Phosphorylation at specific residues can activate a protein, lead to its localization to particular compartments, be a trigger for protein degradation and fulfill many other biological functions. Protein phosphorylation is increasingly being studied at a large scale and in a quantitative manner that includes a temporal dimension. By contrast, structural properties of identified phosphorylation sites have so far been investigated in a static, non-quantitative way. Here we combine for the first time dynamic properties of the phosphoproteome with protein structural features. At six time points of the cell division cycle we investigate how the variation of the amount of phosphorylation correlates with the protein structure in the vicinity of the modified site. We find two distinct phosphorylation site groups: intrinsically disordered regions tend to contain sites with dynamically varying levels, whereas regions with predominantly regular secondary structures retain more constant phosphorylation levels. The two groups show preferences for different amino acids in their kinase recognition motifs - proline and other disorder-associated residues are enriched in the former group and charged residues in the latter. Furthermore, these preferences scale with the degree of disorderedness, from regular to irregular and to disordered structures. Our results suggest that the structural organization of the region in which a phosphorylation site resides may serve as an additional control mechanism. They also imply that phosphorylation sites are associated with different time scales that serve different functional needs. Cells employ protein phosphorylation – the addition of a phosphate group to serine, threonine or tyrosine residues – as a key regulatory mechanism for modulating protein function. Proteomics technologies can now quantify thousands of phosphorylation sites to reveal the dynamics of phosphorylation at each site in response to a biological process. It is known that phosphorylation does not occur randomly with regard to a protein's structure, but so far the relationship between the dynamics of phosphorylation and these structural properties has not been investigated. Here we relate the relative levels of phosphorylation for more than 5,000 sites through the cell cycle to the predicted structural features of the vicinity of the sites. We find that dynamic phosphorylation tends to occur in disordered regions, whereas phosphorylation sites that did not vary as much over the cell cycle are often located in defined secondary structure elements. Kinases that prefer charged amino acids in their substrate motives are more often associated with unchanging sites whereas proline-directed protein kinases phosphorylate cell cycle regulated sites in disordered regions more frequently. The structural organization of the region in which a phosphorylation site resides may therefore serve as an additional control mechanism in kinase mediated regulation. Phosphorylation is a ubiquitous post-translational modification that is known to be important for the regulation of a myriad of cellular processes, among which are cell growth, apoptosis, differentiation, signal transduction and transport Given the availability of these data, much research has been devoted to analyzing and understanding the structural features of phospho-sites. This includes creation of online resources containing structural information The main challenge in studying structural properties of phospho-sites from experimental data is their preference for unstructured regions Since phosphorylation events both depend on the structural environment and influence its properties, protein structure and phosphorylation should be considered interrelated and mutually dependent. On one hand, disorder facilitates the access of a kinase to the residue to be modified. On the other hand, the addition of a phosphate moiety may lead to structural changes. Both order-to-disorder and disorder-to-order transitions upon phosphorylation have been observed in nature or studied via molecular dynamics simulations et al., which elucidated phosphorylation site occupancy during mitosis et al. clustered sites according to their distinct phosphorylation patterns and similarities in regulation with the aim to infer each site's functional importance. Here, in contrast, we focus on structural properties of the phosphorylation sites and, for the first time, distinguish between two groups of sites with respect to the overall variation of phosphorylation over time.Although numerous previous studies have focused on structural properties of phosphorylation sites We find that sites that lie within regular secondary structures exhibit less variable phosphorylation fold changes during the cell cycle than sites that are found in disordered regions. Analysis of the amino acid composition of the flanking regions of these two groups of sites revealed enrichment of positively charged residues and depletion of disorder-related residues such as proline, serine and threonine in the former group.et al. investigation Using the data from the Olsen We sought to investigate a possible relation between the structural organization of the environment in which a modified residue is found and the experimentally measured changes in phosphorylation during the cell cycle. To do so, we compared the phosphorylation variation of two groups of sites. These two groups were composed of sites that reside in ordered regions and sites that lie within disordered regions as predicted with DISOPRED Our results revealed notable differences in the distributions of phosphorylation variations of the two sets . The sites associated with structurally characterized regions were found to exhibit smaller changes in phosphorylation during the cell cycle (median 1.77) as compared to sites located in disordered regions : ‘ordered coils’ are much shorter on average as they mainly correspond to turns and short loops connecting regular secondary structures. By contrast, ‘disordered regions’ are longer and represent large protein regions lacking defined structure , irregular structures (predicted as coil and ordered), and disordered regions (predicted as coil and disordered) . We founi.e. low and high variation) come from the same distribution. We found statistically significant enrichment of charged amino acids and depletion of proline, serine and threonine in the surrounding of sites with small phosphorylation variability . Additional comparisons of the amino acid distributions of the two sets against a background distribution accounting for structural differences using the composition profiling technique We wanted to investigate if sites with distinct phosphorylation patterns over the cell cycle differ not only according to structural context, but also with respect to the amino acid content in their local sequence environment. A two-sample logo The enrichment of serine and threonine residues in the vicinity of the detected phosphorylation sites could correlate with additional modification events. To check this hypothesis, we determined if multiple phosphorylation sites are found with higher preference in disordered regions. Phosphorylation sites that had at least one neighboring phosphorylation site in both ordered and disordered regions were compared. A ‘neighbor’ was defined as any phosphorylated residue that lies within +/−1,2,3,4, or 5 residue-long flanking region of a given modification site. Regardless of which of these five cut-offs was chosen, multiple phosphorylation sites were always highly significantly enriched in disordered regions .et al.Next, we were interested in potential differences in evolutionary constraints on the phospho-sites in structured and disordered regions. When analyzing conservation it is important to take into account the different evolutionary rates of disordered and ordered regions. We therefore compared conservation scores between phosphorylated serines, threonines and tyrosines with ‘control’ serine, threonine and tyrosine residues with a similar structural background. We define the set of ‘control’ residues, as all potential phosphorylation sites that were not found to be phosphorylated in the study of Olsen As expected, phospho-sites that were predicted to lie in regular regions appeared significantly more conserved than phospho-sites in disordered regions , due to the more conserved structural background of the former . In agreWe next asked if different groups of kinases would exhibit preferences for less variable or highly variable phosphorylation sites. To identify kinase recognition motifs that show similar behavior with respect to two variables – protein disorder and phosphorylation variation, we used the recently described 2D Annotation Enrichment technique see . It emplThe class of tyrosine kinases shows a strong preference for low phosphorylation variability and structured regions, whereas the other three classes favor more disordered regions, but span a wider range of phosphorylation variation values. Also among the latter three groups higher quantitative variability is clearly associated with higher disorder. As seen in The proline-related class represented by two acidophilic, one basophilic and one atypical protein kinases shows preferences for intermediate level of disorderedness and phosphorylation variation properties. The Casein kinase II is characterized by various substrate recognition motifs Proline-directed kinases such as PLK1 are known to actively regulate the progression of the cell division cycle, thus implying that disordered regions (which are enriched for prolines) are subjected to regulation and therefore to variable phosphorylation patterns. We therefore checked if the tendency of phosphorylation variability to scale with the level of disorder persists if we control for proline-directed kinases and excluded all sites modified by such from the data set. Indeed, the effect of lower phosphorylation variability being associated with ordered regions and higher - with disordered regions remained the