Global transcriptome response to ionic liquid by
a tropical rain forest soil bacterium,
Jane I. Khudyakova,b, Patrik D’haeseleera,c, Sharon E. Borglind, Kristen M. DeAngelisa,d, Hannah Wooa,d,
Erika A. Lindquiste, Terry C. Hazena,d, Blake A. Simmonsa,f, and Michael P. Thelena,b,1
aDeconstruction Division, Joint BioEnergy Institute, Emeryville, CA 94608;bPhysical and Life Sciences andcComputations Directorates, Lawrence Livermore
National Laboratory, Livermore, CA 94550;dEarth Sciences Division, Ecology Department, Lawrence Berkeley National Laboratory, Berkeley, CA 94720;
eUS Department of Energy Joint Genome Institute, Walnut Creek, CA 94598; andfBiomass Science and Conversion Technology Department, Sandia National
Laboratories, Livermore, CA 94551
Edited by Steven E. Lindow, University of California, Berkeley, CA, and approved April 9, 2012 (received for review August 6, 2011)
To process plant-based renewable biofuels, pretreatment of plant
feedstock with ionic liquids has significant advantages over
current methods for deconstruction of lignocellulosic feedstocks.
However, ionic liquids are often toxic to the microorganisms used
subsequently for biomass saccharification and fermentation. We
previouslyisolatedEnterobacter lignolyticus strainSCF1,a lignocel-
lulolytic bacterium from tropical rain forest soil, and report here
that it can grow in the presence of 0.5 M 1-ethyl-3-methylimida-
zolium chloride, a commonly used ionic liquid. We investigated
molecular mechanisms of SCF1 ionic liquid tolerance using a com-
bination of phenotypic growth assays, phospholipid fatty acid
analysis, and RNA sequencing technologies. Potential modes of
resistance to 1-ethyl-3-methylimidazolium chloride include an in-
crease in cyclopropane fatty acids in the cell membrane, scavenging
of compatible solutes, up-regulation of osmoprotectant transport-
ers and drug efflux pumps, and down-regulation of membrane
porins. These findings represent an important first step in under-
standing mechanisms of ionic liquid resistance in bacteria and pro-
vide a basis for engineering microbial tolerance.
osmotic stress|osmolytes|membrane lipids|differential gene
expression|whole genome metabolic reconstruction
carbon emissions (1). Although lignocellulose stored within the
cell wall of plants is one of the largest reserves of convertible
energy on the planet, extraction of this resource remains a chal-
lenge because of the recalcitrance of the plant cell wall to degra-
dation (2, 3). Cellulose and hemicellulose polysaccharides, the
sources of fermentable sugars, are semicrystalline in nature and
deeplyembedded within a complex network ofhighly stable lignin
polymers (4, 5). Pretreatment of feedstock can remove lignin and
reduce cellulose crystallinity, which is critical for improving sub-
sequent saccharification of polysaccharides by enzymes derived
from lignocellulolytic microorganisms (6). Ionic liquid solvents, a
diverse class of molten organic salts, have been used effectively
for biomass pretreatment because they disrupt inter- and intra-
molecular hydrogen bonds within plant cell wall components to
improve cellulose recovery, leading to significant improvement of
subsequent enzymatic hydrolysis kinetics and product yield (7–
10). Nevertheless, one of the problems with using this technology
in large-scale industrial biomass pretreatment is its toxicity to
microorganisms used in downstream fermentation (11–13).
Although the current standard for a lignocellulosic biofuels
process involves discrete production steps, there is a potential
economic incentive for unifying the process by using a single
engineered strain or collection of strains that would perform both
saccharification and fermentation of pretreated biomass during
consolidated bioprocessing (CBP) (14–17). The main challenge to
this “one pot” strategy is process inhibition of laboratory micro-
ustainable production of biofuels from renewable feedstocks
is a key strategy for reducing dependence on fossil fuels and
organisms by secondary products of polysaccharide catabolism
and fermentation, as well as by residual ionic liquid from the
pretreatment step (18). For instance, many ionic liquids are highly
toxic to microorganisms as a result of the increase in osmotic
inhibition of enzymatic activity (11, 13, 19–22); however, the
specific mechanisms of toxicity are currently not well-understood,
making this an area of intense interest in the field. Because ionic
liquids present a promising alternative feedstock pretreatment
method, discovery of novel bacterial strains and/or engineering
existing strains for ionic liquid tolerance is critical to successful
employment of CBP. Utilization of microorganisms isolated from
natural environments, such as tropical rain forest (23) soil, can
greatly improve the current biofuels strategy. Natural microbial
communities that degrade biomass are often exposed to fluctuat-
ing environmental conditions, and thus represent a vast resource
for both stress-tolerant organisms and highly efficient, stable
lignocellulolytic enzymes (23–25).
We recently isolated the bacterium Enterobacter lignolyticus
strain SCF1 from tropical rain forest soil, where microbial com-
munities possess a high potential for both biomass degradation
in the presence of >0.5 M 1-ethyl-3-methylimidazolium chloride
([C2mim]Cl), an effective biomass pretreatment component (27)
that is toxic to most bacteria. The cytotoxicity mechanism of many
ionic liquids, specifically [C2mim]Cl, has not been investigated;
likewise, the molecular basis for rare bacterial tolerance to ionic
liquids is not understood. To approach these questions, we used a
transcriptome and found that resistance to [C2mim]Cl likely in-
volves a functional alteration of cell membrane composition, im-
port and synthesis of compatible solutes, increase in efflux pump
Author contributions: J.I.K., K.M.D., T.C.H., B.A.S., and M.P.T. designed research; J.I.K., S.E.B.,
K.M.D., and H.W. performed research; P.D., S.E.B., K.M.D., H.W., and E.A.L. contributed new
reagents/analytic tools; J.I.K., P.D., S.E.B., H.W., E.A.L., and M.P.T. analyzed data; and J.I.K.,
P.D., and M.P.T. wrote the paper.
