staphylococcus aureus strain typing by single-molecule...

White, E.J., et al. 1

Supplemental Data

Staphylococcus aureus Strain Typing by Single-Molecule DNA Mapping in Fluidic

Microchips with Fluorescent Tags

Eric J. White, Sergey V. Fridrikh, Nirupama Chennagiri, Douglas B. Cameron, Gregory P.

Gauvin, Rudolf Gilmanshin

Mini-Reactor System for Preparation of Tagged DNA Samples

The automated mini-reactor (MR) system has been designed to extract, purify, and process large

fragments of bacterial genomic DNA (1). Injected cells are collected on the ultrafiltration

membrane within the MR and are subjected to a series of consecutive enzymatic and

hybridization reactions at various temperatures as well as to selective wash and buffer exchange

steps. Cells and subsequently DNA are held on the membrane throughout the procedure by a

small flow through the membrane, while cell debris and byproducts of the reactions are

selectively removed from the MR. The system can produce long DNA fragments (up to 0.5 Mb)

of bacterial genome restriction digest and perform tagging of DNA with fluorescent sequence-

specific probes. The MR produces DNA of high purity, floating free in solution, ready for direct

linear analysis (DLA). Except for injection of the cells and reagents, all other steps of the

protocol are automated. Therefore, the processing excludes operator-related variations and is

very reproducible. The quality of MR-produced DNA is equal or superior to that of agarose plug

preparations.


The MR function is based on three concepts. First, from the moment DNA molecules are

released from cells and until specifically digested down to submegabase fragments, they remain

immobilized on the membrane and encounter only low flow rates. This approach protects DNA

from damage. Second, introduction of reagents into the MR occurs by forced penetration through

the sample layer in an injection mode. This approach eliminates both reliance on diffusion and

the need for mixing. The former accelerates processing, the latter preserves DNA. Third, rapid

and efficient buffer exchange and removal of reaction byproducts can be achieved with a

selective wash mode. In this mode, even particles too large to pass through the membrane can

still be efficiently removed from the MR by tangential flow along the membrane. This permits,

for example, injection of cells in broth for processing directly from cultures.

DNA isolation and processing is performed within a conical reaction chamber. In every

mode, except for elution mode, all sample solutions, reagents, and buffers are injected through

the injection inlet on top of the chamber. The inlet flow can leave the chamber either through the

membrane, or through the side outlets, or both. All flows are carefully controlled. Samples and

reagents are introduced through a manual injection valve.

The sample preparation protocol consists of sequential, computer-controlled, steps. Each

step belongs to one of 5 modes: injection, selective wash, elution, backside frit wash, or line

priming. Every mode defines the directions of the flows through the chamber. Each step has

variables such as: solution to be used, volume to be delivered, flow rates, chamber temperature,

and incubation time.

In injection mode, the flow controller valve is closed and the bottom outlet is opened;

therefore, only normal flow (through the membrane) exits the reactor.


In selective wash mode, both the flow controller valve and the bottom outlet are open. A

portion of the inlet flow exits through the side outlets and the flow controller valve. The

remaining portion of the flow passes through the membrane into the bottom cavity.

Incubation steps are usually performed in the absence of flow by closing all inlets and

outlets of the MR.

Elution of the DNA sample from the chamber is performed by reversing the flow through

the membrane. The flow lifts the DNA sample from the membrane and carries it out through the

injection line for fraction collection.

In this work, we used the MR system to produce samples of tagged genomic DNA from

Staphylococcus aureus. The sample preparation protocol is presented in the Supplemental Data

Table 4. The complete procedure took approximately 5 hours. Cells or reagents were injected

manually in 100 µL aliquots into the injection loop and pushed into the reaction chamber by the

volume of buffer indicated in Supplemental Data Table 4. We typically injected 108 cells for

each preparation.

Direct Linear Analysis

SYSTEM AND MEASUREMENTS

DLA technology (2) employed both hybridization of long DNA molecules with fluorescent

sequence-specific tags, such as bisPNA, and non-specific staining with another color fluorescent

dye, such as intercalator. The stained and tagged DNA molecules were directly introduced into a

microfluidic chip, where they were uncoiled and conveyed in this stretched conformation to the

detection zone for single-molecule mapping. There were two displaced spots at which the

fluorescence of stained DNA was measured. Using the known distance between the spots and the

delay between the detections at the spots, the velocity and length of each DNA molecule were


determined. Simultaneously, using detection of different color fluorescence, the positions of the

hybridized tags along the DNA molecule were determined. Measurements were performed as

described previously (2, 3) at a linear flow rate of ~12 µm/ms, and data was recorded at 30 kHz.