same.Previous studies had already found a preference of phosphorylation to occur in loops or disordered regions et al. defined regions with no regular secondary structures (NORs) as one specific category of disordered regions. They demonstrated that NORs differ significantly from regular structured loops and argued that these might have different functional implications, a hypothesis which finds support in our study.Interestingly, the sets of sites within ordered loops and disordered structures showed significant differences. It has been shown before that different flavors of disordered regions exist with regards to their lengths, amino acid composition, and the conformational transitions that they undergo upon binding Functional analysis of the highly variable set of sites revealed enrichment of cell cycle-related, biosynthesis and cellular organization and localization processes . Some exPhosphorylation is an important mechanism for regulation of a myriad of intricate processes during cell division. A detailed study of the cell cycle regulation through phosphorylation focused on functional analysis of protein groups that are up or down regulated at specific time points et al. found proteins that regulate metabolic processes to be weakly phosphorylated during S phase and highly phosphorylated at mitosis. An explanation to this discovery is the possibly inhibitory character of phosphorylation on proteins that regulate metabolic processes, as protein synthesis and related functions tend to shut down during mitosis. Furthermore, DNA replication takes place during S phase, which rationalizes the up-regulation through phosphorylation of various proteins involved in DNA replication repair. High phosphorylation of cytokinesis-related proteins in S phase appears to play an important role in the control of the correct segregation of the two daughter cells.Interestingly, Olsen The tendency of modification sites in regular structures to be less variable may be facilitated by proximal charged residues acting as stabilizers of the phosphate group. Charged flanking regions offer a suitable environment for hosting a phosphate group and allow for favorable interactions that potentially result in phosphorylation acting on a longer time scale. For instance, these favorable interactions could reduce the efficiency of phosphatases in removing a phosphate group, thereby contributing to the tendency for smaller variation in the phosphorylation level that we observe in our data. In contrast, negatively charged residues could lead to repulsion-driven conformational changes and polarization of the entire protein surface by creating clusters of negatively charged residues.Several mechanisms that are known from literature furthermore contribute to the observed tendency for structural rather than regulatory phosphorylation sites to be present in ordered regions. Specific structural changes due to phosphorylation include stabilization of the N-termini of α-helices via favorable interactions of the added phosphate group with the helix backbone Multiple experimental studies show the regulatory role of modification sites that show variation in their phosphorylation patterns and lie within intrinsically disordered regions For example, the cyclin-dependent kinase inhibitor 1B (p27) is an intrinsically unstructured protein, which is multiply phosphorylated and regulates the cell cycle by inhibition of cyclin-dependent kinases (CDKs) In another example, multiple phosphorylation sites on the transcription regulator Retinoblastoma protein (Rb) influence its ability to interact with transcription factors and other regulatory proteins. A detailed structural study reports that the different phospho-sites found within disordered regions induce distinct conformational changes and also serve different functional roles We found that the set of sites with varying phosphorylation patterns was enriched in amino acids associated with disorder, specifically Pro, Gly and Ser. Interestingly the same sites were more likely to have additional modified residues in their vicinity. Phosphorylation of a protein often occurs at several distinct residues and it has been reported that modification sites tend to cluster and function in a cooperative manner We showed that phosphorylated residues tend to be more conserved than their equivalent non-modified residues. Conservation of phosphorylated residues has been a broadly debated issue The idea that it is the cluster of phosphorylation sites that plays a functional role is becoming increasingly accepted Here we showed that disordered regions harbor variable sites, which tend to be surrounded by additional phosphorylated sites. This raises the possibility that the variability of these sites is related to some of the above-described phenomena. It is known that disordered regions can facilitate a large number of interaction partners, and that multiple sites can control their association and dissociation. Given the wide range of functions of multiple phosphorylated sites in disordered regions, a larger variability in their phosphorylation patterns may provide an adequate functional mechanism to effect the desired regulation. In contrast, structural regularity imposes certain constrains on the less variable sites. The necessity of evolutionary conservation of the structure tends to prevent the accumulation of disorder-associated serine and threonine residues and a consequent change of their positions. Furthermore, the more rigid structure implies a more limited number of interactions partners. Therefore, we reason that the requirement for regulation for these sites in structured regions can be smaller.Our data allowed us to investigate the kinase preferences of phosphorylation sites with high vs. low levels of regulation. Tyrosine kinases and kinases that require charged residues in their substrate recognition motives clearly preferred sites with smaller phosphorylation variation, whereas proline-directed kinases were clearly associated with sites that were dynamically regulated. Proline is known to be a helix and sheet breaker, due to the planarity of its side-chain. Proline lacks an NH backbone donor to form a hydrogen bond and thus disrupts the formation of regular hydrogen bond patterns, which are the basis of regular structure formation. Due to its unique stereochemistry the proline residue can adopt two different conformational states – cis and trans – and a large number of folded proteins contain both states of the residue. The intrinsic conformational changes resulting from the proline isomerization play an important role in determining the function, ligand recognition and interactions of the protein Our results highlight the central role of proline, as a disorder-promoting residue that is also part of regulatory motifs In conclusion, we have related the tendency of phosphorylation sites to be dynamically regulated throughout the cell cycle with the structural features of the sites. While we have found clear relations between phosphorylation dynamics and protein structure, we are only scratching the surface of what we believe could be an exciting new area at the interface of proteomics and structural biology.i.e. synchronized heavy-labeled cells in S phase and non-synchronized medium-labeled cells). In order to account for the possible influence of protein abundance, changes in the phosphorylation ratios between the reference and the stimulated cells were normalized by the protein change. We mainly focused on the phosphorylation ratios as they were available for a larger number of sites compared to the absolute occupancy values.In the data set underlying our analysis The data set contained information about the UniProt id of the phosphorylated protein, sequence positions of phosphorylated residues, and quantitative measures of phosphorylation  at 6 time points . In total 1,059 proteins and 5,173 phosphorylation sites with measured phospho-ratios for each of the six time points of the cell cycle were used in the analysis.i.e. the one containing information about all six time points) was found.In order to assure that the observed phenomena are not due to the properties of the chosen subset of sites, we repeated the analysis of phosphorylation variation between different structural groups with data sets containing five , four , and three  time points only , while low variation describes those sites that retain constant or slightly variable phosphorylation fold change during the cell cycle.The secondary structure of each site was predicted with PsiPred An intrinsic disordered state was also predicted for each site using DISOPRED Based on a combination of secondary structure and disorder predictions, we defined three distinct structural categories for each phosphorylated site: (i) regular regions , (ii) irregular regions , and (iii) disordered regions .lattice package was utilized for comparing distributions of phosphorylation variation in different structural categories. Differences between distributions were assessed with the standard non-parametric Kolmogorov-Smirnov test. In the case of three structural categories, analysis of variance of the phosphorylation fold change was performed using the structural category as an independent variable. Data on phosphorylation site variation and structure predictions are available in the Supporting material Click here for additional data file.Table S2Data set of phosphorylation variations and structure predictions.(XLS)Click here for additional data file.Text S1Additional analysis.(DOCX)Click here for additional data file.