The authors declare no conflict of interest.
This article is a PNAS Direct Submission.
Freely available online through the PNAS open access option.
Data deposition: The genome sequence reported in this paper has been deposited in the
GenBank database (accession no. CP002272.1). [This organism was previously called Enter-
obacter cloacae SCF1 and has been renamed Enterobacter lignolyticus SCF1. The name
has not yet been changed in the National Center for Biotechnology Information (NCBI)
database.] The data reported in this paper have been deposited in the Sequence Read
Archive (SRA) database, http://www.ncbi.nlm.nih.gov/sra [accession nos. SRX059720–
SRX059739 (raw Illumina RNA deep sequencing data)].
1To whom correspondence should be addressed. E-mail: email@example.com.
See Author Summary on page 12856 (volume 109, number 32).
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.
| Published online May 14, 2012
expression, and decrease in unique membrane porins. Our find-
ings represent an important advance in understanding mecha-
for subsequent efforts to engineer tolerant strains.
SCF1 Metabolism and Growth in [C2mim]Cl. The response of SCF1 to
[C2mim]Cl was examined using the Omnilog Phenotypic Micro-
Array (Biolog, Inc.) (28–30). In this system, cell respiration leads
to reduction of a redox dye, causing darkening color that serves as
an analog for increasing cell density over time because it mirrors
the growth profile measured by other methods (30, 31). In most of
our experiments, where salts were tested at relatively high con-
centrations, we cultivated cells in a low-osmolality, nutrient-rich
culture medium [10% (vol/vol) trypticase soy broth (TSB10)]
because it supports the rapid growth and healthy appearance of
SCF1 cells, resulting in a higher level of stress tolerance and
sufficient accumulation of biomass for further experiments.
However, when testing the response of SCF1 to compounds such
as osmoprotectants at low (millimolar) levels, Modified Combined
Carbon defined medium (MOD-CCM) was used so as not to in-
troduce compatible solutes or mask any effects of the test
Using the Omnilog phenotypic microarray in the empty plate
mode, SCF1 growth was observed over a range of [C2mim]Cl con-
centrations in TSB10, reaching an inhibitory level at 562.5 mM
presented as the natural log of average OL units for three biological replicates vs. time. OL unit readings were collected at 15-min intervals throughout
a culture period of 72 h. Negative control (NC) measurements were obtained from wells containing growth medium and redox dye but no cells. Error bars
show SD for three biological replicates with six technical replicates for each. (B) Effects of adding 2 mM glutamate, proline, ectoine, or glycine betaine on SCF1
growth in defined medium in the absence or presence of 250 mM [C2mim]Cl. Error bars show SD for two biological replicates.
Effects of [C2mim]Cl on SCF1 growth and the role of compatible solutes. (A) Growth was measured using the Omnilog phenotypic assay and is
| www.pnas.org/cgi/doi/10.1073/pnas.1112750109Khudyakov et al.
(Fig. 1A). Parameters, such as lag time, maximum growth rate,
and final biomass yield, were obtained using a Gompertz curve-
fitting model (30, 32) (Fig. S1). [C2mim]Cl increased the lag time
at all concentrations tested, and the maximum growth rate was
decreased at 187.5 mM [C2mim]Cl and above (Table 1). Final
biomass yield, as measured by the asymptotic amplitude of the
response curve, was decreased at concentrations above 437.5 mM
[C2mim]Cl. The greatly increasedlag time (morethan a day at 500
mM [C2mim]Cl) and the somewhat biphasic pattern observed at
these high concentrations (Fig. 1 and Fig. S1) suggest that an
adaptive change is required to enable ionic liquid tolerance. The
biphasic growth observed in Fig. 1B, even with no additions, may
be attributable to the fact that the medium is nonoptimal for this
environmental bacterium. The effect of ionic liquid on SCF1
growth in TSB10 was also examined by OD600measurements
during 10 h of growth in 0–500 mM [C2mim]Cl and was found to
mirror the phenotypic microarray results closely (Fig. S2). SCF1
outcompetes several commonly used Escherichia coli laboratory
strains, including BW25113 (33), which is inhibited by [C2mim]Cl
concentrations above 250 mM and cannot grow at all in concen-
trations above 312.5 mM, even in rich medium.
Both lignocellulose dissolution activity and toxicity to micro-
organisms are mediated by the cation species of ionic liquids (11).
We examined if this holds true in our system by testing SCF1
growth in NaCl concentrations ranging from 0–625 mM in a sim-
ilar experimental setup as [C2mim]Cl Omnilog experiments. The
results demonstrate that SCF1 is a relatively halotolerant organ-
ism that can grow in the presence of up to 625 mM NaCl (Fig. S3),
with higher growth rates than in equimolar concentrations of
[C2mim]Cl (Table S1). Mild growth inhibition was observed at
437.5mM and above.It is likely that thehalotolerant properties of
SCF1 contribute to its [C2mim]Cl tolerance. We presume it is
imidazolium cation, rather than the chloride anion of [C2mim]Cl,
that is responsible for its toxicity at high concentrations.
Many microorganisms isolated from the environment are able
to reduce the toxic effects of anthropogenic compounds, including
some ionic liquids, by at least partially metabolizing the chemical
(11). The potential ability of SCF1 to degrade ionic liquid was in-
vestigated by FTIR spectroscopy measurements of SCF1 culture
ing to imidazolium did not change between measurements of
indicating that [C2mim]Cl was not degraded by SCF1 during this
time (Fig. S4). This is consistent with other reports of low bio-
degradability of imidazolium-based ionic liquids (34).
