Transcript Nucleic_Acid_Processor_Part_

A Nanoliter-Scale Nucleic Acid Processor
with Parallel Architecture
Jong Wook Hong, Vincent Studer, Giao Hang,
W French Andreson, Stephen R Quake
presented by:
Anna Shcherbina
Michael Meyer
Motivation for Single-Cell mRNA/ DNA Extraction
Goal: Use Single Cell To Establish
cDNA Library
 Gene Expression Profile
Primary cells hard to
obtain in large
quantities .
Isolating cells from
animals or patients
results in a mixture
of cell types.
Epigenetic variation
between cells with
identical genotypes
influences development.
Existing Technologies and their Limitations
Affinity capture and elution of purified DNA
from silicon microstructures
 Deep Reactive Ion Etching (DRIE)
 On the order of uL, not nL
 No parallelization
 No integration

Microarrays measure expression of a few genes from a
single cell
 Amplification process introduces distortion
 Require choice of finite set of possible transcripts

Currently, cDNA library construction methods requires
1000-10,000 input cells.

Innovation:
Microfluidic Chip to Sequentially Process nL Volumes and Isolate Cells
Small-Volume Scaling
Process Integration

Fabricated by multi-layer soft
lithography

Lysing and purification performed
directly on the chip.
 No pre/post-treatment needed.

Compatible with many biological
assays
 Protein crystallization
 nL -volume PCR
 FACS
 single-cell enzyme screening

mRNA Purification Chip Design
bead
chamber
Lysing buffer
chamber
cell
chamber
Fig 1. a. Layout of microfluidic chip, version 1.
Channels are 100 um wide. Fluidic ports are
named; actuation ports are numbered 1-11.
b. Photograph of the in situ affinity column
construction. Scale bar 200 um.
c. Cell loaded into cell chamber before lysis
step. Scale bar 100 um. (Hong et al.)
Performance & Sensitivity Assay
Primers used to identify high abundance B-actin transcript and moderate abundance
OZF transcript.
18 experiments performed.
 5 of these used a single cell.

Fig 2. RT-PCR analysis of isolated mRNA. RT-PCR products analyzed on 2% agarose gel
loaded with 5% of reaction. (Hong et al.)
Chip Sensitivity Assay Results
B-actin purified from cells in 14
out of 18 experiments
Between 2-10 cells required to
detect OZF mRNA signal
Monotonically increasing
relationship between band
intensity and cell number in Bactin mRNA.
No functional relationship
observed in non-normalized
data.

Fig 3. RT-PCR products for both transcripts were
analyzed on a 2% agarose gel, whose bands were
quantified and normalized. Zero values indicate absence
of detectable band in gel. (Hong et al.)
DNA Purification Chip Architecture (advances)
•Parallelization
•Align several linear processors and use
same cross-junction structures to load
them simultaneously.
•Loading & Processing Flow
•Loading--fluid flows north/south
•Processing--fluid flows east/west, along
each batch processor
•Customization
Fig 4. Temporal action of DNA isolation
circuitry (Hong et al.)
Full Chip and Experimental Setup - Characterization of Sensitivity
•Each processor hold 5 nL
•Volume of cells used: 1.6, 1.0, 0.4 nL
•remaining volume is reaction
buffer and lysis buffer
Fig 5. Food-coloring reveals the interconnectivity of
chip. (Hong et al.)
DNA Yield Experimental Results
a. Undiluted E. coli culture
Lane 1: 1.6 nL culture (~1120 cells)
Lane 2: 1.0 nL culture (~700 cells)
Lane 3: 0.4 nL culture (~280 cells)
Lanes 4-6: Negative control (pure H2O)
b. 1:10 dilutions
Lanes 1,4,7: diluted 1.6 nL
Lanes 2,5,8: diluted 1.0 nL
Lanes 3,6,9: diltued 0.4 nL
c. Intensity of gel bands
Fig 6. Verification of the successful recovery of
E. coli genomic DNA. Samples have been PCR
amplified. (Hong et al.)
Potential Uses and Impact
•Increasing throughput in single-cell analysis
•Automation of reagent preparation for large cell populations
•industrial-scale microarray analysis
•Preparation step for environmental analysis or medical
diagnostics
•Tool for microculture and analysis of slow-growing or
unculturable bacteria
•Generation of subtractive libraries from pairs of single cells
•eliminate commonly expressed transcripts &
•enrich differentially expressed transcripts