The first spot for detection of intercalated DNA was 40 µm apart from the funnel. A new color

scheme was used with DNA intercalated by POPO-1, which was excited with blue light at 445

nm. Emission from the ATTO550 (bisPNA tag) fluorophore was excited by green laser light at

532 nm. The new optical components required for POPO-1 detection are presented in (1). Other

components of the optical system were the same as published previously (3).

MICROFLUIDIC CHIP

The fused silica chip used in this study was similar to the microfluidic device described

earlier (4). It also employed a four-port design with hydrodynamic flow focusing. However, its

geometry had been modified to be compatible with longer DNA. The chip is 1 µm deep with a 5

µm wide interrogation channel. The taper shape has a profile width described by W(x) ~

Wi/(1+(x/a)) where W is the width, x is the coordinate along the flow direction, and a = 4.040816

(all measured in microns). The taper length is 198 µm and the width of the channel before the

taper, Wi, is 250 µm. The injection port and sheathing buffer pressures were adjusted to obtain

the focusing ratio of about 20 (the width of the sample flow is 1/20 of the width of the

interrogation channel. The chips were manufactured by Micralyne, Inc. (Edmonton, Alberta,

Canada).

Data Analysis

SINGLE-MOLECULE MAPS

Using an in-house software package, single molecule DNA traces were located in the data stream

by identifying correlated signals between the two laser light spots, which excite intercalator


fluorescence. The length, velocity, average intensity, and tag signal of each molecule were

extracted as described previously (2, 5).

GENERATION OF THEORETICAL MAPS

To assess the accuracy of maps obtained with DLA, we generated theoretical maps of restriction

fragments of the strains with known genomic sequences. Using the known cognate sequence of

the restriction enzyme and complementary sequence of the bisPNA tag, we determined the

expected restriction fragments, their lengths, and the positions of the hybridized tags. The

hybridization sites with both exactly and partially matching sequences were considered as

possible tag sites. Of the latter, only the sites with a single mismatch at one of the termini (single

end mismatch sites, SEMM) were included (2, 3). All hybridization sites were assigned binding

probabilities, differing for matching and SEMM sites, which defined the intensities of the peaks

in the averaged theoretical fragment map. The degrees of tagging, which varied slightly from

experiment to experiment, could be adjusted to fit the experimental traces.

IDENTIFICATION OF MAPS OF ALL LONG FRAGMENTS

Data analysis was a multistep process, starting with interpolation and filtering of single-molecule

traces (Supplemental Data Fig. 6). Interpolation involved transforming the data associated with

each molecule from uniform time intervals (bins), which varied in number depending on the

length and velocity of each molecule, onto a regular grid of 200 intervals for every molecule.

This facilitated the comparison of molecules in subsequent steps.

Filtering involved excluding molecules that were unlikely to be identified due to hairpin

conformations, overlapping, or spurious contaminants with bright fluorescence detected

simultaneously with the DNA molecules. Folded and overlapped molecules were readily

identified by uneven intensity profile of intercalator fluorescence. They were excluded if the


intercalator fluorescence intensity surpassed a threshold of approximately twice the median value

for that molecule over a fixed number of consecutive bins. Contaminants were identified by

anomalous brightness in the tag detection channel, and DNA molecules were excluded if the

number of photons in any bin detected in that channel exceeded the threshold of 200 photons,

which was about 5-fold stronger than the expected maximal peak intensity. Both filters combined

excluded 25% to 75% of single molecule traces in different experiments.

Next, we calibrated the conversion between observed geometric DNA length in microns

and genomic length in kilobases. The conversion depended on the degree of intercalation, which

varied between experiments. We added a length standard to each sample, a 126 kb recombinant

DNA fragment, which was developed in our laboratory and produced in large quantities. This

fragment was intercalated but untagged to be readily identifiable by its low average intensity in

the tag detection channel. By testing E.coli samples whose fragments were of known length (data

not shown), we found that the conversion was slightly non-linear and a small fixed quadratic

term was included in the calibration. The final length accuracy was ±2-3%.

The molecules passing filtration were then grouped into clusters to identify average

restriction maps. The software was written to perform k-means clustering over several stages

(Supplemental Data Fig. 6). Initially we employed a rank-based metric to evaluate the similarity

of each pair of traces expressed as a trace-to-trace distance. The trace with the closest n nearest

neighbors on average was selected as a center of a potential cluster with the parameter n an

adjustable parameter. This trace and its n nearest neighbors were declared a cluster. This

procedure was repeated until all traces were divided into preliminary clusters of n+1 traces.

