Abstract
For organisms to coordinate their growth and development with nutrient availability they must be able to sense nutrient levels in their environment. Here, we review select nutrient sensing mechanisms in a few diverse organisms. We discuss how these mechanisms reflect the nutrient requirements of specific species and how they have adapted to the emergence of multicellularity in eukaryotes.
Introduction
All organisms have the capacity to sense the presence and absence of the nutrients required to generate energy and the building blocks of cells. In this review we survey a variety of nutrient sensing strategies and discuss how these mechanisms have evolved to suit the particular needs and environments of diverse organisms.
We first illustrate how varied sensing mechanisms can be using examples from unicellular organisms, including the sensing of amino acids by E. coli and of ammonium and glucose by S. cerevisiae. We then shift our focus to sensing pathways conserved in most eukaryotes, including those anchored by the AMPK, GCN2, and TOR kinases (Figure 1). We emphasize how in multicellular organisms the architectures of these core pathways has been adapted to respond to hormones in addition to nutrients and to control feeding. Furthermore, we highlight how the emergence of subcellular compartments in eukaryotes allows for new ways to store and sense nutrients.
Figure 1. Nutrient sensing pathways throughout evolution.
An overview of the nutrient sensing pathways described in this review. Pathways specific to unicellular organisms are denoted, followed by the sensing pathways that are conserved from yeast to man. Black bars indicate the presence of the pathway within the denoted species or organism.
Prokaryotes
Bacteria have evolved many interesting mechanisms for sensing diverse nutrients, undoubtedly an adaptation to living in environments where the concentrations and types of nutrients can vary unpredictably. We have chosen to discuss mechanisms that serve as examples of important concepts, such as the use of enzymes or receptors to detect molecules of interest, or the indirect sensing of a nutrient through the levels of metabolites generated from it. The variety of post-translational modifications that bacterial sensing pathways use, from phosphorylation to adenylylation and methylation, is remarkable as is the concentration range over which some nutrients can be detected.
Chemoreceptors: Coupling extracellular nutrient concentrations to cell motility
Bacteria can face large fluctuations in the levels of nutrients in their environment and so motile species couple nutrient sensing to taxis to bias their movements towards higher nutrient concentrations. While we focus on nutrient-regulated chemotaxis in E. coli, the process is conserved in many prokaryotes (Szurmant and Ordal, 2004).
E. coli swim by rotating their flagella, bundles of filaments localized at the pole and powered by a rotary motor (Berg, 2008; Eisenbach, 1996). The motor is bidirectional: counterclockwise rotation produces smooth swimming whereas clockwise rotation leads to random tumbling due to dispersal of the flagellar filaments (Larsen et al., 1974; Turner et al., 2000). The default rotation of the motor is counterclockwise, and nutrients signal through transmembrane chemoreceptors to maintain this state to promote directed movement along a nutrient gradient. The absence of nutrients triggers a pathway that permits flagella to alternate between clockwise and counterclockwise rotations so that cells forage their environment in a random walk (Berg and Brown, 1972; Sourjik and Wingreen, 2012).
E. coli express five dimeric, single pass transmembrane chemoreceptors, Tar, Tsr, Tap, Trg, and Aer, which function as distinct nutrient sensors. In aggregate, they allow E. coli to detect and respond to a broad spectrum of extracellular molecules, with aspartate, maltose, Co2+ and Ni2+ binding to Tar (Reader et al., 1979; Wang and D E Koshland, 1980); ribose and galactose to Trg (Kondoh et al., 1979); flavin adenine dinucleotide to Aer (Szurmant and Ordal, 2004); serine to Tsr; and dipeptides to Tap (Hedblom and Adler, 1980; Manson et al., 1986). Of the five receptors, Tar and Tsr are the most abundant (Sourjik and Berg, 2004). Remarkably, the chemoreceptors sense ligand concentrations as low as 3 nM and function over a concentration range of five orders of magnitude (Mesibov et al., 1973). This high sensitivity stems from the clustering at the cell pole of the receptors into higher order arrays, enabling one ligand binding event to affect multiple neighboring receptors and effectors (Bray et al., 1998; Briegel et al., 2009; Kentner et al., 2006; Levit et al., 2002; Maddock and Shapiro, 1993; Sourjik and Berg, 2004; Zhang et al., 2007), which presumably allows cells to detect even highly dilute nutrient environments.
The chemoreceptors signal through CheA, a homodimeric histidine kinase that constitutively associates with the chemoreceptors and its adaptor protein, CheW (Figure 2A). In the absence of a ligand, CheA phosphorylates the associated response regulator, CheY (Borkovich et al., 1989; Hess et al., 1988; Hess et al., 1987; Stock et al., 1988), which then diffuses to the flagellar motor to promote clockwise rotation (Dyer et al., 2009; Sarkar et al., 2010; Scharf et al., 1998; Welch et al., 1993). Nutrients diffuse into the periplasm through channels in the outer membrane and directly or indirectly contact chemoreceptors to trigger a conformational change that inhibits CheA and CheY (Ottemann et al., 1999), causing bacteria to swim in a positive direction for longer periods of time.
Figure 2. Select sensing pathways in unicellular organisms.
A. Chemotaxis in E. coli: In the absence of nutrients, the chemoreceptor activates the CheA kinase associated with CheW. CheA in turn phosphorylates and activates two critical effectors: CheY, which promotes clockwise rotation in the flagellar motor and random tumbling motions, and CheB, a demethylase involved in the adaptation process which counteracts CheR, the constitutive methylase. Conversely, the presence of nutrients suppresses this pathway and the default counterclockwise rotation of the rotor ensues to yield smooth runs. B. PII proteins in alpha-proteobacteria: This tightly regulated protein family serves to control the adenylylation state and activity of glutamine synthase (GS). When nitrogen is absent, the precursor of nitrogen assimilation reactions, 2-OG, accumulates, binds to, and inhibits the unmodified PII protein GlnB, which is unable to stimulate the adenylylation reaction of ATase. The unmodified and active form of GS accumulates. When nitrogen is abundant, glutamine levels are high, and this molecule binds and inhibits UTase, which permits the unmodified form of GlnB to accumulate and promote GS inhibition, by activating the adenylylation of GS by ATase. C. SPS pathway in S. cerevisiae: Extracellular amino acids bind directly to Ssy1, a transceptor with homology to amino acid permeases but lacking transport activity, to activate the SPS (Ssy1-Ptr3-Ssy5) pathway. Amino acids bind to Ssy1 to stimulate a conformational change in Ssy5, resulting in the phosphorylation and subsequent ubiquitin-mediated degradation of its inhibitory pro-domain. Ptr3 acts as an adapter to mediate this process. Release of the catalytic domain of Ssy5 permits it to cleave the latent transcription factors Stp1 and Stp2, which translocate to the nucleus to activate transcription of genes involved in amino acid transport and metabolism. (Figure adapted from Conrad et al, 2014).