Compatible Solutes and [C2mim]Cl Tolerance. A potential role of
compatible solutes (35) in SCF1 ionic liquid tolerance was ex-
amined by comparing SCF1 growth in defined medium con-
taining 250 mM [C2mim]Cl, either alone or with the addition of
2 mM glycine betaine, proline, ectoine, or glutamate. All four
were able to relieve most of the growth inhibition at this in-
termediate concentration of ionic liquid, as measured by the
maximum growth rate and final biomass yield, suggesting that
SCF1 can use glutamate, glycine betaine, ectoine, and proline as
compatible solutes to tolerate ionic liquid stress (Fig. 1B). Ad-
dition of glutamate resulted in the largest improvement in final
biomass yield, followed, in decreasing order, by glycine betaine,
ectoine, and proline (Table 2). Glutamate and glycine betaine
improved final biomass yield to levels observed in defined me-
dium without [C2mim]Cl. The greatest improvement in SCF1
maximum growth rate in 250 mM [C2mim]Cl was mediated by
glycine betaine, followed by glutamate, ectoine, and proline.
Effect of [C2mim]Cl on SCF1 PLFA Composition. To investigate
whether cell membrane reorganization (36) is involved in ionic
liquid tolerance, we compared the phospholipid fatty acid
(PLFA) profile of SCF1 cells during log phase growth in either
TSB10 (control), 375 mM [C2mim]Cl, or 375 mM NaCl. The
palmitic (16:0), palmitoleic (16:1w7c), vaccenic (18:1w7c), and
myristic (14:0) fatty acids made up the majority of total phos-
pholipid composition and did not change significantly in these
conditions (Fig. 2A and Table S2). Surprisingly, we did not detect
large changes in PLFA components that are altered by stress in
other organisms (36–38), with the exception of cyclopropane
fatty acids (Fig. 2B). The mole fractions of 17cy and 19cy were
dramatically increased in response to [C2mim]Cl and NaCl (Fig.
2 C and D), with a corresponding decrease in parent monoenoic
fatty acids (Fig. 2A). In contrast, other stress indices, such as the
ratios of saturated/unsaturated (16:0/16:1 and 18:0/18:1) and
stearic/palmitic (18:0/16:0) fatty acids did not change signifi-
cantly, and did not differ between [C2mim]Cl and NaCl treat-
ments (Fig. 2B). Therefore, we found that cyclopropane fatty
acids are increased during SCF1 growth with exposure to
[C2mim]Cl, a response that is partially shared with salt stress.
[C2mim]Cl-Induced Changes in Gene Expression. Global gene ex-
pression changes during SCF1 growth with [C2mim]Cl were ana-
(39, 40), with thegoalofelucidating molecularmechanisms driving
tolerance. Transcriptome libraries were generated from SCF1 cells
Two concentrations of stressor were used based on their mild (250
and cells cultured in these conditions were collected during early-
phase (OD600= 0.2) and active-phase (OD600= 0.6) periods of
growth representing initial and sustained stress responses (Fig. 3).
Of 4,556 genes annotated in the SCF1 genome, 4,399 transcripts
were detected by RNA-Seq, with a range of 1.6–7.2 million reads
per sample. A wide range of expression patterns was observed, but
the most significant overall changes in gene expression occurred at
OD600= 0.6 in 375 mM [C2mim]Cl and NaCl; consequently, de-
tailed analysis was focused on these specific libraries.
Differential expression (DE) analysis of RNA-Seq data using
the DESeq software package (41) revealed 1,245 genes with
significant differential expression and an increase of twofold or
greater in [C2mim]Cl vs. NaCl (Fig. 3B). Only 688 genes showed
significant differential expression in [C2mim]Cl vs. control, partly
because the two control replicates at OD600= 0.6 were less well-
correlated, such that a higher fold-change was required to reach
statistical significance (Fig. 3A). We found that the SCF1 re-
sponse to [C2mim]Cl was significantly different from the σS-
regulated general stress response in E. coli. Weber et al. (42)
identified 140 σS-dependent genes in E. coli up-regulated during
Table 1.Effect of [C2mim]Cl on E. lignolyticus SCF1 growth
[C2mim]Cl, mMLag time (λ), hRate (μm), h−1
0.51 ± 0.22
2.81 ± 0.24
3.09 ± 0.35
2.51 ± 0.42
2.60 ± 0.66
5.60 ± 1.20
10.81 ± 1.54
24.34 ± 2.90
10.05 ± 3.21
0.146 ± 0.009
0.167 ± 0.014
0.137 ± 0.013
0.115 ± 0.015
0.092 ± 0.019
0.068 ± 0.021
0.061 ± 0.021
0.058 ± 0.016
0.026 ± 0.006
0.017 ± 0.011
0.029 ± 0.013
2.43 ± 0.04
2.73 ± 0.06
2.70 ± 0.07
2.77 ± 0.07
2.81 ± 0.08
2.61 ± 0.09
2.48 ± 0.09
2.08 ± 0.10
1.71 ± 0.15
0.67 ± 0.05
0.61 ± 0.04
The effects of increasing [C2mim]Cl concentration on SCF1 culture lag
time (λ), maximum specific growth rate (μm), and asymptotic amplitude of
the response (A) were calculated from data presented in Fig. 1A by fitting to
the modified Gompertz equation given in Materials and Methods. Each
parameter is shown as the average of all technical and biological replicates
± SE. Negative control refers to measurements for samples containing cul-
ture medium without cells. N/A, not applicable.
Khudyakov et al. PNAS
| Published online May 14, 2012
short and long-term stress responses, including osmotic and pH
shock, as well as transition into stationary phase. Eighty-one of
these nonspecific stress response genes had a bidirectional best
BLAST hit at >70% sequence identity to SCF1. However, only
27 of these orthologs were significantly differentially expressed in
[C2mim]Cl vs. NaCl, accounting for less than 4% of the 688
differentially expressed genes, and included none of the top 50
genes with highest fold-change under those conditions.
We found that transporters accounted for more than a quarter of
functional gene categories differentially expressed in [C2mim]Cl vs.
NaCl (Fig. 4A). Translation; ribosomal structure; and biogenesis
genes, including ribosomal gene clusters, were strongly down-reg-
ulated, followed by nucleotide metabolism; cell wall/membrane/
envelope biogenesis; and replication, recombination, and repair
genes. In contrast, energy production and conversion as well as
amino acid and carbohydrate metabolism were up-regulated.