Drosophila and mammals have defined a conserved core Hippo signalling module, composed of members of the Ste20-like kinase, the MOB co-activator and the AGC kinase families. In Drosophila, stimulated Hippo kinase phosphorylates and thereby activates the Mats/Warts complex, which consequently phosphorylates and inactivates the transcriptional co-activator Yorkie. In mammals, the counterparts of the Hippo/Mats/Warts/Yorkie cascade, namely MST1/2, MOB1A/B, LATS1/2 and YAP/TAZ, function in a similar fashion. These canonical Hippo pathways are so highly conserved that human MST2, hMOB1A and LATS1 can compensate for the loss of Hippo, Mats and Warts in flies. However, recent reports have shown that Hippo signalling is more diverse and complex, in particular in mammals. In this review, we summarize our current understanding of mammalian LATS1/2 kinases together with their closest relatives, the NDR1/2 kinases. The regulation of the LATS/NDR family of kinases will be discussed, followed by a summary of all currently known LATS/NDR substrates. Last, but not least, the biological roles of LATS/NDR kinases will be reviewed with specific emphasis on recent discoveries of canonical and non-canonical LATS/NDR functions in the extended Hippo pathway.The metazoan Hippo pathway is an essential tumour suppressor signalling cascade that ensures normal tissue growth by co-ordinating cell proliferation, cell death and cell differentiation. Over the past years, various genetic and biochemical studies in  Drosophila, the stimulated Ste20-like Hippo kinase phosphorylates and thereby activates a complex composed of Mats (mob as tumour suppressor) and the AGC Warts kinase. The Mats/Warts complex then phosphorylates and inactivates the transcriptional co-activator Yorkie. In mammals, the counterparts of the Hippo/Mats/Warts/Yorkie cascade, namely MST1/2 , MOB1A/B, LATS1/2 (large tumour suppressor 1/2) and YAP/TAZ, function in a similar fashion. While all core Hippo components upstream of Yorkie have been defined as tumour suppressors in flies, Yorkie displays proto-oncogenic properties[The Hippo tumour suppressor pathway regulates cell proliferation, cell death and cell differentiation in multicellular organisms to ensure normal tissue development,2. The foperties. In mammoperties, MOB1A/Boperties, or LATSoperties results operties. Therefooperties,11. Sincoperties, we willoperties.Drosophila Warts and mammalian LATS1/2 kinases are members of the serine/threonine AGC class of protein kinases[ kinases. More sp kinases. Like ot kinases. TherefoDrosophila, Warts and Tricornered  were discovered more than 10 years ago[In budding and fission yeast, the LATS/NDR kinases Dbf2p and Sid2p were described as central members of MEN/SIN signalling which is essential for proper mitotic exit, while tears ago-17, and ears ago,18. Signears ago,20, stroears ago. In 2002ears ago. Howeverears ago-26, demoears ago. The samears ago. Next, tears ago, and theears ago. These sears ago,29, whicDrosophila community has continued to discover positive and negative regulators of Hippo signalling, which has been reviewed in detail recently[Drosophila Salvador is not conserved in mammals[Drosophila and mammals[Drosophila genetics still supports a linear Mats/Warts/Yorkie cascade downstream of Hippo[Since these discoveries were published nearly a decade ago, the recently. Based orecently,31 and Yrecently,33, resprecently. However mammals. This mo mammals, and Bos mammals. Neverthof Hippo. In lighin vitro[In spite of the fast progress with deciphering Warts and LATS1/2 functions in flies and mammals, the mechanism of NDR1/2 regulation by phosphorylation currently must serve as a model for LATS1/2 regulation,37. Therin vitro and treain vitro,41,47. Nin vitro,47, suggImportantly, these regulatory mechanisms are more complicated in mammalian cells. MST1/2 kinases also phosphorylate hMOB1A/B on Thr12 and Thr35, thereby increasing the affinity of hMOB1A/B towards NDR1/2. MoreoveDrosophila[LATS1/2 also contain the two conserved key regulatory phosphorylation sites of AGC kinases, the Ser909/872 AS and Thr1079/Thr1041 HM, respectively,49. Likerosophila, suggestrosophila. In summBesides these regulatory AS and HM phosphorylations, LATS1/2 kinases are controlled by additional phosphorylation events (Table Besides the regulatory protein-protein interaction (PPI) between hMOB1A/B and LATS1/2 kinases, mammaliAs already mentioned, LATS1/2 phosphorylation of YAP/TAZ is a key event of the canonical Hippo pathway Tables . LATS1/2Not surprisingly, LATS1/2 have additional substrates in mammalian cells Tables . LATS1 pin vitro[in vivo phosphorylation of YAP by NDR1/2 has not been documented so far. Intriguingly, two of three NDR1/2 substrates are also phosphorylated on the HXRXXS/T motif  is larval lethal[In l lethal,17. In cl lethal, while Ll lethal,110. Howl lethal, and imml lethal,110, indl lethal. More spl lethal. LATS1/2l lethal,113, sinl lethal or heartWhile studies of tissue specific ablation of LATS1/2 function in animals are still limited in number, the roles of LATS1/2 as major regulators of the YAP/TAZ proto-proteins are well established. MoreoveThis last point is also supported by studies of breast cancer patients, which currently suggest that YAP might have oncogenic and tumour suppressive functions dependent on the breast cancer subtype. Now a sSignificantly, LATS1/2 signalling could play a further role in mammalian stem cells,120. YAPWhatever the case might be in cancer and stem cells, in mostly normal human cell lines (in particular HEK293 and MCF10A cells) LATS1/2 function downstream of G-protein-coupled receptors (GPCRs) as central controllers of YAP/TAZ activities,124. MorDrosophila[EGF  signalling seems also to be able to regulate Hippo signalling in MCF10A cells, which irosophila. Howeverrosophila,124. In rosophila. The Kolrosophila,129. MSTrosophila. Moreoverosophila. LATS1/2rosophila,127. TakWhile the activation mechanism of NDR1/2 is much better understood than the one of LATS1/2, much less is known about the biological functions of NDR1/2. NDR1 KO mice are viable, but develop T-cell lymphoma, most likely due to defective pro-apoptotic signalling. NDR2 KONDR1 functions additionally in apoptotic signalling,60,131, As already mentioned NDR1/2 kinases play a part in centrosome biology, most likely by associating with centrosomes,102,133.Drosophila and human cells F-actin remodelling alters Hippo signalling[In particular, the actin cytoskeleton has recently gained more attention in the Hippo community. In gnalling. Piccolognalling. Signifignalling. The Sasgnalling. In suppgnalling. Moreovegnalling,125. BasDrosophila, mutation of Warts results in altered F-actin levels[Intriguingly, it has been reported that LATS1 can bind to actin and inhibit actin polymerisation. Moreoven levels, suggestn levels, becausen levels. Howevern levels. In summWhile the involvement of LATS/NDR in the regulation of the actin cytoskeleton is yet to be elucidated in more detail, it is undisputed that YAP/TAZ function as sensors and mediators of mechanical inputs coming from the cellular architecture and microenvironment. Besides F-actin remodelling, changes in the microtubule cytoskeleton should also to be considered in future studies, since the Guan laboratory could already show that LATS1/2 activity is modulated by anti-microtubule drugs. It is nFuture research is further needed to decipher how LATS1/2 are regulated by hMOB1A/B and MST1/2, since currently the mechanism of NDR1/2 regulation by phosphorylation must serve as the model for LATS1/2 regulation. NDR1/2 are mainly controlled (1) by binding of hMOB1A/B to the NTR of NDR1/2 triggering auto-phosphorylation of NDR1/2 on the AS, and (2) by phosphorylation of NDR1/2 by MST1/2/3 on the HM. Phosphorylation of LATS1/2 on the conserved AS and HM regulatory sites is also essential for LATS1/2 kinase activity, but the molecular regulatory mechanisms of these phosphorylation events are currently not understood. The regulation of LATS/NDR activities is even more complex in cells, since MST1/2-mediated phosphorylation of hMOB1A/B influences hMOB1/LATS and hMOB1/NDR complex formation. In addition, changes in subcellular localisation, additional phosphorylation events, and competition between activating and inhibitory factors for kinase binding influence LATS/NDR activities. Furthermore, MST1/2 signalling is dispensable for LATS/NDR phosphorylation in selected cell types and biological functions, indicating that additional upstream kinases of LATS/NDR need to be studied in the future. In this context, it is worth mentioning that McCollum and colleagues recently reported that the activities of the yeast LATS/NDR kinases Sid2 and Orb6 are cross-regulated by Sid2 phosphorylating Nak1, the upstream Hippo kinase of Orb6 in yeast. This raTo date, the best characterised LATS1/2 function is the regulation of YAP/TAZ by phosphorylation, thereby playing a crucial role in mammalian cancer and stem cell biology. In canonical Hippo signalling LATS1/2 phosphorylate YAP/TAZ on Ser127/89 and Ser381/311, respectively, thereby controlling YAP/TAZ on two levels, namely Ser127/89-mediated spatial regulation and Ser381/311-mediated temporal regulation. However, LATS1/2 also function in non-canonical Hippo signalling and even in Hippo independent pathways, thereby playing roles in Ras/Raf-1 signalling, the regulation of p53, and cell cycle progression. In contrast to LATS1/2, NDR1/2 functions have only recently been reported, proposing that NDR1/2 function in the regulation of cell cycle progression, centrosome biology, stress/apoptotic signalling, and neuronal dendrite/synapse formation. The recently reported mitochondrial role of Trc will potYAP: Yes-associated protein; TAZ: Transcriptional co-activator with PDZ-binding motif; MST: Mammalian Ste20-like serine/threonine kinase; MOB: mps one binder; Mats: mob as tumour suppressor; AGC: Protein kinase A (PKA)/PKG/PKC-like; LATS: Large tumour suppressor; NDR: Nuclear dbf2 related; STK38/STK38L: serine/threonine kinase 38/38L; Trc: Tricornered; NTR: N-terminal regulatory domain; AS: Activation segment motif; HM: Hydrophobic motif; MEN: Mitotic exit network; SIN: Septation initiation network; OA: Okadaic acid; PP2A: Protein phosphatase type 2A; KO: Knock-out; DKO: Double knock-out; PPI: Protein-protein interaction; MYPT1: Myosin phosphatase-targeting subunit 1; Rab8: Guanine nucleotide exchange factor (Rabin 8); AP-2: Associated kinase-1 (AAK1).The author declares that he has no competing interests.