A crucial aspect of chemotaxis is adaptation - the ability to restore prestimulus behavior. Chemoreceptor methylation by the methyltransferase CheR and demethylation by the methylesterase CheB facilitates adaptation (Anand and Stock, 2002; Borkovich and Simon, 1990; Bren and Eisenbach, 2000; Kondoh et al., 1979). In addition to phosphorylating CheY, the CheA kinase phosphorylates and activates CheB, which demethylates the chemoreceptor and reduces its capacity to activate CheA despite persistently low ligand concentrations. Conversely, sustained increases in nutrient concentrations lead to an accumulation of receptor methylation over time as CheB is inactive and CheR constitutively active. This enhances the ability of the chemoreceptor to stimulate CheA despite constant high concentrations of attractant. Thus, CheB promotes adaptation to decreasing levels of attractants while CheR promotes adaptation to increasing levels of attractants. Methylation therefore resets the signaling state of the receptors so that E. coli can adapt to the present environment and be poised to respond to subsequent changes (Wadhams and Armitage, 2004; Weis and D E Koshland, 1988).
The capacity to couple motility to nutrient concentrations allows bacteria to forage for limited resources. However, all bacteria, motile or not, must possess mechanisms that relay nutrient levels to the metabolic systems that counteract nutrient deficits so as to maintain the metabolites needed for viability and growth. One such mechanism is the PII protein pathway, which uses a cascade of posttranslational modifications to control nitrogen assimilation.
PII proteins: Controllers of nitrogen assimilation
Under nitrogen-limiting conditions, many prokaryotes increase nitrogen assimilation by synthesizing nitrogen-containing organic molecules, such as amino acids, from inorganic nitrogen compounds in the environment. Assimilation occurs via a dedicated glutamine synthase (GS)/glutamate synthase (GOGAT) cascade that generates glutamate from 2-oxoglutarate (2-OG; also known as α-ketoglutarate), ammonium, and ATP. The first step of the process, catalyzed by GS, produces glutamine, and thus its presence represents nitrogen sufficiency, while 2-OG, its precursor, signals nitrogen deficiency (Forchhammer, 2007; Leigh and Dodsworth, 2007). The PII proteins play a key role in sensing nitrogen deficiency and although they vary greatly in structure and function they are found in most prokaryotes and plants (Heinrich et al., 2004)(Figure 1).
Within the PII superfamily of proteins the related GlnB and GlnK proteins in E. coli have been particularly well studied (Leigh and Dodsworth, 2007). These proteins have significant homology only to other PII proteins and form homotrimeric complexes. Their main function is to control the adenylylation of GS, which inhibits it and thus reduces nitrogen assimilation (Figure 2B) (Leigh and Dodsworth, 2007). The PII proteins exist in two forms: unmodified and uridylylated. Only when unmodified do they bind to and activate the adenylyltransferase (ATase) enzyme (encoded by glnE) to adenylylate GS (Brown et al., 1971; Stadtman, 2001). The uridylylated form, on the other hand, stimulates the deadenylylation activity of ATase (Jaggi et al, 1997).
How nitrogen is sensed is complex and involves two sensors, the PII proteins themselves as well as the uridylyltransferase (UTase) enzyme (encoded by glnD) that uridylylates the PII proteins. Under conditions of nitrogen excess, UTase directly binds to and is inhibited by glutamine, which is at high levels when nitrogen is abundant (Jiang et al, 1998a). The glutamine-bound UTase is unable to uridylylate GlnB, which accumulates in its unmodified form and therefore allosterically activates the adenylylation activity of ATase (Adler et al., 1975; Mangum et al., 1973). This leads to the accumulation of adenylylated, and therefore inactive, GS. During nitrogen deprivation, however, 2-OG levels increase and the binding of 2-OG to unmodified GlnB allosterically inhibits its ability to activate adenylylation by ATase (Jiang et al, 1998c). The GlnB homotrimer has three 2-OG binding sites, the first of which binds 2-OG with micromolar affinity, well below its physiological concentration of 0.1-0.9 mM. Because the binding of 2-OG to GlnB exhibits high negative cooperativity, the second and third sites are occupied only at the high 2-OG concentrations that occur upon nitrogen deprivation. Only upon binding multiple molecules of 2-OG does unmodified GlnB adopt a conformation in which it is unable to activate the adenylylation activity of ATase, leaving GS unmodified and thus active (Jiang et al., 1998a; Jiang et al., 1998b, c) (Adler et al., 1975; Mangum et al., 1973). While high levels of 2-OG inhibit the activity of unmodified GlnB, uridylylated GlnB is unaffected by high levels of this metabolite. GlnK, a PII protein that is highly similar to GlnB, also regulates AmtB, an ammonia transporter, in response to nitrogen availability, by binding to and inhibiting the transporter under high glutamine levels (Coutts, 2002; Hoving et al., 1996).
While we have focused on the implications of 2-OG binding to the PII proteins, they are also well appreciated to bind ATP, which acts synergistically with 2-OG at low concentrations and is necessary for both GlnB and uridylylated GlnB to be able to stimulate the adenylylation and deadenylylation reactions, respectively, of ATase (Jiang et al, 1998c). While GlnB binds ATP with micromolar affinity and free ATP concentrations in the cell can be as high as 1 mM (Jiang and Ninfa, 2007; Jiang et al., 1998a), ATP binding, like that of 2-OG, displays negative cooperativity (Jiang and Ninfa, 2007). The first crystal structure of GlnK in complex with AmtB showed that ADP could bind in place of ATP (Conroy et al., 2007), leading to the hypothesis that PII proteins may also act as energy sensors by responding to the ratio of ADP to ATP. However, more recent data suggest that additional work is needed to validate this hypothesis (Bennett et al., 2009; Chapman et al., 1971; Huergo et al., 2013; Radchenko et al., 2013; Zhang et al., 2009). In addition to roles in sensing nitrogen and perhaps energy, some PII proteins may also be carbon sensors (Feria Bourrellier et al., 2010; Huergo et al., 2013).
For several reasons the sensing system anchored by the PII proteins is fascinating. First, two separate sensors detect two distinct metabolites, one that represents nitrogen depletion (2-OG) and the other abundance (glutamine). Second, because 2-OG binding exhibits negative cooperativity, the PII proteins are sensitive to differential flux through the nitrogen assimilation pathway rather than acting as binary switches. Lastly, the PII protein pathway is a good example of a particular sensing strategy: instead of directly sensing, like chemoreceptors, the nutrient of interest, it senses metabolites involved in nitrogen assimilation, thus providing specificity to this process over other ammonium-using reactions.
Eukaryotes
Nutrient sensing systems unique to yeast
In this section we discuss several pathways that sense extracellular nutrients and are specific to yeast, including those controlled by Ssy1, MEP2, Snf3, and Rgt2. Like bacterial chemoreceptors, these transmembrane proteins sense a diverse set of nutrients including amino acids, ammonium, and glucose. They connect the status of the external world to varied intracellular processes - from the expression of transporters to the formation of pseudohyphae. Unlike bacterial chemoreceptors, Ssy1, MEP2, Snf3, and Rgt2 are homologous to nutrient transporters and are an important class of sensors sometimes termed transceptors. Many of these transceptors play key roles in allowing yeast to decide which nutrient to uptake and utilize when many are available and thus ensure an optimal growth rate.
