An evolutionary proteomics approach identifies substrates of the cAMP-dependent protein kinase.
ABSTRACT Protein kinases are important mediators of much of the signal transduction that occurs in eukaryotic cells. Unfortunately, the identification of protein kinase substrates has proven to be a difficult task, and we generally know few, if any, of the physiologically relevant targets of any particular kinase. Here, we describe a sequence-based approach that simplified this substrate identification process for the cAMP-dependent protein kinase (PKA) in Saccharomyces cerevisiae. In this method, the evolutionary conservation of all PKA consensus sites in the S. cerevisiae proteome was systematically assessed within a group of related yeasts. The basic premise was that a higher degree of conservation would identify those sites that are functional in vivo. This method identified 44 candidate PKA substrates, 5 of which had been described. A phosphorylation analysis showed that all of the identified candidates were phosphorylated by PKA and that the likelihood of phosphorylation was strongly correlated with the degree of target site conservation. Finally, as proof of principle, the activity of one particular target, Atg1, a key regulator of autophagy, was shown to be controlled by PKA phosphorylation in vivo. These data therefore suggest that this evolutionary proteomics approach identified a number of PKA substrates that had not been uncovered by other methods. Moreover, these data show how this approach could be generally used to identify the physiologically relevant occurrences of any protein motif identified in a eukaryotic proteome.
- SourceAvailable from: Tamas Korcsmaros[Show abstract] [Hide abstract]
ABSTRACT: Autophagy, the lysosome-mediated self-degradation process, is implicated in survival during starvation in yeast, Dictyostelium and animals. In these eukaryotic taxa (collectively called Unikonts), autophagy is induced primarily through the Atg1/ULK1 complex in response to nutrient depletion. Autophagy has also been well-studied in non-unikont parasites, such as Trypanosoma and Plasmodium, and found important in their life-cycle transitions. However, how autophagy is induced in non-unikonts remains largely unrevealed. Using a bioinformatics approach, we examined the presence of Atg1 and of its complex in the genomes of 40 non-unikonts. We found that these genomes do not encode typical Atg1 proteins: BLAST and HMMER queries matched only with the kinase domain of Atg1, while other segments responsible for regulation and protein-binding were missing. Non-unikonts also lacked other components of the Atg1-inducing complex. Orthologs of an alternative autophagy inducer, Atg6 were found only in the half of the species, indicating that the other half may possess other inducing mechanisms. As key autophagy genes have differential expression patterns during life-cycle, we raise the possibility that autophagy in these protists is induced mainly at the post-transcriptional level. Understanding Atg1-independent autophagy induction mechanisms in these parasites may lead to novel pharmacological interventions, not affecting human Atg1-dependent autophagy.Scientific reports. 01/2014; 4:5829.
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ABSTRACT: The regulatory mechanisms by which hydrogen peroxide (H2O2) modulates the activity of transcription factors in bacteria (OxyR and PerR), lower eukaryotes (Yap1, Maf1, Hsf1 and Msn2/4) and mammalian cells (AP-1, NRF2, CREB, HSF1, HIF-1, TP53, NF-κB, NOTCH, SP1 and SCREB-1) are reviewed. The complexity of regulatory networks increases throughout the phylogenetic tree, reaching a high level of complexity in mammalians. Multiple H2O2 sensors and pathways are triggered converging in the regulation of transcription factors at several levels: (1) synthesis of the transcription factor by upregulating transcription or increasing both mRNA stability and translation; (ii) stability of the transcription factor by decreasing its association with the ubiquitin E3 ligase complex or by inhibiting this complex; (iii) cytoplasm-nuclear traffic by exposing/masking nuclear localization signals, or by releasing the transcription factor from partners or from membrane anchors; and (iv) DNA binding and nuclear transactivation by modulating transcription factor affinity towards DNA, co-activators or repressors, and by targeting specific regions of chromatin to activate individual genes. We also discuss how H2O2 biological specificity results from diverse thiol protein sensors, with different reactivity of their sulfhydryl groups towards H2O2, being activated by different concentrations and times of exposure to H2O2. The specific regulation of local H2O2 concentrations is also crucial and results from H2O2 localized production and removal controlled by signals. Finally, we formulate equations to extract from typical experiments quantitative data concerning H2O2 reactivity with sensor molecules. Rate constants of 140 M(-1) s(-1) and ≥1.3 × 10(3) M(-1) s(-1) were estimated, respectively, for the reaction of H2O2 with KEAP1 and with an unknown target that mediates NRF2 protein synthesis. In conclusion, the multitude of H2O2 targets and mechanisms provides an opportunity for highly specific effects on gene regulation that depend on the cell type and on signals received from the cellular microenvironment.Redox biology. 01/2014; 2:535-562.
