SUPPLEMENTARY MATERIALS AND METHODS
Hydrolysates of lignocellulosic biomass preparation method
To perform the enzymatic hydrolysis, the pH of the solution (slurry/ water) was first
titrated to pH=5.0 using 1M KOH. The following equations were used to determine the required
amount of enzyme for the hydrolysis reaction:
a.
Cellulase: For X ml of corn slurry at pH 5, for m minutes of incubation at 37C.
𝑤(𝑢𝑚𝑜𝑙/𝑚𝐿)∗𝑋(𝑚𝑙 𝑜𝑓 𝑐𝑜𝑟𝑛 𝑠𝑙𝑢𝑟𝑟𝑦)
𝐶𝑒𝑙𝑙𝑢𝑙𝑎𝑠𝑒(𝑚𝑔) = 𝑚(𝑚𝑖𝑛/𝑈)∗1(𝑢𝑚𝑜𝑙/𝑚𝑖𝑛)∗1.24𝑈/𝑚𝑔
b.
Equation (S1)
Cellobiase: For X ml of corn slurry at pH 5, for m minutes of incubation at 37C.
𝐶𝑒𝑙𝑙𝑜𝑏𝑖𝑎𝑠𝑒(𝑚𝐿) =
𝑤(𝑢𝑚𝑜𝑙/𝑚𝐿)∗𝑋(𝑚𝑙 𝑜𝑓 𝑐𝑜𝑟𝑛 𝑠𝑙𝑢𝑟𝑟𝑦)
250𝑈
𝑔
∗1.2( )
𝑔
𝐿
𝑚(𝑚𝑖𝑛/𝑈)∗2(𝑢𝑚𝑜𝑙/𝑚𝑖𝑛)∗
Note: W g/L or w (
Equation (S2)
𝐺(𝑔)∗1000
umol/mL) is the desired concentration of glucose in the
𝑔
)
𝑚𝑜𝑙
180.2(
solution.
After the addition of the enzymes, the biomass slurry solution was incubated at 37ºC for m=60
minutes with continuous shake at 220 rpm.
Neutrality Test
A neutrality test was performed to ensure that there are no fitness differences between the
three fluorescently-marked strains used in this work (GFP, YFP, DsRed). For this test, roughly
equal numbers of these labeled strains were inoculated in a batch culture with YNB and glucose
as carbon source. See Figure S1 for the results of the neutrality test.
RNA extraction
Each isolated mutant was inoculated in 30ml of selective media H (hydrolysates/YNB) in
125ml flask at an initial OD600 of 0.05. The cells were harvested in middle exponential phase by
filtration using NALGENE analytical test filter funnels (Nalgene), immediately resuspended in
10mL of RNAlater (Sigma) and stored at -80ºC for future analysis. For the extraction of the
total RNA, the ZR Fungal/Bacterial RNA MiniPrep™ (Zymo) kit was used by following
manufacturers' instructions using 2mL of each stored sample in RNAlater. The extracted RNA
was quantified using the NanoDrop™ 1000® (Thermo Scientific).
Labeled cDNA generation, microarray hybridization and data analysis
The SuperScript® Indirect cDNA Labeling System (Invitrogen) with Oligo(dT)20 primer
was used to synthesized the cDNA with incorporation of aminoallyl dUTP.
cDNA was
recovered with ice cold ethanol precipitation. Cy3- and Cy5- mono-Reactive Dye Pack (GE
Healthcare) were used to label cDNA samples. The labeled cDNA was hybridized to the S.
cerevisiae G4813A Gene Expression Microarray (Agilent Technologies).
The arrays were
scanned using the GenePix 4100A Microarray Scanner and image analysis was performed using
GenePix Pro 6.0 software (Molecular Devices).
The Microarray Data Analysis System
(MIDAS) software was used to normalize the data using LOWESS based normalization
(Quackenbush, 2002; Yang et al., 2001) (Quackenbush 2002; Yang et al. 2002). Differentially
expressed genes were identified using the rank product method with a critical p-value <0.05.
The MeV (TM4) (Saeed et al. 2003) microarray analysis software was used for clustering and
other expression profile analysis. The Saccharomyces Genome Database SGD (1997-2012) was
use to analyze the data using gene ontology. The Network Component Analysis (NCA) (Tran et
al. 2005) was used to analyze the relative activities of S. cerevisiae transcription factors. The
number of permutations used to calculate the FDR (false discovery rate) was 1000.
The
transcription factors reported have a statistical significance with a p-value threshold of <0.05.
SUPPLEMENTAL FIGURE LEGEND
Figure S1 Neutrality test. The yellow bars indicate the relative proportion of the yellow
subpopulation, green bars indicate the proportion of green subpopulation, and red bars indicate
the proportion of the red subpopulation.
SUPPLEMENTARY REFERENCES
1997-2012. The Saccharomyces Genome Database
Quackenbush J. 2002. Microarray data normalization and transformation. Nature Genetics
32:496-501.
Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T,
Thiagarajan M and others. 2003. TM4: A free, open-source system for microarray data
management and analysis. Biotechniques 34(2):374-+.
Tran LM, Brynildsen MP, Kao KC, Suen JK, Liao JC. 2005. gNCA: A framework for
determining transcription factor activity based on transcriptome: identifiability and
numerical implementation. Metabolic Engineering 7(2):128-141.
Yang IV, Chen E, Hasseman JP, Liang W, Frank BC, Wang SB, Sharov V, Saeed AI, White J,
Li J and others. 2002. Within the fold: assessing differential expression measures and
reproducibility in microarray assays. Genome Biology 3(11).