◽

Hard Copy ◽

Time Analysis ◽

Real Time Analysis ◽

Transmission Electron ◽

One Step ◽

Diffraction Patterns

Computer programs are now available in various laboratories for the indexing and simulation of transmission electron diffraction patterns. Although these programs address themselves to the solution of various aspects of the indexing and simulation process, the ultimate goal is to perform real time diffraction pattern analysis directly off of the imaging screen of the transmission electron microscope. The program to be described in this paper represents one step prior to real time analysis. It involves the combination of two programs, described in an earlier paper(l), into a single program for use on an interactive basis with a minicomputer. In our case, the minicomputer is an INTERDATA 70 equipped with a Tektronix 4010-1 graphical display terminal and hard copy unit.A simplified flow diagram of the combined program, written in Fortran IV, is shown in Figure 1. It consists of two programs INDEX and TEDP which index and simulate electron diffraction patterns respectively. The user has the option of choosing either the indexing or simulating aspects of the combined program.

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