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ABSTRACT: SNF1-related kinase (SnRK1) in plants belongs to a conserved family that includes sucrose non-fermenting 1 kinase (SNF1) in yeast and AMP-activated protein kinase (AMPK) in animals. These kinases play important roles in the regulation of cellular energy homeostasis and in response to stresses that deplete ATP, they inhibit energy consuming anabolic pathways and promote catabolism. Energy stress is sensed by increased AMP:ATP ratios and in plants, 5'-AMP inhibits inactivation of phosphorylated SnRK1 by phosphatase. In previous studies, we showed that geminivirus pathogenicity proteins interact with both SnRK1 and adenosine kinase (ADK), which phosphorylates adenosine to generate 5'-AMP. This suggested a relationship between SnRK1 and ADK, which we investigate in the studies described here. We demonstrate that SnRK1 and ADK physically associate in the cytoplasm, and that SnRK1 stimulates ADK in vitro by an unknown, non-enzymatic mechanism. Further, altering SnRK1 or ADK activity in transgenic plants altered the activity of the other kinase, providing evidence for in vivo linkage but also revealing that in vivo regulation of these activities is complex. This study establishes the existence of SnRK1-ADK complexes that may play important roles in energy homeostasis and cellular responses to biotic and abiotic stress.PLoS ONE 01/2014; 9(1):e87592. · 3.73 Impact Factor
An evolutionary proteomics approach identifies
substrates of the cAMP-dependent protein kinase
Yelena V. Budovskaya*, Joseph S. Stephan*, Stephen J. Deminoff, and Paul K. Herman†
Department of Molecular Genetics, Ohio State University, Columbus, OH 43210
Edited by Anthony J. Pawson, University of Toronto, Toronto, ON, Canada, and approved August 12, 2005 (received for review February 7, 2005)
Protein kinases are important mediators of much of the signal
transduction that occurs in eukaryotic cells. Unfortunately, the
identification of protein kinase substrates has proven to be a
difficult task, and we generally know few, if any, of the physio-
logically relevant targets of any particular kinase. Here, we de-
scribe a sequence-based approach that simplified this substrate
identification process for the cAMP-dependent protein kinase
(PKA) in Saccharomyces cerevisiae. In this method, the evolution-
ary conservation of all PKA consensus sites in the S. cerevisiae
proteome was systematically assessed within a group of related
yeasts. The basic premise was that a higher degree of conservation
would identify those sites that are functional in vivo. This method
identified 44 candidate PKA substrates, 5 of which had been
described. A phosphorylation analysis showed that all of the
identified candidates were phosphorylated by PKA and that
the likelihood of phosphorylation was strongly correlated with the
activity of one particular target, Atg1, a key regulator of autoph-
agy, was shown to be controlled by PKA phosphorylation in vivo.
These data therefore suggest that this evolutionary proteomics
approach identified a number of PKA substrates that had not been
uncovered by other methods. Moreover, these data show how this
approach could be generally used to identify the physiologically
relevant occurrences of any protein motif identified in a eukaryotic
Ras proteins ? sequence conservation ? stationary phase
(1, 2). The protein kinase gene family is one of the largest in
eukaryotic organisms and typically constitutes almost 2% of all
the transfer of the terminal phosphate from ATP to the hydroxyl
group of particular serine, threonine, or tyrosine residues in a
defined set of protein targets. This phosphorylation ultimately
alters cell physiology by modifying the activities associated with
these substrate proteins. A complete understanding of the
biology of any protein kinase therefore requires the identifica-
tion of the particular substrates of this enzyme. Unfortunately,
this identification process is often a difficult and labor-intensive
relevant substrates of any protein kinase (5).
The cAMP-dependent protein kinase (PKA) has been exten-
sively studied and is one of the best understood members of the
protein kinase family (6, 7). In Saccharomyces cerevisiae, PKA is
GTP-binding Ras proteins (8–10). The two Ras proteins, Ras1
and Ras2, bind to adenylyl cyclase and stimulate the production
of cAMP (11, 12). This stimulation results in elevated PKA
activity and the increased phosphorylation of substrates that are
presumably important for cell growth and proliferation (13).
Although several PKA substrates have been described, the
biological activities of these proteins are not sufficient to explain
the global effect that PKA activity has on S. cerevisiae growth.
In the past decade, there has been a tremendous accumulation
of DNA sequence information for a wide variety of organisms.
rotein kinases are key components of signal transduction
pathways that regulate many aspects of eukaryotic biology
One of the major challenges for modern biology is the devel-
opment of methods to mine the information inherent in these
data so as to further our understanding of basic biology and to
provide insights into human disease. Comparative analyses
between related species is one approach that seems to hold great
promise in this pursuit. By comparing the DNA sequence of
organisms separated by a range of evolutionary distances, ex-
perimenters have been able to identify important features of
both entire genomes and individual genes and their protein
products (14–18). In this report, we describe a comparative
approach that uses sequence information to identify the biolog-
ically relevant occurrences of a protein motif of interest. In this
approach, the evolutionary conservation of all occurrences of a
particular sequence element in the proteome is systematically
assessed within a group of related organisms. The underlying
premise is that a higher degree of sequence conservation would
identify those elements that are functional in vivo (15, 16).
The general utility of this approach was assessed here by
examining whether the evolutionary conservation of a consensus
phosphorylation site would identify physiologically relevant sub-
strates of a particular protein kinase, PKA, in S. cerevisiae. By
comparing the sequences of orthologous proteins present in a
substrates for this protein kinase. A phosphorylation analysis
indicated that all of these candidates can be phosphorylated by
PKA in vitro and suggested that these proteins might be in vivo
targets of this enzyme. A more detailed analysis of one particular
target, the autophagy-related protein kinase, Atg1, showed that
this protein was phosphorylated and regulated by PKA in vivo.
In all, these data demonstrate the general potential this type of
a comparative approach has for determining the physiological
relevance of any sequence element found in any type of protein.