Preliminary clusters with similar averages were merged. Averages of the resulting clusters were

used as seed templates for clustering in a second clustering stage. For this stage, trace-to-seed


template distances were defined as 1 – c(i,j), where c(i,j) is the correlation coefficient of the i-th

trace and j-th seed template The final clustering step employed a probability distance metric

based on intensity probability distributions generated for all bins of all clusters. As a result of

this clustering, we obtained a set of average trace maps for each restriction fragment of a

digested microorganism.

In some cases, the resulting trace average included non-linear distortions of position

along the DNA as a result of molecule acceleration in the stretching funnel during detection. This

occurred if the length of a DNA fragment exceeded the distance between the stretching funnel

and the excitation light spot. We developed and applied a numerical routine to correct for the

dominant harmonic term of this distortion by optimizing the similarity between head-first and

inverted tail-first pairs of the same fragment.

SAMPLE SIMILARITY INDEX

To quantify the similarity of samples, the average trace from each fragment in one sample was

compared to the average trace of each fragment in the other sample. The minimum of Spearman

and Pearson correlation coefficients between average traces was used to quantify the similarity

of fragments. The current algorithm was capable of comparing either two fragments as a whole

or one whole fragment as subset of another fragment (Supplemental Data Fig. 7). Two fragments

were considered matching if the correlation coefficient between them was greater than an

empirically determined threshold of 0.7.

To determine the threshold, we compared all fragments and plotted a histogram of the

correlation coefficients. The histogram exhibited two peaks at low and high correlation

coefficients corresponding to pairs of different and similar fragments, respectively. The peaks

were separated by a distinct valley between correlation coefficients of 0.65 and 0.75. We picked


a value of 0.7 around the center of the valley as the threshold. However, the results were not

sensitive to the exact value of the threshold until it was in the range between 0.65 and 0.75.

To quantify the similarity between two samples, an index called the sample similarity

index (SSI) was defined as the ratio of total length of matching traces to the average total length

of the traces from the two samples. Thus two strains sharing all optical traces have an SSI of 1.0,

while two strains sharing no optical traces have an SSI of 0. We used (1 – SSI) as the “distance”

between the two samples. A matrix of the distances between all pairs of the measured samples

was generated (Supplemental Data Fig. 8), and this matrix was used to generate a phylogenetic

tree using the Fitch–Margoliash least-squares method (6).

NEIGHBORHOOD-BASED RESISTANCE PREDICTION

The SSI's between a test sample and known samples can be used to predict properties such as

antibiotic resistance. We classify a sample as resistant to an antibiotic if a fraction f of samples

within a distance d is resistant to the antibiotic. Parameters f and d are thresholds that define the

'neighborhood'. These parameters can be varied to operate at different true positive (sensitivity)

and false positive (1 – specificity) rates. To calculate these rates for a particular value of f and d

based on a set of known samples, we predict the antibiotic resistance of each sample as if it were

an unknown. For each (f,d) pair, the true positive rate is the fraction of antibiotic-sensitive

samples correctly predicted to be antibiotic-sensitive, and the false positive rate is the fraction of

antibiotic-resistant samples incorrectly predicted to be sensitive. The receiver operating

characteristic (ROC) shows the optimal rates that can be obtained by varying these thresholds

(Supplemental Data Fig. 5). The classifier can attain approximately 95% true positive rate with

5% false positive rate for the identification of oxacillin resistance in the small sample size of this

study.


References

1. Mollova ET, Patil VA, Protozanova E, Zhang M, Gilmanshin R. An automated sample preparation system with mini-reactor to isolate and process submegabase fragments of bacterial DNA. Analytical Biochemistry 2009;391:135-43.

2. Phillips KM, Larson JW, Yantz GR, D'Antoni CM, Gallo MV, Gillis KA, et al. Application of single molecule technology to rapidly map long DNA and study the conformation of stretched DNA. Nucleic Acids Res 2005;33:5829-37.

3. Chan EY, Goncalves NM, Haeusler RA, Hatch AJ, Larson JW, Maletta AM, et al. DNA mapping using microfluidic stretching and single-molecule detection of fluorescent site-specific tags. Genome Res 2004;14:1137-46.

4. Krogmeier JR, Schaefer I, Seward G, Yantz GR, Larson JW. An integrated optics microfluidic device for detection single DNA molecules. Lab on a Chip 2007;7:1767-74.