We explore a framework to model the dose response of allosteric multisite phosphorylation proteins using a single auxiliary variable. This reduction can closely replicate the steady state behavior of detailed multisite systems such as the Monod-Wyman-Changeux allosteric model or rule-based models. Optimal ultrasensitivity is obtained when the activation of an allosteric protein by its individual sites is concerted and redundant. The reduction makes this framework useful for modeling and analyzing biochemical systems in practical applications, where several multisite proteins may interact simultaneously. As an application we analyze a newly discovered checkpoint signaling pathway in budding yeast, which has been proposed to measure cell growth by monitoring signals generated at sites of plasma membrane growth. We show that the known components of this pathway can form a robust hysteretic switch. In particular, this system incorporates a signal proportional to bud growth or size, a mechanism to read the signal, and an all-or-none response triggered only when the signal reaches a threshold indicating that sufficient growth has occurred. A large number of proteins in the cell are modified post-translationally by phosphorylation at multiple specific locations. This can help bring about interesting dynamical behaviors such as bistability or all-or-none responses to stimuli. Such behaviors are in turn important for cellular decision-making, differentiation, or the regulation of cellular processes. In this paper we propose the use of a specific technique for modeling allosteric multisite proteins, which can be thought of as the reduced version of a more detailed set of reactions. After validating this technique computationally by comparison to more detailed systems, we apply it to a new model of a signal transduction pathway with several multisite proteins. The model is concerned with a mechanism in budding yeast that is thought to measure the extent of daughter bud growth and send a signal to initiate mitosis when sufficient growth has occurred. Using the given framework we derive an analytically tractable model that creates the desired all-or-none signal. Overall, we give quantitative support to a newly discovered biochemical pathway, and we show the utility of the new modeling framework in the context of a realistic biological problem. Protein phosphorylation is a common form of post-translational modification frequently used in nature to alter protein activity, for instance by changing the electrostatic properties of the protein or its spatial structure. The phosphorylation of the same protein at multiple different aminoacid residues is also very common, and it is found in proteins such as p53 The differences in the function of single-site vs. multisite phosphorylation are not completely understood. Many multisite proteins are involved in regulatory processes that can benefit from the presence of bistability, hysteresis, or limit cycles, which require sufficiently nonlinear interactions in addition to the right type of feedback On the other hand, such detailed multisite mechanisms are normally not used as part of actual mathematical models of biochemical interactions. This is because explicitly modeling multiple sites usually involves the introduction of numerous variables, one or more for each phosphorylation state, and realistic models are often too complex already to justify this additional effort. Systems that attempt to model biochemical reactions explicitly often use the assumption that the protein has two states, one active and one inactive, with a simple reaction to transform one into the other, effectively assuming that the protein only has one site. Other models are more phenomenological in nature and include, for example, Hill function terms in the equation that are less clearly tied to the actual biochemical reactions In this paper we describe a simple mechanistic approach for modeling multisite allosteric proteins. This approach, named modified fraction (MF) modeling, is capable of describing ultrasensitive dynamics without introducing a large number of additional variables. Under this framework one keeps track of the fraction of modified sites in the protein, and the concentration of active protein over time is estimated from this information. The protein is activated in a way that requires the phosphorylation of several but not all of the sites. The approximation becomes increasingly precise as the number of sites increases, with good estimates already for around four or more sites. In a sense, this mechanism can be considered a one-variable, quasi-steady state reduction of a model similar to the Monod-Wyman-Changeux allosteric system Perhaps the best way to test the versatility of a modeling tool such as the one proposed is to implement it in an actual biochemical system. In the current work we describe a detailed mechanistic model of a cell size checkpoint. Cell size checkpoints halt the cell cycle at specific points until sufficient cell growth has occurred The MF approximation equation was first developed in In the first two We start by describing the assumptions on our model in the context of multisite phosphorylation . Suppose that a protein substrate Suppose that the phosphorylations lead to the concerted, redundant activation of the protein. That is, multiple phosphorylations are necessary for activation (concerted), and not all sites need to be phosphorylated for full activation (redundant). We define the activity function There are many systems that likely fall within this general framework. For instance, Ste5 is a scaffold protein in budding yeast with active protein asAccording to the modified fraction framework, we estimate the concentration of a particular protein state from the overall fraction of modified sites. For instance, if the protein has A timescale decomposition argument can be made to use this approximation away from steady state. If It is necessary to calculate the fraction of phosphorylation That is, As for the activity function See also In A validation of the performance of this model for Using this multisite model, we now derive parameters for a corresponding MF model. For instance, one can define the ‘average’ phosphorylation rate at a given phosphorylation site, regardless of whether the protein is active or inactive, At any given time, the active protein concentration of the full model is defined as For comparison, we also plot the behavior of an overly simplified but all too commonly used model, in which the substrate is assumed to have a single phosphorylation site instead of We carried out a calculation of the distance between be small . See alsIt is worth comparing this methodology with the approach known in the literature as rule-based modeling, where a series of chemical reactions is defined using a streamlined algorithm, and high-powered computing is used to handle the resulting large number of variables; see e.g. BioNetGen It is interesting that the MWC model can actually be described in terms of rule-based modeling. In In this section, we will embed the MF system within increasingly complex systems of equations. We consistently use upper case for proteins and lower case for modified fractions of sites. However, we will first provide some technical experimental background regarding this specific pathway.Any theory for cell size checkpoints should ideally account for several mechanistic features. First, cell size checkpoints should translate growth into a proportional checkpoint signal. Second, they should read the signal to detect when it reaches a threshold that indicates when sufficient growth has occurred. Finally, when the threshold is reached the checkpoint should trigger a switch-like cell cycle transition. All of these mechanisms should be robust and adaptable to function in cells of diverse size and shape, and under conditions of fluctuating growth rates.It was recently hypothesized that the timing of the polar to isotropic growth transition described in the introduction is controlled by a mitotic cell size checkpoint. Mitotic cell size checkpoints are controlled by Wee1 and Cdc25 Signaling is thought to be initiated by delivery of the GTPase Rho1 to the site of membrane growth. Rho1 is delivered by vesicles that are sent to the bud and fuse with the membrane to increase its size Cdc55 that includes the Cdc55 regulatory subunit Regarding the downstream component in We can now analyze a model involving two different multisite proteins, Zds1 and PP2A, each of them described according to the MF framework. This forms the downstream component of a larger model for the signal transduction of Rho1, and it is described inside the lower dashed rectangle in The activity of each of the two proteins can be modified through phosphorylation and dephosphorylation, and both proteins bind together to form a dimer. Only the dimer configuration of these molecules is active as an enzyme, and only to the extent that the Zds1 and PP2A components have been modified appropriately through phosphorylation or dephosphorylation. Moreover, as shown in the figure and justified by experimental data, the active dimer is itself involved in the modification of the Zds1 protein.Denote by Now, following the argument in the previous section and given that both Zds1 and PP2A have been found to have 5 to 10 phosphorylation sites each, we keep track of dephosphorylated Zds1 sites, while Since Zds1 is activated through dephosphorylation, here See  helpful . As  incGiven a solution for One can interpret this graph in the following way. There is a positive feedback loop in the system consisting of Zds1 promoting its own activation via dimerization with PP2A. This positive feedback allows the possibility of two stable steady states in the system. When In a similar way as it was carried out for the interaction between Zds1 and PP2A, one can study the activation of Rho1 and its binding with Pkc1. This upstream system includes all the variables and interactions that are not in the Zds1/PP2A module. Once again following the biological evidence and the diagram in For the study of this subsystem, Notice that Rho1 needs to be active to bind with Pkc1. However active Rho1 binds with Pkc1 regardless of the activity or inactivity of the latter. Pkc1 does need to be active in order for the dimer to become active as a kinase, so that Once again, one can carry out a complete mathematical analysis of this multi-dimensional system at steady state and essentially reduce its solutions to one equation for The bifurcation graph can be interpreted as follows. For all but small values of the PP2A/Zds1 dimer In order to find the steady states of both subsystems together, recall that each one can be reduced to a single equation, so that the steady states correspond to the joint solution of the two equations. For fixed Although it is natural that an increase in the Rho1 flow can eventually trigger the activation of the pathway, the main focus here is not in the flow but in the overall Rho1 concentration at the bud tip. Given that Rho1 has a rate of growth proportional to Let's look at how the system has a hysteretic response for increasing values of the flow signal In Since both the downstream  switch and the upstream  switch are driven by positive feedback loops, it is valid to ask which of the two loops is more relevant for the overall system behavior. We argue that it is the downstream loop that is more essential, using the bifurcation analysis in Notice that this system contains the standard elements of a signal transduction pathway, including an initiating signal (vesicles), a sensor (Rho1), a series of transducers , and an effector (active Zds1/PP2A). Total Rho1 is a proxy for the membrane concentration, even if bud growth slows for a period of time, and the cascade of reactions allows the signal to be transduced from the membrane to Zds1/PP2A and ultimately the cyclin dependent kinase. To ensure the high fidelity of the signal transmission In this paper we have introduced a simple and compact framework to describe the dynamics of allosteric multisite phosphorylation systems, and we have applied this tool to a new molecular model of a size checkpoint in budding yeast. Multisite phosphorylation modeling can be problematic because ignoring the multiple sites can have significant effects in the dynamics, while introducing many auxiliary phosphoform variables can be cumbersome in more realistic models. The modified fraction approach is intuitive and flexible (model the sites instead of the protein), and it only introduces one additional variable per protein.The components of the MF model, namely the function There are several reasons why the MF method might be particularly suitable for modeling many multisite phosphorylation systems. Nonsequential phosphorylation is likely more common in nature than the more often modeled sequential systems, since enforcing sequential phosphorylations would require an additional mechanistic effort. Bioinformatic data suggests that most phosphorylation sites in multisite proteins are located in unstructured and unconserved protein regions One of the best known mechanisms for ultrasensitive dose responses is zero-order ultrasensitivity, as suggested by Goldbeter and Koshland In the case of the checkpoint pathway, the active proteins Pkc1 and PP2A have been found to have an approximate More generally, in cell regulatory networks there is a need to implement nontrivial dynamics such as bistable switches and hysteresis, which requires some form of nonlinear response in addition to the right feedback interconnections. It has been observed that several regulatory proteins have multiple phosphorylation sites, and there are many open questions regarding their intended function. Together with the onerous nature of modeling several multisite proteins using sequential networks and multiple variables each, it can be seen why a one-variable reduction such as MF can allow for much-needed simplicity.The actual mechanisms regulating the interactions between cell size and cell division remain largely unanswered in many cases. This has left few alternative options apart from somewhat heuristic approaches in otherwise very detailed models, see e.g. The MF framework eliminates several parameters such as the number of phosphorylation sites Since it is assumed in the derivation of the formula (1) that the sites are roughly independent from each other, one might think that the MF framework doesn't work for allosteric or cooperative systems. However the detailed model in Questions for future work include the following: if phosphorylation and dephosphorylation of the multisite protein For convenience we include in one location all chemical reactions of the model, mass conservation laws, the definition of auxiliary variables following the multisite modeling formalism, and a self contained set of differential equations after eliminating additional variables. Recall that for multisite proteins Since most quantitative information about the pathway is unknown, we make educated estimates on the order of magnitude of the parameters. Since parameters are clustered in Very little is known about the values of the individual rates Regarding the activity functions The initial conditions used in the model correspond to the system in the off state. They are equal to zero for all variables, except Figure S1A: A rule-based approach for modeling multisite phosphorylation, which results in a system equivalent to MWC. Here (EPS)Click here for additional data file.Figure S2For the MWC model in (EPS)Click here for additional data file.Text S1The supplementary material to this paper has three sections. In Section S1.1 and S1.2 we carry out a mathematical analysis of the downstream and upstream subsystems of the checkpoint model, respectively. Each analysis results in the reduction of the system at steady state to a single equation. In Section S1.3 we derive the MWC model using a system of equations involving all (PDF)Click here for additional data file.