MEP2: A putative extracellular ammonium sensor
Yeast evaluate and respond to a diverse set of nitrogen-containing compounds, and have a hierarchical preference for nitrogen sources. In a process termed nitrogen catabolite repression, the presence of desired sources such as ammonium and glutamine represses the transcription of genes involved in scavenging and metabolizing poor sources such as proline (Zaman et al., 2008). Yeast can utilize ammonium as their sole source of nitrogen and assimilate it via biochemical reactions akin to those described in prokaryotes: glutamate dehydrogenase transaminates α-ketoglutarate to produce glutamate, which glutamine synthase uses with ammonium to make glutamine (Marini et al., 1994).
S. cerevisiae trigger a dimorphic transition under limiting ammonium conditions. Diploid cells form pseudohyphae that extend from the colony into the surrounding medium (Gimeno et al., 1992), permitting normally sessile yeast colonies to forage for nutrients at a distance from their colonization point (Gimeno et al., 1992). For this metamorphosis to take place, the lack of ammonium outside the cell must be sensed and transduced to downstream signaling pathways that control filamentous growth. MEP2 is proposed to mediate the sensing role in this pathway (Lorenz and Heitman, 1998).
The MEP (methylamine permease) proteins are members of a family of ammonium channels conserved from bacteria to animals (Marini et al., 1997a; Siewe et al., 1996), although their role in physiology has diverged in metazoans, as discussed below. In yeast, there are three MEP proteins, the most divergent being MEP2 (Marini et al., 1997b; Marini et al., 1994), and all three can uptake extracellular ammonium ions into cells. Of the three, MEP2 has the highest affinity with a Km of 1-2 uM which contrasts with that of MEP3, which is 1-2 mM (Marini et al., 1997b). Given the dual role of MEP2 in detecting low ammonium concentrations in the environment and scavenging it for use as a nitrogen source, it makes sense that the highest affinity transporter of the three evolved to be the sensor. Under low or absent ammonium, MEP2 is essential for pseudohyphal growth and expressed on the plasma membrane (Dubois and Grenson, 1979; Rutherford et al., 2008) (Figure 2C). When ammonium is plentiful, MEP2 is internalized and targeted for degradation (Marini et al., 1997b; Zurita-Martinez et al., 2007).
Substantial evidence supports the notion that MEP2 is an ammonium sensor that controls pseudohyphal growth upon ammonium deprivation (Lorenz and Heitman, 1998). First, MEP2, but not MEP1 or MEP3, is required for pseudohyphal formation under these conditions, and its first intracellular loop is critical for this action (Lorenz and Heitman, 1998). Later mutagenesis studies revealed that a transport deficient MEP2 prevents pseudohyphal growth despite proper localization and expression (Marini et al., 2006). However, transport is necessary but not sufficient for ammonium sensing as there are transport proficient but signaling defective MEP2 mutants (Rutherford et al., 2008). The identity of the proteins that MEP2 engages to induce signaling remains unknown. Current evidence points to the involvement of GPA2, a G protein alpha subunit, and RAS2, in increasing cAMP levels to activate protein kinase A (PKA) in response to the absence of ammonium (Gimeno et al., 1992; Kübler et al., 1997; Lorenz and Heitman, 1997; Lorenz and Heitman, 1998; Van Nuland et al., 2006).
As a transceptor, passage of ammonium through MEP2 is likely to induce a conformational change that enables it to interact with downstream effectors that signal pseudohyphal growth. Conformational changes have been observed in the bacterial homologue of MEP2, AmtB, but these remain to be linked to ammonium sensing (Andrade et al., 2005; Khademi et al., 2004; Zheng et al., 2004).
While ammonium is a valuable nitrogen source for bacteria, fungi, and plants, at high levels it is cytotoxic to animals (Biver et al., 2008). Therefore, in animals ammonium transport is essential for its excretion, and MEP-like proteins have persisted throughout evolution (Marini et al., 1997a). Reflecting their functional conservation, human orthologs of MEP2, the erythroid specific Rh(rhesus)-type proteins, can transport ammonium in yeast (Marini et al., 2000; Marini et al., 1997a). Proteins of the Rh family are expressed in various organs and play critical roles in physiology. For instance, renal cortex cells excrete ammonium into urine via an Rh transporter (Biver et al., 2008; Garvin et al., 1988; Knepper et al., 1989). A role for these proteins as ammonium sensors has not been ascertained.
Extracellular amino acid sensing: The SPS pathway
Yeast coordinate signals from several major pathways to detect amino acids and alter gene expression and developmental decisions. While the GCN2 and TOR pathways discussed later respond to intracellular amino acids, the Ssy1-Ptr3-Ssy5 (SPS) pathway senses extracellular amino acids (Klasson et al., 1999). The SPS pathway is conserved in other yeast, such as Candida albicans, but not in higher eukaryotes (Davis et al., 2011), which have evolved distinct pathways for sensing extracellular amino acids (Conigrave et al., 2000; Cummings and Overduin, 2007) (Figure 1).
Ssy1 is a transporter-like protein in the plasma membrane of S. cerevisiae that functions, like MEP2, as a transceptor. Although it has sequence homology to amino acid permeases (AAP), it lacks transport activity, and, unlike other AAPs, possesses a long N-terminal extension that is important for transmitting the availability of nutrients to downstream signaling elements (Bernard and Andre, 2001; Iraqui et al., 1999). Ssy1 forms a complex with Ptr3 and Ssy5 that, when amino acids are present, activates a signaling pathway that enhances the transcription of amino acid transport and metabolism genes (Didion et al., 1998).
Ssy5 is an endoprotease composed of an inhibitory pro-domain and a catalytic domain (Abdel-Sater et al., 2004; Andreasson, 2006). Amino acid binding to Ssy1 on the extracellular side of the plasma membrane induces a conformational change in Ssy5 that leads to the phosphorylation and ubiquitin-mediated degradation of its pro-domain (Abdel-Sater et al., 2011; Omnus et al., 2011; Pfirrmann et al., 2010). This relieves the inhibition of the catalytic domain of Ssy5, which can cleave and activate Stp1 and Stp2, transcription factors that translocate into the nucleus to activate relevant genes. Ptr3, the third subunit of SPS, is essential for Ssy5 activation, and is an adaptor that helps transduce conformational changes from Ssy1 to Ssy5 upon amino acid binding, and to bring the prodomain of Ssy5 into proximity with its kinase to facilitate its phosphorylation (Omnus and Ljungdahl, 2013). Evidence that SPS acts as a direct sensor of amino acids came from mutagenesis experiments demonstrating that certain Ssy1 mutants can alter the sensitivity of the SPS complex to extracellular amino acids (Poulsen et al., 2008). Interestingly, S. cerevisiae which harbor mutations in either Ptr3 or Ssy1 have increased vacuolar pools of basic amino acids (Klasson et al., 1999). This observation suggests that in the absence of a signal relaying the presence of extracellular amino acids, yeast attempt to increase their vacuolar stores of amino acids, perhaps allowing them to be more independent of extracellular amino acid availability. Ssy1 is an interesting variant of the transceptor class of sensors because, unlike MEP2, it does not retain transport activity.
