Element Bio (@elembio) is announcing their first instrument today. I'll concentrate on my own highlights on the presentation, which I am sure it'll be available as a video later on.
My professional interest on the announcement today is: could this be a replacement to a mid-throughput instrument like the NextSeq 2000/1000? If the price in the first specs slide is right, I think the answer is yes!
The Challenge -- Decrease Cost/Gbp without requiring ultra-high throughput
AVITI Instrument for $289K with 2 flow cells at $5-7/Gbp with read lengths at 2x75, 2x100, 2x150.
Details on how this works, technology-wise:
Surface chemistry is low binding, which means the proteins from previous cycles don't attach to it, lower background. Description of the Avidity Advantage.
A difference of 100-fold reduction in reagent consumption per cycle, which makes the system more cost effective than "traditional methods". The multivalency is key: the fluorophore is attached to many avidites.
More details on how the Avidite system works
On the optics, they managed to use better optical properties from the new CNR. Data quality impressive.
Sample prep and analysis. On the former, we've already seen a plethora of announcements with other companies. Primary analysis gives FASTQ files ready for the next step. Multiplexing to up to 96plex, minimal index hopping.
Data ecosystem and partnerships
A slide of the elements of the system, with the idea of going into DNA, RNA, Protein, Cells...
Open to collaborations
AVITI instrument in the field. Hudson Alpha one of the beta testers.
Very cleverly, there is a library conversion process: take existing (Illumina) libraries and convert them so they can be sequenced on the Element Bio AVITI instrument.
Tunable output: I think this means you can interrupt a run if it's not going well, and reuse the remaining reagents later on.
Element Bio announced recently that they acquired Loop Genomics, a SanFran company that creates synthetic long read molecules from short-read readouts. Importantly, they will continue selling to non-Element Bio customers.
The sample prep kit has all needed for taking the long molecules into an NGS sequencer, then analyse via the associated software to transform into the synthetic long reads.
Loop barcode with a UMI attaches to the long molecule, it is then amplified, and then the "Distribute" step, which is a copy+paste step of the barcode "within" the long read molecule.
Each cluster of short reads with the same barcode is then assembled in silico to produce long read FASTQ files.
I am thinking how this differs to the Moleculo approach: it's probably bead-based instead of diluting plates, but other than that, the assembly process seems similar. Compared to Longas (Illumina Infinity?) there is no introduced long PCR mutation to "label" short-reads.
Data shown concentrating on amplicons (1KB, 2KB, 4KB, 8KB) and RNA full-length molecules.
LoopSeq Solo: Sanger-like sequencing using NGS. Multiplex your sequences of interest in plates, then put on an NGS instrument, then reconstruct the Sanger-like longer reads.
The Loop kits with the Avidity kits will allow people to run not only short-read but also synthetic long-reads with the AVITI instrument.
More emphasis on the new surface chemistry with a 10x better CNR. The whole method took only 4 years to develop and implement into the AVITI instrument.
Who is getting AVITI Instruments? First come first served. Wanting to incentivise the first wave of customers to people that show the power of the platform.
3 beta customers that they could disclose, then another round currently ongoing.
Entering the market with a very robust ecosystem.
Christopher Mason @mason_lab on the testing of the AVITI instrument.
Tried a 10X Genomics multiome kits on the AVITI instrument. Very similar results to Illumina.
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=== Linked-Reads Chromium Genome and Exome ===
10x Genomics started as a company by selling instruments and reagents for their Linked-Reads method to generate long synthetic DNA reads out of short-read readouts such as those from Illumina SBS sequencers.
These Linked-Reads were useful for de novo genome assembly applications, where the length of the reads is crucial to produce long assembled sequences. As of June 30, 2020, the company discontinued the sale of the Chromium Genome and Exome product lines.
Those who follow my account for a while will already know that I've been following the field of Next Generation Sequencing for many years now, and I keep a series of resources comparing different platforms and technologies.
Beyond the first tier of 4-5 large NGS companies out there, such as Illumina, PacBio, Oxford Nanopore, Thermo's Ion Torrents and MGI Tech, there is now a growing group of small companies pinning for an NGS market which is growing and maturing in many ways.
I keep a table comparing these companies, with around 40 different ones, although some of them have a small chance of making it into the market, and they may be acquired by someone else to expand their technological capabilities. bit.ly/nngseq
So after Oxford @nanopore's #NCM21 tech dev presentation, where does this leave ONT technology in comparison of Illumina? (thread)
The ONT technology offers a lower barrier to entry with the MinION, and this results in a competitive advantage over turn-around time sensitive applications (Point of Care settings).
ONT showed their competitiveness in both long-read and short-read applications yesterday, a limitation for Illumina which tried to overcome with their failed attempt to acquire PacBio.
Clive (probably sipping a piña colada by the beach) is updating on tech at @NanoporeConf@nanopore
Three steps: (1) Sample Preparation, (2) Data Acquisition and (3) Sequence Data (basecalling)
"[...] everything apart from the computer is designed by Nanopore, but [the computer side] may change in the future, by the way". Unreasonable to think they will build their own silicon specialized for base-calling?
Their DNBSEQ-Tx sequencing factory, with dip-immersion reagent delivery and 4 high-throughput imagers, can produce >50K WGS annually. Technology being upgraded from PE100 to PE150 (2021Q3)
A presentation from a user shows how #singlecell 10X Genomics libraries can be inputted into the MGI machines. Small difference between FASTQ files, but tools available to transform.