The second hypothesis suggests that the feed forward excitatory and inhibitory inputs to a postsynaptic cell are already balanced. This latter hypothesis thus does account for the balance of transient inputs. However, it remains unclear what mechanism underlies the fine tuning required for balancing feed forward excitatory and inhibitory inputs. Here we investigated whether inhibitory synaptic plasticity is responsible for the balance of transient feed forward excitation and inhibition. We address this issue in the framework of a model characterizing the stochastic dynamics of temporally anti-symmetric Hebbian spike timing dependent plasticity of feed forward excitatory and inhibitory synaptic inputs to a single post-synaptic cell. Our analysis shows that inhibitory Hebbian plasticity generates ‘negative feedback’ that balances excitation and inhibition, which contrasts with the ‘positive feedback’ of excitatory Hebbian synaptic plasticity. As a result, this balance may increase the sensitivity of the learning dynamics to the correlation structure of the excitatory inputs.It has been suggested that excitatory and inhibitory inputs to cortical cells are balanced, and that this balance is important for the highly irregular firing observed in the cortex. There are two hypotheses as to the origin of this balance. One assumes that it results from a stable solution of the recurrent neuronal dynamics. This model can account for a balance of  One of the longstanding enigmas in neuroscience is the origin of inherent neural noise. It has been suggested that this noise results from a careful balance of excitatory and inhibitory inputs to neurons. Obtaining this balance requires fine tuning of the relative strengths of the inhibitory and excitatory inputs to each cell. However the mechanism that enables this fine tuning of parameters remains unclear. We suggest that a balance of excitatory and inhibitory inputs can be achieved via a process of unsupervised learning of the inhibitory synaptic strengths. We find that whereas Hebbian learning induces strong positive feedback on excitatory inputs that acts as a force that pulls them towards their boundaries, Hebbian learning of inhibition induces negative feedback. This negative feedback acts to balance the average excitatory input to the cell and makes the learning process less sensitive to the statistics of the inhibitory inputs. Surprisingly, this balance increases the sensitivity of learning to the statistics of the excitatory inputs. Thus, the balance of feed-forward excitation and inhibition emerges as a natural outcome of Hebbian learning applied to the inhibitory inputs to the cell. In terms of the balance hypothesis, the firing of the postsynaptic cell in the above example is not determined by the mean input of 100 excitatory postsynaptic potentials every 10 ms, which will be canceled by the mean inhibitory input, but rather by the fluctuations that are an order of magnitude smaller. Thus, the firing rate of the postsynaptic cell will not saturate and will be characterized by a high degree of variability.steady state excitation and inhibition can be obtained as a stable solution to the network dynamics, and requires no special fine tuning of parameters due to the feedback from the network dynamics. These studies focused on the balancing of the lateral inputs via feedback of recurrent interactions and ignored the feed forward inputs to the system. However, empirical findings have shown there is a fast balance of transient inputs to a barrel cortical cell feed forward excitation and inhibition inputs in feed forward (propagating) neural networks. However, it remains unclear what mechanism underlies the fine tuning required for balancing feed forward excitatory and inhibitory inputs.There is, however, some confusion as to the nature and origin of the balanced state. One approach to this problem suggested that this balance results from recurrent neural dynamics anti Hebbian plasticity, The overwhelming majority of scientific works on synaptic plasticity has focused on excitatory synapses. It is generally believed that synaptic plasticity is the basis for learning and memory. According to Hebb's rule Considerable theoretical effort has been devoted to studying the characteristics of STDP learning of excitatory synapses recurrent excitation Theoretical studies have also explored the development of neuronal response properties In contrast to the considerable number of empirical studies on excitatory synaptic plasticity, much less is known about inhibitory plasticity. Nevertheless, evidence for STDP of inhibitory synapses is beginning to emerge Here we investigate the hypothesis that the temporally asymmetric Hebbian STDP of inhibitory synapses is responsible for the balance of transient feed forward excitation and inhibition. This issue is addressed in the framework of a stochastic dynamical model for learning feed forward inputs to a single postsynaptic cell, and then illustrated using numerical simulations or the learning dynamics of feed forward connections onto an integrate and fire neuron. We start by analyzing the stochastic learning dynamics of a single inhibitory synapse. Then we turn to investigate the learning dynamics of a population of inhibitory feed forward synapses. Finally we study a model that incorporates learning of both feed forward excitatory and inhibitory inputs to a single postsynaptic cell.Considerable theoretical attention has been devoted to the study of learning a single excitatory synapse, see e.g., 0 ms see , or by a0 ms see . For conIn the limit of slow learning rate, the synaptic weight, Substituting equation (13) into equation (10) one obtains:negative feedback, which is characterized by a unimodal distribution for the inhibitory synapses. This contrasts with the temporally asymmetric Hebbian STDP rule for an excitatory synapse, which yields a positive feedback and allows for bi-stable solutions.The temporally asymmetric Hebbian STDP rule, equation (1), yields a As there is only one stable fixed point for the drift velocity, which is stable for all The relative strength of the depression needs to be weaker than the potentiation; i.e., in the To test our results beyond the analysis of the above simplified model we performed numerical simulations of the learning dynamics of a feed forward inhibitory synapse to a conductance based integrate and fire postsynaptic neuron  deviation from the homogeneous solution, The STDP learning rule is an unsupervised learning rule and as such can learn salient features of the statistics of its inputs. The input statistics are expressed in the learning dynamics, equation (18), by the effective interactions between the synapses generated via the input correlations, homogeneous with uniform correlation structure between all inhibitory presynaptic neurons, with a correlation coefficient of non-homogeneous system, where the inhibitory presynaptic population is composed of two sub-populations of equal size with a correlation coefficient of heterogenous population with a more elaborate correlation structure (see inset), yet the homogeneous solution of the STDP dynamics remains stable.Numerical simulations corroborate the claim that the negative feedback of inhibitory plasticity stabilizes the homogeneous solution.  compare A and 5BThe fixed point, equation (20), for the We now turn to generalize the above formalism to study the effect of Hebbian inhibitory synaptic plasticity in the framework of a simplified model for learning Using the fixed point equations (29)–(30) one can show that the homogeneous solution is always stable to fluctuations in the homogeneous direction. Additionally, similar to the analysis of the previous section, the homogeneous solution is always stable to fluctuations in directions of modifying the inhibition, excitatory input, balance the net excitatory input to the cell. In the absence of cross-correlations between inhibitory synapses, Nevertheless, since the learning dynamics of the inhibitory neurons, equation (28), is only sensitive to the mean We simulated the learning dynamics of a population of The sensitivity of excitatory plasticity to the statistical structure of the presynaptic input layer is illustrated in the example of asticity B than wasticity A. NeverWe have studied the computational effect of temporally asymmetric Hebbian plasticity of feed forward inhibition. Hebbian plasticity of inhibition generates negative feedback, in contrast to the positive feedback generated by Hebbian plasticity of excitation. This can be understood by the following intuitive explanation. If the feed forward inhibitory synapse is very strong, then it is less likely that a postsynaptic spike will follow a presynaptic spike. As a result more pre-post spike pairs will fall on the acausal branch of the STDP learning curve than on the causal branch. This, in turn, will depress the strong synapse. On the other hand, if the synapse is weak, then pre and post spike times will be largely uncorrelated and the STDP dynamics will sample uniformly both branches of the STDP curve with equal probability. If the area under the acausal branch is smaller than the area under the causal branch, inhibitory synapses is stable, even when the homogenous solution for the excitatory synapses