Cell Metabolism

Review

The Dawn of the Age of Amino AcidSensors for the mTORC1 Pathway

Rachel L. Wolfson1,2,3,4,5 and David M. Sabatini1,2,3,4,5,6,*1Whitehead Institute for Biomedical Research, 455 Main Street, Cambridge, MA 02142, USA2Department of Biology, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA3Howard Hughes Medical Institute, Department of Biology, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge,MA 02139, USA4Koch Institute for Integrative Cancer Research at MIT, 77 Massachusetts Avenue, Cambridge, MA 02139, USA5Broad Institute, 415 Main Street, Cambridge, MA 02142, USA6Lead Contact*Correspondence: sabatini@wi.mit.eduhttp://dx.doi.org/10.1016/j.cmet.2017.07.001

The mechanistic target of rapamycin complex 1 (mTORC1) is a master regulator of cell growth that respondsto a diverse set of environmental inputs, including amino acids. Over the past 10 years, a number of proteinshave been identified that help transmit amino acid availability to mTORC1. However, amino acid sensors forthis pathway have only recently been discovered. Here, we review these recent advances and highlight thevariety of unexplored questions that emerge from the identification of these sensors.

IntroductionThe mechanistic target of rapamycin complex 1 (mTORC1) is a

protein kinase that acts as a central controller of cell growth.

mTORC1 was originally identified as the target of rapamycin, a

macrolide antibiotic discovered in the soil on Easter Island

(Abraham and Wiederrecht, 1996). Rapamycin is a potent anti-

proliferative agent (Eng et al., 1984) due to its inhibition of

mTORC1 and is currently used in the clinic in a number of con-

texts, including blocking organ transplant rejection and as a can-

cer therapy (Chan, 2004; Groth et al., 1999).

mTORC1 acts as a regulator of cell growth through the phos-

phorylation of substrates that potentiate anabolic processes

and inhibit catabolic ones, such as mRNA translation and auto-

phagy, respectively. A variety of environmental signals impinge

on mTORC1 to control its activity, including growth factors,

cellular stresses, and energy and amino acid levels (Saxton and

Sabatini, 2017). The Rheb and Rag GTPases reside on the lyso-

somal surface and coordinate mTORC1 activity in response to

environmental conditions (Buerger et al., 2006; Kim et al., 2008;

Saito et al., 2005; Sancak et al., 2008). Many of these inputs,

including growth factors, cellular stresses, and energy levels,

impinge on the TSC complex, comprised of TSC1, TSC2, and

TBC1D7, which is a GTPase-activating protein (GAP) for Rheb

(Dibble et al., 2012; Inoki et al., 2003a;Manning et al., 2002; Potter

et al., 2002). Growth factors regulate the TSC complex by control-

ling its localization to the lysosomal surface (Menon et al., 2014).

Multiple other regulators, such as hypoxia and energy stress,

impact the mTORC1 signaling pathway upstream of the TSC

complex (Brugarolas et al., 2004; Inoki et al., 2003b), although

whether this is by affecting its localization is unclear. Thus, in

the presence of growth factors and the absence of stresses,

Rheb isGTP loadedand, in this state, can act as a kinase activator

of mTORC1, but only if mTORC1 is on the lysosomal surface.

The Rag GTPases control mTORC1 localization to the lyso-

somal surface in response to nutrient levels, specifically amino

acids and glucose (Efeyan et al., 2013; Sancak et al., 2008). The

Rag GTPases consist of a constitutive heterodimer of RagA or

RagB bound to RagC or RagD (Hirose et al., 1998; Sch€urmann

et al., 1995; Sekiguchi et al., 2001). In the presence of nutrients,

RagA/B is GTP loaded and RagC/D is GDP loaded. This active

conformation of the Rag GTPases promotes the translocation

ofmTORC1 to the lysosomal surface, where it can come into con-

tact with its kinase activator, Rheb (Buerger et al., 2006; Saito

et al., 2005; Sancak et al., 2008). In this way, the Rag and Rheb

GTPases comprise a ‘‘coincidence detector,’’ such that mTORC1

is active only in the presence of both growth factors and nutrients.

Since the discovery of the Rag GTPases as components of the

mTORC1 pathway, a number of other proteins have been identi-

fied as playing a role in nutrient sensing upstream of mTORC1.

