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Application of Metagenomic Next Generation Sequencing to Detect and Identify Pathogens (Round 22)


**NOTE: Although this challenge topic’s open date (October 15th) and close date (December 5th) differ from the other Round 22 GCE Grant Opportunities, grantees will still be a part of this round’s cohort.

The Opportunity

In order to identify and treat existing and emergent infectious disease efficiently, clinicians and the global health community must have access to accurate and timely estimates of disease burden and distribution. Traditionally, summaries of these data have been manually reported by national health ministries from regional clinical data, aggregated from local health centers. Local institutions, however, face multiple challenges to accurately assess the emerging needs of their community with current toolsets. For example, most clinical tests are based on common or easily detectable pathogens previously identified, which can miss occult and/or emerging pathogens. In addition, curation of large-scale pathogen data across multiple locations/platforms is time consuming and expensive, preventing facile integration of individual patient-level diagnostic data into a larger pathogen landscape on the regional and national level.

Recent breakthroughs in pathogen sequencing technology - both at the hardware and software level - enable the combination of rapid deep sequencing of patient samples with subsequent sequence mapping to a custom, continuously updated reference database to provide near-real-time pathogen detection. Yet, these advancements alone have not been sufficient to provide metagenomic sequencing to patients in low- and middle-resource settings that could benefit the most, largely due to limitations in access or availability of the following essential components: a) expensive equipment/reagents, b) specialized biochemical training, c) accurate reference pathogen sequence databases, d) and advanced computational analytics.

The Challenge

Recognizing barriers for adoption of next-generation sequencing in global health, the Bill & Melinda Gates Foundation has partnered with the Chan Zuckerberg Biohub and the Chan Zuckerberg Initiative to enable patients in low- and middle-resource settings to benefit from cutting-edge pathogen detection and discovery. This partnership will provide highly specialized training in biosample preparation and sequencing to technical staff from awardee global health centers. Trainees will learn to use the open-source, open-access IDseq software developed by CZ-Biohub for the global health community to upload and analyze patient sequencing data. The BMGF-CZ-Biohub partnership will therefore aim to provide selected applicants the benefits of onsite next generation sequencing and rapid pathogen detection to better understand their local pathogen landscape. We are specifically seeking projects that endeavor to build upon their initial locally-focused effort to contribute to future data-informed decision-making at the population level via data sharing and pathogen data comparison across sites.

Through this GCE award, BMGF will support travel and accommodation of grantees for pilot analysis of samples from their home region during hands-on, intensive mentoring provided by the CZ-Biohub in San Francisco. This 2-week instructional period will include both biochemical sample preparation for sequencing and bioinformatic analysis using the IDseq software platform. Specifically, the hands-on training for bench scientists will include best practices and standards for sample processing, DNA & RNA extraction, library preparation and data analysis on the Global IDseq software platform. Upon completion of training at CZ-Biohub, laboratory teams are expected to use the remaining GCE award primarily on the following items: 1) a sequencer[1],[2] suitable for the global health environment, 2) a dedicated sequencing technician, and 3) sequencing reagents for the duration of the award. The combination of intensive training with molecular, capital equipment, reagent, and personnel support is intended to maximize the potential for sustainable, prospective, onsite analysis of patient samples upon return to the home site. A list of compatible sequencers appropriate for global health use is listed here.

Molecular data generated at individual global sites is intended to be linked and automatically aggregated into IDseq for referencing by all participating clinics and associated sites. This method of local sequence analysis coupled with cross-site comparison could serve as a model for a process that would eventually lead to a network of pathogen detection nodes that could provide increased global transparency into regional pathogen distribution in an accurate and timely manner.

Examples of insights could include:

  1. Deciphering unknown medical cases
  2. Identification of new pathogens
  3. Detection of local outbreaks
  4. Characterization of the local pathogen landscape, including vector-borne diseases
  5. Detection and classification of AMR Markers, with potential for insight into antibiotic treatment discordance
  6. Data-informed healthcare and resource allocation

We are specifically looking for sites that believe in collaborative approaches and data sharing. Grantees will be expected to partner closely with scientists and engineers and provide feedback to help guide the cloud computing software’s development. Sites will also be expected to share data and collaborate with other labs in the network.

We will consider sites that:

  • Provide a clearly scoped initial project that demonstrates why this technology will provide insights that are not currently possible.
  • Have space and capacity to run samples on a basic, globally rugged sequencer once provided with training, reagents, sequencer, and a dedicated computer.
  • Have consistent access to electricity and the ability to upload data via internet to a designated cloud server at least once a day.
  • Are willing to give product feedback and collaborate with an engineering team through scheduled video calls, email, or other messaging service.
  • Are committed to open science, preprints, and data sharing.
  • Already have, or can rapidly acquire, necessary IRB approval for pathogen DNA and RNA sequence sharing from patients.
  • Include neonatal and infant patients as a substantial fraction of overall sampling
  • Are representative of larger geographic regions

We will not consider sites that:

  • Do not articulate how they will leverage the value of next generation sequencing to impact health outcomes.
  • Are interested exclusively in Whole Genome Sequencing
  • Do not plan to share their pathogen data and discoveries.
  • Have extremely limited internet access.
  • Are limited to previously stored samples, without substantial potential for prospective sample collection.


[1] Recognizing that shipping costs and tariffs for the sequencer could significantly impair the intended impact of projects, grantees will be allowed to submit invoices for these costs to the foundation for reimbursement.

[2] To ensure the sequencer continues to be used for purposes consistent with the foundation’s charitable objectives, we may request that funded applicants other than charities, universities, and similar organizations donate any sequencer purchased with grant funds to a charity or university, after the 18-month term of the project.

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