Protein Sequence Comparisons. The pattern match program,
PATMATCH, at the Saccharomyces Genome Database (SGD) web
site (www.yeastgenome.org) was used to identify the consensus
PKA sites present in the S. cerevisiae proteome. The proteins
containing these PKA sites were then aligned with their likely
orthologs from the other budding yeast species used in this
analysis with the BLASTP and DIALIGN alignment programs. The
final sequence alignments were also examined by eye to ensure
that no conserved PKA site had been missed. The protein
sequences for the five Saccharomyces species used in this analysis
were obtained from the web site for the Genome Sequencing
Center at Washington University (genome.wustl.edu). The Can-
dida albicans sequences were obtained from the CandidaDB
website (www.pasteur.fr?Galar?Fungail?CandidaDB) devel-
oped by the Galar Fungail European Consortium. The PKA
This paper was submitted directly (Track II) to the PNAS office.
PrA, protein A.
*Y.V.B. and J.S.S. contributed equally to this work.
†To whom correspondence should be addressed. E-mail: firstname.lastname@example.org.
© 2005 by The National Academy of Sciences of the USA
September 27, 2005 ?
vol. 102 ?
no. 39 ?
consensus site used here, R?3-R?2-x?1-S?T-B?1, was deduced
from a variety of studies, including work with combinatorial
peptide libraries and an analysis of known PKA target sites
(19–22). In this site, ‘‘x’’ refers to any amino acid, ‘‘B’’ to a
residue with a hydrophobic side chain and the ‘‘S?T’’ to the
serine or threonine residue that is the site of phosphate addition.
A second consensus site of R?6-x?5-x?4-R?3-x?2-x?1-S?T-B?1
because it is not yet known whether this site is also recognized
by the S. cerevisiae enzyme, we have focused on the former
consensus site in this study. Also, it should be pointed out that
previous studies have indicated that PKA phosphorylation can
occur at sequences that differ from both of these potential
consensus sites. Such potential targets would also be missed by
Alkaline Phosphatase-Based Autophagy Assays. Autophagy levels
were measured with an alkaline phosphatase-based assay that
has been described (24, 25). Autophagy was induced by trans-
ferring cells to a medium that lacks a nitrogen source, SD-N, and
alkaline phosphatase levels were assessed after 0 and 15 h at
30°C. SD-N consists of 0.17% yeast nitrogen base lacking amino
acids and ammonium sulfate (Difco) and 2% glucose.
Analysis of Protein Phosphorylation. In general, the in vitro phos-
phorylation assays were performed with GST fusion proteins
that were under the control of the GAL1 promoter in the yeast
strain, Y258 (MATa his4-580 ura3-52 leu2-3,112 pep4-3) (26).
transferred to galactose for 4 h at 30°C. The GST fusion proteins
were then isolated on glutathione-agarose beads (Pierce) and
incubated with 1 ?Ci (1 Ci ? 37 GBq) [?-32P]ATP
(PerkinElmer) and either 0 or 5 units of bovine PKA catalytic
subunit (Sigma) as described (27). A Western immunoblot was
performed with an ?-GST antibody (Cell Signaling Technology,
Beverly, MA) to quantify the relative amount of GST fusion
subcloning PCR fragments encoding Atg1 residues 345–559 into
a plasmid, pPHY1044, that contains two repeats of the Ig-
binding region of PrA from Staphylococcus aureus (28). The
hemagglutinin (HA)-tagged full-length Atg1 and PrA-Atg1 fu-
sion proteins were expressed in the protease-deficient strain,
TVY614 (MAT? his3-?200 leu2-3,112 lys2-801 suc2-?9 trp1-101
ura3-52 prc1?::HIS3 pep4?::LEU2 prb1?::hisG) (29). The site-
directed mutageneses were performed as described (28, 30, 31).
For the in vivo phosphorylation experiments, yeast cells were
labeled with [32P]inorganic orthophosphate (32), and the labeled
PrA-Atg1 was precipitated as described (27). The PKA-minus
strain used for this analysis, NB13-14D (MATa ade8 his3 leu2
trp1 ura3 tpk1::URA3 tpk2::HIS3 tpk3::TRP1 rim15::kanMX2),
has been described (33).
Fluorescence Microscopy. The CFP-Atg11, RFP-Atg11, and YFP-
Atg1 fusions were under the control of the inducible promoter
from the yeast CUP1 gene (34). Expression of these fusion
proteins was induced by the addition of 100 ?M CuSO4for 1 h
at 30°C. For the starvation experiments, the cells were trans-
ferred to SD-N medium containing 100 ?M CuSO4for 1 h at
30°C. The GFP-Atg23 fusion protein has been described (35).
The samples were imaged with an Axioplan 2 Imaging E Mot
microscope (Zeiss) equipped with a ?100 Plan Neofluar objec-
tive (1031-172) and filter sets 31044v2 (CFP), 41017 (Endow
GFP), and 41028 (YFP) (Chroma Technology, Rockingham,
VT) and model C4742-95-12ERG charge-coupled device (CCD)
(Hamamatsu Photonics, Hamamatsu City, Japan). Image pro-
cessing and contrast enhancement were performed with
OPENLAB 3 (Improvision, Lexington, MA) and PHOTOSHOP
(Adobe Systems, San Jose, CA) software.
Assessing the Evolutionary Conservation of the Consensus PKA Sites
in the S. cerevisiae Proteome. The comparative analysis used here
consisted of two major steps. In the first, a pattern match
program was used to identify the S. cerevisiae proteins that
contain a consensus PKA phosphorylation site (see Methods).