5. Larson JW, Yantz GR, Zhong Q, Charnas R, D'Antoni CM, Gallo MV, et al. Single DNA molecule stretching in sudden mixed shear and elongational microflows. Lab Chip 2006;6:1187-99.

6. Fitch WM, Margoliash E. Construction of phylogenetic trees. Science 1967;155:279-84.


Supplemental Data Figure Legends

Supplemental Data Figure 1. PFGE analysis of restriction digests of control S. aureus strains

with SmaI (A, B) and SanDI (C, D) restriction endonucleases. Strain NCTC8325 (NRS77) is

used as the length standard and indicated by an asterisk. Bands corresponding to the fragments

differing from those expected from published genomic sequences are circled.

Supplemental Data Figure 2. Comparison of theoretical maps from genomic sequences (red)

with experimental maps (head- and tail-first orientations are in green and blue, respectively) for

the 193 kb DNA fragments of S. aureus strains Mu50 (A) and Mu3 (B). Instead of a 153 kb long

fragment with the same map for both Mu50 and Mu3 strains expected from their published

sequences, we have detected the same 193 kb fragment for both of them. The theoretical map

overlaps nicely with a part of it.

Supplemental Data Figure 3. Reproducibility of DLA measurements. Maps of SanDI

restriction fragments of S. aureus strain NCTC8325 were measured 7 times on different days by

different operators on different devices. Raw traces for all 9 fragments detected within 100-250

kb range (108, 109, 116, 134, two 150, 160, 180, and 242 kb long fragments) are presented

without normalization. See Fig. 4 for examples of the traces normalized to their maximal

intensity.

Supplemental Data Figure 4. Pulsed field electrophoresis gels of all Mount Auburn Hospital

isolates measured in this study. Genomic DNA was digested with SmaI restriction endonuclease.

Supplemental Data Figure 5. Receiver operator characteristic (ROC) for the prediction of

methicillin (oxacillin) resistance of Mount Auburn Hospital samples. The curve indicates that we

can achieve approximately 95% true positive rate with 5% false positive rate (intersection of blue

dotted lines).


Supplemental Data Figure 6. Flow chart of the identification and extraction of the maps of the

long restriction fragments of the sample DNA. See the Supplemental Data text for details.

Supplemental Data Figure 7. Comparison of two hypothetical samples. Suppose that for two

measured samples of different bacteria, we detected 3 and 4 maps of restriction fragments,

respectively (A). The current algorithm identifies matching sections of the maps when either two

fragments from the different samples match completely or one fragment of one sample matches

as a whole a section of a fragment from another sample (B). The latter case is illustrated with the

experimental data (C). One of the fragment maps of E. coli strain K12 MG1655 strain (blue)

matches a section of a fragment map of E. coli strain K12 W3110 strain (red).

Supplemental Data Figure 8. Part of the distance matrix, representing the similarity between

the clinical isolates from MA1124 to MA1142. The differences equal (1 – SSI), where SSI is the

sample similarity index. Smaller values correspond to more similar isolates.


Supplemental Data Tables

Supplemental Data Table S1. Known S. aureus strains used in this study.

Strain name Common name Source1) Strain name Common name Source1)

NRS12) Mu50 NARSA NRS383 USA200 NARSA NRS22) Mu3 NARSA NRS384 USA300-0114 NARSA NRS22 USA600 NARSA NRS385 USA500 NARSA NRS702) N315 NARSA NRS386 USA700 NARSA NRS712) Sanger 252 NARSA NRS387 USA800 NARSA NRS722) Sanger 476 NARSA NRS4822) USA300 NARSA NRS772) NCTC 8325 NARSA NRS483 USA1000 NARSA NRS1002) COL NARSA NRS484 USA1100 NARSA NRS1232) MW2/USA400 NARSA 35556 SA113 ATCC NRS382 USA100 NARSA

1) NARSA, Network on Antimicrobial Resistance in Staphylococcus aureus program (supported

under NIAID, NIH Contract No. HHSN272200700055C); ATCC, American Type Culture

Collection.

2) Strains with known genome sequences.