Ragulator, a pentameric complex composed of p18, p14,

HBXIP, C7orf59, and MP1, controls the lysosomal localization

and nucleotide loading state of the Rag GTPases (Bar-Peled

et al., 2012; Sancak et al., 2010). Ragulator interacts with the

vacuolar H+-adenosine triphosphatase ATPase (v-ATPase),

which acts as a positive regulator of the pathway through an un-

known mechanism (Zoncu et al., 2011). Folliculin and its binding

partners, FNIP1/2, haveGAP activity toward RagC/D (Tsun et al.,

2013), while GATOR1 (GAP activity toward the RagGTPases 1) is

a GAP for RagA/B (Bar-Peled et al., 2013). GATOR1 is a trimeric

complex composed of DEPDC5, Nprl2, and Nprl3 that interacts

with GATOR2, a pentameric complex of unknown function (Bar-

Peled et al., 2013). More recently, the KICSTOR complex (which

stands for KPTN, ITFG2, C12orf66, and SZT2-containing regu-

lator of mTORC1) was identified as a scaffold for GATOR1 on

the lysosomal surface (Wolfson et al., 2017; Peng et al., 2017)

(Figure 1). Until recently, most members of the nutrient sensing

pathway that had been characterized function to directly

modulate the nucleotide loading state of the Rag GTPases or

localization of other components of the pathway; the amino

acid sensors, however, remained elusive.

SLC38A9The fact that this important growth regulatory pathway centers

on the surface of the lysosome led to the prediction that

Cell Metabolism 26, August 1, 2017 ª 2017 Elsevier Inc. 301

KICSTOR

lysosome

GATOR2Sestrin2

leucine

arginine

mTORC1

Rheb

CASTOR1

GTP

GTP

SLC38A9

RagC

Ragu-latorV-ATPase

GATOR1

GDP

RagA

aminoacids arginine

FLCNFNIP1/2

TSCcomplex

Figure 1. The Amino Acid Sensing Pathway Upstream of mTORC1Schematic detailing the key molecular players in the nutrient sensing branchupstream of mTORC1.

Cell Metabolism

Review

nutrients, specifically amino acids, within the lysosome could

activate the pathway (Zoncu et al., 2011). The vacuole, an acidic

organelle that is the yeast equivalent of the lysosome, is consid-

ered a storage site for metabolites, including basic and neutral

amino acids (Li and Kane, 2009). Mammalian lysosomes, while

distinct from vacuoles, have amino acid transporters on their sur-

face and are involved in protein degradation, particularly as part

of the process of autophagy, and thus may also function as a

storage site for amino acids. Indeed, isolated lysosomes can

be loaded with amino acids and this is sufficient for recruitment

of mTORC1 in vitro, indicating that the mTORC1 pathway can

respond to intra-lysosomal amino acid levels (Zoncu et al.,

2011). Further evidence for this model of intra-lysosomal amino

acid sensing came with the identification of SLC38A9, a lyso-

somal transmembrane protein with homology to amino acid

transporters, as a positive regulator of the mTORC1 pathway

(Jung et al., 2015; Rebsamen et al., 2015; Wang et al., 2015).

SLC38A9 was identified through immunoprecipitation fol-

lowed by mass spectrometry (IP/MS) analyses of the Rag

GTPases and Ragulator. Unlike other proteins in the SLC38 fam-

ily of transporters, SLC38A9 is unique in that it has a 119 amino

acid extension at its N terminus, through which it binds Ragula-

tor. Surprisingly, overexpression of full-length SLC38A9 or sim-

ply this 119 amino acid N-terminal extension is sufficient to

render cells insensitive to amino acid deprivation, establishing

SLC38A9 as a positive regulator of the pathway. Cells lacking

SLC38A9 have a defect in mTORC1 activation in response to

amino acids, particularly arginine. In vitro amino acid transport

assays established that SLC38A9 has very low-affinity transport

activity for arginine (Wang et al., 2015). Its low affinity may reflect

that for technical reasons the transport assays measure influx by

SLC38A9, and that the affinity for arginine efflux, which has not

been measured, could be higher, perhaps better correlating

with intracellular arginine levels. Additionally, SLC38A9 may

transport amino acids other than arginine with higher affinity,

but extensive evaluation of its substrate preference has not yet

302 Cell Metabolism 26, August 1, 2017

been performed. Further, reliable methods for detecting amino

acid levels within subcellular compartments, such as the lyso-

some, do not exist, and thus how its affinity correlates with

intra-lysosomal levels of amino acids is unknown.

The identification of a likely arginine transporter as a positive

regulator of the mTORC1 pathway established SLC38A9 as a

putative arginine sensor—and the first likely amino acid sensor

for the pathway. However, for SLC38A9 to be validated as a

bona fide amino acid sensor, it will be necessary to connect its

arginine-binding capacity to arginine sensing by the mTORC1

pathway. While this has not yet been accomplished for

SLC38A9, bona fide amino acid sensors for relaying the levels

of cytosolic amino acids to mTORC1 have been discovered.