For this study, we used the consensus site, R?3-R?2-x?1-S?T-
B?1, that had been defined by previous work with PKA enzymes
from a variety of sources, including yeast and humans (19–22).
A search of the S. cerevisiae proteome found 553 occurrences of
this consensus sequence in 491 proteins (Table 2, which is
published as supporting information on the PNAS web site).
Fifty-one proteins were found to have multiple sites, with 5 sites
being the most present in any one protein.
The second stage of this analysis assessed whether these
consensus PKA sites were conserved in the likely orthologous
proteins present in six different budding yeasts, including five
Saccharomyces species that represent the three major subgroups
of this genus and the pathogenic yeast, C. albicans (Fig. 1A) (17,
36). The Saccharomyces species used in this analysis were the
sensu stricto species S. mikatae, S. kudriavzevii, and S. bayanus,
the sensu lato species S. castellii, and the petite-negative species
S. kluyveri. It is important to point out that recent work has
indicated that PKA activity is regulated, at least in part, by the
to S. cerevisiae in this analysis (37, 38). These observations
therefore suggest that a Ras?PKA signaling pathway is func-
tional in all of the yeasts being used for this study.
As expected, this analysis found that the number of conserved
increased (Fig. 1A). Only 92 of the original 553 sites (?17%)
present in S. cerevisiae were conserved in the other Saccharo-
myces species and C. albicans. The 85 proteins that contain these
strates of PKA in S. cerevisiae. The relative number of S. cerevisiae candidates
of the indicated budding yeast species is shown. The approximate evolution-
tree (36, 49).
An evolutionary proteomics approach identified 85 potential sub-
www.pnas.org?cgi?doi?10.1073?pnas.0501046102Budovskaya et al.
conserved sites are involved in a wide variety of processes
important for cell growth (Table 3, which is published as
supporting information on the PNAS web site). This observation
is consistent with both the highly pleiotropic phenotypes asso-
ciated with mutations affecting the Ras?PKA pathway and with
a model proposing that Ras?PKA signaling activity might be
functioning as part of a general growth checkpoint mechanism
in S. cerevisiae (9, 10). It is important to point out that many of
these 85 proteins are highly conserved among these budding
yeasts, and thus it was unclear whether the observed conserva-
tion of their PKA sites was significant. Therefore, we limited the
subsequent analysis to those candidates that possessed a con-
served PKA site in a region exhibiting ?50% identity between
the S. cerevisiae and C. albicans proteins. This constraint reduced
the number of potential PKA substrates to 44 proteins, or ?1%
of the total proteome (Table 1). Significantly, these candidates
included 5 of the best characterized PKA substrates in the
S. cerevisiae literature (Table 1).
The Candidates Identified by the Evolutionary Proteomics Approach
Were Phosphorylated by PKA in Vitro. The underlying premise in
this analysis was that the more highly conserved PKA consensus
PKA phosphorylation sites. To test this hypothesis, we asked
whether proteins with highly conserved sites were more likely
than other S. cerevisiae proteins to be phosphorylated by PKA in
an in vitro assay. Representative proteins from five different
groups were examined: proteins lacking a PKA consensus site;
proteins with sites only in S. cerevisiae; proteins with sites
conserved among the sensu stricto Saccharomyces species; pro-
teins with sites conserved to the sensu lato and petite-negative
Saccharomyces species; and proteins with sites conserved to
In general, we found that the likelihood of phosphorylation
correlated well with the degree of conservation of the PKA
consensus sites. In particular, all of the candidates tested with
sites conserved to C. albicans (23?23) were phosphorylated by
PKA (Fig. 2 A and E). In contrast, only 20–33% of the proteins
Table 1. The 44 candidate PKA substrates identified by the
evolutionary proteomics approach described here
Biological processGene name
ATG1, ATG13, ATG18, AVT1, MNR2,
MRS6, TOM71, YOL075c
BCY1*, IRA2, IRA1, RIM15*, SYG1,
ACA1, CST6, MSN2*, STP1, STP2
SFP1, WHI3, WHI4
STB2, STB3, STB6
IKS1, PSP1, YBL029w, YBR028c,
YHR032w, YJL046w, YLL029w,
YLR177w, YLR419w, YPL260w
Signal transduction (6)
RNA pol II transcription (5)
Cell size regulation (3)
Chromatin assembly (3)
Cell wall synthesis (2)
Spindle assembly (2)
Bud site selection (1)
Lipid biosynthesis (1)
Protein synthesis (1)
RNA pol III transcription (1)
are indicated with an asterisk. The genes encoding the 23 candidates that
were phosphorylated by PKA in this study are underlined.
were more likely to be phosphorylated by PKA than proteins
with less conserved sites. Shown is a phosphorylation analysis
of representative proteins from the following five groups
identified by the comparative analysis performed here: (i)
(ii) proteins with sites conserved to the sensu lato and petite-
negative Saccharomyces species; (iii) proteins with sites con-
served amongst the sensu stricto Saccharomyces species (B);
with no consensus PKA sites (D). For this analysis, the amount
of label incorporated into a full-length GST fusion protein
27). Note that the labeled protein bands have been appropri-
ately lined up to facilitate comparisons between samples.
Western immunoblots were performed with an ?-GST anti-
body to quantify the relative amount of fusion protein
present. (E) A summary graph indicating the percentage of
candidates in each of the above groups that was phosphory-
lated by PKA.
