Tag Archives: sequencing

August 12, 2016 · 13:22

Background on the poreFUME pre-print

porefumlogoLast week our pre-print on nanopore sequencing came online at bioRxiv. Nanopore sequencing is a relatively new sequencing technology that is starting to come of age. As part of this process we last year started playing with the ONT MinION sequencer. This post summarizes a bit of the background behind the pre-print.

Previously I covered the London Calling 2015 event  where a lot of progress on the development of the MinION was showcased. We were keen to find out how the MinION could contribute to our daily lab work, but also to see what new ground can be covered with this new sequencing technology.

One of the aspects colleagues in the lab are working on is the dissemination of antibiotic resistance genes, as a major healthcare challenge is the emergence of pathogens that are resistant against antibiotics. Therefor we thought of combining the MinION with antibiotic resistance gene profiling. More specifically; coupling functional metagenomic selections with nanopore sequencing.

Previous work in this field, for example by Justin O’Grady and colleagues, showed the use of the MinION [$] to identify the structure and chromosomal insertion site of a bacterial antibiotic resistance island in Salmonella Typhi.

Instead of going after single isolates, we set out the map the antibiotic resistance genes that are present in the gut (resistome) of a hospitalized patient. The resistome can influence the outcome of antibiotic treatment and it is therefor highly interesting to get insights in this complex network.   Through a collaboration under the EvoTAR programma with Willem van Schaik of the University of Utrecht we had a clinical fecal sample available of an ICU patient, which we used in the experiments.

Typical workflow of the construction and selection of a metagenomic workflow.

Typical functional metagenomic workflow where metagenomic DNA is isolated from a (complex) environment, in this case a fecal sample. The DNA is sheared, ligated and transformed in E. coli. When profiling for antibiotic resistance genes, the cells are plated on agar containing various antibiotics. Finally the metagenomic inserts are sequenced an annotated.

Key in the whole experimental setup to capture the resistome is the use of functional metagenomic selections. In contrast to culturing individual microorganisms directly from a fecal sample, metagenomic DNA is extracted from the sample. This metagenomic DNA is subsequently sheared, ligated and transformed in E. coli and finally plated out on solid agar containing various antibiotics. Only E. coli cells that harbor a metagenomic DNA fragment that encodes for an antibiotic resistant phenotype can survive. With these functional metagenomic selections in hand, the complexity of the resistome can be rapidly mapped.

And this is were the MinION comes in. Although other sequencing technologies, such as the Illumina and the PacBio platform, are available, they do not provide both long reads and low capital requirements.

 

 

After some initial failed attempts to get the MinION sequencer running in our lab, we started to see >100 Mbase runs in October last year. Also PoreCamp last December in Birmingham provided, on top of a great experience and nice people, some useful data (next week a new round of PoreCamp takes place).

In order to analyze the sequencing data that Metrichor generates we developed the poreFUME pipeline, which automates the process of barcode demultiplexing, error correction (using nanocorrect) and antibiotic resistance gene annotation (using CARD). The poreFUMe software is available on Github as a python script. The subsequent analysis is as well available on Github in a Jupyter notebook.

The jupyter notebook is available here

The Jupyter notebook with the analysis in the pre-print is available here.

In order to benchmark the nanopore sequencing data we also Sanger and PacBio sequenced the sample. From these results we could achieve a >97% sequence accuracy and we were able to identify all the 26 antibiotic resistance genes in both the Pacbio and nanopore set.

Since the whole workflow can be performed relatively quickly, it would be really interesting to move these techniques to the next stage and do in-situ resistome profiling. Especially integrating Matt Loose’s read-until functionally could open up new avenues. Furthermore these experiments were done with the R7 chemistry, however it seems that the new R9 chemistry is able to deliver even higher accuracies and faster turn-around.