Snf3 and Rgt2: Extracellular glucose sensors
In addition to sensing extracellular amino acids, S. cerevisiae also detect extracellular glucose. Fermentation of this hexose yields the energy and carbon precursors needed to fuel growth, and glucose rapidly stimulates restructuring of the transcriptome to permit yeast to take full advantage of its presence (Zaman et al., 2008). In a process termed carbon catabolite repression, glucose and fructose repress processes involved in the metabolism of less preferred carbon sources, with this repression occurring primarily at the transcriptional level (Gancedo, 1998; Santangelo, 2006). Here, we discuss the glucose-sensing pathway that regulates Rgt1, a transcription factor, and is necessary for glucose utilization. In the absence of glucose the Snf1 (AMPK) pathway discussed later is essential for the use of less preferred carbon sources (Zaman et al., 2008)
Under glucose limitation, Rgt1, in complex with the Ssn6-Tup1 repressor and the Mth1 and Std1 co-repressors, binds to the promoters of hexose transporter genes (HXT) and inhibits their transcription (Kim et al., 2003; Lakshmanan et al., 2003; Ozcan and Johnston, 1995; Polish, 2005; Theodoris et al., 1994; Tomas-Cobos and Sanz, 2002). Glucose binds to two transporter-like glucose sensors, Snf3 and Rgt2, which are needed to activate HXT expression. Snf3 senses low glucose concentrations and elevates the transcription of high affinity hexose transporter genes while Rgt2 senses high glucose levels and promotes low-affinity hexose transporter expression (Bisson et al., 1987; Ozcan et al., 1996). Glucose binding to Snf3 and Rgt2 recruits Mth1 and Std1, through an unknown mechanism, to the plasma membrane, where they are subsequently phosphorylated, ubiquitylated, and degraded (Flick, 2003; Kim et al., 2006; Moriya and Johnston, 2004; Schmidt et al., 1999). Without its co-repressors, Ssn6-Tup1 also dissociates from Rgt1(Roy et al., 2013), leaving it free to be phosphorylated by the cAMP-dependent protein kinase (PKA) and to become a transcriptional activator of the HXT genes (Jouandot et al., 2011).
The Snf3/Rgt2 pathway represents yet another example of a nutrient sensing pathway controlled by transceptors. In addition, analogous to the regulation of the PII proteins by 2-OG, the Snf3/Rgt2 pathway senses varied glucose levels rather than behaving like an on-off switch. Unlike the PII proteins, which use negative cooperativity between 2-OG binding sites to allow for graded responses, the Snf3/Rgt2 pathway utilizes two separate sensors, with different affinities for the nutrient of interest.
Nutrient sensing pathways conserved from yeast to mammals
In this section we highlight the AMPK, GCN2, and TOR pathways, which are conserved, at least in part, from yeast to man. In multicellular organisms, evolution has adapted the architectures of these pathways so they can sense hormonal cues in addition to the nutrients that the pathways detect in yeast. Given their roles in sensing essential nutrients, like amino acids and glucose, it is perhaps not surprising that the three pathways regulate feeding behavior.
Lastly, we briefly discuss how the emergence of the vacuole/lysosome in eukaryotes and its use as a storage depot for nutrients in fungi (Klionsky et al., 1990; Li and Kane, 2009), and likely mammals, has led to a need to sense its contents, which is a recently appreciated obligation of the TOR pathway.
AMPK: A eukaryotic fuel gauge
A key event in the emergence of eukaryotes and their diversification and increase in complexity was the engulfment of oxidative bacteria, the predecessors of mitochondria. It has been argued that prokaryotes lack the energetic resources to maintain large amounts of regulatory DNA, but that the acquisition of mitochondria nearly 4 billion years ago alleviated the pressure to remove excess DNA and permitted eukaryotes to explore hundreds of thousands-fold more genes (Lane and Martin, 2010).
Eukaryotes must sense their cellular energy balance and relay it to mitochondria and other parts of the cell that help maintain energy homeostasis (Hardie et al., 2012). A key energy sensor is the serine/threonine-directed AMP-activated protein kinase (AMPK), which regulates many catabolic and anabolic processes in response to energy levels (Gowans and Hardie, 2014).
AMPK was initially discovered in mammals as a kinase that phosphorylates and inactivates acetyl-CoA carboxylase (ACC) and HMG-CoA reductase, rate-limiting enzymes in fatty acid and cholesterol synthesis, respectively (Carling et al., 1989; Carling and Hardie, 1986). The S. cerevisiae homolog of AMPK, SnfI (sucrose nonfermenting), had been found earlier in a screen for yeast that failed to grow on nonfermentable carbon sources, but it was not recognized as a homolog of AMPK until later (Carlson et al., 1981; Mitchelhill et al., 1994; Woods et al., 1994). AMPK orthologs have also been identified in plants and are referred to as SNF-1 related kinases (SnRK1). SnRK1 from rye endosperm can complement yeast snf1 mutants, highlighting the conserved function of AMPK (Alderson et al., 1991).
In response to decreasing energy levels, AMPK and Snf1 phosphorylate substrates that activate processes that generate ATP and inhibit those that consume it. The conservation of the pathway throughout evolution is apparent in the high degree of similarity between the key effectors of AMPK and Snf1. For instance, both AMPK and Snf1 control glucose-linked processes. Snf1 inactivates the Mig1 transcriptional repressor, relieving glucose-repressed genes (Chronakis et al., 2004). Analogously, AMPK stimulates glucose uptake and glycolysis and inhibits glycogen synthesis (Yuan et al., 2013). Additional key effectors include the TORC1 and mTORC1 complexes, which function as master regulators of growth in yeast and mammals, respectively, and are discussed below. By regulating mTORC1 and TORC1, AMPK and Snf1 govern the switch between anabolism and catabolism to maintain metabolic homeostasis. In mammals, AMPK inhibits mTORC1 via two mechanisms. First, it phosphorylates and activates the TSC2 GTPase activating protein, a major inhibitor of the pathway (Inoki et al., 2003b). Second, it phosphorylates raptor, a subunit of mTORC1, resulting in 14-3-3 binding and inhibition of mTORC1 kinase activity (Gwinn et al., 2008; Inoki et al., 2003b). Likewise, Snf1 has also been proposed to phosphorylate critical subunits of TORC1 (Braun et al., 2014). Aside from these well-characterized targets, AMPK and Snf1 likely have hundreds of additional substrates that control a wide range of processes (Hardie et al., 2012; Mihaylova and Shaw, 2011).