Results for [C2mim]Cl vs. control were broadly similar, with some
notable exceptions: [C2mim]Cl vs. control demonstrated only half
as many up-regulated transporters (65 up-regulated transporters
for [C2mim]Cl compared with 128 up-regulated transporters for
control), whereas [C2mim]Cl vs. salt showed far more up-regu-
lated proteins of unknown function and hypothetical proteins for
[C2mim]Cl than for salt (SI Materials and Methods).
The effect of [C2mim]Cl stress on SCF1 metabolism was exam-
ined by mapping RNA-Seq data onto a reconstruction of SCF1
metabolic pathways using Pathway Tools (43) software (Fig. 5).
Pathways that were up-regulated specifically in [C2mim]Cl rather
than NaCl conditions included those for cyclopropane fatty acid
synthesis, fatty acid β-oxidation, lipid biosynthesis, and amino acid
degradation and conversion. Consistent with results of PLFA
analysis, we found that the cyclopropane fatty acyl phospholipid
cells compared with control (Fig. 5a), whereas salt stress caused
only a modest 1.3-fold increase. Many of the fatty acid β-oxidation
pathways were also up-regulated (Fig. 5b), and a number of other
fatty acid and lipid biosynthesis pathways showed shifts from one
isozyme to another. One of the most highly down-regulated path-
ways in [C2mim]Cl was the enterobactin biosynthesis pathway
encoded by the entCEBAH operon (Entcl_3202–Entcl_3198),
which showed a 66-fold down-regulation compared with either
control or NaCl (Fig. 5c). A variety of amino acid degradation and
conversion pathways were up-regulated in [C2mim]Cl vs. salt, some
of which may be involved in production of compatible solutes, such
as glutamate or glutamine (Fig. 5d).
Sugar, amino acid, and peptide transporters were up-regulated
in [C2mim]Cl (Fig. 4B), consistent with up-regulation of the
corresponding metabolic pathways and energy metabolism
shown in Fig. 5. A wide variety of Fe2+, Fe3+, heme, and side-
rophore transporters were strongly down-regulated. There was
a larger number of significantly down-regulated than up-regu-
lated drug efflux pumps; however, some of the up-regulated
drug efflux pumps showed very high fold-changes (Table 3).
One of the most highly up-regulated transporter operons in
both [C2mim]Cl and NaCl encodes a glycine betaine/L-proline
ATP-binding cassette (ABC) transporter, which was up-regu-
lated 63-fold in [C2mim]Cl and 167-fold in NaCl vs. control.
Three porins were down-regulated in both [C2mim]Cl and NaCl
vs. control, two of which had extremely high RNA-Seq ex-
pression counts: Entcl_4131 (porin LamB type), which was
down-regulated 19-fold in [C2mim]Cl and 10-fold in NaCl, was
the 27th most abundant transcript in the entire control library
normalized by transcript length, and Entcl_2856 (porin Gram-
negative type), which was down-regulated threefold in [C2mim]
Cl and NaCl, was the third most abundant transcript in control
cells (Table 3).
Technical and biological validation of RNA-Seq data was per-
formed by RT-quantitative PCR (qPCR) using nine genes with
distinct changes in expression between conditions, including genes
of interest, such as cyclopropane fatty acyl synthase, major facili-
tator superfamily (MFS) efflux pump, and ABC family glycine
betaine/proline transporter (Fig. S5). We found that gene ex-
pression changes were highly correlated between RNA-Seq and
qPCR data. In addition, changes in expression of these specific
transcripts were mirrored in an independently conducted bi-
by [C2mim]Cl exposure.
Bacterial strains isolated from such environments as forest soils,
which experience fluctuating nutrient, temperature, oxygen, and
water levels, have been found to be extremely robust compared
with model laboratory organisms, which succumb to process inhi-
bition at almost every step during biofuels production (18). For
instance, we found that E. coli strain BW25113 growth was com-
pletely inhibited by [C2mim]Cl concentrations above 312.5 mM.
Likewise, other strains of E. coli show high sensitivity to a number
of ionic liquids (19–21). Because residual ionic liquids in pre-
treated feedstocks can be highly toxic to many microorganisms,
identifying microbes that possess both high degradation activity
and stress tolerance and developing an understanding of the un-
derlying mechanisms are critical to engineering effective strains
for the biofuels process.
E. lignolyticus SCF1 is a facultatively anaerobic, fast-growing,
and moderately halotolerant bacterium isolated from tropical rain
RNA-Seq, a powerful tool for transcriptomics (39, 40), we ana-
lyzed transcriptional changes during SCF1 exposure to [C2mim]Cl
and found that the molecular avenues affected included compati-
Table 2.Effect of compatible solutes on E. lignolyticus SCF1 growth
Growth condition Growth rate (μm), h−1
0 mM [C2mim]Cl
250 mM [C2mim]Cl
250 mM [C2mim]Cl + proline
250 mM [C2mim]Cl + ectoine
250 mM [C2mim]Cl + glycine betaine
250 mM [C2mim]Cl + glutamate
0.146 ± 0.009
0.111 ± 0.011
0.126 ± 0.009
0.128 ± 0.007
0.137 ± 0.010
0.130 ± 0.008
0.027 ± 0.003
2.50 ± 0.10*
1.55 ± 0.08
2.38 ± 0.09*
2.43 ± 0.10*
2.53 ± 0.13*
2.57 ± 0.11*
0.46 ± 0.03*
Effects of addition of 2 mM proline, ectoine, glycine betaine, and glutamate on SCF1 growth with 250 mM
[C2mim]Cl in defined medium. Maximum specific growth rate (μm) and asymptotic amplitude of the response (A)
were calculated from data presented in Fig. 1B by fitting to the modified Gompertz equation given in Materials
and Methods. Each parameter is shown as the average of all technical and biological replicates ± SE. Negative
control refers to measurements for samples containing culture medium without cells.