The SestrinsThe first validated amino acid sensor for the pathway came with

the discovery of Sestrin1 and Sestrin2 as leucine sensors. Ses-

trin1 and 2 were originally identified as proteins that are induced

under various stress conditions and named PA26 (p53-regulated

protein 26) and Hi95 (hypoxia-induced gene 95), respectively

(Buckbinder et al., 1994; Budanov et al., 2002; Peeters et al.,

2003). At first, the only hint as to their function was their weak ho-

mology to a bacterial alkyl-hydroperoxide reductase, AhpD (Bu-

danov et al., 2004). Early studies found that Sestrin2 retained

some antioxidant capacity (Budanov et al., 2004), but this has

been largely refuted, both based on additional antioxidant

studies as well as on the location of the putative key residues

for this activity in its crystal structure (Saxton et al., 2016c;

Woo et al., 2009; Kim et al., 2015). However, Sestrin2 does retain

structural homology to this class of bacterial enzymes (Saxton

et al., 2016c; Kim et al., 2015).

The Sestrins are a group of three homologs (Sestrin1–3) that

have long been recognized to be negative regulators of the

mTORC1 pathway (Budanov and Karin, 2008). Early reports

argue that the Sestrins inhibit the mTORC1 pathway upstream

of TSC and AMPK (Budanov and Karin, 2008), members of the

growth factor sensing branch upstream of mTOR, but recent re-

sults are not compatible with this mechanism (Chantranupong

et al., 2014; Peng et al., 2014). Instead, it has become clear

that the Sestrins negatively regulate mTORC1 upstream of

GATOR2, a positive regulator of the nutrient sensing branch of

the pathway (Chantranupong et al., 2014; Parmigiani et al.,

2014). Under leucine, but not arginine, deprivation conditions,

Sestrin2 binds to GATOR2 and likely inhibits it, although the mo-

lecular function of GATOR2 remains unknown (Wolfson et al.,

2016). Leucine stimulation causes Sestrin2 to dissociate from

GATOR2, likely relieving its inhibition of this positive regulator

(Wolfson et al., 2016). A variety of evidence exists indicating

that Sestrin2 is a leucine sensor for the mTORC1 pathway. First,

Sestrin2 binds leucine with an affinity of �20 mM, which corre-

lates with leucine concentrations in the media that are sensed

by the pathway (Wolfson et al., 2016). Sestrin2 purified from bac-

teria binds leucine both in an in vitro amino acid-binding assay

(Wolfson et al., 2016) and when crystalized in the presence of

leucine, which identified residues important for the leucine-bind-

ing capacity of the protein (Saxton et al., 2016c). Finally, mutants

of Sestrin2 that no longer bind leucine or have reduced leucine-

binding capacity render cells unable to sense the presence of

leucine or alter the concentration of leucine sensed by the

Sestrin2 levels

At constant [leucine] and constant [GATOR2]

At constant [GATOR2]

Leucine levels

no Sestrin2 expression

lowSestrin2

medium Sestrin2 high Sestrin2

very high Sestrin2

leucine

leucine

lysosome

long-term amino acidstarvation

nucleus cytoplasm

Sestrin2 expression

ATF4

Sestrin2

mTORC1 signaling

Sestrin2 leu

GATOR2Sestrin2 GATOR2

mTORC1 signaling

mTO

RC

1 ac

tivi

ty

mTO

RC

1 ac

tivi

ty

A

B C

Figure 2. Bimodal Regulation of Sestrin2(A) Sestrin2 is a leucine sensor and inhibitor ofmTORC1 signaling in response to stresses.Sestrin2, leucine, and GATOR2 exist in equilibriumin the cell that dictates mTORC1 activity inresponse to both leucine levels and other stresses.Increasing leucine levels pushes the Sestrin2-leucine equilibrium forward such that moreGATOR2 is free, leading to increased mTORC1signaling. Increasing levels of Sestrin2, down-stream of ATF4 in response to cellular stresses,pushes the Sestrin2-GATOR2 equilibrium forward,inhibiting mTORC1 signaling.(B) Schematic depicting mTORC1 activity inresponse to increasing Sestrin2 levels, at constantlevels of GATOR2 and leucine.(C) Diagram showing how modulating leucinelevels will impact mTORC1 activity at varyingcellular levels of Sestrin2.

Cell Metabolism

Review

mTORC1 pathway, establishing Sestrin2 (and by analogy Ses-

trin1) as leucine sensors for the mTORC1 pathway (Saxton

et al., 2016c; Wolfson et al., 2016).