How do energy levels regulate AMPK? AMPK binds adenine nucleotides to sense the ratio of ADP or AMP to ATP, a critical barometer of the energy state of the cell. In times of nutrient abundance, this ratio is low. Upon energetic stress, the ratio rises as ATP levels drop with a concomitant rise in ADP, which is converted to AMP due to high cytosolic adenylate kinase activity (Hardie and Hawley, 2001). As opposed to ATP levels, AMP and ADP levels are more sensitive indicators of energy status; a 2-fold drop in ATP levels reflects a 50-fold drop in AMP (Hardie and Mackintosh, 1992). Furthermore, despite the millimolar concentrations of cellular ATP, a significant proportion of it is in complex with Mg2+ and does not bind well to AMPK (Xiao et al., 2011).
The mechanism of adenine nucleotide regulation of AMPK has been extensively characterized. AMPK is a trimeric complex composed of α kinase, β carbohydrate binding, and γ regulatory subunits (Kemp, 2004; Scott et al., 2004). There are theoretically four nucleotides binding sites in the γ subunit, although one remains empty and another constitutively binds AMP (Xiao et al., 2007). A tripartite mechanism controls AMPK in mammalian cells. First, AMPK binds AMP and undergoes a conformational change that enhances the ability of the kinases LKB1 and CaMKKKB to phosphorylate and activate it. Second, AMP binding to AMPK protects it against dephosphorylation by currently unidentified phosphatases. Third, AMP further allosterically activates the kinase up to 13 fold (Carling et al., 1989; Gowans and Hardie, 2014). ATP binding antagonizes all of these effects (Corton et al., 1995). As a result of the two nucleotide binding sites, both of which can bind AMP, ADP, or ATP, AMPK regulation is graded in response to energy status, just like PII protein function is in response to 2-OG. As AMP levels rise under extreme energetic stress, AMP binds both sites to maximally activate AMPK.
Recent studies have uncovered conservation between the regulatory mechanisms of fungal and plant AMPK homologues and those of the mammalian kinase. In yeast, SnfI is also heterotrimeric, binds nucleotides and is regulated by opposing kinases and phosphatases (Hong et al., 2003; Hong et al., 2005; Jin et al., 2007; Sutherland et al., 2003; Townley and Shapiro, 2007). However, unlike AMPK, it appears that ADP, not AMP, promotes phosphorylation of Snf1 by inhibiting its dephosphorylation, and AMP does not allosterically activate Snf1 (Mayer et al., 2011; Mitchelhill et al., 1994; Woods et al., 1994). Hence, in yeast there is a bipartite mechanism of activation, with ADP playing a prominent role.
With the onset of multicellularity, physiological processes evolved in metazoans that maintain homeostasis for the organism as a whole, and AMPK acquired new modes of regulation. Specifically, hormones and cytokines enable the nutrient-sensing organs of multicellular organisms to communicate the nutritional state to other organs to elicit tissue-specific responses. The coordinated actions of leptin, insulin, and ghrelin, amongst others, regulate the organismal response to nutrients, or lack thereof, and are well appreciated to regulate AMPK. Upon food consumption, blood glucose levels rise and pancreatic beta cells release insulin, which promotes anabolic and inhibits catabolic processes in many tissues. These effects are mediated in part through Akt, a kinase that inhibits AMPK by phosphorylating it at Ser485/491, and antagonizing LKB1-mediated Thr172 phosphorylation, which normally activates AMPK (Horman et al., 2006).
Many nutrient-regulated hormones signal to the brain to control feeding behavior. Under fasting or starvation conditions, enteroendocrine cells of the stomach release ghrelin, which signals hunger. Conversely, during feeding, adipocytes release leptin, which signals satiety. These hormones alter the activity of neuronal circuits in the hypothalamic arcuate nucleus, the appetite control center of the brain (Dietrich and Horvath, 2011; Hardie et al., 2012; Pinto et al., 2004). Several studies point to a role for AMPK in the control of feeding. Ghrelin activates AMPK in the hypothalamus and leads to a subsequent increase in food intake. Overexpression of a dominant negative form of AMPK in the hypothalamus restrains feeding while direct injection of pharmacological AMPK activators results in hyperphagia (Andersson et al., 2004; Minokoshi et al., 2004). These effects are likely mediated through modulation of AMPK in presynaptic neurons that impinge on neurons critical for feeding control (Gowans and Hardie, 2014; Yang et al., 2011). Ghrelin likely binds GHSR1, a G protein coupled receptor in the presynaptic neuron, triggering the release of Ca2+ that stimulates CaMKKK to activate AMPK (Yang et al., 2011). Meanwhile, leptin may function in a manner similar to insulin by activating the PI3K-Akt axis and controlling the phosphorylation state of AMPK (Dagon et al., 2012). Therefore, as complex feeding behaviors arose in multicellular organisms, AMPK was coopted to function in neuronal circuits to control intake of food.
GCN2: A sensor of amino acid deprivation
Alongside the SPS pathway, which senses extracellular amino acids in yeast, eukaryotes evolved a parallel pathway to detect intracellular amino acid levels: the general amino acid control non-derepressible 2 (GCN2) pathway. GCN2 senses the uncharged tRNAs that accumulate upon amino acid deprivation. GCN2 attenuates translation, which not only consumes amino acids but is also one of the most energy demanding processes in the cell (Lane and Martin, 2010).
While GCN2 is found only in eukaryotes, the use of uncharged tRNAs to signal amino acid deprivation is conserved to bacteria. Upon amino acid starvation in E. coli, uncharged tRNAs bind directly to ribosomes, leading to the production of the odd nucleotides guanosine tetraphosphate and guanosine pentaphosphate (Cashel and Gallant, 1969). These nucleotides repress the synthesis of stable RNAs (rRNA and tRNA) and activate amino acid biosynthetic genes to promote survival in a process referred to as the stringent response (Srivatsan and Wang, 2008).
In yeast GCN2 is dedicated to sensing uncharged tRNAs (Hinnebusch, 1984). Under conditions of amino acid limitation or a defect in an amino acyl tRNA synthetase, S. cerevisiae upregulate the transcription of genes involved in amino acid biosynthesis, a process termed general amino acid control (Hinnebusch, 1988; Hinnebusch, 2005; Wek et al., 1995). When present, uncharged tRNAs bind to the histidyl tRNA synthetase-like domain of GCN2, which lacks residues critical for synthetase activity and histidine specific binding, thus enabling GCN2 to respond to a variety of uncharged tRNAs (Wek et al., 1989; Wek et al., 1995). The binding triggers GCN2 homodimerization (Narasimhan et al., 2004) and autophosphorylation (Diallinas and Thireos, 1994), allowing it to phosphorylate and inhibit its only known substrate, eukaryotic initiation factor 2a (eIF2a) (Dever et al., 1992). This phosphorylation prevents efficient translation initiation of most mRNAs by limiting the pool of ternary complex, which consists of eIF2, GTP, and methionyl initiator tRNA and is required for translation initiation (Abastado et al., 1991; Dever et al., 1992; Hinnebusch, 1993).