*Denotes amplitude (A) values that differed significantly from those for the 250 mM [C2mim]Cl condition by t
test (P < 0.01).
| www.pnas.org/cgi/doi/10.1073/pnas.1112750109Khudyakov et al.
ble solutetransporters, efflux pumps, porins, and lipid biosynthesis
pathways among others. We compared equimolar concentrations
of [C2mim]Cl and NaCl to present the organism with similar os-
motic stress in each case, with the goal of examining whether ionic
liquid stressis perceived similar tootherstressors. Significantly, we
differently (or to a higher extent) in ionic liquid rather than salt
conditions. Recent studies that measured the osmotic and activity
coefficients of [C2mim]Cl with other salt solutions by the isopiestic
method demonstrated that both coefficients did not vary signifi-
cantly between [C2mim]Cl and NaCl over a wide range of molal-
ities (44). Based on this work, the differences in metabolic
responses of SCF1 to these salts cannot be attributed to significant
differences in the osmotic and activity coefficients of [C2mim]Cl
to each stressor.Furthermore, few of the SCF1 orthologs of E. coli
genes involved in generalized stress response (42) showed tran-
we believe that [C2mim]Cl exposure does not merely reflect
a generalized stress response in SCF1 and is at least partially
unique from the transcriptional response induced by salt stress.
Transporters represented the largest group of genes affected
identify putative substrates for transporters present in our data-
set. The largest group of up-regulated transporters belonged to
the ABC superfamily, with sugars and amino acids as primary
substrates. In addition, one of the genes with the highest log ratio
expression increase over control included the ABC superfamily
transporter for the compatible solutes glycine betaine and pro-
line. We hypothesize that these small-molecule transporters and
symporters, and also some of the up-regulated amino acid deg-
radation and conversion pathways, may be aiding the intracellular
accumulation of compatible solutes or their precursors to offset
the osmotic pressure generated by exposure to ionic liquid. In-
deed, we found that glycine betaine, glutamate, proline, and
ectoine relieved much of the growth inhibition by [C2mim]Cl.
cells grown in TSB10 with 375 mM [C2mim]Cl or 375 mM NaCl, relative to TSB10 alone (control). (B) Stress indices for SCF1 cells grown with [C2mim]Cl and NaCl
calculated as percent change relative to control of ratios of saturated/unsaturated (16:0/16:1 and 18:0/18:1), cyclopropane/unsaturated (17cy/18:1 and 19cy/
20:1), and stearic/palmitic (18:0/16:0) fatty acid mole fractions. (C) Mole fraction of total membrane lipids of 17-cyclopropane (17cy) fatty acid. (D) Mole
fraction of total membrane lipids of 19-cyclopropane (19cy) fatty acid. Error is presented as SD of n = 3 biological replicates. Statistical analysis of the
measurements in C and D using a t test (95% confidence level) indicates that the differences in cyclopropane fatty acid ratios are significant between control
and both additive conditions but not between [C2mim]Cl and NaCl conditions.
Changes in cell membrane composition of SCF1 in response to [C2mim]Cl and NaCl exposure. (A) Percent change in mole fraction of total lipids in SCF1
Khudyakov et al.PNAS
| Published online May 14, 2012
Other studies will be necessary to determine the extent to which
these molecules accumulate intracellularly.
A number of multidrug efflux pumps, such as those of the MFS,
were highly up-regulated by [C2mim]Cl. Although the single-im-
idazole ring structure of [C2mim]Cl does not resemble antibiotics
that are predicted substrates for these transporters, some efflux
pumps are promiscuous to some extent, and may therefore pump
other toxic compounds out of the cell, such as ionic liquids (46).
Efflux pumps contribute greatly to microbial resistance to toxic
compounds (47), and their heterologous expression can improve
tolerance of E. coli to hydrocarbons (48); thus, it is likely that
these pumps could play a similar role in [C2mim]Cl tolerance.
Another approach to reducing toxicity is to decrease passive
membrane permeability to the stressor (e.g., by decreasing ex-
pression of membrane porins) (49). We found that two porin
genes that were among the most highly expressed transcripts in
the control condition were strongly down-regulated in SCF1 cells
exposed to [C2mim]Cl. Regulation of porin expression has been
implicated in antibiotic resistance in a number of bacterial or-
ganisms, as well as in acid resistance in Enterobacteriaceae (47,
49). Therefore, the combination of reduced cell permeability and
active pumping may limit the intracellular ionic liquid concen-
tration, thus reducing its toxicity to the microorganism.
Cell membrane permeability can also be reduced by modifying
the PLFA composition (36). We found that [C2mim]Cl exposure
caused an increase in cyclopropane fatty acids with a concomitant
decrease in the parent monoenoic fatty acids, without significant
alteration in other cell membrane components. Using an in-
dependent method, we also detected an increase in transcripts of
cyclopropane fatty acyl synthase, the enzyme responsible for
cyclopropanation, during SCF1 growth with [C2mim]Cl. This re-
sponse was also seen with NaCl stress but to a lesser degree.
(fold-change) vs. the mean of the log expression levels in the two conditions,
for 375 mM [C2mim]Cl vs. control (A) and 375 mM [C2mim]Cl vs. 375 mM NaCl
(B), at OD600 = 0.6. Red dots indicate genes detected as differentially
expressed at a 10% false discovery rate. Arrows at the upper and lower plot
borders indicate genes with very large or infinite log fold-change.
Statistical analysis of differential gene expression. Plots of log2ratio
Genes differentially expressed in 375 mM [C2mim]Cl vs. 375 mM NaCl at
OD600 = 0.6 were divided into nontransporters (A) and transporters (B).
Nontransporters were characterized by clusters of orthologous groups (COG)
categories (72, 75). Transporter genes were categorized based on predicted
substrate type in TransportDB (45). Blue bars indicate number of genes up-
regulated in [C2mim]Cl ([C2mim]Cl > NaCl), whereas red bars indicate num-
bers of genes up-regulated in NaCl ([C2mim]Cl < NaCl).
