Plasma membrane-associated receptor like kinases relocalize to plasmodesmata in response to osmotic stress

Plasmodesmata act as key elements in intercellular communication, coordinating processes related to plant growth, development, and responses to environmental stresses. While many of the developmental, biotic, and abiotic signals are primarily perceived at the plasma membrane (PM) by receptor proteins, plasmodesmata also cluster receptor-like activities; whether these two pathways interact is currently unknown. Here we show that specific PM-located Leucine-Rich-Repeat Receptor-Like-Kinases (LRR-RLKs), QSK1 and IMK2, which under optimal growth conditions are absent from plasmodesmata, rapidly relocate and cluster to the pores in response to osmotic stress. This process is remarkably fast, is not a general feature of PM-associated proteins, and is independent of sterol- and sphingolipid- membrane composition. Focusing on QSK1, previously reported to be involved in stress responses, we show that relocalisation in response to mannitol depends on QSK1 phosphorylation. Loss-of-function mutation in QSK1 results in delayed lateral root (LR) development and the mutant is affected in the root response to mannitol stress. Callose-mediated plasmodesmata regulation is known to regulate LR development. We found that callose levels are reduced in the qsk1 mutant background with a root phenotype resembling ectopic expression of PdBG1, an enzyme that degrades callose at the pores. Both the LR and callose phenotypes can be complemented by expression of wild-type and phosphomimic QSK1 variants, but not by phosphodead QSK1 mutant which fails to relocalise at plasmodesmata. Together the data indicate that re-organisation of RLKs to plasmodesmata is important for the regulation of callose and LR development as part of the plant response to osmotic stress

Influences of Excluded Volume of Molecules on Signaling Processes on Biomembrane

We investigate the influences of the excluded volume of molecules on biochemical reaction processes on 2-dimensional surfaces using a model of signal transduction processes on biomembranes. We perform simulations of the 2-dimensional cell-based model, which describes the reactions and diffusion of the receptors, signaling proteins, target proteins, and crowders on the cell membrane. The signaling proteins are activated by receptors, and these activated signaling proteins activate target proteins that bind autonomously from the cytoplasm to the membrane, and unbind from the membrane if activated. If the target proteins bind frequently, the volume fraction of molecules on the membrane becomes so large that the excluded volume of the molecules for the reaction and diffusion dynamics cannot be negligible. We find that such excluded volume effects of the molecules induce non-trivial variations of the signal flow, defined as the activation frequency of target proteins, as follows. With an increase in the binding rate of target proteins, the signal flow varies by i) monotonically increasing; ii) increasing then decreasing in a bell-shaped curve; or iii) increasing, decreasing, then increasing in an S-shaped curve. We further demonstrate that the excluded volume of molecules influences the hierarchical molecular distributions throughout the reaction processes. In particular, when the system exhibits a large signal flow, the signaling proteins tend to surround the receptors to form receptor-signaling protein clusters, and the target proteins tend to become distributed around such clusters. To explain these phenomena, we analyze the stochastic model of the local motions of molecules around the receptor.Comment: 31 pages, 10 figure

Phosphoproteomics-Based Modeling Defines the Regulatory Mechanism Underlying Aberrant EGFR Signaling

BACKGROUND: Mutation of the epidermal growth factor receptor (EGFR) results in a discordant cell signaling, leading to the development of various diseases. However, the mechanism underlying the alteration of downstream signaling due to such mutation has not yet been completely understood at the system level. Here, we report a phosphoproteomics-based methodology for characterizing the regulatory mechanism underlying aberrant EGFR signaling using computational network modeling. METHODOLOGY/PRINCIPAL FINDINGS: Our phosphoproteomic analysis of the mutation at tyrosine 992 (Y992), one of the multifunctional docking sites of EGFR, revealed network-wide effects of the mutation on EGF signaling in a time-resolved manner. Computational modeling based on the temporal activation profiles enabled us to not only rediscover already-known protein interactions with Y992 and internalization property of mutated EGFR but also further gain model-driven insights into the effect of cellular content and the regulation of EGFR degradation. Our kinetic model also suggested critical reactions facilitating the reconstruction of the diverse effects of the mutation on phosphoproteome dynamics. CONCLUSIONS/SIGNIFICANCE: Our integrative approach provided a mechanistic description of the disorders of mutated EGFR signaling networks, which could facilitate the development of a systematic strategy toward controlling disease-related cell signaling