While most mRNAs are translationally repressed upon amino acid deprivation, the mRNA encoding the GCN4 transcription factor is derepressed so that GCN4 can accumulate and activate the expression of genes that promote amino acid biosynthesis (Abastado et al., 1991; Dever et al., 1992; Hinnebusch, 1993). A cluster of four upstream open reading frames (uORFs) in the 5′ untranslated region of the GCN2 mRNA permits this unique regulation (Hinnebusch, 2005). Under nutrient replete conditions, a ternary complex forms at the first uORF. It then dissociates and another forms at the subsequent uORFs, thus preventing translation of the main ORF. However, upon starvation, ternary complex formation is delayed, and rebinding at latter uORFs reduced. Larger proportions of preinitiation complexes bypass the uORFs and form ternary complexes before reaching and translating the main ORF (Abastado et al., 1991(Hinnebusch, 1984; Mueller and Hinnebusch, 1986).
In mammals, GCN2 pathway architecture is reminiscent of that in yeast (Berlanga et al., 1999; Sood et al., 2000) as it is activated by a limitation in an essential amino acid or inhibition in the synthesis of a nonessential amino acid. uORFs also regulate the translation of the mammalian GCN4 orthologue, ATF4, a basic leucine zipper transcription factor (Vattem and Wek, 2004). ATF4 induces a cascade of transcriptional regulators that contribute to a gene expression program that modulates apoptosis, autophagy, and amino acid metabolism, including upregulation of select amino acyl tRNA synthetases and amino acid transporters (B’chir et al., 2013; Bunpo et al., 2009; Harding et al., 2000; Harding et al., 2003); (Krokowski et al., 2013). Deletion of GCN2 in mice decreases their viability during prenatal and postnatal development under conditions of nutritional stress, most notably leucine deprivation (Zhang et al., 2002). When challenged with a leucine-free diet for several days, GCN2-null mice lose more body weight than wild type counterparts and a significant proportion perish (Anthony et al., 2004).
Like AMPK, GCN2 has acquired a critical role in controlling feeding behavior in animals. When rodents encounter a food source that lacks a single essential amino acid, they recognize this deficiency and reduce the intake of the imbalanced food (Koehnle et al., 2003). GCN2 activity in the anterior piriform cortex (APC) mediates this behavior. Injection of amino acid alcohol derivatives such as threoninol into the APC increases the levels of uncharged tRNAs and promotes the rejection of diets low in the corresponding amino acid (Hao et al., 2005). Furthermore, mice with full body or brain specific GCN2 deletions fail to reject food depleted of leucine or threonine, unlike wild type counterparts (Hao et al., 2005; Maurin et al., 2005). At the signaling level, ingestion of a meal imbalanced in amino acid composition rapidly elevates phosphorylated eIF2a in APC neurons of wild type, but not GCN2-null mice (Hao et al., 2005; Maurin et al., 2005(Gietzen et al., 2004). The need to adapt feeding behavior to changes in nutrient levels is by no means restricted to animals. Drosophila also sense changes in dietary amino acids and reduce their intake of foods deficient in essential amino acids (Bjordal et al., 2014; Ribeiro and Dickson, 2010; Toshima and Tanimura, 2012; Vargas et al., 2010). As in animals, GCN2 plays a critical role within neuronal circuits to mediate this rejection by repressing GABA signaling within dopaminergic neurons of the brain (Bjordal et al., 2014). Together, these findings point to a role for the detection of uncharged tRNAs by GCN2 in controlling circuits in flies and animals that protect against the consumption of imbalanced food sources.
A separate pathway discussed below, TORC1/mTORC1, evolved in parallel to the GCN2 pathway to sense the availability of intracellular amino acids. The mechanisms for crosstalk between the TORC1/mTORC1 and GCN2 pathways were acquired at least twice during evolution, albeit in opposing directions. While in yeast GCN2 lies downstream of TORC1, it functions upstream of mTORC1 in mammals (Anthony et al., 2004; (Cherkasova and Hinnebusch, 2003; Kubota et al., 2003; Staschke et al., 2010).
TOR/mTOR: Master regulators of growth
Nutrient availability strongly influences the growth of all organisms and starvation conditions can alter developmental programs in both unicellular and multicellular organisms (Oldham, 2000). When faced with nutritional limitation, S. cerevisiae exit the mitotic cycle and enter a stationary phase (Zaman et al., 2008), C. elegans persist for several months in a state of stasis known as dauer larvae (Klass and Hirsh, 1976) and Drosophila postpone their development (Edgar, 2006). Despite the diversity of these organisms, one common pathway, anchored by the target of rapamycin (TOR) kinase, regulates entry into these alternative states in response to environmental cues. Unlike the GCN2 and AMPK pathways, the TOR pathway is unique in that it integrates not a few but many diverse inputs, particularly in mammals. In fact, GCN2 and AMPK both feed into TOR to convey amino acid or energy deprivation, respectively. While we focus on the two major inputs that control mTOR activity - nutrients and growth factors – numerous additional cues converge on it (Laplante and Sabatini, 2012).
The study of TOR began several decades ago with the isolation of a potent antifungal compound from the soils of Rapa Nui, more commonly known as Easter Island. This macrolide, named rapamycin in deference to its site of discovery, garnered clinical and research interest because of its powerful immunosuppressive and anti-proliferative qualities (Morris, 1992; Segall et al., 1986). Genetic studies in yeast led to the identification of TOR1 and TOR2 as key genes mediating rapamycin sensitivity (Cafferkey et al., 1993; Kunz et al., 1993), and biochemical work in mammals revealed the mTOR (mechanistic target of rapamycin) protein as the direct target of rapamycin (Brown et al., 1994; Sabatini et al., 1994; Sabers et al., 1995). mTOR is a serine/threonine protein kinase that responds to a variety of environmental cues, including nutrient, energy, and growth factor levels, as well as diverse forms of stress, to regulate many anabolic and catabolic processes (Howell et al., 2013; Kim et al., 2013; Laplante and Sabatini, 2012).
Unlike most eukaryotes, S. cerevisiae, encode two different TOR proteins, Tor1 and Tor2, which nucleate distinct multi-protein complexes (Helliwell et al., 1994; Loewith et al., 2002). TOR complex 1 (TORC1) consists of Tor1 bound to Kog1, Lst8, and Tco89 and promotes ribosome biogenesis and nutrient uptake under favorable growth conditions. Inhibition of TORC1 by nutrient starvation or rapamycin treatment leads to the activation of macroautophagy and nutrient and stress-responsive transcription factors like GLN3, which is required for the use of secondary nitrogen sources (Jacinto et al., 2004; Wullschleger et al., 2006). TORC2 contains Tor2 bound to Avo1-3, Bit61, and Lst8, is largely rapamycin insensitive, and is thought to regulate spatial aspects of growth, such as cytoskeletal organization (Loewith et al., 2002; Reinke et al., 2004; Wedaman et al., 2003).
Mammals also have two mTOR-containing complexes but only one gene encoding mTOR. mTOR complex 1 (mTORC1) consists of raptor, mLST8, PRAS40, and Deptor (Laplante and Sabatini, 2012) and modulates mass accumulation through the control of many anabolic and catabolic processes, including protein, lipid, and nucleotide synthesis; ribosome and lysosome biogenesis; and autophagy. mTORC2 controls cell proliferation and survival and is further reviewed elsewhere (Jacinto et al., 2004; Oh and Jacinto, 2011; Sarbassov et al., 2004).