It has long been appreciated that Sestrin2 levels increase in

response to various stresses (Buckbinder et al., 1994), and

recent evidence indicates that the ATF4 transcription factor,

which is activated by long-term amino acid deprivation, can con-

trol Sestrin2 expression (Ye et al., 2015). These data lead to the

model that Sestrin2 likely has a bimodal regulation. Sestrin2,

leucine, and GATOR2 exist in an equilibrium such that in the

absence of any cellular stresses, and the presence of leucine,

Sestrin2 binds leucine (and not GATOR2), thus allowing the

mTORC1 pathway to be active (Figure 2A). This equilibrium

can be pushed by one of two levers: the concentration of leucine

or that of Sestrin2. With short-term leucine deprivation, Sestrin2

levels are unchanged, favoring free Sestrin2 binding to GATOR2

and inhibiting the pathway. Under conditions of cellular stress,

including long-term amino acid deprivation or DNA damage,

Sestrin2 levels increase, pushing both equilibriums forward,

such that the amount of Sestrin2 bound to leucine increases (if

leucine is available) and the level of Sestrin2 bound to GATOR2

increases, inhibiting the mTORC1 pathway even in the presence

of leucine. In this manner, the mTORC1

pathway is sensitive to both leucine and

Sestrin2 levels.

For example, at constant leucine and

GATOR2 levels, an increase in Sestrin2

expression will inhibit mTORC1 signaling.

At lower levels of Sestrin2 this inhibition

will be weak, as there is plenty of leucine

to bind to Sestrin2 and prevent its interac-

tion with GATOR2 (Figure 2B). However,

upon higher expression of Sestrin2, the

cellular levels of leucine will not saturate

Sestrin2, given the relatively low affinity

of Sestrin2 for leucine, and more Sestrin2

will bind to GATOR2, until the positive

regulator becomes saturated and the

pathway is fully inhibited, regardless of

leucine concentrations (Figure 2B). In a

similar manner, one can assess how

changing the levels of both Sestrin2 and leucine will modulate

mTORC1 activity. For example, in the absence of Sestrin2 (and

its homologs Sestrin1 and 3) mTORC1 activity will be completely

insensitive to leucine concentrations (Figure 2C). At low Sestrin2

levels, themTORC1 pathway will be responsive to leucine fluctu-

ations, such that under leucine deprivation the pathway is in-

hibited and increasing leucine levels increases pathway activity.

With higher Sestrin2 expression, more leucine is needed for the

same degree of mTORC1 activity, as additional leucine is

needed to compete the increased amount of Sestrin2 off of

GATOR2. Finally, extremely high levels of Sestrin2 will render

the pathway constitutively inhibited, regardless of leucine con-

centrations (Figure 2C). In this manner, Sestrin2 can act as a

leucine sensor at basal conditions and as an inhibitor of

mTORC1 in response to a variety of stresses that increase its

expression.

One major unsolved question in the Sestrin field revolves

around how the Sestrins inhibit GATOR2. The solution awaits

the understanding of the molecular function of GATOR2, but

some insight into this problem could come from identifying struc-

tural differences between Sestrin2 that is leucine bound, free,

and GATOR2 bound. At this point, however, only the structure

Cell Metabolism 26, August 1, 2017 303

Table 1. Affinities of Nutrient Sensors for Their Amino Acid Substrates and Corresponding Plasma Concentrations of Those

Amino Acids

AA

AA Binding

Protein Kd (mM)

Plasma

Concentration (mM)

Interstitial

Concentration

Free Cytosolic

Concentration

Fed Fasted Fed Fasted Fed Fasted

Leu Sestrin1 10–15 287 129 ? ? ? ?

Sestrin2 20 287 129 ? ? ? ?

Sestrin3 N/A 287 129 ? ? ? ?

LRS 45 287 129 ? ? ? ?

dSestrin 100 ? (mm range for

other AAs)

? ? ? ?

Arg CASTOR1 30 161 97 ? ? ? ?

CASTOR2 N/A 161 97 ? ? ? ?

Data from Stegink et al. (1991); Stein and Moore (1954); Piyankarage et al. (2008).

Cell Metabolism

Review

of leucine-bound Sestrin2 has been solved (Saxton et al., 2016c).

Although claims have been made that apo-Sestrin2 was crystal-

lized (Kim et al., 2015; Lee et al., 2016), further analyses revealed

that those crystals also contained leucine (Saxton et al., 2016b),

and thus understanding the exact conformational change that

Sestrin2 undergoes upon binding to leucine or GATOR2, and

how this could impact its activity, awaits further investigation.

Thermal shift assays revealed that leucine shifts themelting tem-

perature of Sestrin2 by up to 8.5�C (Wolfson et al., 2016), indi-

cating that even though the structure of apo-Sestrin2 remains

elusive, a conformational change in Sestrin2 most likely occurs

on leucine binding.