Categories of differentially expressed genes in [C2mim]Cl vs. NaCl.
| www.pnas.org/cgi/doi/10.1073/pnas.1112750109 Khudyakov et al.
Given the pronounced shift in cyclopropane fatty acids and the
widespread differences in other metabolic pathways between
[C2mim]Cl and salt exposure, it is somewhat unexpected that the
changes in PLFA profiles between these conditions are otherwise
fairly similar, presumably attributable to a generalized membrane
fatty acid production during [C2mim]Cl exposure demonstrates
the distinct effect of ionic liquid on the bacterium. A number of
studies using E. coli and lactobacilli have demonstrated that
methylation of the cis-acyl chain double bond to form a cyclo-
propane ring plays a significant role in tolerance to acid, salt,
butanol, and other stressors by reducing membrane fluidity and
decreasing permeability (50–54). It is probable that cyclopropane
fatty acid production plays a similar role in [C2mim]Cl tolerance
by stabilizing the cell membrane. Furthermore, up-regulation of
fatty acid β-oxidation pathways and changes in other lipid bio-
synthesis genes suggest that cell membrane remodeling is an
important component of the response to ionic liquids. It remains
to be seen whether [C2mim]Cl or other ionic liquids, such as
[C2mim]acetate (OAc), cause a similar up-regulation in cfa and
17cy and 19cy production in E. coli, and whether this pathway can
be enhanced to improve tolerance of ionic liquids.
The up-regulation of sugar and amino acid metabolism and
and nucleotide synthesis, suggested that the organism may be
diverting energy from cell replication towardfighting the effects of
[C2mim]Cl toxicity. The strong down-regulation of a wide variety
biosynthesis, export, and reuptake, as well as heme, siderophore,
ferric, and ferrous iron transporters, indicated an as yet un-
explained involvement of iron homeostasis in [C2mim]Cl toxicity
or tolerance, possibly involving activation of the global Fur reg-
ulon. The homologous Fur regulator in SCF1 (Entcl_3132) was
not differentially expressed in our RNA-Seq data, but Fur activity
is typically regulated after translation by binding to Fe2+(55). It is
possible that [C2mim]Cl toxicity causes an increase in free in-
formed using TransportDB (45) as described in Materials and Methods. Reactions in the network corresponding to significantly over- or underexpressed genes
in 375 mM [C2mim]Cl vs. 375 mM NaCl were colored based on their log ratio, ranging from orange for log ratio >4.0 (16-fold or more up-regulated in [C2mim]
Cl) to light green for log ratio <−4.0 (16-fold or more up-regulated in NaCl). Transporters are arranged around the boundary. Selected enzymatic reactions or
pathways include cyclopropane synthesis (a), fatty acid β-oxidation (b), enterobactin biosynthesis (c), and amino acid degradation and conversion (d).
Whole-genome metabolic reconstruction of SCF1 showing differentially expressed pathways and transporters. Metabolic reconstruction was per-
Table 3.Top SCF1 transporter genes with significant change in expression in [C2mim]Cl relative to control and NaCl
Locus tag Control[C2mim]ClNaCl Log2[C2mim]Cl/control Log2[C2mim]Cl/NaCl Substrate
Aromatic amino acid
Sodium ion/citrate symporter
21,041 147 10,013
Top SCF1 transporters affected by ionic liquid are shown as the 10 most up-regulated (highest log ratios) and 10 most down-
regulated (lowest log ratios) genes in 375 mM [C2mim]Cl relative to 375 mM NaCl. Normalized gene counts are shown for SCF1 cells
cultured in TSB10 alone (control), 375 mM [C2mim]Cl, and 375 mM NaCl. Log ratio calculations and predicted transporter substrate
assignments were performed as described in Materials and Methods. N/A, not applicable (transcripts were not detected in 375 mM
Khudyakov et al.PNAS
| Published online May 14, 2012
tracellular Fe (e.g., by disrupting formation or increasing degra-
dation of iron-containing proteins or prosthetic groups).
In conclusion, we propose a preliminary ionic tolerance model
for bacteria like SCF1, involving (i) rapid phospholipid cell mem-
brane remodeling and down-regulation of porins to decrease cell
permeability to ionic liquid; (ii) up-regulation of multidrug efflux
pumps to reduce intracellular ionic liquid concentration; and (iii)
increase in compatible solute scavenging, transport, and synthesis
to reduce adverse osmotic pressure effects of residual ionic liquid
influx. This model remains to be tested by direct intracellular
measurements of [C2mim]Cl concentration during SCF1 exposure
to thisionic liquid, although a current limitation ofthisapproachis
the difficulty in resolving subcellular localization and temporal
dynamics of ionic liquids in single cells. It will also be important to
determine whether this model is applicable to other ionic liquids
used for biomass pretreatment, such as [C2mim]OAc. In the
meantime, however, we have found that RNA-Seq is a highly ef-
response to a “novel” chemical at the transcriptome level. The
results presented here provide an important basis for further work
in tolerant strain engineering and for understanding microbial
stress and adaptation responses to anthropogenic chemicals used
Materials and Methods
Strains and Culture Conditions. E. lignolyticus strain SCF1 was isolated from
tropical forest soils collected from the Short Cloud Forest site inthe El Yunque
National Forest in Puerto Rico (26). SCF1 growth assays were performed
aerobically at 30 °C in TSB10. The osmolality of TSB10 is ∼30 mOsm/kg based
on that reported for trypticase soy broth (TSB) (56). MOD-CCMA–defined
medium (26) for osmoprotectant experiments contained the following: 2.8