The connection between TORC1 and the response to the nutritional state emerged from observations in S. cerevisiae, D. melanogaster, and mammalian cells where TOR inhibition leads to phenotypes akin to those observed under starvation (Barbet et al., 1996; Oldham, 2000; Peng et al., 2002; Zhang et al., 2000). Environmental amino acid levels were found to activate the mTORC1 pathway as measured by the phosphorylation of S6K1 and 4EBP1, two well-known mTORC1 substrates (Hara, 1998; Wang et al., 1998), and to signal independently of the growth factor input to mTORC1 (Hara, 1998; Nobukuni et al., 2005; Roccio et al., 2005; Smith et al., 2005; Svanberg and Moller-Loswick, 1996; Wang et al., 1998)
More recent work showing that the Rag GTPases are necessary and sufficient for mTORC1 to sense amino acids (Kim et al., 2008; Sancak et al., 2008) is beginning to reveal the logic of how the pathway integrates inputs from nutrients and growth factors. What has emerged is a bipartite mechanism of mTORC1 activation involving two distinct small GTPases: first, the control of mTORC1 subcellular localization by nutrients through the Rag GTPases, and, second, the control of mTORC1 kinase activity by growth factors and energy levels through the Rheb GTPases (Zoncu et al., 2011). Both inputs are needed for full activation of mTORC1 as in the absence of either the pathway is off.
The Rag GTPases exist as heterodimers of the related and functionally redundant RagA or RagB bound to RagC or RagD, which are also very similar (Hirose et al., 1998; Schürmann et al., 1995; Sekiguchi et al., 2001). Under nutrient replete conditions the Rag GTPases bind mTORC1 and promote its recruitment to the lysosomal surface where its activator Rheb also resides (Buerger et al., 2006; Saito et al., 2005; Sancak et al., 2008) (Figure 3). The function of each Rag within the heterodimer is poorly understood and their regulation is undoubtedly complex as many distinct factors play key roles. A lysosome-associated molecular machine consisting of the Ragulator and vacuolar ATPase (v-ATPase) complexes regulates the Rag GTPases and is necessary for the sensing of amino acids by mTORC1 (Sancak et al., 2010; Zoncu et al., 2011). Ragulator binds the Rag GTPases to the lysosome and also has nucleotide exchange activity for RagA/B (Bar-Peled et al., 2012; Sancak et al., 2010), but the function of the v-ATPase in the pathway is unknown. Two GTPase activating protein (GAP) complexes, which are both tumor suppressors, promote GTP hydrolysis by the Rag GTPases, with GATOR1 acting on RagA/B (Bar-Peled et al., 2013) and Folliculin-FNIP2 on RagC/D (Tsun et al., 2013). Lastly, a distinct complex called GATOR2 negatively regulates GATOR1 through an unknown mechanism (Bar-Peled et al., 2013). The Sestrins were recently identified as GATOR2-interacting proteins that negatively regulate mTORC1 (Chantranupong et al., 2014; Parmigiani et al., 2014).
Figure 3. Nutrient sensing by the TOR pathway.
A. In the absence of amino acids and growth factors, mTORC1 is inactive. This is controlled by two separate signaling pathways. First, in the absence of amino acids GATOR1 is an active GAP towards RagA, causing it to become GDP bound. In this state, mTORC1 does not localize to the lysosomal surface. Secondly, in the absence of insulin or growth factors, TSC is an active GAP towards Rheb and stimulates it to be GDP bound. B. In the presence of amino acids and growth factors, mTORC1 is active. Amino acids within the lysosome signal through SLC38A9 to activate the amino acid sensing branch. Ragulator is active, causing RagA to be GTP bound. This binding state is reinforced by the fact that GATOR1 in inactive in the presence of amino acids, as GATOR2 inhibits it. The Rag heterodimer in this nucleotide conformation state recruits mTORC1 to the lysosomal surface. In addition, the presence of insulin or growth factors activates a pathway that inhibits TSC, leaving Rheb GTP bound. In this state, Rheb activates mTORC1 when it translocates to the lysosomal surface.
Growth factors and energy levels regulate the Rheb input to mTORC1 (Inoki et al., 2003a; Long et al., 2005) through a heterotrimeric complex comprised of the tuberous sclerosis complex (TSC) proteins, TSC1, TSC2, and TBC1D7, which together act as a GAP for Rheb (Brugarolas et al., 2004; Dibble et al., 2012; Garami et al., 2003; Inoki et al., 2003a; Long et al., 2005; Sancak et al., 2008; Saucedo et al., 2003; Stocker et al., 2003; Tee et al., 2002). Not all unicellular organisms encode all components of the TSC axis. For instance, S. cerevisiae only have a gene for Rheb, and it is not required for growth or viability, unlike TOR itself, suggesting that it likely plays a diminished, if any, role in the TOR pathway in budding yeast (Urano et al., 2000). In contrast, S. pombe, which diverged from S. cerevisiae more than 400 million years ago, encode TSC1, TSC2, and Rheb (Rhb1), whose functions mirror their mammalian equivalents. Rhb1 is essential for growth and it is negatively regulated by TSC1 and TSC2, whose loss results in defects in amino acid uptake and the nitrogen starvation response (Ma et al., 2013; Mach et al., 2000; Matsumoto et al., 2002; Nakashima et al., 2010; Urano et al., 2007; Uritani et al., 2006; van Slegtenhorst et al., 2004)
While in mammals, growth is intimately linked to amino acid availability, yeast are more concerned with the quality and abundance of nitrogen and can uptake and metabolize a host of nitrogen sources, including amino acids which are deaminated to yield ammonia which will rapidly become ammonium in the cell. In yeast, the aforementioned SPS and GCN2 pathways directly or indirectly, respectively, sense amino acid levels but the actual intracellular signal for TORC1 remains less clear (Broach, 2012). Early studies showed that TORC1 is a major regulator of the nitrogen catabolite repression program (Hardwick et al., 1999; Shamji et al., 2000), although later work emphasizes that TORC1 is likely not the sole player regulating this pathway (Broach, 2012). Further studies are needed to ascertain whether TOR is involved in the sensing of an as yet unidentified nitrogen source in yeast.