CASTOR1Following the discovery of Sestrin1/2 as cytosolic leucine sen-

sors that bind toGATOR2, a protein-protein interaction database

generated using IP/MS analyses from 2,594 proteins stably ex-

pressed in HEK293T cells revealed the proteins encoded by

the GATSL3 and GATSL2 (GATS protein-like 3/2) genes as puta-

tive GATOR2 interactors (Chantranupong et al., 2016). The pro-

teins were renamed CASTOR1/2 (for cellular arginine sensor for

mTORC1) after their identification as cytosolic arginine sensors

for the pathway, through a mechanism analogous to that of

the Sestrins. The CASTOR proteins, specifically either a homo-

dimer of CASTOR1 or heterodimer of CASTOR1 and 2, bind to

GATOR2 only under arginine deprivation conditions, thereby

likely inhibiting it. Both an in vitro binding assay and crystal struc-

ture found that these proteins directly bind arginine, and do so

with an affinity of �30 mM, which correlates with concentrations

of arginine in the media that lead to half-maximal mTORC1

signaling (Chantranupong et al., 2016; Saxton et al., 2016a).

Finally, CASTOR1 mutants that are unable to bind arginine

render the mTORC1 pathway insensitive to arginine stimulation

when added back to cells.

CASTOR1 contains four tandem ACT (aspartate kinase, cho-

rismate mutase, and TyrA) domains, which are evolutionarily

ancient domains associated with binding a diverse set of small

molecules, and shares structural homology to the regulatory

domain of bacterial aspartate kinases (Saxton et al., 2016a).

Specifically, the arginine-binding pocket has striking structural

similarities to the lysine-binding pocket of an aspartate kinase

in Escherichia coli (AKeco). While aspartate kinases are well

304 Cell Metabolism 26, August 1, 2017

conserved throughout bacterial and fungal species, they

were lost before the emergence of metazoa, in which CASTOR1

homologs are almost exclusively expressed (Saxton et al.,

2016a). Thus, the mTORC1 pathway may have adapted this

ancient lysine-sensitive regulatory mechanism for the evolution

of arginine sensing in metazoa.

Intracellular Amino Acid LevelsThe discovery of the elusive leucine and arginine sensors for the

mTORC1 pathway represents an exciting advance in the field.

How the affinities of these sensors for their respective amino

acids correlate with concentrations of those amino acids in cells

or in vivo, however, is not entirely clear. Sestrin1 and 2, for

example, bind leucine with affinities of �15–20 mM (Wolfson

et al., 2016), which is similar to that of another cytosolic

leucine-binding protein, leucyl tRNA-synthetase (LRS), which

binds leucinewith an affinity of 45 mM(Chen et al., 2011) (Table 1).

Furthermore, while it is clear that these sensors bind leucine and

arginine with affinities that are consistent with those in the media

that lead to half-maximal mTORC1 pathway activity (Wolfson

et al., 2016), it is not known how concentrations of amino

acids in the media correlate with intracellular, specifically cyto-

solic, amino acid concentrations. Despite recent advances in

measuring small molecules with mass spectrometry (MS), a

few challenges arise when trying to measure intracellular amino

acid concentrations.

First, amino acid levels within different subcellular compart-

ments, specifically within various organelles, could easily vary

with respect to the cytosol, as organelles are enclosed by mem-

branes and contain a distinct set of amino acid transporters

compared to those that are on the plasma membrane. Recent

advances in rapid isolation of mitochondria have allowed for

the accurate measurement of metabolites within this compart-

ment (Chen et al., 2016), but these advances need to be

expanded to other organelles that may be more difficult to

isolate. Indeed, the varied concentrations of amino acids within

organelles means that whole-cell measurements of amino acid

levels may vary drastically from those that are actually available

to proteins within certain subcellular spaces. Further, when esti-

mating concentrations of amino acids in certain compartments,

the compartmental volume is necessary. While it is relatively

simple to measure the volume of a certain organelle, say the

Cell Metabolism

Review

mitochondria, it is difficult to measure the volume of the space

that does not contain any organelles (i.e., the cytosol), compli-

cating estimations of cytosolic amino acid concentrations.

In addition, concentrations of amino acids may exist in gradi-

ents across the intracellular space. For example, as mentioned

previously lysosomes may serve as amino acid storage sites,

perhaps containing higher concentrations of amino acids than

in the cytosol. It is not difficult to imagine, then, that at the lyso-

somal surface, where the mTORC1 pathway machinery resides,

amino acid concentrations are locally higher than in other parts

of the cytosol. Measuring these gradients of amino acid concen-

trations across the cell presents a particular challenge given

currently available technology.

Finally, inside the cell, amino acids exist in both free and bound

pools, including being bound specifically and non-specifically to

proteins, lipids, and other molecules. The pools of amino acids

that are bound are not available to bind to SLC38A9, Sestrin2,

or CASTOR1, but would be measured when intact cells are ex-

tracted and analyzed by MS-based metabolomics. These pools

likely exist in equilibrium with the free pools, and thus estimating

what fraction of each amino acid measured is bound or free is a

significant challenge to understanding the levels of these small

molecules that are available to the sensors.