AYUMS: an algorithm for completely automatic quantitation based on LC-MS/MS proteome data and its application to the analysis of signal transduction

BACKGROUND: Comprehensive description of the behavior of cellular components in a quantitative manner is essential for systematic understanding of biological events. Recent LC-MS/MS (tandem mass spectrometry coupled with liquid chromatography) technology, in combination with the SILAC (Stable Isotope Labeling by Amino acids in Cell culture) method, has enabled us to make relative quantitation at the proteome level. The recent report by Blagoev et al. (Nat. Biotechnol., 22, 1139–1145, 2004) indicated that this method was also applicable for the time-course analysis of cellular signaling events. Relative quatitation can easily be performed by calculating the ratio of peak intensities corresponding to differentially labeled peptides in the MS spectrum. As currently available software requires some GUI applications and is time-consuming, it is not suitable for processing large-scale proteome data. RESULTS: To resolve this difficulty, we developed an algorithm that automatically detects the peaks in each spectrum. Using this algorithm, we developed a software tool named AYUMS that automatically identifies the peaks corresponding to differentially labeled peptides, compares these peaks, calculates each of the peak ratios in mixed samples, and integrates them into one data sheet. This software has enabled us to dramatically save time for generation of the final report. CONCLUSION: AYUMS is a useful software tool for comprehensive quantitation of the proteome data generated by LC-MS/MS analysis. This software was developed using Java and runs on Linux, Windows, and Mac OS X. Please contact [email protected] if you are interested in the application. The project web page is

Current challenges in software solutions for mass spectrometry-based quantitative proteomics

This work was in part supported by the PRIME-XS project, grant agreement number 262067, funded by the European Union seventh Framework Programme; The Netherlands Proteomics Centre, embedded in The Netherlands Genomics Initiative; The Netherlands Bioinformatics Centre; and the Centre for Biomedical Genetics (to S.C., B.B. and A.J.R.H); by NIH grants NCRR RR001614 and RR019934 (to the UCSF Mass Spectrometry Facility, director: A.L. Burlingame, P.B.); and by grants from the MRC, CR-UK, BBSRC and Barts and the London Charity (to P.C.

Epidermal growth factor mediates spermatogonial proliferation in newt testis

The complex processes of spermatogenesis are regulated by various factors. The aim of the current study is to determine the effect of epidermal growth factor (EGF) on spermatogonial proliferation and clarify the mechanism causing the proliferation in newt testis. In the organ culture, EGF stimulated spermatogonial proliferation, but not their differentiation into spermatocytes. cDNA cloning identified 3 members of the EGF receptors, ErbB1, ErbB2, and ErbB4, in the testis. RT-PCR showed that all the receptors cloned were expressed in both Sertoli and germ cells at the spermatogonial stage. In the organ cultures with inhibitors for the EGF receptors, mitogen-activated protein kinase (MAPK), and phosphoinositide 3-kinase (PI3K), the EGF-induced spermatogonial proliferation was suppressed. Furthermore, when the organ culture was exposed to EGF, the expressions of stem cell factor (SCF), immunoglobulin-like domain containing neuregulin1 (Ig-NRG1), and ErbB4 mRNA were increased. These results suggested that, since the spermatogonia are sequestered within cysts by the blood-testis barrier consisted of Sertoli cells, EGF possibly mediates spermatogonial proliferation in an endocrine manner through the receptors including ErbB1, ErbB2, and ErbB4 expressed on Sertoli cells via activation of MAPK cascade or/and PI3K cascade by elevating the expressions of SCF, Ig-NRG1, and ErbB4

Exact model reduction of combinatorial reaction networks

Receptors and scaffold proteins usually possess a high number of distinct binding domains inducing the formation of large multiprotein signaling complexes. Due to combinatorial reasons the number of distinguishable species grows exponentially with the number of binding domains and can easily reach several millions. Even by including only a limited number of components and binding domains the resulting models are very large and hardly manageable. A novel model reduction technique allows the significant reduction and modularization of these models

