Fluent Biosciences

TL;DR

Fluent Biosciences is a biotechnology company revolutionizing single cell analysis through simple, cost-effective, and scalable solutions.

In offering reactions of up to 1,000,000+ cells, Fluent noticed many labs lack the informatics infrastructure to analyze data at this scale.

Fluent Biosciences uses Latch to empower scientists to easily analyze data from all their kits, flexibly and at scale. Complete with a UI and user guides.

• A simple informatics solution for all kits (T2, T10, T20, T100, T1000)

  “If customers have any concerns about processing data, we tell them about Latch. It is really easy to refer users to Latch, it’s low burden to make that connection and the team is very responsive.”

  
• Scalability for massive kits (over 30 billion+ single-cell reads)

  “We were able to analyze 1 million+ single-cells in 48 hrs. I think it’s a great solution for all scales.”

  
• Happier customers with 80% faster time-to-insight

  “When we’re speaking to customers, we refer to the fact they can run it on Latch, it’s available now in almost every customer call.”

  

Fluent Bioscience's story

Fluent’s internal bioinformatics team built PIP-seeker, a powerful tool to analyze sequencing data from PIPseq™ V Single Cell3′ Gene Expression libraries.

PIP-seeker offers user count matrices, summary metrics, diagnostic plots, clustering and differential gene expression tables to get insight from kits.

Challenges

The tool is hard to access and use without bioinformatics training and large computers. This can lead to delays in insight and repurchasing kits.

Solving this is hard. Creating a simple informatics solution to process 20,000 cells to 1,000,000+ cells requires cloud infrastructure and user interfaces that are prohibitive for Fluent to build.

The solution is either for Fluent to process the data for customers, or for the customer to struggle with their own HPC, leading to delays.

An example: WUSTL struggled to process 1 million+ cells

One of fluent customers is named Sadie VanHorn, a PhD Candidate in Morris Lab at WUSTL.

Sadie used the T1000 prototype kit to capture up to 1 million cells, with the goal of showing clonal lineage trees that have restriction of specific cell reprogramming fates.

But the data became a huge bottleneck. To align the reads, the team was struggling with memory limitations on local High Performance Computers (HPCs) that led to weeks of delay getting insight.

Solution

After partnering with Latch, Fluent’s team used the SDK to upload PIPseeker to Latch, generating a simple user interface to run the tool.

This gave users access to virtually unlimited computing resources, a simple user interface, and the ability to explore downstream results.

With this in place, Sadie was able to process a 1 million+ cell dataset on Latch. Processing time took under 2 days, reduced the AWS costs for Fluent by over 80%, and led to a simpler user experience for Sadie.

Expanding to all kits

With this success proving out 1 million+ cells, the team at Latch expanded support to all Fluent kits, working with Fluent Biosciences’ internal bioinformatics team to support T2, T20, T100 kits for all customers.

The workflow UI can be updated any time instantly by Fluent developers, including core workflow changes, chemistry, and kit updates.

Learn more

To learn more about the breakthrough science being done at Fluent Biosciences, visit their website.

To learn more about Sadie Van Horn’s research on Cellular reprogramming, watch her case research presentation.

To learn about single-cell lineage tracing at Samanth Morris’ lab, read the following paper: Single-cell lineage capture across genomic modalities with CellTag-multi reveals fate-specific gene regulatory changes.

Thank you to contributors!

Yigal Agam for innovation and development of PipSeq algorithms. Aaron-May Zhang for rapid iteration, feedback, and development. Rahul Desai for cloud infrastructure management and SDK development. Kristina Fontanez for bringing everyone together to work on this project. Sadie Vanhorn for pushing the edge of cellular reprogramming research.