Proteins with highly conserved consensus PKA sites
Budovskaya et al.PNAS ?
September 27, 2005 ?
vol. 102 ?
no. 39 ?
containing less conserved sites were labeled in this assay (Fig. 2
B and C). Finally, none of the proteins that lacked a consensus
site were efficiently phosphorylated by PKA (Fig. 2D). Thus, the
presence of a highly conserved PKA consensus site was a very
strong predictor of PKA phosphorylation (Fig. 2E). The striking
correlation between the conservation of the PKA site and its
tendency to be phosphorylated suggested that the candidates
with the most highly conserved sites might all be in vivo targets
of PKA. Consistent with this prediction, five of these candidate
proteins, Bcy1, Cki1, Msn2, Rim15, and Yak1, have been
previously shown to be substrates of this kinase (Table 1) (33,
39–42). Finally, it is important to point out that several proteins
with less conserved sites were phosphorylated by PKA in this
study and could also be relevant targets of this enzyme in vivo
(Fig. 2 B–D). The key point here is that the degree of evolu-
likely physiological relevance of a given sequence motif in the
a proof of principle, we tested whether the function of one
particular candidate was indeed regulated by PKA phosphory-
lation in vivo. For this analysis, we chose to examine the
autophagy-related protein kinase, Atg1. Autophagy is a highly
conserved, membrane-trafficking pathway responsible for much
of the protein and membrane turnover in eukaryotic cells (43,
44). Atg1 is a serine?threonine-specific protein kinase that is a
key regulator of the initial induction stage of this degradative
pathway (43, 45). Interestingly, three proteins important for
autophagy, Atg1, Atg13 and Atg18, were all identified in this
study as potential substrates for PKA. These observations sug-
gested that the Ras?PKA pathway was regulating autophagic
activity in yeast cells, and recent work from our lab has con-
firmed this possibility (Fig. 3A) (25).
Atg1 has two conserved sequences, R-R-P-S508-L and R-R-
L-S515-I, that conform to the PKA consensus site discussed
above. Interestingly, we found that the full-length Atg1 was
phosphorylated in vitro by PKA and that this phosphorylation
required the presence of the serine residues in these two
consensus sites (Figs. 3B and 5, which is published as supporting
information on the PNAS web site). The ability of PKA to
phosphorylate an Atg1 fusion protein in vitro was also dependent
upon these same serine residues (Fig. 3C). Finally, the in vivo
phosphorylation of this Atg1 fusion protein also required the
presence of the two PKA consensus sites and PKA activity (Fig.
3D). In mutants lacking all three of the PKA catalytic subunits,
Atg1 was not phosphorylated appreciably at Ser-508 or Ser-515.
In all, these data indicated that Atg1 was likely a bona fide
substrate for PKA in S. cerevisiae.
PKA Phosphorylation Regulates the Association of Atg1 with the
Preautophagosomal Structure (PAS). Two observations indicated
that Atg1 protein kinase activity was not regulated by PKA
phosphorylation. First, the loss of the consensus PKA sites had
no significant effect on Atg1 protein kinase activity in vitro in
assays measuring either autophosphorylation or the phosphor-
ylation of an exogenous substrate (Fig. 6A, which is published as
supporting information on the PNAS web site). Second, the
in vivo level of Atg1 autophosphorylation was not affected by
alterations of the two PKA sites in this protein (Fig. 6B). Thus,
PKA phosphorylation must be affecting some other aspect of
Atg1 function in vivo. Because previous work had indicated that
the subcellular localization of Atg1 is influenced by nutrient
availability, we tested whether PKA might be regulating this
facet of Atg1 behavior.
Atg1 is predominantly cytoplasmic in dividing cells but is
recruited to a specialized site, known as the PAS, upon the
induction of autophagy (34, 46) (Fig. 4A). The PAS is thought to
be the site of autophagosome formation; the autophagosome is
the double-membrane intermediate responsible for transporting
bulk cytoplasm to the vacuole?lysosome during autophagy (34,
43, 46). We therefore tested whether PKA phosphorylation
might control the association of Atg1 with the PAS. In support
of this possibility, we found that an Atg1 variant lacking both
PKA sites, Atg1-AA, was constitutively localized to the PAS
(Fig. 4A). In addition, the introduction of a constitutively active
allele of RAS2, known as RAS2val19, blocked Atg1 localization to
the PAS in a manner that depended upon the two PKA sites in
Atg1 (Fig. 4A). In the RAS2val19mutant, wild-type Atg1 was not
found at the PAS in either growing or starved cells. PKA
phosphorylation therefore seems to control the recruitment of
Atg1 to the PAS during nutrient limitation, conditions that
normally induce the autophagy pathway.