Supplemental Data Table S2. Isolate source and antimicrobial sensitivity Sa

mpl

e ID

Isolated From Sample Origin

Cef

azol

in

Clin

dam

ycin

Eryt

hrom

ycin

Levo

floxa

cin

Oxa

cilli

n

Rifa

mpi

n

Tetr

acyc

line

Trim

/Sul

fa

Vanc

omyc

in

1168 5) urine outpatient R1) N/A N/A R R R S2) S S 1126 skin, left leg outpatient R R R R R S S S S 1128 sputum inpatient R R R R R S S S S 1138 sputum inpatient R R R R R S S S S 1144 bronchial lingular lavage inpatient R R4) R R R S S S S 1166 right wrist drainage inpatient R R4) R R R S S S S 1167 sputum outpatient R R4) R R R S S S S 1229 sputum inpatient R R R R R S S S S 1156 abdomen inpatient R R R R R S R S S 1133 skin, axilla outpatient R S R R R S S S S 1152 swab #2, drainage outpatient R S R R R S S S S 1151 swab #1, drainage outpatient R S R I3) R S S S S 1153 abdominal abscess drainage outpatient R S R I R S S S S 1142 back outpatient R S R I R S S S S 1170 left leg drainage outpatient R S R R R S S S S 1154 left leg drainage outpatient R S R S R S S S S 1135 axila left drainage outpatient R S R S R S S S S 1230 left axilla drainage outpatient R S R S R S S S S 1139 left buttock drainage outpatient R S R S R S S S S 1143 skin, left leg outpatient S S R S S N/A S S S 1134 bronchial wash inpatient S R4) R R S N/A S R S 1155 toe drainage outpatient S R R S S N/A R S S 1125 left thigh drainage outpatient S S R S S N/A R S S 1124 sinus drainage outpatient S S S S S N/A R S S 1233 skin, deep finger outpatient S S S S S N/A S S S 1157 skin, toe inpatient S R4) R S S N/A S S S 1131 right shoulder drainage outpatient S S S S S N/A S S S 1141 right breast skin outpatient S S S S S N/A S S S 1158 right ear drainage outpatient S R R S S N/A S S S 1137 skin, right index finger outpatient S S S S S N/A S S S 1145 nasal drainage outpatient R S S I R S S S S 1129 blood outpatient S S S S S N/A S S S 1169 blood inpatient S S S S S N/A S S S 1171 finger inpatient S S S S S N/A S S S 1140 left hand drainage outpatient S S S S S N/A S S S 1159 left leg drainage inpatient S S S S S N/A S S S 1160 right leg drainage inpatient S S S S S N/A S S S 1173 skin, axilla outpatient S S S S S N/A S S S 1228 sputum outpatient S S S S S N/A I S S 1127 skin, wound outpatient S S S S S N/A S S S 1130 right thigh drainage outpatient S S S S S N/A S S S 1132 right foot drainage outpatient S S S S S N/A S S S 1136 elbow drainage outpatient S S S S S N/A S S S 1146 right eye drainage inpatient S S S S S N/A S S S 1147 abscess drainage outpatient S S S S S N/A S S S 1148 skin, lip ulcer outpatient S S S S S N/A S S S 1149 skin, toe outpatient S S S S S N/A S S S 1150 skin outpatient S S S S S N/A S S S 1165 nares surveilance inpatient S S S S S N/A S S S 1172 sputum inpatient S S S S S N/A S S S 1174 left fifth finger inpatient S S S S S N/A S S S 1227 skin, left axilla outpatient S S S S S N/A S S S


1) R = Resistant to antimicrobial agent (MIC Interpretive Standard)

2) S = Sensitive to antimicrobial agent (MIC Interpretive Standard)

3) I = Intermediate resistance to antimicrobial agent (MIC Interpretive Standard)

4) Isolate displays inducible clindamycin resistance

5) Sample identification is random


Supplemental Data Table S3. Theoretical (seq.) and DLA-measured (obs.) DNA fragments

generated by restriction enzyme SanDI.

Seq.1) Obs. Seq.1) Obs. Seq.1) Obs. Seq.1) Obs. Seq.1) Obs. Seq.1) Obs. Seq.1) Obs. Seq.1) Obs. Seq.1) Obs.232 231 231 228 231 229 189 189 264 268 242 244 184 183 265 263 205 204201 202 201 198 201 200 155 156 252 253 180 179 180 179 206 203 180 180152 193 152 193 178 178 149 150 206 202 160 161 164 164 191 189 164 179178 178 178 176 159 160 128 128 191 188 150 151 149 150 180 179 148 150159 159 159 159 148 150 123 124 180 177 150 151 134 134 179 178 133 136148 148 148 148 134 134 118 120 177 175 134 135 116 118 166 165 117 118134 134 134 134 131 132 100 101 164 162 116 117 111 111 164 163 109 112132 133 132 132 122 124 94 96 146 143 109 111 90 89 144 144 90 92115 115 115 115 110 111 142 141 108 110 89 89 135 137 88 91110 110 110 111 100 102 133 132 90 91 133 134

