A. B. C.

D. E. F.

Chaitali Parikh, Dalia DhingraThermo Fisher Scientific, 180 Oyster Point Blvd, South San Francisco, CA 94080

MATERIALS & METHODS

ABSTRACT

Whole-transcriptome profiling of bacterial samples can provide significant insights into mechanisms of prokaryotic metabolism. Unlike DNA profiling, it can also potentially discriminate between live and dead organisms in a mixed population, since RNA molecules have a shorter half-life than DNA molecules. Here, we describe how the Ion Torrent™ platform can be used to profile the transcriptome from E.coli and S.aureus cultures.

The Ion Total RNA-Seq kit and AB Library Builder™ were used for semi-automated library synthesis from Ribo-depleted RNA. Using the Partek Flow Pipeline for Ion Whole Transcriptome Analysis, we performed our alignment and analysis. We obtained between of 18-29 million reads per sample, allowing average coverage depth of around 500x for E.coli and around 1000x for S.aureus. Correlations of expression levels between replicates was excellent, with a Pearson Correlation Coefficient averaging greater than 0.97. between replicate samples. The top quartile of expressors had Pearson Correlation Coefficients of greater than 0.99 for both E.coli and S.aureus.These data demonstrate that the Ion Torrent Proton system provides an ideal workflow and capacity for sequencing and analysis of prokaryotic transcriptomes. 

CONCLUSIONS

The Ion Torrent Proton™ system provides an automated workflow for generating highly reproducible data that simplifies prokaryotic transcriptome research.

For Research Use Only. Not for use in diagnostic procedures.

REFERENCES

1.For more information, please visit www.lifetechnologies.com.

© 2015 Thermo Fisher Scientific Inc. All rights reserved. All trademarks are the property of Thermo Fisher Scientific and its subsidiaries unless otherwise specified. Partek and Flow are trademarks of Partek Incorporated.

Bacterial transcriptome profiling using Ion Torrent Proton technology

Thermo Fisher Scientific • 5791 Van Allen Way • Carlsbad, CA 92008 • lifetechnologies.com

RESULTS

Workflow Steps Done on ABLB Instrument

2 Hrs 1-2 Hrs 3 Hrs

~70-85% of total sample prep workflow (~6-7 hrs) can be

automated by the AB Library Builder

AB Library

Builder™With Ion

Total RNA-Seq

kit

Size Select

Purify RNA

Ribo-depletion

Frag &PurifyRNA

Hyb & Lig adapters

Reversetranscribe

PCR &Clean-up Sequence

AB Library Builder™

With iPrep RNA

kit

A. B. C. D.

Figure 1. Total RNA Library workflow on AB Library Builder ™ System: Fast and Simple(A) RNA purification can be performed in two hours with the AB Library Builder ™ using the iPrep RNA kit. (B) After ribo-depletion and fragmentation, automated library preparation for an Ion Torrent platform can be done in 3 hours using AB Library Builder ™ with the Total RNA-Seq kit. (C) These libraries can then be amplified for templating on the Ion One Touch 2 System. (D) Sequencing is performed with the Ion Proton System.

Figure 2. Partek Flow for Whole Transcriptome Analysis.Partek Flow WT Pipeline for Ion Torrent was used alignment and analysis. Using the PartekFlowUploader plugin, the unmapped reads were automatically transferred into Partek Flow. The Partek Flow WT Pipeline for Ion Torrent was then started that includes the two-step alignment method for Ion Proton™ transcriptome data (Tophat2 and Bowtie2) followed by quantification and differential gene expression analysis.

Figure 3. ERCC AnalysisOutput from the ERCC_Analysis plugin in Torrent Suite is shown, a logarithmic graph of the ERCC concentration versus the ERCC counts from the transcriptome sequencing data with an R-squared of 0.94. The R-squared ranged from 0.90 up to 0.96 for all the samples with 3 of the samples at 0.96. The ERCCs comprised of 1.19% of total reads for this sample. They ranged from 0.80% up to 2.22% for all samples. The colors of the data points reflect the map quality with the majority of reads having greater than 80 for the ERCCs above the threshold count of 10.