MES, 1.1 mL·L−1K2HPO4, 12.5 mL·L−1trace minerals (57, 58), 1 mL·L−1Thauer’s
vitamins (59), 20 mM D-glucose, and 0.1% yeast extract. The E. coli strain used
for stress tolerance experiments was BW25113, a derivative of the E. coli K-12
strain BD792. BW25113 was used to make the Keio KO collection of single-
gene KOs, and it has the genotype Δ(araD-araB)567, ΔlacZ4787(::rrnB-3), λ-,
rph-1, Δ(rhaD-rhaB)568, hsdR514 (33). E. coli growth assays were performed
at 37 °C in Luria–Bertani–Miller broth. Several media constituents, including
TSB, were obtained from EMD Chemicals, Inc. The [C2mim]Cl, NaCl, proline,
ectoine, glycine betaine, glutamate, and D-glucose were obtained from
Omnilog Phenotypic Microarray Assays. SCF1 was cultured in 50 mL of TSB10
until OD600= 0.4 at 30 °C with shaking at 200 rpm and used to inoculate
empty sterile multiwell plates (Biolog, Inc.) at a 10% (vol/vol) dilution of
a total volume of 100 μL. A range of [C2mim]Cl or NaCl concentrations (0–625
mM) in TSB10 was tested in each plate using the empty plate function. After
addition of proprietary Redox Dye A (Biolog, Inc.) according to the manu-
facturer’s instructions, multiwell plates were incubated in the Omnilog in-
strument at 30 °C for 72 h. Three biological replicates were grown in parallel
within the same run. Growth in each 100-μL well was measured in Omnilog
(OL) units, calculated as the change in tetrazolium redox dye color intensity
attributable to dye reduction during cell respiration (29). Dye intensity values
were measured at 15-min intervals throughout the incubation period. Results
are reported as the natural log of average OL values (average of 6 technical
replicate wells for each of 3 biological replicate plates, with the exception of
the experiment presented in Fig. 1B, for which only 2 biological replicates
were used). A negative control containing medium and dye with no cells was
run in each plate to rule out contamination and obtain background readings.
as the base medium at 37 °C incubation temperature.
Omnilog Curve Fitting and Growth Parameters. Omnilog growth curve data
were log-transformed and fitted to a modified Gompertz equation (30, 32):
where N0is the lower asymptote for the color intensity (fitted as a separate
parameter of the growth curve, because the initial color intensity at time 0 is
highly sensitive to measurement noise at low intensity levels), λ is the lag
time before onset of exponential growth (constrained to be greater than or
equal to 0), μmis the maximum specific growth rate, and A is the asymptotic
response. These parameters are demonstrated in Fig. S1B. For visualization
purposes, the growth curve data in Fig. 1 and Fig. S1 was slightly smoothed
using a Gaussian kernel ([1 4 6 4 1]) to reduce some of the measure-
FTIR Determination of Ionic Liquid Concentration. [C2mim]Cl was measured
quantitatively on a VERTEX 70 Series FTIR Spectrometer (Bruker Optics) by
recording the unique peak height at 1,170.59 cm−1corresponding to imi-
dazolium-based ionic liquid. Supernatants of SCF1 cultures in TSB10 (base-
line control) or TSB10 with 272.8 mM [C2mim]Cl were collected after 6.9 h
and 24.3 h of growth and analyzed by FTIR. A standard curve was prepared
using 0 mM, 34.1 mM, 68.2 mM, 136.4 mM, 204.6 mM, and 272.8 mM
[C2mim]Cl in TSB10. Averaged peak height values for three biological rep-
licates were used to calculate the concentration of ionic liquid remaining in
culture from the standard curve equation.
PLFA. SCF1 cells cultured in 40 mL of TSB10 (control), 375 mM [C2mim]Cl, or
375 mM NaCl were grown until OD600= 0.6 and then collected on Sterivex
GP 0.22-μm filter units (Millipore). Fatty acid methyl esters were extracted by
the Bligh–Dyer method (60–62), detected on an Agilent 6890N GC/MS in-
strument on an HP1 60-m column × 0.25-mm inner diameter, and quantified
by comparison to known standards. Average masses of all lipids profiled for
triplicate biological samples are given in Table S2. Stress indicators were
calculated as ratios of saturated/unsaturated, cyclopropane/unsaturated,
and 18:0/16:0 lipids (60, 63–67).
Total RNA Isolation. SCF1 cultures in TSB10 (control), 250 mM [C2mim]Cl,
375mM[C2mim]Cl,250mM NaCl,and375mMNaCl werecollectedatOD600=
0.2 and OD600 = 0.6, and treated with RNA Protect reagent (Qiagen)
according to the manufacturer’s protocol. RNA extraction and purification
were performed with the RNeasy Miniprep Kit (Qiagen) using 2 mg/mL ly-
sozyme for cell lysis (Sigma–Aldrich) and including on-column DNase digest
(Qiagen). Residual genomic DNA contamination was removed by TURBO
DNase I (Ambion) treatment according to the manufacturer’s protocol.
Samples were purified by phenol/chloroform/isoamyl alcohol (25:24:1, pH 8;
Sigma–Aldrich) extraction and precipitated with 3 M NaOAc (Fermentas).
(Ambion), and sample concentration was quantified using the Qubit RNA-
specific fluorescent dye assay system (Invitrogen). RNA integrity was assayed
using the RNA Nano 6000 chip on the Bioanalyzer system (Agilent).
RNA Sequencing. Total RNA was treated with the MICROBExpress Bacterial
mRNA Enrichment kit (Ambion) following the manufacturer’s instructions.
rRNA removal was evaluated using the Agilent 2100 Bioanalyzer. mRNA-
enriched RNAs were chemically fragmented to the size range of 200–250 bp
using 1× fragmentation solution (Ambion) for 5 min at 70 °C. Double-
stranded cDNA was generated using the SuperScript Double-Stranded cDNA
Synthesis Kit (Invitrogen). Briefly, first-strand cDNA was synthesized using
SuperScript II and random hexamers, and second-strand cDNA was synthe-
sized using E. coli RNaseH, ligase, and DNA polymerase I for nick translation.