133 132 90 91 133 134117 117 89 89 117 116113 113 71 70 113 113101 100 62 64 105 104

91 90 101 101

Total2) 1561 1560 1514 1056 2410 1751 1217 2332 1234Fract3) 0.54 0.54 0.55 0.36 0.86 0.62 0.43 0.83 0.43

Mu50 Mu3 N315 MW2 USA300Sanger 252 Sanger 476 NCTC 8325 COL

1) Sequence can be found at: http://www.ncbi.nlm.nih.gov/genomes/lproks.cgi

2) Total amount of the genome in kilobases measured by DLA

3) Fraction of the genome measured by DLA


Supplemental Data Table S4. Protocol for isolation, purification, and site-specific tagging of

Staphylococcus aureus genomic DNA.

Step Buffer Volume,1) Finj,2) Ftan,2) Temp. Time, mL mL/min mL/min ºC min Prime chamber 0.1×B1,3) 0 0 0 40 0 Inject cells 0.1×B1 0.7 0.1 0 40 7 Inject lytic solution,3) 0.1×B1 0.4 0.1 0 40 4 Incubate 0.1×B1 NA NA NA 40 32 Inject SDS buffer,3) TE + 0.1%SDS 0.2 0.05 0 40 4

Wash with SDS buffer TE + 0.1%SDS 6 (3)4) 0.8 0.75 40 7.5

(3.75)4) Inject UL buffer,3) TE + 0.1%SDS 0.075 0.05 0 40 1.5 Inject PK solution,3) TE 0.4 0.05 0 40 8 Incubate TE NA NA NA 58 18 Cool down TE 1 0.35 0 24 2.85 Inject SDS buffer TE + 0.1%SDS 0.2 0.05 0 40 4

Wash with SDS buffer TE + 0.1%SDS 6 (3)4) 0.8 0.75 40 7.5

(3.75)4)

Wash with TES,3) TE + 200 mM NaCl 10 (5)4) 0.8 0.75 40 12.5

(6.25)4) Incubate with TES TE + 200 mM NaCl NA NA NA 40 21 Inject RE buffer,3) RE Buffer 0.2 0.05 0 40 4 Wash with RE buffer RE Buffer 5 0.8 0.75 40 6.25 Inject RE,3) RE Buffer 0.4 0.05 0 40 8 Incubate with RE RE Buffer NA NA NA 40 29.35 Wash frit TE + EDTA 2 0.35 0 40 5.7 Inject with TE + EDTA TE + EDTA 0.2 0.05 0 40 4 Wash with TE + EDTA TE + EDTA 5 0.8 0.75 40 6.25 Wash with TE buffer TE 5 0.8 0.75 40 6.25 Inject bisPNA,3) TE 0.5 0.05 0 40 10 Incubate with bisPNA TE NA NA NA 68 17.3 Cool down TE 1 0.35 0 24 2.85 Inject TES buffer TE + 200 mM NaCl 0.2 0.05 0 40 4 Wash with TES TE + 200 mM NaCl 13.4 0.53 0.48 40 25.3 Incubate with bisPNA TE + 200 mM NaCl NA NA NA 68 10 Cool down TE 1 0.35 0 24 2.85 Inject TES buffer TE + 200 mM NaCl 0.2 0.05 0 40 4 Wash with TES TE + 200 mM NaCl 2.5 0.53 0.48 40 4.7 Wash with TE TE 9 0.53 0.48 40 17 Wash frit TE 2 0.35 0 40 5.7

Total Time

303.35(289.6)4)


1) Total volume of the injected solution.

2) Finj and Ftan are injection and tangential flow rates, respectively. Normal flow rate is the

difference between the injection and tangential flow rates.

3) B1 buffer, 50 mM Tris pH 8.0, 0.5% Tween 20, 0.5% TX-100; Lytic solution, 150,000 U of

lysozyme, 1,000 U of achromopeptidase, 120 U of lysostaphin, and 6 µg/mL of RNAse A in

1×B1 buffer; SDS buffer, 0.1% SDS in TE buffer; UL buffer, 50mM Tris pH 8, 10mM EDTA,

1% SDS, 2% β-mercaptoethanol; PK solution, 4 µg/mL of proteinase K in UL buffer (universal

lysis buffer); TES buffer, 200 mM NaCl in TE; RE buffer, 200mM potassium acetate, 50mM

Tris pH 7.6, 20mM magnesium acetate; RE, 100 U of SanDI restriction enzyme in RE buffer, 6

µg/mL RNAse A; bisPNA, 2 µM of bisPNA 268 in TE buffer.