The data here suggest that, when nutrients are plentiful,
Ras?PKA signaling levels are high and Atg1 is phosphorylated
and largely cytoplasmic. Upon nutrient deprivation, Atg1 would
become dephosphorylated and associate with the PAS. This
model is consistent with previous work indicating that PKA
activity decreases upon nutrient limitation (47). We tested the
basic tenet of this model by examining the in vivo phosphory-
lation of an Atg1 fusion protein in dividing and starved cells. The
phosphorylation of this fusion is completely dependent upon the
presence of the PKA consensus sites and PKA activity (see
levels were assessed with an alkaline phosphatase-based assay that has been
described (24). The values shown represent the difference between the alka-
line phosphatase levels found in starved and nonstarved cultures of the
indicated yeast strains. HC-TPK1, high-copy plasmid encoding a catalytic sub-
serine residues within the two consensus PKA sites. The residues at positions
508 and 515 within the two PKA sites are indicated: S, serine; A, alanine. Note
that this experiment was performed with a kinase-inactive variant of Atg1,
Atg1-K54A, to avoid the background autophosphorylation signal. (Lower) A
Western immunoblot control indicating the relative levels of Atg1 present in
of an Atg1 fusion protein depended upon both PKA activity and the two PKA
sites in Atg1. This fusion protein contained two repeats of the Ig-binding
region of protein A fused in frame to residues 345–559 of Atg1 (28). In both
cases, the Upper panel is the phosphorylation assay and the Lower is the
incubated with [32P]orthophosphate, and the amount of label incorporated
strain lacks all three catalytic subunits of the S. cerevisiae PKA enzyme (33).
www.pnas.org?cgi?doi?10.1073?pnas.0501046102Budovskaya et al.
above). Consistent with the model, we found that the relative
level of Atg1 phosphorylation decreased by ?10-fold after a
period of nitrogen starvation (Fig. 4B).
We also tested whether the presence of the RAS2val19allele
had any effect on the subcellular localization of Atg23. Atg23 is
a peripheral membrane protein that has been shown to cycle
between the PAS and unknown structures in the cytoplasm in an
Atg1-dependent manner (35). In wild-type cells, an Atg23-GFP
fusion is found associated with a number of punctate foci in cells,
some that correspond to the PAS and others that do not (48)
(Fig. 4C). In contrast, in atg1 mutants, Atg23 is found at the PAS
only and not with the other punctate structures seen in wild-type
cells (35). These results have been interpreted as evidence that
Atg1 is required for the recycling of Atg23 from the PAS.
Consistent with a role for the Ras?PKA pathway in the regula-
tion of this Atg1 activity, we found that Atg23 was also restricted
to the PAS in RAS2val19mutants (Fig. 4C). Because Atg1 (and
its regulatory partner, Atg13) is the only Atg protein known to
be required for the proper recycling of Atg23, these data
reinforced the above phosphorylation analysis and suggested
that the Ras?PKA pathway was regulating Atg1 activity in
S. cerevisiae cells.
This report makes use of a sequence-based, comparative method
for finding functionally relevant sequences within a eukaryotic
proteome. In this approach, the evolutionary conservation of all
occurrences of a given sequence motif is systematically assessed
within a group of related organisms. The underlying premise is
a higher degree of sequence conservation. The general utility of
this approach was assessed here with an attempt to identify
candidate substrates for the protein kinase, PKA, in S. cerevisiae.
In this study, the conservation of consensus PKA target sites was
assessed within a group of budding yeast species that are
separated by up to 800 million years of evolutionary distance
(49). This analysis identified 44 proteins as potential substrates
of PKA, and, remarkably, we found that all of the candidates
tested were phosphorylated by this enzyme in an in vitro assay.
Moreover, our data indicated that the degree of sequence
conservation was a very strong predictor of the likelihood of
PKA phosphorylation. The more highly conserved the PKA site,
the more likely it was to be phosphorylated by PKA. In all, the
data suggested that this evolutionary proteomics approach had
successfully identified a number of novel substrates of the
S. cerevisiae PKA.
Similar types of comparative approaches have been used
extensively to identify functional motifs in individual proteins.
However, this study emphasizes how this strategy can be sys-
examining a short sequence motif that was relatively low in
information content. Nonetheless, we were able to successfully
identify proteins that had been previously shown to be targets of
PKA and many additional candidate substrates. In theory, this
approach should be applicable to any type of sequence element
in any protein. In fact, structure-function studies of proteins
often identify similarly short, but biologically interesting, se-
quence domains. This study demonstrates how the biological
relevance of these elements can be assessed. The only prereq-
uisite is that there must be sequence information available for an
appropriate group of evolutionarily related organisms.
The power of these comparative approaches is illustrated by the
fact that more potential PKA substrates were identified here than
had been found in the past two decades by other means. Although
further work is obviously needed to show that these proteins are
indeed regulated by PKA phosphorylation, this candidate pool
already contains five previously identified substrates of PKA. The
related kinase, Atg1, is both phosphorylated and regulated by PKA
have already been linked to the Ras?PKA signaling pathway. For
example, a recent study has suggested that Ras?PKA pathway
regulates the activity of Ifh1 and Sfp1, two key regulators of
ribosome synthesis and cell size in S. cerevisiae (50, 51). Finally, it
is important to point out that the proteins identified here are
equally likely to be substrates for PKA in the pathogenic yeast,
work indicating that PKA activity is important for virulence in this
yeast (37, 38).