loses its stability. However, in our analysis we focused on a simple case where there are no correlations between excitatory and inhibitory neurons. Incorporating such correlations to our model adds a term of the form This negative feedback, in the case of temporally asymmetric Hebbian plasticity and instantaneous correlations as was studied here, implies that the inhibitory synaptic weight distribution is unimodal and that the homogeneous solution of learning a population of In addition we found that inhibitory Hebbian plasticity works to balance the net excitatory inputs of the cell. Two terms govern the homogeneous fixed point of the inhibitory synapses. The first term results from the contribution of the product of the mean firing rates to the pre-post full-correlations to the In the presence of correlations, for the The balance has a twofold effect. First, balancing the mean excitation and inhibition inputs to the cell increases the relative contribution of the fluctuations to the cell's response. Note that we find that even if exact balance is not obtained the fluctuations are not expected to be negligible relative to the mean input. Second, the exact balance reduces the stability of the homogeneous solution to the learning dynamics to fluctuations of excitatory synaptic weights in a non-homogeneous direction. Hence, it increases the sensitivity of the STDP dynamics to the structure of the excitatory input.Our analysis was performed using the framework of simplified models of postsynaptic neural response. Although these simplified models provide a mere caricature of the rich response dynamics of a neuron to its synaptic inputs, they further our analytical understanding of the possible outcomes of Hebbian inhibitory synaptic plasticity, which cannot be achieved if the neural response dynamics need to be solved numerically. Furthermore, numerical simulations support our analytical results qualitatively beyond the framework of the simplified linear neuron model.symmetric STDP rule in which the learning rule acts as a coincidence detector of post- and pre-spikes, We introduced several additional simplifying assumptions to our model. First, we focused on temporally asymmetric Hebbian STDP for the inhibitory synapses. However, STDP rules may be highly variable and this variability may be manifested by a qualitative difference from our results. For example an anti-Hebbian STDP rule, such as depicted in Of particular interest is the ‘thalamocortical’ circuit, in which feed forward excitatory inputs arrive directly from thalamus to cortex whereas inhibitory inputs result from a relay of the thalamic input via local  interneurons. This network architecture manifests in a rich temporal and functional (similarity of preferred stimuli) correlation structure between excitation and inhibition, which may have a significant qualitative effect on learning dynamics. However, here we assumed a very basic correlations structure between the responses of the presynaptic neurons. The investigation of the different effects of various STDP rules and the elaborate spatial and temporal correlations structure of presynaptic neuron responses is beyond the scope of the current paper. Nevertheless, this work suggests a theoretical framework for addressing these issues.We simulated learning dynamics of feed forward synaptic inputs into a single post synaptic integrate and fire cell. Following Song et al For the conductance, we introduced a scaling mechanism on the values used by Gütig et al The synaptic spike trains to the integrate and fire neuron were simulated by Bernoulli processes  defined over discrete time bins of duration Integration of the synaptic and leak currents in equation (38) to estimate the postsynaptic membrane potential, The firing rate statistics of all presynaptic cell activity throughout all our simulations followed Poisson statistics with stationary mean firing rates of For the learning rate,


Thyroid hormone receptor (TR) belongs to the nuclear hormone receptor (NHR) superfamily and regulates the transcription of its target genes in a thyroid hormone (T3)-dependent manner. While the detail of transcriptional activation by T3 (positive regulation) has been clarified, the mechanism of T3-dependent repression (negative regulation) remains to be determined. In addition to naturally occurring negative regulations typically found for the thyrotropin β gene, T3-bound TR (T3/TR) is known to cause artificial negative regulation in reporter assays with cultured cells. For example, T3/TR inhibits the transcriptional activity of the reporter plasmids harboring AP-1 site derived from pUC/pBR322-related plasmid (pUC/AP-1). Artificial negative regulation has also been suggested in the reporter assay with firefly luciferase (FFL) gene. However, identification of the DNA sequence of the FFL gene using deletion analysis was not performed because negative regulation was evaluated by measuring the enzymatic activity of FFL protein. Thus, there remains the possibility that the inhibition by T3 is mediated via a DNA sequence other than FFL cDNA, for instance, pUC/AP-1 site in plasmid backbone. To investigate the function of FFL cDNA as a transcriptional regulatory sequence, we generated pBL-FFL-CAT5 by ligating FFL cDNA in the 5' upstream region to heterologous thymidine kinase promoter in pBL-CAT5, a chloramphenicol acetyl transferase (CAT)-based reporter gene, which lacks pUC/AP-1 site. In kidney-derived CV1 and choriocarcinoma-derived JEG3 cells, pBL-FFL-CAT5, but not pBL-CAT5, was strongly activated by a protein kinase C activator, phorbol 12-O-tetradecanoate-13-acetate (TPA). TPA-induced activity of pBL-FFL-CAT5 was negatively regulated by T3/TR. Mutation of nt. 626/640 in FFL cDNA attenuated the TPA-induced activation and concomitantly abolished the T3-dependent repression. Our data demonstrate that FFL cDNA sequence mediates the TPA-induced transcriptional activity, which is inhibited by T3/TR. Thyroid hormone receptor (TR) belongs to the nuclear hormone receptor (NHR) superfamily. In a T3-dependent manner, TR not only activates (positive regulation) but also inhibits (negative regulation) its target genes. In contrast to that for the positive regulation, the molecular mechanism of the negative regulation has been elusive Unexpectedly, Lopez et al. Besides the negative regulation via pUC/AP-1 site, it was suggested that T3/TR may artificially suppress the activity of firefly luciferase (FFL)-based reporter genes driven by thymidine kinase (TK) promoter It is noteworthy that artificial repression by T3/TR was not detected for chloramphenicol acetyl transferase (CAT)-based reporter gene in CV1 To isolate the DNA fragment containing the FFL coding region, the sequence GGATCT (nt. 1891/1896) at the 3′ flanking region of FFL cDNA in pGL2-basic vector  was mutated to the BamHI site (GGATCC) using a site-directed mutagenesis kit . This mutant plasmid was digested with HindIII and BamHI, and the 1750 bp DNA fragment was separated in gel electrophoresis and was ligated in the HindIII-BamHI site in the multi-cloning site in pBL-CAT5 2/95% air in Dulbecco's modified Eagle's medium (DMEM) containing 10% fetal calf serum, penicillin G (100 units/ml), and streptomycin (100 µg/ml). CV1 and 293T cells were trypsinized and plated in 60-mm dishes for 24 h before transient transfection using the calcium-phosphate technique 6 cells/plate were transfected with 0.4 µg of TR expression vector (pCMX-hTRβ1) along with 1.0 µg of pBL-FFL-CAT5, 1.8 µg of β-galactosidase expression vector pCH111 , and pCMX empty vector as carrier DNA . After the cells were exposed to the calcium phosphate/DNA precipitates for 20 h, the medium was replaced with fresh DMEM containing 5% fetal calf serum depleted of thyroid hormones or the same medium was supplemented with 100 ng/ml phorbol 12-O-tetradecanoate-13-acetate (TPA) and/or 1 µM T3. After incubation for an additional 24 h, the cells were harvested and the CAT activity was measured and normalized by the β-galactosidase activity as described previously. JEG3 cells A monkey kidney cell line, CV1 5′-CCTAAGGGTGTGGCCCTTCCGCATAGAACTGCCTGCGTCA-3′ and antisense: 5′-TGACGCAGGCAGTTCTATGCGGAAGGGCCACACCCTTAGG-3′) and consensus AP-1 probes (sense: 5′-TCGACGGTATCGATAAGCTATGACTCATCCGGGGGATC-3′ and antisense: 5′-GATCCCCCGGATGAGTCATAGCTTATCGATACCGTCGA-3′) were annealed and labeled with γ-32P-ATP using T4 polynucleotide kinase . CV1 nuclear extracts (CV1-NE) were prepared as described previously 32P-labeled probes and 2 µg of CV1-NE were incubated for 30 min on ice in 20 µl of binding buffer containing 20 mM Hepes-NaOH (pH 7.9), 50 mM KCl, 0.05 mM EDTA, 2.5 mM MgCl2, 8.5% glycerol, 1 mM dithiothreitol, and 0.5 µg/ml poly(dI-dC). For the supershift assays, anti-cJun antibody  was added to the binding reaction mixture. DNA-protein complexes were resolved by electrophoresis on a 5% polyacrylamide gel at 150 V for 120 min at room temperature. For the competition assay, 100-fold excess of cold FFL14G was added. The gel was dried and labeled bands were visualized using the BAS-1000 autoradiography system .FFL14 probe , which consists of a direct repeat of half-sites  with 4 random spacing nucleotides  nTRE was defined as the sequence where unliganded TR may function as a transcriptional activator 32P-labeled