Amino Acid Levels In VivoWith cells in culture, researchers often completely starve cells of

amino acids by removing them from the media. How amino acid

levels fluctuate in vivo, however, would likely differ considerably

from these in vitro manipulations, as even under starvation

conditions proteolysis would keep amino acid levels from falling

to 0. Amino acid concentrations in the plasma have been

measured in humans and mice in the fed and fasted states.

For leucine in humans, these values range from �130 mM under

the fasted state to �300 mM under the fed state, while arginine

ranges from �100 to �150 mM (Stegink et al., 1991; Stein and

Moore, 1954) (Table 1). While these levels are above the binding

affinities of Sestrin1/2 and CASTOR1 (Chantranupong et al.,

2016; Wolfson et al., 2016), how the plasma levels of amino

acids under these conditions correlate with interstitial amino

acid levels in various tissues is unknown. Even once the intersti-

tial concentrations of amino acids are appreciated, all the chal-

lenges described previously for estimating free cytosolic amino

acid concentrations in cells in culture will persist in cells in vivo,

further complicating our ability to fully understand how the

in vitro binding affinities of the sensors correlate with the fluctu-

ations of amino acids under fed and fasted states in vivo.

Amino Acid Sensors for the mTORC1 Pathway in ModelOrganismsThe discovery of SLC38A9, Sestrin1/2, and CASTOR1 as puta-

tive or bona fide amino acid sensors for the mTORC1 pathway

was an important advance in the field.While several components

of the pathway are conserved in many eukaryotes, amino acid

sensors upstream of mTORC1 have not been discovered or

characterized in most other species, and even if amino acid

sensing per se is conserved throughout eukaryotes is unclear.

One putative amino acid sensor in a non-mammalian organism

that has been recently studied is the D. melanogaster Sestrin

(dSestrin). While mammals have three Sestrin homologs,

D. melanogaster have only one, which has been previously char-

acterized as a negative regulator of the TOR pathway, as its loss

leads to phenotypes in flies that are analogous to those seenwith

lack of autophagy, an important process downstream of dTOR

(the D. melanogaster homolog of mTOR) (Lee et al., 2010).

dSestrin retains leucine-binding capacity, but it binds leucine

more weakly than Sestrin2 (Wolfson et al., 2016), with an affinity

of �100 mM (unpublished data). The relative affinities of dSestrin

for leucine over similar amino acids such as methionine and

isoleucine are unchanged in comparison to Sestrin2, but

because the affinity of dSestrin is lower for leucine, its affinity

for methionine and isoleucine is also much lower, approximately

2.5 and 10 mM, respectively (unpublished data). Although

leucine and methionine concentrations have not been studied

in fly hemolymph, concentrations of six other amino acids were

measured and found to be in the low millimolar range (Piyankar-

age et al., 2008), while most of these amino acids are in the hun-

dreds of micromolar range in humans and mice (Cantor et al.,

2017; Stegink et al., 1991; Stein and Moore, 1954). Additionally,

in Schneider’s media (a commonly used media for the culture

of fly cells) leucine and methionine concentrations are at

1.1 and 5.4 mM, respectively (Schneider, 1964). While this con-

centration of leucine is well above the binding affinity of dSestrin

for leucine, this concentration ofmethionine is similar to the bind-

ing affinity of dSestrin for methionine. Methionine restriction is

known to lead to lifespan extension via the dTOR pathway in

D. melanogaster (Lee et al., 2014), and thus it is tantalizing to hy-

pothesize that dSestrin could act, at least under certain situa-

tions, as a methionine sensor in this organism.

Conservation of the Amino Acid Sensors acrossEvolutionStudy of the nutrient sensing pathway revealed that some of its

components were conserved in many eukaryotes (Figure S1).

Components of mTORC1, such as TOR itself and raptor, are

conserved throughout all eukaryotes, including plants (Figure 3).

Much of the rest of the core machinery of the pathway, such as

the Rag GTPases, or components that control the nucleotide

loading state of the Rag GTPases (like GATOR1), is conserved

through fungi (Figures 3 and 4). Additionally, GATOR2, a com-

plex of unknown function that acts upstream of or parallel to

GATOR1, has a relatively similar pattern of conservation as

GATOR1 (Figure S1). Two components of Ragulator that lack ho-

mologs by sequence were recently found to have structural ho-

mologs in yeast (Kogan et al., 2010; Zhang et al., 2012). Similarly,

structural homologs that were not uncovered by sequence anal-

ysis alone allowed for the identification of Lst4-Lst7 as the FLCN-

FNIP complex orthologs in S. cerevisiae (Peli-Gulli et al., 2015).