A. B. C.

Figure 4. Example a whole transcriptome sequencing run with E. .coli(A) Heat map of an Ion Proton PIv2 chip indicating 95% loading of the wells with ISPs. (B) After filtering out low quality and polyclonal reads, there were close to 80 million reads. (C) Read length histogram after quality trimming demonstrated median read length of 110 base pairs.

  total reads aligned (%) unique (%) coverage (%)average coverage

depthaverage length

average quality

average mapping quality GC (%)

E. coli

BC3 18,569,344 98.04 96.39 95.36376.16

(SD 3,282.17) 102.34 23.81 45.99 (SD 10.94) 51.23

BC4 26,008,453 97.84 96.59 94.01636.28

(SD 7,113.69) 123.43 23.28 45.78 (SD 10.34) 51.89

BC5 20,678,168 97.94 96.54 94.52489.07

(SD 5,189.36) 119.04 23.36 45.89 (SD 10.52) 51.75

Staph aureus

BC1 23,600,051 94.80 93.80 87.41976.79

(SD 22,791.1) 111.97 23.29 44.33 (SD 12.25) 38.83

BC2 27,563,733 96.15 94.92 96.281,118.51

(SD 17,078.3) 122.98 23.00 41.77 (SD 14.54) 37.12

BC6 29,589,992 94.87 92.35 89.611,301.93

(SD 30,244.2) 116.93 23.34 41.63 (SD 15.88) 39.51

Table 1. Alignment statistics.The combined alignments from a two-step alignment method (TopHat2 and Bowtie2) automated in the Partek Flow WT Pipeline for Ion Torrent. Default parameters for the pipeline was used for all alignments. Over 94% of all reads aligned with over 92% of all reads aligning uniquely.

 E. Coli Staph aureus

BC3 BC4 BC5 BC1 BC2 BC6

rRNA (%) 0.077 0.031 0.059 0.340 0.149 1.347

5S rRNA (%) 0.005 0.002 0.004 0.023 0.012 0.136

16S rRNA (%) 0.007 0.025 0.021 0.106 0.046 0.440

23S rRNA (%) 0.008 0.026 0.017 0.210 0.091 0.771

non-ribosomal reads from 3-plex PI chip 18,190,630 25,439,651 20,240,890 22,296,402 26,462,369 27,695,202

Table 2. Percent ribosomal RNA reads after ribo-depletion.The percent reads classified as rRNA and separated into 5S rRNA, 16S rRNA, and 23S rRNA are shown here as the percent of reads for each E. coli and Staph aureus sample. All samples had over 18 million reads that were not rRNA when 3 samples were sequenced on a single Ion Proton PIv2 chip.

E. coli BC3 BC4 BC5

BC3  0.9777 0.9865  0.9891 0.9934  0.7305 0.6783

BC4    0.9967    0.9981    0.6781

Staph aureus BC1 BC2 BC6

BC1  0.9918 0.9993  0.9924 0.9993  0.7699 0.7046

BC2    0.9932    0.9936    0.7928

All genes Top quartile (Highest expressed genes) Bottom quartile (Lowest expressed genes)

A. B.

Table 3. Pearson correlation coefficients.(A) Pearson correlation coefficients were determined between the E. coli technical replicates for all genes, the top quartile of expressed genes and the bottom quartile of expressed genes. For all genes and the top quartile, the Pearson correlation coefficient was over 0.97. For the bottom quartile of expressed genes, the Pearson correlation coefficient was lower, as expected, but still higher than 0.67. (B) Pearson correlation coefficients were determined between the Staph aureus technical replicates for all genes, the top quartile of expressed genes and the bottom quartile of expressed genes. For all genes and the top quartile, the Pearson correlation coefficient was over 0.99. For the bottom quartile of expressed genes, the Pearson correlation coefficient was lower, as expected, but still higher than 0.70.

E. Coli

Staphylococcus Aureus

Figure 5. High degree of overlap in the E. coli samples for genes that are the (A) top 20 expressors, (B) the top quartile expressors , and (C) the bottom quartile expressors. High degree of overlap in the staph aureus samples for genes that are the (D) top 20 expressors, (E) the top quartile expressors , and (E) the bottom quartile expressors.