Fungi Unearthed: Transcripts Encoding Lignocellulolytic and Chitinolytic Enzymes in Forest Soil

BACKGROUND: Fungi are the main organisms responsible for the degradation of biopolymers such as lignin, cellulose, hemicellulose, and chitin in forest ecosystems. Soil surveys largely target fungal diversity, paying less attention to fungal activity. METHODOLOGY/PRINCIPAL FINDINGS: Here we have focused on the organic horizon of a hardwood forest dominated by sugar maple that spreads widely across Eastern North America. The sampling site included three plots receiving normal atmospheric nitrogen deposition and three that received an extra 3 g nitrogen m(2) y(1) in form of sodium nitrate pellets since 1994, which led to increased accumulation of organic matter in the soil. Our aim was to assess, in samples taken from all six plots, transcript-level expression of fungal genes encoding lignocellulolytic and chitinolytic enzymes. For this we collected RNA from the forest soil, reverse-transcribed it, and amplified cDNAs of interest, using both published primer pairs as well as 23 newly developed ones. We thus detected transcript-level expression of 234 genes putatively encoding 26 different groups of fungal enzymes, notably major ligninolytic and diverse aromatic-oxidizing enzymes, various cellulose- and hemicellulose-degrading glycoside hydrolases and carbohydrate esterases, enzymes involved in chitin breakdown, N-acetylglucosamine metabolism, and cell wall degradation. Among the genes identified, 125 are homologous to known ascomycete genes and 105 to basidiomycete genes. Transcripts corresponding to all 26 enzyme groups were detected in both control and nitrogen-supplemented plots. CONCLUSIONS/SIGNIFICANCE: Many of these enzyme groups are known to be important in soil turnover processes, but the contribution of some is probably underestimated. Our data highlight the importance of ascomycetes, as well as basidiomycetes, in important biogeochemical cycles. In the nitrogen-supplemented plots, we have detected no transcript-level gap likely to explain the observed increased carbon storage, which is more likely due to community changes and perhaps transcriptional and/or post-transcriptional down-regulation of relevant genes

Topological Analysis of MAPK Cascade for Kinetic ErbB Signaling

Ligand-induced homo- and hetero-dimer formation of ErbB receptors results in different biological outcomes irrespective of recruitment and activation of similar effector proteins. Earlier experimental research indicated that cells expressing both EGFR (epidermal growth factor receptor) and the ErbB4 receptor (E1/4 cells) induced E1/4 cell-specific B-Raf activation and higher extracellular signal-regulated kinase (ERK) activation, followed by cellular transformation, than cells solely expressing EGFR (E1 cells) in Chinese hamster ovary (CHO) cells. Since our experimental data revealed the presence of positive feedback by ERK on upstream pathways, it was estimated that the cross-talk/feedback pathway structure of the Raf-MEK-ERK cascade might affect ERK activation dynamics in our cell system. To uncover the regulatory mechanism concerning the ERK dynamics, we used topological models and performed parameter estimation for all candidate structures that possessed ERK-mediated positive feedback regulation of Raf. The structure that reliably reproduced a series of experimental data regarding signal amplitude and duration of the signaling molecules was selected as a solution. We found that the pathway structure is characterized by ERK-mediated positive feedback regulation of B-Raf and B-Raf-mediated negative regulation of Raf-1. Steady-state analysis of the estimated structure indicated that the amplitude of Ras activity might critically affect ERK activity through ERK-B-Raf positive feedback coordination with sustained B-Raf activation in E1/4 cells. However, Rap1 that positively regulates B-Raf activity might be less effective concerning ERK and B-Raf activity. Furthermore, we investigated how such Ras activity in E1/4 cells can be regulated by EGFR/ErbB4 heterodimer-mediated signaling. From a sensitivity analysis of the detailed upstream model for Ras activation, we concluded that Ras activation dynamics is dominated by heterodimer-mediated signaling coordination with a large initial speed of dimerization when the concentration of the ErbB4 receptor is considerably high. Such characteristics of the signaling cause the preferential binding of the Grb2-SOS complex to heterodimer-mediated signaling molecules