Certain amino acids, such as glutamine, have a stronger effect

than others on Lst4-Lst7 localization to the lysosomal mem-

brane, indicating that this complex may play a role in the sensing

of particular amino acids (Peli-Gulli et al., 2015). As of yet, the

FLCN-FNIP complex has not been found to have any specific

amino acid sensing functions.

The discovery of the amino acid sensors, however, has re-

vealed that not all components of the nutrient sensing pathway

are as conserved beyond vertebrates (Figure S1). SLC38A9

has a homolog in C. elegans, but lacks a detectable one in

D. melanogaster or in any fungal species (Wang et al., 2015).

Cell Metabolism 26, August 1, 2017 305

mTORC1 (mTOR and raptor)

Rags

GATOR1

GATOR2

SLC38A9

Sestrins

CASTORs

SZT2

KPTN

ITFG2

Cl2orf66

*

*

*

*

*

*

*

Plants Fungi Parasites Nematodes Flies Mouse Humans

Figure 3. Conservation of Members of theNutrient Sensing Pathway across EvolutionDiagram depicting conservation of mTORC1pathway members across evolution. Dark bluebars indicate that the protein is well conservedacross the specified group or species; light bluebars indicate that the protein is conserved in many,but not all, organisms within the group; asterisksindicate conservation in only a few organismswithin the group; and no bars indicate the protein isnot conserved in the indicated group or organism.

Cell Metabolism

Review

The Sestrins have a clear homolog in D. melanogaster and

C. elegans, but are not as well conserved across various para-

sites or fungal species. Some fungal species, such as Tuber mel-

anosporum and Arthrobotrys oligospora, do seem to have a Ses-

trin homolog, but most lack one (Figure S1). The CASTOR

proteins lack homologs in D. melanogaster or C. elegans, but

follow a similar pattern as the Sestrin proteins in lower organisms

(Figures S1 and 3).

These different patterns of conservation across components

of the mTORC1 pathway lead to many intriguing questions. Are

the sensors less well conserved because other organisms

evolved in distinct environments with different nutritional require-

ments and thus sense other molecules? There is a variety of data

suggesting that nitrogen sensing occurs in fungi, but if amino

acids are sensed in non-engineered, non-auxotrophic fungal or-

ganisms remains under debate (Chantranupong et al., 2015).

Perhaps the species that lack SLC38A9, Sestrin, and CASTOR

homologs have another set of sensors that are responsible for

stimulating the mTORC1 pathway in the presence of nutrients

other than leucine and arginine. Until more sensors have been

discovered in other organisms, it will be hard to address these

questions (Figure 4).

While most fungal organisms lack Sestrin and CASTOR homo-

logs, a very few number of species do appear to have homologs

of these sensors (Figure S1). How these were retained (or ac-

quired through horizontal transmission) is unclear, and if they

act as amino acid sensors (or even modulators of the TOR

pathway) has not been investigated. For example, Tuber mela-

nosporum, or the black truffle, appears to have a Sestrin homo-

log, while Microbotryum violaceum, a fungus that infects a spe-

cific plant species, may have a homolog of the CASTOR

proteins. However, only a few fungal species appear to have

any homologs to Sestrin or CASTOR, and these species are

the exceptions. Further work will be needed to uncover if more

fungal species have homologs to these sensors. It is tantalizing

to imagine that the specific environment of an organism would

dictate the type of sensors that it may need, and that as more

306 Cell Metabolism 26, August 1, 2017

sensors are discovered we can begin to

dissect out these correlations.

Finally, unlike other coremembers of the

pathway, the components of KICSTORare

much less well conserved. KPTN, ITFG2,

and C12orf66 are not even conserved

throughout all metazoans, as C. elegans

and D. melanogaster lack homologs

to these proteins (Figure 3). The final

component of KICSTOR, SZT2, which is

necessary for the other three components to bind GATOR1, has

a homolog inC. elegans but lacks one inD.melanogaster or other

lower organisms, such as fungi, with a few rare exceptions

(Figure S1). This different pattern of conservation between

KICSTOR and other complexes that regulate the pathway but

are not amino acid sensors (such as GATOR1/2, Ragulator, and

the Rag GTPases) suggests that perhaps targeting GATOR1 to

the lysosome is not the only function of KICSTOR. Further work

will be needed to uncover if these proteins have any direct nutrient

sensing properties, or if environmental inputs that are specific to

higher eukaryotes feed in to the mTORC1 pathway upstream of

KICSTOR.

