Real-time analysis and visualization of pathogen sequence data

Mapping Intimacies ◽

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.

Download Full-text

Real-Time Analysis and Visualization of Pathogen Sequence Data

Journal of Clinical Microbiology ◽

10.1128/jcm.00480-18 ◽

2018 ◽

Vol 56 (11) ◽

Cited By ~ 12

Author(s):

Richard A. Neher ◽

Trevor Bedford

Keyword(s):

Real Time ◽

Sequence Data ◽

Rapid Development ◽

Clinical Diagnostics ◽

Clinical Settings ◽

Sequencing Technologies ◽

Real Time Analysis ◽

Routine Surveillance ◽

Daunting Task ◽

Recent Developments

ABSTRACTThe rapid development of sequencing technologies has to led to an explosion of pathogen sequence data, which are increasingly collected as part of routine surveillance or clinical diagnostics. In public health, sequence data are used to reconstruct the evolution of pathogens, to anticipate future spread, and to target interventions. In clinical settings, whole-genome sequencing can identify pathogens at the strain level, can be used to predict phenotypes such as drug resistance and virulence, and can inform treatment by linking closely related cases. While sequencing has become cheaper, the analysis of sequence data has become an important bottleneck. Deriving interpretable and actionable results for a large variety of pathogens, each with its own complexity, from continuously updated data is a daunting task that requires flexible bioinformatic workflows and dissemination platforms. Here, we review recent developments in real-time analyses of pathogen sequence data, with a particular focus on the visualization and integration of sequence and phenotype data.

Download Full-text

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.

Download Full-text

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

10.1101/180406 ◽

2017 ◽

Cited By ~ 13

Author(s):

Richard M. Leggett ◽

Cristina Alcon-Giner ◽

Darren Heavens ◽

Shabhonam Caim ◽

Thomas C. Brook ◽

...

Keyword(s):

Gut Microbiota ◽

Real Time ◽

Time Course ◽

Sequence Data ◽

Clinical Samples ◽

Metagenomic Sequencing ◽

Time Analysis ◽

Metagenomic Sequence ◽

Real Time Analysis ◽

Increased Risk

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.

Download Full-text

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.

Download Full-text

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.

Download Full-text