This study identified three proteins important for autophagy,
Atg1, Atg13 and Atg18, as potential substrates for PKA. These
observations led us to investigate the role of the Ras?PKA
signaling pathway in the control of this degradative process. Our
work indicates that Ras?PKA activity inhibits an early step in
autophagy, a step that precedes the formation of the autopha-
gosome (25). Interestingly, all three of these Atg proteins seem
to act at this stage of the autophagy process (43, 52, 53). In this
study, we found that the PKA phosphorylation of Atg1 regulates
the localization of this protein in accordance with nutrient
availability and ensures that Atg1 is associated with the PAS only
preautophagosomal structure, or PAS. (A) A fluorescence microscopy analysis
or starved cultures of the indicated strains. The location of the PAS is shown
by a CFP-Atg11 reporter construct (34). (B) The level of Atg1 phosphorylation
decreased upon nitrogen starvation. Wild-type cells containing either a con-
trol vector (Vector) or a plasmid encoding a Protein A-Atg1 fusion protein
(pATG1) were incubated with [32P]orthophosphate either before (Log) or
after (Starved) a 2-h incubation in a medium lacking nitrogen. The amount of
radiolabel incorporated into Atg1 was assessed by autoradiography. (Lower)
The Western immunoblot control. (C) The presence of the RAS2val19allele
resulted in the redistribution of a GFP-Atg23 fusion protein from a number of
punctate structures within the cell to the PAS. The identity of these punctate
structures is not yet known. The location of the PAS is indicated by an
RFP-Atg11 fusion protein.
PKA phosphorylation regulates the association of Atg1 with the
Budovskaya et al.PNAS ?
September 27, 2005 ?
vol. 102 ?
no. 39 ?
under conditions that result in the induction of autophagy.
Because most Atg proteins are present constitutively at the PAS,
we feel that this PKA phosphorylation is likely indirectly influ-
encing Atg1 protein kinase activity by regulating its ability to
associate with its most likely substrates in the cell. Finally, it is
important to point out that Atg1 does not seem to be the only
PKA target important for the control of autophagy. This asser-
tion follows from our observation that the hyperactive RAS2val19
allele still inhibits autophagy in mutants carrying the Atg1-AA
variant (our unpublished observations). It will be important to
test whether Atg13 and?or Atg18 might be these other relevant
targets of PKA phosphorylation in vivo.
In summary, this report describes a systematic, sequence-
based approach that uses a basic tenet of the theory of natural
selection to identify the functionally relevant occurrences of a
given sequence element in a eukaryotic proteome. The success
we had identifying potential substrates of the S. cerevisiae PKA
illustrates the potential inherent in this general strategy. In
addition to identifying autophagy as an important target of the
Ras?PKA pathway, the other substrates identified here are likely
to provide fundamental insights into the manner in which this
signaling pathway controls the growth of these budding yeasts.
phosphorylated by PKA and those that are not could identify
additional sequence elements that are important for PKA sub-
We thank Russell Hill for the use of his fluorescence microscope and his
assistance with the imaging software; Daniel Klionsky (University of
Michigan, Ann Arbor), Yoshinori Ohsumi (National Institute for Basic
Biology, Okazaki, Japan), Steven Osmani (Ohio State University), and
Jonathan Warner (Albert Einstein College of Medicine, Bronx, NY) for
plasmids and strains; Michael Snyder (Yale University, New Haven, CT)
for the yeast GST-ORF fusion library; and Susie Howard for comments
on the manuscript. This work was supported by National Institutes of
Health Grant GM65227 (to P.K.H.).
1. Cohen, P. (2002) Nat. Rev. Drug Discov. 1, 309–315.
2. Hunter, T. (2000) Cell 100, 113–127.
3. Hunter, T. (1987) Cell 50, 823–829.
4. Manning, G., Whyte, D. B., Martinez, R., Hunter, T. & Sudarsanam, S. (2002)
Science 298, 1912–1934.
5. Manning, B. D. & Cantley, L. C. (2002) Sci. STKE 162, 1–4.
6. Taylor, S. S., Yang, J., Wu, J., Haste, N. M., Radzio-Andzelm, E. & Anand, G.
(2004) Biochim. Biophys. Acta 1697, 259–269.
7. Taylor, S. S., Buechler, J. A. & Yonemoto, W. (1990) Annu. Rev. Biochem. 59,
8. Broach, J. R. (1991) Trends Genet. 7, 28–33.
9. Herman, P. K. (2002) Curr. Opin. Microbiol. 5, 602–607.
10. Thevelein, J. M. & de Winde, J. H. (1999) Mol. Microbiol. 33, 904–918.
11. Suzuki, N., Choe, H. R., Nishida, Y., Yamawaki-Kataoka, Y., Ohnishi, S.,
Tamaoki, T. & Kataoka, T. (1990) Proc. Natl. Acad. Sci. USA 87, 8711–8715.
12. Field, J., Xu, H. P., Michaeli, T., Ballester, R., Sass, P., Wigler, M. & Colicelli,
J. (1990) Science 247, 464–467.
13. Toda, T., Cameron, S., Sass, P., Zoller, M. & Wigler, M. (1987) Cell 50,
14. Cliften, P. F., Hillier, L. W., Fulton, L., Graves, T., Miner, T., Gish, W. R.,
Waterston, R. H. & Johnston, M. (2001) Genome Res. 11, 1175–1186.
15. Tagle, D. A., Koop, B. F., Goodman, M., Slightom, J. L., Hess, D. L. & Jones,
R. T. (1988) J. Mol. Biol. 203, 439–455.
16. Hardison, R. C., Oeltjen, J. & Miller, W. (1997) Genome Res. 7, 959–966.
17. Cliften, P., Sudarsanam, P., Desikan, A., Fulton, L., Fulton, B., Majors, J.,
Waterston, R., Cohen, B. A. & Johnston, M. (2003) Science 301, 71–76.