PerspectivesThe mTORC1 pathway has emerged as a critical growth regula-

tory node that is deregulated in a variety of diseases, including

cancer, diabetes, and epilepsy. While it has been well appreci-

ated that amino acids are a key input to the pathway, how these

molecules were sensed remained elusive until recently. The dis-

covery of three amino acid sensors upstream of mTORC1

(SLC38A9, Sestrin1/2, and CASTOR1) has explained, at least

in part, how leucine and arginine are sensed. However, if other

amino acid sensors exist remains undetermined—across sub-

cellular compartments, cell types, tissues, or species. These

recent discoveries represent only the first glimpse at how amino

acids are directly sensed—the dawn of the age of amino acid

sensors for the mTORC1 pathway.

SUPPLEMENTAL INFORMATION

Supplemental Information includes Supplemental Experimental Proceduresand two figures and can be found with this article online at http://dx.doi.org/10.1016/j.cmet.2017.07.001.

ACKNOWLEDGMENTS

We thankGregory A.Wyant for helpful input andGeorge Bell andMeredith Lef-fler for assistance with figures. This work was supported by grants from the

RhebTSC2ITFG2KPTNC12orf66SZT2CASTOR1Sestrin2SLC38A9MiosNprl3RagATOR

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Figure 4. mTORC1 Signaling Pathway Conservation across EvolutionCladogram showing conservation of members of the mTORC1 signaling in various organisms across evolution. Data are a subset of the organisms shown inFigure S1. Legend on the right side indicates colored bars for each gene. Locations of the three kingdoms (plants, fungi, and animals) are listed.

Cell Metabolism

Review

NIH (R01 CA103866 and AI47389) and Department of Defense (W81XWH-15-1-0230) to D.M.S. and fellowship support from the NIH to R.L.W. (T32GM007753 and F30 CA189333). D.M.S. is an investigator of the HowardHughes Medical Institute. D.M.S. is a founder, member of the Scientific Advi-sory Board, paid consultant, and shareholder of Navitor Pharmaceuticals,which is targeting for therapeutic benefit the amino acid sensing pathway up-stream of mTORC1. R.L.W. is a shareholder of Navitor Pharmaceuticals.R.L.W., D.M.S., and the Whitehead Institute have filed two provisional patentsthat relate to amino acid sensing by the mTOR pathway.

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Cell Metabolism, Volume 26

Supplemental Information

The Dawn of the Age of Amino Acid

Sensors for the mTORC1 Pathway

Rachel L. Wolfson and David M. Sabatini

S e r p u l a l a c r y m a n s v a r . l a c r y m a n s

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N e m a t o s t e l l a v e c t e n s i s

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0 1 2 3 4 5 6 7 8 9

10+

-log10 HMMER score

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S a p r o l e g n i a d i c l i n a V S 2 0

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C a p s a s p o r a o w c z a r z a k i

M o n o s i g a b r e v i c o l l i s

Supplementary Figure 1 homology analysis by phmmer

TOR ra

ptor

RagA

RagC

RagD

Nprl3

DEPDC5

Nprl2

Mios

WDR59

WDR24

SLC38A9

Sestrin2

CASTOR1

CASTOR2

SZT2

C12orf66

ITFG2

KPTN

TBC1D7

TSC1

TSC2

Rheb

Supplementary Figure 1: Conservation of mTORC1 pathway members across evolution Cladogram showing which organisms contain homologs to each member of the mTORC1 pathway listed. Bottom part of the chart shows organisms in the plant kingdom, above that shows organisms in the fungi kingdom, and organisms in the animal kingdom are shown at the top.

Supplementary Figure 2

Protein Sequence used Domain excludedmTOR 1-2152 Kinase domainraptor 1-1026 WD40 repeatsRagA 23-end GTPase domainRagC whole sequenceRagD whole sequenceNprl3 whole sequence

DEPDC5 whole sequenceNprl2 whole sequenceMios 298-end WD40 repeats

WDR59 280-end WD40 repeatsWDR24 324-end WD40 repeats

SLC38A9 59-110 Transmembrane domainsSestrin2 whole sequence

CASTOR1 whole sequence CASTOR2 whole sequence

SZT2 whole sequence C12orf66 whole sequence

ITFG2 whole sequence KPTN whole sequence

TBC1D7 whole sequence TSC1 whole sequence TSC2 1-1538 GAP domainRheb 132-184 GTPase domain

Supplementary Figure 2: Sequences used for evolutionary analysis Portions of the protein sequences that were used for the evolutionary analysis and the domains that were excluded in order to reduce false positives.

Methods: Evolutionary Analysis Evolutionary analysis was performed using the PHMMER software (as described in Wolfson et al., 2017). To decrease false positives, common domains of some of the protein sequences were excluded, and thus portions of the sequences were used for the analysis (Figure S2).