DNA probes encompassing various regions between nt. 613/640. The sequence between nt. 626/640 has weak homology with consensus AP-1 site (32P-labeled consensus AP-1 site (Using nuclear extract from CV1 cells (CV1-NE), we performed gel shift assay with P-1 site . We founP-1 site  that wasP-1 site . As a coP-1 site . As showOn the basis of the results of the gel shift assay in The sequence homology between FFL and modified Renilla reniformis-derived luciferase (hRluc) In this study, we confirmed the existence of the sequence in FFL cDNA that mediates artificial negative regulation by T3/TR. FFL assay has many advantages compared with CAT assay Although one may argue that, in experimental conditions without PKC activity or Jun/Fos, FFL-based reporter assay can be utilized for the study of negative regulation, at least 11 different PKC subtypes have been reported and some of them are expressed ubiquitously Although the artificial negative regulation by FFL cDNA or pUC/AP-1 site can be neglected when the promoter/enhancer activity is much stronger than that of these sequences Negative regulation has been regarded as the mirror image of positive regulation and unliganded TR was postulated to be a transcriptional activator. On the basis of this hypothesis, deletion analysis of the TSHβ gene was performed in the absence of T3 and the putative nTRE was reported Because the majority of previous studies paid little attention to the artificial inhibition by T3/TR via FFL cDNA or pUC/AP-1 site, there has remained the possibility that the transcriptional activity via FFL cDNA or pUC/AP-1 site might be regarded as that by unliganded TR. Current data combined with our previous reports


Antrodia cinnamomea is a traditional healthy food that has been demonstrated to possess anti-inflammatory, antioxidative, and anticacer effects. The purpose of this study was to evaluate whether the ethanolic extract of A. cinnamomea (EEAC) can affect the efflux function of P-glycoprotein (P-gp) and the effect of ABCB1 genetic variants on the interaction between EEAC and P-gp. To investigate the mechanism of this interaction, Flp-In™-293 cells stably transfected with various genotypes of human P-gp were established and the expression of P-gp was confirmed by Western blot. The results of the rhodamine 123 efflux assay demonstrated that EEAC efficiently inhibited wild-type P-gp function at an IC50 concentration of 1.51±0.08 µg/mL through non-competitive inhibition. The IC50 concentrations for variant-type 1236T-2677T-3435T P-gp and variant-type 1236T-2677A-3435T P-gp were 5.56±0.49 µg/mL and 3.33±0.67 µg/mL, respectively. In addition, the inhibition kinetics of EEAC also changed to uncompetitive inhibition in variant-type 1236T-2677A-3435T P-gp. The ATPase assay revealed that EEAC was an ATPase stimulator and was capable of reducing verapamil-induced ATPase levels. These results indicate that EEAC may be a potent P-gp inhibitor and higher dosages may be required in subjects carrying variant-types P-gp. Further studies are required to translate this basic knowledge into clinical applications. Antrodia cinnamomea, a well-known medicinal mushroom, has attracted lots of attentions to public due to the potential therapeutic efficacy of liver function protection, antihypertension and anti-inflammation A. cinnamomea has been demonstrated to exhibit anticancer and chemopreventive effects ABCB1 gene, belongs to the ATP-binding cassette superfamily and is constitutively expressed in the apical membranes of the liver, kidney, intestines, lung, and adrenal glands, as well as in the luminal surface of the blood-brain, blood-testis, and blood-ovarian barriers P-glycoprotein (P-gp), encoded by the ABCB1 gene ABCB1 gene is a highly polymorphic gene and several genetic polymorphisms have been demonstrated to affect P-gp expression, protein conformation, and efflux function ABCB1 1236C>T, 3435C>T, and 1199G>A with irinotecan concentrations in patients To overcome MDR to chemotherapeutic agents, several P-gp inhibitors have been generated and evaluated both in vitro and clinically A. cinnamomea induces a wide range of biological activities, including antiinflammation, antioxidation, liver function protection, and antitumor effects A. cinnamomea exhibited cytotoxic effects on prostate, breast, bladder, and lung cancers A. cinnamomea bodies on P-gp efflux function have not been investigated.The systemic toxicities of synthetic P-gp inhibitors have elicited an increasing amount of attention to the potential use of natural products. Among traditional healthy natural products, increasing evidence supports the hypothesis that ABCB1 gene on the potency of P-gp inhibition. Furthermore, we explored the underlying molecular mechanisms of the P-gp inhibition effects.In the present study, we evaluated whether EEAC inhibits P-gp and investigated the influences of genetic polymorphisms in the A.cinnamomea was a kindly gift from Cosmox Biomedical Co., Ltd. . The preparation of the ethanolic extracts of fruiting bodies of A.cinnamomea (EEAC), methods of HPLC and MS analysis were the same as our previous studies ABCB1cDNA in pMDRA1 was provided by the Riken BRC DNA bank (RDB No. 1372) .The 2. The pcDNA5/ABCB1 containing different genotypes of ABCB1cDNA were constructed in our previous studies ABCB1 plasmid and pOG44 (the Flp recombinase expression plasmid) were co-transfected into the Flp-In™-293 cells. Stable transfected with wild-type P-gp (1236C-2677G-3435C) and variant types P-gp (1236T-2677A-3435T and 1236T-2677T-3435T) cell lines were selected on the basis of hygromycin B resistance. The protein and mRNA expressions of P-gp were confirmed by Western blot analysis and real-time quantitative RT-PCR, respectively, in our previous studies Flp-In™-293 cells were cultured in DMEM medium supplemented with 10% fetal bovine serum and selected with 100 µg/mL zeocin at 37°C, 95% humidity and 5% COCytotoxicities of EEAC at concentrations used in the present study were determined by MTT assay. Briefly, the cells were seeded into 24-well plates and cultured overnight. Various concentrations of EEAC (from 1 µg/mL to 5 µg/mL) were then added and incubated for 72 hours. After incubation, the medium was removed and added fresh culture medium 200 µl containing 0.5 mg/ml MTT and then incubated at 37°C for 4 hours. The medium was removed and 200 µl DMSO was added. After incubation for 30 minutes at room temperature, 100 µl of solution was transferred to a 96-well plate and absorbance was measured using an ELISA plate reader  at 570 nm with a reference wavelength of 650 nm.The effect of EEAC on P-gp ATPase activity was examined by Pgp-GIO assay system  according to manufacturer’s protocol. To be brief, in a 96-well untreated white plate, 25 µg recombinant human Pgp was incubated with P-gp-GIO assay buffer (untreated control) or 200 µM verapamil (positive control of drug induced P-gp ATPase activity) or 100 µM sodium orthovanadate (selective inhibitor of P-gp ATPase activity) or EEAC (from 0.01 µg/mL to 200 µg/mL). The reaction was initiated by adding 5 mM MgATP and incubated for 40 min at 37°C. The luminescence was initiated by adding 50 µl of ATP detection reagent after 20 min of incubation at room temperature and read on the SpectraMax Gemini XS microplate spectrofluorometer . Each experiment was performed at least three times, each in triplicate on different days.5 cells were harvested after trypsinization by centrifugation and resuspended in fresh culture medium. Rhodamine123  was added and the cells were incubated in a water bath at 37°C in the dark. Cells were pelleted at 1, 5, 10, 15, 30, 45, 60, and 90 min. After washed with ice-cold PBS, cells were resuspended in 1-ml, ice-cold PBS prior to FACS analysis using CellQuest software . Each cell type was performed at least three experiments, each in triplicate on different days.For FACS analysis, 5×105 cells were seeded on 96-well plates and cultured for 24 hours. After incubation, cells were washed with warm Hanks’ balanced salt solution (HBSS) and pre-incubated with HBSS for 30 min, and subsequently incubated in 1 µM rhodamine123 for 30 min with or without EEAC in triplicate. After washed with warm PBS, cells were allowed to efflux rhodamine123 for 10 min at 37°C in the incubator. Samples (150 µl) were collected and transferred to 96-well black plates. Rhodamine123 concentrations were measured using a set of standards (from 62.5 nM to 8 µM) in HBSS analyzed by the SpectraMax Gemini XS microplate spectrofluorometer  with the excitation set at 485 nm and the emission set at 535 nm. The measured rhodamine123 concentrations were normalized to the total protein content in the cells. Total protein concentrations were measured by a microplate assay protocol , and bovine serum albumin was used as the standard. Each experiment was repeated at least three times across cell passages to ensure stability of transfection and consistency and reproducibility of the experiments.For efflux assays, 1×105 cells were placed on 96-well black plates and cultured for 24 hours. Before the uptake assay, cells were washed with warm Hanks’ balanced salt solution (HBSS) and pre-incubated with HBSS for 30 min, and subsequently with EEAC for 30 min in triplicate. After pre-incubation, calcein AM  was added and incubated at 37°C in the incubator