4) A variation of the protocol parameters during repeated measurements of Mt. Auburn Hospital

isolates presented in parenthesis.


Supplemental Data Figures

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1100

SanDI: Set 2

* * * * *USA

600

USA

100

CO

L

USA

200

USA

300-

0114

USA

500

USA

800

USA

1000

USA

1100

250 kb

100 kb

SanDI: Set 1

* * * * *Mu5

0

MW

2/U

SA40

0

USA

700

USA

300

SA11

3

Sang

er 2

52

Sang

er 4

76

Mu3

N31

5

250 kb

100 kb

250 kb

100 kb

SanDI: Set 1

* * * * *Mu5

0

MW

2/U

SA40

0

USA

700

USA

300

SA11

3

Sang

er 2

52

Sang

er 4

76

Mu3

N31

5

SanDI: Set 1

* * * * *Mu5

0

MW

2/U

SA40

0

USA

700

USA

300

SA11

3

Sang

er 2

52

Sang

er 4

76

Mu3

N31

5

Supplemental Data Figure 1.


A

B20

15

10

5

0

Pho

ton

Inte

nsity

(a.u

.)

150100500

Length (kb)

Mu3

Mu50

Pho

ton

Inte

nsity

(a.u

.)

Length (kb)

20

15

10

5

150100500

0

A

B20

15

10

5

0

Pho

ton

Inte

nsity

(a.u

.)

150100500

Length (kb)

20

15

10

5

0

Pho

ton

Inte

nsity

(a.u

.)

150100500

Length (kb)

Mu3

Mu50

Pho

ton

Inte

nsity

(a.u

.)

Length (kb)

20

15

10

5

150100500

0

Pho

ton

Inte

nsity

(a.u

.)

Length (kb)

20

15

10

5

150100500

0

20

15

10

5

150100500

0



MA

1129

MA

1132

MA

1140

MA

1146

MA

1159

MA

1160

MA

1169

MA

1171

MA

1173

MA

1174

MA

1131

MA

1136

MA

1141

MA

1145

MA

1147

MA

1148

MA

1150

MA

1157

MA

1165

MA

1172

MA

1228

MA

1124

MA

1125

MA

1127

MA

1130

MA

1134

MA

1142

MA

1149

MA

1155

MA

1227

MA

1233

MA

1133

MA

1135

MA

1139

MA

1143

MA

1151

MA

1152

MA

1153

MA

1154

MA

1170

MA

1230

MA

1126

MA

1128

MA

1137

MA

1138

MA

1144

MA

1156

MA

1158

MA

1166

MA

1167

MA

1168

MA

1229

MA

1129

MA

1132

MA

1140

MA

1146

MA

1159

MA

1160

MA

1169

MA

1171

MA

1173

MA

1174

MA

1129

MA

1132

MA

1140

MA

1146

MA

1159

MA

1160

MA

1169

MA

1171

MA

1173

MA

1174

MA

1131

MA

1136

MA

1141

MA

1145

MA

1147

MA

1148

MA

1150

MA

1157

MA

1165

MA

1172

MA

1228

MA

1131

MA

1136

MA

1141

MA

1145

MA

1147

MA

1148

MA

1150

MA

1157

MA

1165

MA

1172

MA

1228

MA

1124

MA

1125

MA

1127

MA

1130

MA

1134

MA

1142

MA

1149

MA

1155

MA

1227

MA

1233

MA

1124

MA

1125

MA

1127

MA

1130

MA

1134

MA

1142

MA

1149

MA

1155

MA

1227

MA

1233

MA

1133

MA

1135

MA

1139

MA

1143

MA

1151

MA

1152

MA

1153

MA

1154

MA

1170

MA

1230

MA

1133

MA

1135

MA

1139

MA

1143

MA

1151

MA

1152

MA

1153

MA

1154

MA

1170

MA

1230

MA

1126

MA

1128

MA

1137

MA

1138

MA

1144

MA

1156

MA

1158

MA

1166

MA

1167

MA

1168

MA

1229

MA

1126

MA

1128

MA

1137

MA

1138

MA

1144

MA

1156

MA

1158

MA

1166

MA

1167

MA

1168

MA

1229



0.0 0.2 0.4 0.6 0.8 1.00.0

0.2

0.4

0.6

0.8

1.0

False Positive Rate

True

Posi

tiveR

ate

Oxacillin

0.0 0.2 0.4 0.6 0.8 1.00.0

0.2

0.4

0.6

0.8

1.0

False Positive Rate

True

Posi

tiveR

ate

Oxacillin

0.0 0.2 0.4 0.6 0.8 1.00.0

0.2

0.4

0.6

0.8

1.0

False Positive Rate

True

Posi

tiveR

ate

Oxacillin

0.0 0.2 0.4 0.6 0.8 1.00.0

0.2

0.4

0.6

0.8

1.0

False Positive Rate

True

Posi

tiveR

ate

Oxacillin



Filter by brightness Filter hairpins

Identify length standardCalibrate length

ReportSearch fragments

Characterize detection parameters, cluster statistics

Filtration and calibration

Read and interpolate traces

Direct Linear Analysis (DLA)