More recent evidence indicates that TORC1 is involved in amino acid signaling in yeast (Binda et al., 2009; De Virgilio and Loewith, 2006). TORC1 resides on the vacuole, the equivalent of the metazoan lysosome, although it does not shuttle on and off its surface in response to nutrient levels as it does in mammals (Binda et al., 2009). Homologs of the Rag GTPases, Gtr1 and Gtr2, exist in yeast and they associate with a vacuolar docking complex consisting of Ego1 and Ego3, which has some structural similarity to Ragulator (Bun-Ya et al., 1992; Dubouloz et al., 2005; Gao and Kaiser, 2006; Kogan et al., 2010). Yeast also have GATOR1 and GATOR2 equivalents, called SEACIT and SEACAT (Panchaud et al., 2013a, b). SEACIT has been proposed to inhibit TORC1 in response to deprivation of sulfur-containing amino acids, such as methionine and cysteine, and controls glutamine synthesis and consumption (Laxman et al., 2014; Laxman et al., 2013; Sutter et al., 2013). Although TORC1 has been posited to respond to amino acids, constitutively active Gtr1 does not make the TORC1 pathway completely resistant to leucine deprivation, unlike constitutively active RagA/B, which in mammals makes mTORC1 signaling resistant to total amino acid deprivation (Binda et al., 2009; Sancak et al., 2008(Efeyan et al., 2012). Furthermore, the Gtr GTPases are dispensable for growth on glutamine or ammonium (Stracka et al., 2014) and constitutively active Gtr1 fails to rescue the TORC1 signaling defect under ammonium deprivation (Binda et al., 2009). If amino acids signal to TORC1, the mechanisms of its activation are likely to be distinct from those through which amino acids activate mTORC1. For instance, orthologs of Sestrins do not exist in yeast, suggesting divergence in the regulation of the upstream components of the nutrient-sensing pathway.
While many components of the pathway upstream of mTORC1 have been identified, the identity of the amino acid sensor(s) remains elusive. Amino acid sensing could initiate from the extracellular, cytosolic, or lysosomal compartments (Figure 4). The presence of many mTORC1 pathway components on the lysosome suggests that this organelle is more than simply a scaffold surface for mTORC1 activation. Rather, there is the intriguing possibility that lysosomes act as storage sites for amino acids, and that amino acid availability within this compartment is sensed by mTORC1. The storage of nutrients in vacuoles, which is established in yeast, may also occur in mammalian cells as some studies suggest that certain amino acids, like arginine, are highly enriched in lysosomes relative to the cytosol (Harms et al., 1981). A cell free assay revealed that the lysosome itself contains the minimal machinery needed for the amino acid-mediated recruitment of mTORC1 to the lysosomal surface (Zoncu et al., 2011).
Figure 4. Evolution of nutrient sensing with the emergence of multicellularity and compartmentalization.
A. Prokaryotes have two compartments that may contain amino acids: the extracellular space and the cytosol. Amino acid transporters such as the chemoreceptors Tsr and Tar can sense extracellular amino acids. A variety of sensors, including the PII proteins, can detect intracellular amino acids. B. Similar to prokaryotes, yeast sense extracellular amino acids via plasma membrane transporters, such as Ssy1. In addition, they sense cytosolic amino acid availability with sensors like GCN2. Unlike prokaryotes, however, eukaryotes have organelles such as the vacuole, an additional compartment which may contain amino acids. While it has not yet been established if yeast directly sense amino acid levels within the vacuole, they do contain organelles which can act as alternate storage depots for nutrients and are therefore another potential compartment in which sensing may occur. C. In mammalian cells, there are three distinct compartments in which sensing may occur, similar to yeast. First, extracellular nutrients are sensed via transporters, not discussed in detail in this review. In addition, cytosolic amino acids are sensed by the GCN2 pathway. Finally, amino acids stored within the lysosome are sensed by the mTORC1 pathway.
In an “inside-out” model of sensing, a lysosome-based transmembrane protein would be an alluring candidate amino acid sensor. One such protein is SLC38A9, a newly identified Ragulator-interacting amino acid transporter that resides in the lysosomal membrane and is required for arginine sensing by mTORC1 (Rebsamen et al., 2015; Wang et al., 2015). Like Ssy1 of the SPS pathway, SLC38A9 contains an N-terminal extension that appears necessary for the downstream signaling event (Bernard et al, 2001; Wang et al., 2015). In cells lacking SLC38A9 the mTORC1 pathway has a selective defect in sensing arginine, suggesting that SLC38A9 is an attractive candidate to be an arginine sensor (Wang et al., 2015). While the mechanism through which SLC38A9 regulates the mTORC1 pathway remains unknown, this transporter is the best candidate so far identified for reporting the contents of lysosomes to mTORC1 in the cytosol. It is very likely that in addition to sensing lysosomal amino acids, mTORC1 will be found to also sense cytosolic amino acids and integrate information from both amino acid pools.
Perspectives
Nutrient sensors are of diverse structure and function, from membrane spanning transceptors like MEP2 and Ssy1 to the cytosolic kinases AMPK and GCN2. They can directly sense nutrients of interest, such as ammonium by MEP2, or indirectly via a metabolite, such 2-OG by the PII proteins. While direct nutrient sensing will give a good reflection of its overall levels, indirect sensing strategies may allow the sensor to detect each nutrient under specific contexts, such as when flux through the GS/GOGAT pathway is low in the case of the PII proteins.
In eukaryotic cells, the vacuole/lysosome emerged as a nutrient storage compartment and there is increasing evidence that a function of mTORC1 is to sense lysosomal contents and/or function. Although it is unclear if this is true in yeast, the presence of TORC1 on the vacuolar surface suggests it will also be the case in this organism although it is unclear if a homologue of SLC38A9 exists. Many intriguing questions remain concerning nutrient sensing by mTORC1/TORC1. Does the pathway sense all amino acids, or are there particular single amino acids or combinations that are especially important? It is already known that leucine or arginine withdrawal inhibits mTORC1 signaling almost as well as total amino acid deprivation in a few cell lines in culture (Hara, 1998) but how true is this in vivo or in diverse cell types? Furthermore, could other Rag-independent mechanisms be involved in relaying amino acid signals to mTORC1? A recent work revealed that in mammalian cells, glutamine, unlike leucine, signals to mTORC1 in a v-ATPase dependent but Rag GTPase independent manner (Jewell et al., 2015). Are different amino acids differentially important in the cytosol versus lysosome? The lysosome is enriched for basic amino acids, hinting that these amino acids may matter more than others in sensing that initiates from this organelle (Harms et al., 1981), which is consistent with the specific defect of cells lacking SLC38A9 in sensing arginine (Wang et al., 2015). Finally, how well conserved the sensors are between organisms will hint at how different or similar the amino acid and nutrient inputs are that drive mTORC1/TORC1 signaling in diverse organisms.
Acknowledgments
We thank Zhi-Yang Tsun for insightful input and Tom DiCesare for assistance with figures. This work was supported by grants from the NIH (R01 CA103866 and AI47389) and Department of Defense (W81XWH- 07-0448) to D.M.S. and fellowship support from the NIH to L.C. (F31 CA180271), and to R.L.W. (T32 GM007753). D.M.S. is an investigator of the Howard Hughes Medical Institute.
Contributor Information
Lynne Chantranupong, Whitehead Institute for Biomedical Research and Massachusetts Institute of Technology, Department of Biology, 9 Cambridge Center, Cambridge, MA 02142, USA.
Rachel L. Wolfson, Howard Hughes Medical Institute, Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
David M. Sabatini, Koch Institute for Integrative Cancer Research, 77 Massachusetts Avenue, Cambridge, MA
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