The fasta files and poreFUME output used in the analysis are already online, the raw PacBio and MinION data is available at ENA

Update 2016-11-01: Added the ENA link to the raw data

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May 16, 2015 · 18:07

Recap of the Nanopore sequencing conference ‘London Calling’ by ONT

MinionLast Thursday and Friday Oxford Nanopore Technologies (ONT) hosted it’s first conference ‘London Calling’ where participants of the MinION Access Program (MAP) presented their results and experiences after 11 months of the program. The CTO of ONT also delivered  a session where the future directions where outlined. Below a quick recap of two days of London Calling.

There were about 20 talks (agenda) by a broad range of scientist from microbiologists to bioinformaticians. A few observations I found interesting to share:

  • John Tyson (University of British Columbia) wrote a script that slightly alters the voltage along the run to keep the yield curve linear, he uses this method standard for each of his runs
  • The majority of the presenters just only use the 2D reads
  • A nice month-by-month overview of the MAP program can be found in Nick Lomans talk here
  • Miles Carroll (Public Health England), Josh Quick (University of Birmingham) and Thomas Hoenen, NIH/NIAID) went to Africa last year to sequence the Ebola virus outbreak and were able to map the outbreak on phylogenetic timescale, they used RT-PCR to generate the input material. Main conclusion here was that field sequencing with the MinION works, the Ebola mutation rate is not higher than other viruses, key drug targets are not mutating.
  • People are exploring a lot of options to use it in clinical setting, for example for rapid identification of bacterial infections (Justin O’Grady, University of East Anglia) or for pharmacogenomics (Ron Ammar, University of Toronto); in short which drugs not to prescribe to patients because their liver cannot metabolise them due to a genetic modification, read the paper here.
  • A detailed account on how to assemble a bacterial genome with only Nanopore data by Jared Simpson can be found on Slideshare, it’s an interaction version of this pre-print
  • Currently MinION + MiSeq data is the way to go short-term future (according to Mick Watson) for genome assembly. Alistair Darby, University of Liverpool argued to just use 1 sequencing technology to perform the whole genome assembly because to much time can/is wasted to integrate all the different sequencing methods with different algorithms.
Minion

DNA sequencing becomes really personal now

During the talks some requests were put forward:

  • More automation for lib prep / faster lib prep protocol (this will be tackled either with VolTRaxx and/or a bead protocol for low input material and a 10 minute protocol for 1D reads announced by CTO Clive Brown)
  • More stable performance between individual flow cells
  • Base calling off-line so no need to connect to the cloud
  • Tweaking the base caller for base pair modifications (for example methylation)

On Thursday afternoon there was the talk of Clive Brown the CTO of ONT. On Twitter the talk was compared with a “Steve Jobs style” way to reveal the new products.

A few points he presented:

  • There will be at the end of the year/next year a new MinION release that has the ASIC electronics not in the flow cell but in the MinION itself, this would drastically cut the price of the flow cells (from 1000$ -> 25$). Another big change here is the chip will contain 3000 channels instead of 512. Furthermore runtime of these device will also be around 2 weeks.
  • All the shipments should be room temperature soon
  • A “fast mode“ will be available within the next 3 months where a typical run will not generate 2Gbase of data but 40Gbase of data.
  • VoltTRAX is developed which can be clicked on a flow cell and will automate the full lib prep process, they imagine users can load a mL of blood sample on the VolTRAX and it will be prepped automatically.
  • At the same time ONT will implement a different price structure where you pay per hour of sequencing instead of per flow cell, so you can just run a MinION for 3 hours and pay, say 270$ and don’t pay anything else.
  • The PromethION (kind of 48 MinIONs in 1 machine and more channels per chip) will be launched with Sequencing Core facilities as their main costumer in mind, however they will create a MAP for this (PEAP) as well. The PromethION It will include the above improvements as well, making it potentially more productive than a HiSeq.
Oxford Nanopore Tcchnologies CTO Clive Brown showcasing the VolTraxx automatic sample preparation unit

Oxford Nanopore Tcchnologies CTO Clive Brown showcasing the automatic sample preparation device VolTRAXX.

In conclusion the conference atmosphere was very upbeat with a lot of enthusiasm for the future of nanopore sequencing. Can’t wait to get this MinION started.

 

 

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