Identification and analysis of DNA fragments

Preliminary clustering

Merge similar clusters

Cluster by correlation coeff.

Cluster by probability distance

Clustering

Filter by brightness Filter hairpins

Identify length standardCalibrate length

ReportSearch fragments

Characterize detection parameters, cluster statistics

Filtration and calibration

Read and interpolate traces

Direct Linear Analysis (DLA)

Identification and analysis of DNA fragments

Preliminary clustering

Merge similar clusters

Cluster by correlation coeff.

Cluster by probability distance

Clustering


2.3 kb


Matching algorithm currently covers the following scenarios

A fragment from Sample 1 matching a fragment from Sample 2

150 kb

150 kb

A fragment from Sample 2 matching part of a fragment from Sample 1

50 kb

100 kb

Part of a fragment from Sample 1 matching a fragment from Sample 2

250 kb

220 kb

B

Sample 1 Sample 2A

E. coli K12 MG1655 vs. K12 W3110 example

C



150 kb

150 kb


50 kb

100 kb


250 kb

220 kb

B Matching algorithm currently covers the following scenarios


150 kb

150 kb


50 kb

100 kb


250 kb

220 kb



150 kb

150 kb


150 kb

150 kb


50 kb

100 kb


50 kb

100 kb


250 kb

220 kb


250 kb

220 kb

B

Sample 1 Sample 2A Sample 1 Sample 2Sample 1Sample 1 Sample 2Sample 2A

E. coli K12 MG1655 vs. K12 W3110 example

C

E. coli K12 MG1655 vs. K12 W3110 exampleE. coli K12 MG1655 vs. K12 W3110 example

C



A1124_0A1125_0A1126_0A1127_0A1128_0A1129_0A1130_0A1131_0A1132_0A1133_0A1134_0A1135_0A1136_0A1137_0A1138_0A1139_0A1140_0A1141_0A1142_01124_ 0.001125_ 0.01 0.001126_ 0.55 0.62 0.001127_ 0.57 0.47 0.71 0.001128_ 0.67 0.68 0.06 0.63 0.001129_ 1.00 1.00 1.00 1.00 1.00 0.001130_ 0.01 0.00 0.48 0.47 0.53 1.00 0.001131_ 0.69 0.53 0.58 0.84 0.55 1.00 0.53 0.001132_ 1.00 1.00 1.00 1.00 1.00 0.52 1.00 1.00 0.001133_ 0.43 0.43 0.55 0.66 0.45 1.00 0.43 0.70 1.00 0.001134_ 0.10 0.01 0.54 0.30 0.59 1.00 0.01 0.66 1.00 0.43 0.001135_ 0.44 0.43 0.55 0.66 0.52 1.00 0.43 0.70 1.00 0.00 0.43 0.001136_ 0.55 0.64 0.59 0.53 0.56 1.00 0.55 0.78 1.00 0.65 0.72 0.66 0.001137_ 0.73 0.52 0.59 0.66 0.56 1.00 0.61 0.87 1.00 0.92 0.60 0.92 0.82 0.001138_ 0.49 0.56 0.00 0.65 0.06 1.00 0.41 0.58 1.00 0.48 0.54 0.48 0.59 0.59 0.001139_ 0.43 0.43 0.55 0.66 0.52 1.00 0.43 0.70 1.00 0.00 0.43 0.00 0.65 0.92 0.48 0.001140_ 1.00 1.00 0.87 1.00 1.00 0.83 1.00 1.00 0.82 1.00 1.00 1.00 0.92 1.00 0.87 1.00 0.001141_ 0.62 0.69 0.76 0.78 0.74 1.00 0.69 0.01 1.00 0.70 0.76 0.76 0.84 0.87 0.76 0.70 1.00 0.001142_ 0.45 0.44 0.55 0.67 0.46 1.00 0.44 0.71 1.00 0.23 0.45 0.24 0.66 0.92 0.49 0.23 1.00 0.71 0.00


staphylococcus aureus strain typing by single-molecule...

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