18. Rubin, G. M., Yandell, M. D., Wortman, J. R., Gabor Miklos, G. L., Nelson,
C. R., Hariharan, I. K., Fortini, M. E., Li, P. W., Apweiler, R., Fleischmann,
W., et al. (2000) Science 287, 2204–2215.
19. Denis, C. L., Kemp, B. E. & Zoller, M. J. (1991) J. Biol. Chem. 266,
20. Songyang, Z., Blechner, S., Hoagland, N., Hoekstra, M. F., Piwnica-Worms, H.
& Cantley, L. C. (1994) Curr. Biol. 4, 973–982.
21. Tegge, W., Frank, R., Hofmann, F. & Dostmann, W. R. (1995) Biochemistry 34,
22. Shabb, J. B. (2001) Chem. Rev. 101, 2381–2411.
23. Smith, C. M., Radzio-Andzelm, E., Madhusudan, Akamine, P. & Taylor, S. S.
(1999) Prog. Biophys. Mol. Biol. 71, 313–341.
24. Noda, T., Matsuura, A., Wada, Y. & Ohsumi, Y. (1995) Biochem. Biophys. Res.
Commun. 210, 126–132.
25. Budovskaya, Y. V., Stephan, J. S., Reggiori, F., Klionsky, D. J. & Herman, P. K.
(2004) J. Biol. Chem. 279, 20663–20671.
26. Zhu, H., Bilgin, M., Bangham, R., Hall, D., Casamayor, A., Bertone, P., Lan,
N., Jansen, R., Bidlingmaier, S., Houfek, T., et al. (2001) Science 293,
27. Chang, Y. W., Howard, S. C. & Herman, P. K. (2004) Mol. Cell 15, 107–116.
28. Budovskaya, Y. V., Hama, H., DeWald, D. B. & Herman, P. K. (2002) J. Biol.
Chem. 277, 287–294.
Chem. 273, 15818–15829.
J. A. & Struhl, K. (1995) Current Protocols in Molecular Biology (Wiley, New
31. Kunkel, T. A. (1985) Proc. Natl. Acad. Sci. USA 82, 488–492.
32. Herman, P. K., Stack, J. H. & Emr, S. D. (1991) EMBO J. 10, 4049–4060.
33. Reinders, A., Burckert, N., Boller, T., Wiemken, A. & De Virgilio, C. (1998)
Genes Dev. 12, 2943–2955.
34. Kim, J., Huang, W. P., Stromhaug, P. E. & Klionsky, D. J. (2002) J. Biol. Chem.
35. Reggiori, F., Tucker, K. A., Stromhaug, P. E. & Klionsky, D. J. (2004) Dev. Cell
36. Barnett, J. A. (1992) Yeast 8, 1–23.
37. Rocha, C. R., Schroppel, K., Harcus, D., Marcil, A., Dignard, D., Taylor, B. N.,
Thomas, D. Y., Whiteway, M. & Leberer, E. (2001) Mol. Biol. Cell 12,
38. Leberer, E., Harcus, D., Dignard, D., Johnson, L., Ushinsky, S., Thomas, D. Y.
& Schroppel, K. (2001) Mol. Microbiol. 42, 673–687.
39. Kuret, J., Johnson, K. E., Nicolette, C. & Zoller, M. J. (1988) J. Biol. Chem. 263,
40. Kim, K. H. & Carman, G. M. (1999) J. Biol. Chem. 274, 9531–9538.
41. Gorner, W., Durchschlag, E., Wolf, J., Brown, E. L., Ammerer, G., Ruis, H. &
Schuller, C. (2002) EMBO J. 21, 135–144.
42. Garrett, S., Menold, M. M. & Broach, J. R. (1991) Mol. Cell. Biol. 11,
43. Noda, T., Suzuki, K. & Ohsumi, Y. (2002) Trends Cell Biol. 12, 231–235.
44. Reggiori, F. & Klionsky, D. J. (2002) Eukaryot. Cell 1, 11–21.
45. Matsuura, A., Tsukada, M., Wada, Y. & Ohsumi, Y. (1997) Gene 192, 245–250.
46. Suzuki, K., Kirisako, T., Kamada, Y., Mizushima, N., Noda, T. & Ohsumi, Y.
(2001) EMBO J. 20, 5971–5981.
47. Russell, M., Bradshaw-Rouse, J., Markwardt, D. & Heideman, W. (1993) Mol.
Biol. Cell 4, 757–765.
48. Tucker, K. A., Reggiori, F., Dunn, W. A., Jr. & Klionsky, D. J. (2003) J. Biol.
Chem. 278, 48445–48452.
49. Heckman, D. S., Geiser, D. M., Eidell, B. R., Stauffer, R. L., Kardos, N. L. &
Hedges, S. B. (2001) Science 293, 1129–1133.
50. Jorgensen, P., Rupes, I., Sharom, J. R., Schneper, L., Broach, J. R. & Tyers, M.
(2004) Genes Dev. 18, 2491–2505.
51. Martin, D. E., Soulard, A. & Hall, M. N. (2004) Cell 119, 969–979.
52. Tsukada, M. & Ohsumi, Y. (1993) FEBS Lett. 333, 169–174.
53. Guan, J., Stromhaug, P. E., George, M. D., Habibzadegah-Tari, P., Bevan, A.,
Dunn, W. A., Jr. & Klionsky, D. J. (2001) Mol. Biol. Cell 12, 3821–3838.
www.pnas.org?cgi?doi?10.1073?pnas.0501046102 Budovskaya et al.