for 30 min. After washed by ice-cold HBSS, cells were lysed with 1% Triton X-100 and calcein fluorescence generated within the cells was analyzed by the SpectraMax Gemini XS microplate spectrofluorometer  with the excitation set at 485 nm and the emission set at 535 nm. Each experiment was performed at least three times, each in triplicate on different days.For calcein-AM uptake study, 1×105 cells were harvested after trypsinization by centrifugation and resuspended in fresh culture medium. Fluorescent doxorubicin  was added and the cells were incubated in a water bath at 37°C in the dark. Cells were pelleted at 1, 5, 10, 15, 30, 45, 60, 90, 120, 150 and 180 min. After washed with ice-cold PBS, cells were resuspended in 1 ml ice-cold PBS prior to FACS analysis using CellQuest software . Each cell type would be used to perform at least three experiments, each in triplicate on different days.For FACS analysis, 5×105 cells were seeded on 96-well plates and cultured for 24 hours. After incubation, cells were washed with warm Hanks’ balanced salt solution (HBSS) and preincubated with HBSS for 30 min, and subsequently incubated in 10, 20 or 30 µM fluorescent doxorubicin for 3 hours with or without EEAC in triplicate. After being washed with warm PBS, cells were allowed to efflux fluorescent doxorubicin for 2 hours at 37°C in the incubator. Samples (100 µl) were collected and transferred to 96-well black plates. Fluorescent doxorubicin concentrations were measured using a set of standards (from 0.5 µM to 10 µM) in HBSS analyzed by the SpectraMax Gemini XS microplate spectrofluorometer  with the excitation set at 485 nm and the emission set at 590 nm. The measured fluorescent doxorubicin concentrations were normalized to the total protein content in the cells. Total protein concentrations were measured by a microplate assay protocol , and bovine serum albumin was used as the standard. Each experiment was repeated at least three times across cell passaging to ensure stability of transfection and consistency and reproducibility of the experiments.For efflux assays, 1×10For ATPase Assay data analysis, basal P-gp activity, verapamil-stimulated P-gp ATPase activity, EEAC effect on P-gp ATPase activity and fold stimulation by EEAC were calculated as following equations:Basal P-gp activity:Verapamil-stimulated P-gp ATPase activity:EEAC effect on P-gp ATPase activity:Fold stimulation by EEAC:50 values were calculated by the following equation:For evaluation of inhibitor potency, IC0, the efflux in the absence of inhibitor; I, the inhibitor concentration; IC50, the concentration that caused 50% inhibition of the maximal drug effect and s is the slope factor.Where E is the observed efflux in the presence of inhibitor; EFor kinetic studies, kinetic parameters were estimated by nonlinear regression using Scientist v2.01  according to the following equation:max, the maximal efflux rate; Km, the Michaelis-Menten constant and C is the substrate concentration. Statistical comparisons among different cells were performed by using SYSTAT v10 . Statistical differences were evaluated by ANOVA and post hoc analysis (Tukey’s test) and the statistical significance was set at p value <0.05.Where V denoted the efflux rate; VABCB1 gene stable transfected cells expressed large quantities of human P-gp, whereas little expression of ABCB1 mRNA and protein was found in the Flp-In™-293 cells (host cells). There was no significant difference among the mRNA and protein expression levels of wild type ABCB1 and the two variant types as showed in our previous studies ABCB1 mRNA and protein expression remained unchanged in wild type ABCB1 and the two variant types , ABCB1 1236T-2677T-3435T and ABCB1 1236T-2677A-3435T were 21.27±1.26, 29.31±1.72, 20.60±0.94 and 22.74±1.04 µg/ml, respectively (The nt types . The cytectively f).M and Vmax values for rhodamine 123 efflux in wild-type human P-gp were estimated to be 20.17±4.45 µM and 11.22±0.73 nmole/mg protein/10 min, respectively, whereas the non-specific first-order rate constant was estimated to be 10.08±1.12 µL/mg protein/10 min. Since the intrinsic clearance, Vmax/KM, of rhodamine 123 was 556.3 µL/mg protein/10 mins, non-specific transport accounted for only 1.8% of the total efflux. The KM values for rhodamine 123 efflux in wild-type and variant-types P-gp were similar, while the Vmax value for rhodamine 123 efflux was significantly lower in variant type 1236T-2677A-3435T P-gp than wild-type 1236C-2677G-3435C P-gp and variant type 1236T-2677T-3435T P-gp  values for EEAC in wild-type P-gp, variant type 1236T-2677T-3435T P-gp, and variant type 1236T-2677A-3435T P-gp were 1.51±0.08 µg/mL, 5.56±0.49 µg/mL and 3.33±0.67 µg/mL, respectively  were incubated with recombinant human P-gp. EEAC was demonstrated to stimulate P-gp ATPase activity by two fold higher than basal ATPase activity and inhibited 200 µM verapamil-stimulated P-gp ATPase activity at 5 µg/mL .The inhibition kinetics of EEAC was further investigated in the wild type and the variant types of P-gp by Lineweaver-Burk plot . In the As for the kinetics of P-gp mediated doxorubicin efflux, the EEAC was demonstrated to inhibit doxorubicin transport by distinctive kinetics among different types P-gp. In the wild-type P-gp, when the concentration of EEAC increased, the maximum rate of doxorubicin efflux (Vmax) remaining unchanged with affinity (Km) increased . These r50, whereas the variant-type 1236T-2677T-3435T P-gp was the least sensitive to EEAC at the highest concentration of IC50. Regarding the inhibition kinetics, EEAC inhibited wild-type P-gp and variant-type 1236T-2677T-3435T P-gp through noncompetitive inhibition, whereas it inhibited variant-type 1236T-2677A-3435T P-gp through uncompetitive inhibition. In our previous study, we have reported the P-gp inhibition kinetics of methadone The present study demonstrated that EEAC may inhibit human P-gp efflux function through ATPase stimulation. The common genetic polymorphisms of human P-gp influence the inhibition kinetics and inhibition potency of EEAC. The wild-type human P-gp was the most sensitive to EEAC at the lowest concentration of ICAntrodia camphorate (AC-SS) exhibited adjuvant antiproliferative effects on hepatoma cells and on xenografted cells in tumor-implanted nude mice ABCB1 gene was demonstrated to be reduced by AC-SS treatment in two hepatoma cell lines (C3A and PLC/PRF/5) ABCB1 gene expression. The inhibition of human P-gp efflux function by EEAC occurred rapidly, within 30 min, through non-competitive inhibition and lasted for more than 2 h. These results provide explanations for the mechanism of the significant inhibiting effect of EEAC on P-gp function. Similar to verapamil, a well-known P-gp inhibitor, EEAC acted as an ATPase stimulator and reduced the ATPase stimulating effect of verapamil. These results indicate that EEAC interacted with verapamil on the same binding site of ATPase and exerted a significant P-gp-inhibiting effect at low concentrations (1–5 µg/mL). Potential drug-drug interactions may occur when a P-gp inhibitor, such as EEAC, co-administered with P-gp substrates, such as digoxin and fexofenadine A previous study reported on how P-gp expression was influenced by this traditional natural product ABCB1 genetic polymorphisms on the P-gp-inhibition potency of EEAC, the results of this study indicate that EEAC exhibited 2-fold lower and 4-fold lower inhibition potency toward variant-type 1236T-2677A-3435T and 1236T-2677T-3435T P-gp than toward wild-type P-gp, respectively. Moreover, the inhibition kinetics also changed between the wild-type and variant-type P-gps. These results correspond with those of a previous study that identified the functional effect of ABCB1 1236C>T, 2677G>T/A, and 3435C>T Regarding the influences of ABCB1 genotypes and chemotherapy responses have been reported previously. Patients with the 1236C-2677G-3435C haplotype were associated with poor responses to imatinib treatment for chronic myeloid leukemia The associations between A. cinnamomea has been demonstrated to be a potential anticancer, antiinflammatory, and antioxidative agent. In this study, we demonstrated that A. cinnamomea may possess the ability to overcome MDR.In our previous study, the index compounds within EEAC were measured and quantified using HPLC, LC/MS, and LC/MS/MS and used for controlling the quality of the extraction procedure for each batch ABCB1 gene influence the binding kinetics of EEAC to human P-gp. Additional preclinical and clinical studies are required to verify whether EEAC can be developed as an MDR-reversing agent.In conclusion, we demonstrated that EEAC inhibited the efflux function of human P-gp through an ATPase stimulation mechanism. The common SNPs on the Figure S1Representative HPLC and mass spectrometry of the index compounds in EEAC. The relative content of adenosine, cordycepin, and zhankuic acid A in EEAC were calculated according to the concentration of standard compounds. The index compounds  were confirmed by ESI-MS and ESI-MS/MS within EEAC. (A) HPLC data for adenosine and cordycepin. (B) HPLC data for zhankuic acid A. (C) LC/MS spectra of cordycepin. (D) LC/MS spectra of zhankuic acid A. (E) LC/MS/MS spectra of cordycepin. (F) LC/MS/MS spectra of zhankuic acid A.(PDF)Click here for additional data file.