The Illumina Paired End Sample Prep kit was used for RNA-Seq library cre-
ation according to the manufacturer’s instructions as follows: Fragmented
cDNA was end-repaired, ligated to Illumina adaptors, and amplified by 10
cycles of PCR. Single or paired-end 36-bp reads were generated by se-
quencing using the Illumina Genome Analyzer II instrument.
RNA-Seq Read Counts and Normalization. RNA-Seq reads were aligned to the
E. lignolyticus SCF1 reference genome [GenBank accession no. CP002272.1;
this organism was previously called Enterobacter cloacae SCF1 and has been
renamed E. lignolyticus SCF1 (26), with the old name retained in the Na-
tional Center for Biotechnology Information database] using the Burrows-
Wheeler Aligner (BWA) (68). Read counts were determined for each library
on a per-gene basis. We normalized raw read counts by dividing by a size
factor for each library, as proposed by Anders and Huber (41) and Robinson
and Oshlack (69), such that the median fold change between libraries
^ sj= median
where kijis the raw read count for gene i in library j and ŝjis the size factor
for library j. Because longer transcripts will tend to generate more RNA-Seq
| www.pnas.org/cgi/doi/10.1073/pnas.1112750109Khudyakov et al.
reads, the normalized read counts were further divided by the length of the
gene in kilobase pairs to allow comparisons across genes and comparisons
with qPCR data. Raw and normalized counts for the entire dataset are in-
cluded in Dataset S1.
RNA-Seq Differential Expression Analysis. Pair-wise differential expression
analysis between 375 mM [C2mim]Cl and control and between 375 mM
[C2mim]Cl and 375 mM NaCl conditions at OD600= 0.6 were performed using
the R package DESeq (41), available under Bioconductor (www.bioconductor.
org). DESeq normalizes the raw counts using size factors as described above.
Because estimates of variance per gene based on only two replicates are
highly unreliable, DESeq uses an unbiased variance estimator that is based on
a local regression against the mean expression level across the entire dataset,
and then uses a negative binomial model to test for differential expression.
The resulting P values were adjusted for multiple hypothesis testing with the
procedure of Benjamini and Hochberg for controlling the false discovery rate
(70). Genes with an adjusted P value <0.1 and a fold-change greater than 2
wereassigned asdifferentiallyexpressed.DESeq outputtablesareincluded in
Dataset S1. Fold changes for the enterobactin and ABC transporter operons
were calculated by adding the RNA-Seq counts for the individual genes,
without adjusting for transcript length.
Metabolic Network Reconstruction. ThemetabolicPathway-GenomeDatabase
for SCF1 was computationally generated using Pathway Tools software ver-
sion 12.5 (43) and MetaCyc version 12.5 (71), based on the genome annota-
tion from the Joint Genome Institute’s Integrated Microbial Genomics (IMG)
system (72), supplemented with additional Enzyme Commission numbers
from Rapid Annotation using Subsystem Technology (RAST) (73). It has un-
dergone minimal manual curation and may contain some errors, similar to
a tier 3 BioCyc Pathway-Genome Database (74). Functional annotations for
the significantly differentially expressed genes are included in Dataset S1.
Transporter Substrate Category Assignments. Putative transporters and sub-
strate assignments were derived from a number of different annotation
sources.Tosupplementthegenomeannotation fromtheIMG system (72),we
also consulted transporter annotations generated by RAST (73) and the SCF1
genome annotation by MicrobesOnline (75), scanning for the keywords
“transport,” “export,” “import,” “symport,” “antiport,” “efflux,” “perme-
ase,” and “porin.” In addition, we used BLAST to search for all SCF1 protein
sequences against transporters annotated for the two closest strains in the
TransportDB database (45), Klebsiella pneumoniae Kp342 and K. pneumo-
niae MGH78578, and retained the transporter families and substrate pre-
dictions for the best hits with an E-value <1 E−10. Annotations from the IMG
system, RAST, MicrobesOnline, and TransportDB were combined and cu-
rated manually to remove any likely nontransporters and to assign likely
RT-qPCR. cDNA was synthesized using the SuperScript III First-Strand Synthesis
System for RT-PCR (Invitrogen) according to the manufacturer’s protocol,
using random hexamers and a total input of 100 ng of RNA in each reaction.
cDNA samples were used at 1:100 final concentration. Primers were used at
200nMandare listed inTable S3.Reactionsina20-μLvolume were runonthe
StepOnePlus instrument (Applied Biosystems) using PerfeCta SYBR Green
SuperMix mixwithROX(Quanta Biosciences)according tothemanufacturer’s
instructions. UbiD decarboxylase gene (Entcl_4195) was used as a reference
based on its expression stability across all conditions in the RNA-Seq dataset.
Six dilutions of cDNA were used to run a standard curve for each primer, and
slope of the curve (76, 77). Ratio of expression (R) was quantified by the Pfaffl
method (77, 78) using the equation:
transformed. Error of R values (ΔR) was calculated by the following equation:
where ΔS is the SD of ΔCTof three technical replicates.
ACKNOWLEDGMENTS. We thank Christa Pennacchio, Feng Chen, Zhong
Wang, Tanja Woyke, Lynne Goodwin, and Tijana Glavina del Rio for as-
sistance with the RNA sequencing project; Aindrila Mukhopadhyay, Mario
Ouellet, Adrienne McKee, Swapnil Chhabra, and Joseph Schramm for intel-
lectual input, experimental design, and technical advice; Anthe George and
Kim Tran for providing ionic liquid reagents and technical advice; and Dylan
Chivian, Jason Baumohl, Keith Keller, and Paramvir Dehal for providing
Microbes Online analysis tools. Work performed at theDepartment of Energy
Joint BioEnergy Institute (http://www.jbei.org), Department of Energy Joint
Genome Institute, and Lawrence Berkeley National Laboratory was sup-
ported by the Office of Science of the US Department of Energy through
Contract DE-AC02-05CH11231, and at Lawrence Livermore National Labora-
tory through Contract DE-AC52-07NA27344.
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