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        <datestamp>2026-09-21T21:06:36Z</datestamp>
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          <dc:title>Robotic Centrifugal
Microfluidic Automation Enables
Library Preparation of Nine Samples with a Tenfold Reduction in Reagent
Consumption for Decentralized Sequencing</dc:title>
          <dc:creator>Trong Nguyen (12963380)</dc:creator>
          <dc:creator>Viola Dreyer (9693415)</dc:creator>
          <dc:creator>Yumi Kaku (25085596)</dc:creator>
          <dc:creator>Peter Juelg (11154372)</dc:creator>
          <dc:creator>Tobias Hutzenlaub (9361651)</dc:creator>
          <dc:creator>Stefan Niemann (62805)</dc:creator>
          <dc:creator>Nils Paust (6997982)</dc:creator>
          <dc:creator>Jacob Friedrich Hess (9361645)</dc:creator>
          <dc:subject>Space Science</dc:subject>
          <dc:subject>Medicine</dc:subject>
          <dc:subject>Biotechnology</dc:subject>
          <dc:subject>Environmental Sciences not elsewhere classified</dc:subject>
          <dc:subject>Ecology</dc:subject>
          <dc:subject>Biological Sciences not elsewhere classified</dc:subject>
          <dc:subject>Information Systems not elsewhere classified</dc:subject>
          <dc:subject>wet laboratory workflows</dc:subject>
          <dc:subject>substantially reduced due</dc:subject>
          <dc:subject>settings still rely</dc:subject>
          <dc:subject>placing required reagents</dc:subject>
          <dc:subject>employ standardized pipelines</dc:subject>
          <dc:subject>average coverage depth</dc:subject>
          <dc:subject>manual reference workflow</dc:subject>
          <dc:subject>costs per sample</dc:subject>
          <dc:subject>namely reagent preparation</dc:subject>
          <dc:subject>manual handling steps</dc:subject>
          <dc:subject>supports library generation</dc:subject>
          <dc:subject>mycobacterium tuberculosis &lt;/</dc:subject>
          <dc:subject>lp platform combines</dc:subject>
          <dc:subject>involving complex steps</dc:subject>
          <dc:subject>existing automation approaches</dc:subject>
          <dc:subject>total ngs costs</dc:subject>
          <dc:subject>strains including drug</dc:subject>
          <dc:subject>decentralized sequencing next</dc:subject>
          <dc:subject>sample handling</dc:subject>
          <dc:subject>lp platform</dc:subject>
          <dc:subject>manual pipetting</dc:subject>
          <dc:subject>investment costs</dc:subject>
          <dc:subject>library retrieval</dc:subject>
          <dc:subject>generation sequencing</dc:subject>
          <dc:subject>extensively drug</dc:subject>
          <dc:subject>decentralized laboratories</dc:subject>
          <dc:subject>reagent consumption</dc:subject>
          <dc:subject>tenfold reduction</dc:subject>
          <dc:subject>tenfold decrease</dc:subject>
          <dc:subject>satisfying throughput</dc:subject>
          <dc:subject>samples investigated</dc:subject>
          <dc:subject>pipetting robot</dc:subject>
          <dc:subject>nine samples</dc:subject>
          <dc:subject>microbial genomes</dc:subject>
          <dc:subject>medical diagnostics</dc:subject>
          <dc:subject>mdr ),</dc:subject>
          <dc:subject>crucial tool</dc:subject>
          <dc:subject>critical bottleneck</dc:subject>
          <dc:subject>centrifugal microfluidic</dc:subject>
          <dc:subject>bcg vaccine</dc:subject>
          <dc:subject>based cartridge</dc:subject>
          <dc:subject>98 %.</dc:subject>
          <dc:subject>97 %,</dc:subject>
          <dc:description>Next-generation sequencing (NGS) has become a crucial
tool for
medical diagnostics in decentralized laboratories. While sequencing
and bioinformatics themselves employ standardized pipelines, wet laboratory
workflows in these settings still rely on manual pipetting and sample
handling. In particular, the library preparation procedures represent
a critical bottleneck, accounting for up to 50% of total NGS costs
and involving complex steps. Automation offers potential solutions
to these challenges. However, existing automation approaches have
limitations in satisfying throughput, investment costs, costs per
sample, and degree of automation. Here, we implement a robotic centrifugal
microfluidic platform around the Illumina Nextera XT DNA Library Preparation
Kit or RoCM-LP platform, which supports library generation from microbial
genomes. The RoCM-LP platform combines a centrifugal microfluidic-based
cartridge with a pipetting robot, capable of producing nine libraries
per run at low-medium initial investment costs ($50k–70k).
The costs per sample were substantially reduced due to a tenfold decrease
in reagent consumption in comparison to the manual reference workflow,
and the number of manual handling steps was minimized from 45 to just
three, namely reagent preparation (placing required reagents into
the RoCM-LP platform), sample loading, and library retrieval. The
approach achieved quality metrics comparable to those of the manual
reference workflow and met all required sequencing quality thresholds
across four &lt;i&gt;Mycobacterium tuberculosis&lt;/i&gt; complex (MTBC)
strains including drug-susceptible, BCG vaccine (Pasteur Bacillus
Calmette–Guérin), multidrug-resistant (MDR), and extensively
drug-resistant (XDR) strains for tuberculosis (TB) samples investigated,
with an average coverage depth of 107, an average mapped read percentage
of 97%, and an average coverage breadth percentage of 98%.</dc:description>
          <dc:date>2026-09-21T00:00:00Z</dc:date>
          <dc:type>Dataset</dc:type>
          <dc:type>Media</dc:type>
          <dc:identifier>10.1021/acs.analchem.6c03501.s003</dc:identifier>
          <dc:relation>https://figshare.com/articles/media/Robotic_Centrifugal_Microfluidic_Automation_Enables_Library_Preparation_of_Nine_Samples_with_a_Tenfold_Reduction_in_Reagent_Consumption_for_Decentralized_Sequencing/33960001</dc:relation>
          <dc:rights>CC BY-NC 4.0</dc:rights>
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