Regulatory protein-MAPK interaction strengths.

<p>The binding strengths of each KIM-PTP (KIM peptides and KIM-containing MKBDs (in orange font), light blue; KIMKIS peptides, light purple; proteins, light pink) to p38α and ERK2 represented from weakest to tightest (largest K_d to smallest K_d) binding affinity; ‘^†’ indicates values previously published <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0091934#pone.0091934-Francis1" target="_blank">[14]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0091934#pone.0091934-Francis2" target="_blank">[15]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0091934#pone.0091934-Piserchio1" target="_blank">[17]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0091934#pone.0091934-Kumar1" target="_blank">[18]</a>. KIM-PTP:MAPK complexes determined to be extended using SAXS written in normal text; KIM-PTP:MAPK complexes determined to be compact written in italics; *, compact nature of the ERK2-PTPSL complex determined by Balasu <i>et al</i>. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0091934#pone.0091934-Balasu1" target="_blank">[24]</a> and corroborated by ITC measurements (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0091934#pone-0091934-t001" target="_blank">Table 1</a>).</p

SAXS analysis of the ERK2:STEP complex.

<p>SAXS analysis of the ERK2:STEP complex.</p

Interaction of Kinase-Interaction-Motif Protein Tyrosine Phosphatases with the Mitogen-Activated Protein Kinase ERK2

<div><p>The mitogen-activation protein kinase ERK2 is tightly regulated by multiple phosphatases, including those of the kinase interaction motif (KIM) PTP family (STEP, PTPSL and HePTP). Here, we use small angle X-ray scattering (SAXS) and isothermal titration calorimetry (ITC) to show that the ERK2:STEP complex is compact and that residues outside the canonical KIM motif of STEP contribute to ERK2 binding. Furthermore, we analyzed the interaction of PTPSL with ERK2 showing that residues outside of the canonical KIM motif also contribute to ERK2 binding. The integration of this work with previous studies provides a quantitative and structural map of how the members of a single family of regulators, the KIM-PTPs, differentially interact with their corresponding MAPKs, ERK2 and p38α.</p></div

Comparison of the P(r) functions of the MAPK:KIM-PTP resting state complexes.

<p>p38α:HePTP, maroon; p38α:PTPSL, red; p38α:STEP, dark blue; ERK2:HePTP, pink; ERK2:STEP, light blue (all p38α:KIM-PTP and ERK2:HePTP data were previously published <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0091934#pone.0091934-Francis1" target="_blank">[14]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0091934#pone.0091934-Francis2" target="_blank">[15]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0091934#pone.0091934-Piserchio1" target="_blank">[17]</a>, but are shown here to provide a better comparison of the <i>P</i>(<i>r</i>) functions).</p

The ERK2:STEP resting-state complex.

<p>(<b>A</b>) Constructs used in this study; (<b>B</b>) SAXS data (I(q) vs q) of the ERK2:STEP resting-state complex (black squares); error bars (grey lines). Error bars show the experimental error based on circular averaging of the 2D solution scattering data; theoretical scattering curve from calculated <i>ab initio</i> molecular envelope (red); <i>inset</i>, Guinier plots for samples at 1.0 mg/ml and 1.7 mg/ml; (<b>C</b>) The ERK2:STEP <i>ab initio</i> molecular envelope in two views rotated by 90° with the dimensions of the envelope.</p

Identification of the substrate recruitment mechanism of the muscle glycogen protein phosphatase 1 holoenzyme

Glycogen is the primary storage form of glucose. Glycogen synthesis and breakdown are tightly controlled by glycogen synthase (GYS) and phosphorylase, respectively. The enzyme responsible for dephosphorylating GYS and phosphorylase, which results in their activation (GYS) or inactivation (phosphorylase) to robustly stimulate glycogen synthesis, is protein phosphatase 1 (PP1). However, our understanding of how PP1 recruits these substrates is limited. Here, we show how PP1, together with its muscle glycogen-targeting (GM) regulatory subunit, recruits and selectively dephosphorylates its substrates. Our molecular data reveal that the GM carbohydrate binding module (GMCBM21), which is amino-terminal to the GM PP1 binding domain, has a dual function in directing PP1 substrate specificity: It either directly recruits substrates (i.e., GYS) or recruits them indirectly by localization (via glycogen for phosphorylase). Our data provide the molecular basis for PP1 regulation by GM and reveal how PP1-mediated dephosphorylation is driven by scaffolding-based substrate recruitment.American Diabetes Association Pathway to Stop Diabetes Grant [1-14-ACN-31, R35GM119455, R01GM098482]Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Docking Interactions of Hematopoietic Tyrosine Phosphatase with MAP Kinases ERK2 and p38α

Hematopoietic tyrosine phosphatase (HePTP) regulates orthogonal MAP kinase signaling cascades by dephosphorylating both extracellular signal-regulated kinase (ERK) and p38. HePTP recognizes a docking site (D-recruitment site, DRS) on its targets using a conserved N-terminal sequence motif (D-motif). Using solution nuclear magnetic resonance spectroscopy and isothermal titration calorimetry, we compare, for the first time, the docking interactions of HePTP with ERK2 and p38α. Our results demonstrate that ERK2–HePTP interactions primarily involve the D-motif, while a contiguous region called the kinase specificity motif also plays a key role in p38α–HePTP interactions. D-Motif–DRS interactions for the two kinases, while similar overall, do show some specific differences

Quantitative in vivo imaging of neuronal glucose concentrations with a genetically encoded fluorescence lifetime sensor.

Glucose is an essential source of energy for the brain. Recently, the development of genetically encoded fluorescent biosensors has allowed real time visualization of glucose dynamics from individual neurons and astrocytes. A major difficulty for this approach, even for ratiometric sensors, is the lack of a practical method to convert such measurements into actual concentrations in ex vivo brain tissue or in vivo. Fluorescence lifetime imaging provides a strategy to overcome this. In a previous study, we reported the lifetime glucose sensor iGlucoSnFR-TS (then called SweetieTS) for monitoring changes in neuronal glucose levels in response to stimulation. This genetically encoded sensor was generated by combining the Thermus thermophilus glucose-binding protein with a circularly permuted variant of the monomeric fluorescent protein T-Sapphire. Here, we provide more details on iGlucoSnFR-TS design and characterization, as well as pH and temperature sensitivities. For accurate estimation of glucose concentrations, the sensor must be calibrated at the same temperature as the experiments. We find that when the extracellular glucose concentration is in the range 2-10&nbsp;mM, the intracellular glucose concentration in hippocampal neurons from acute brain slices is ~20% of the nominal external glucose concentration (~0.4-2&nbsp;mM). We also measured the cytosolic neuronal glucose concentration in vivo, finding a range of ~0.7-2.5&nbsp;mM in cortical neurons from awake mice

Quantitative in vivo

Glucose is an essential source of energy for the brain. Recently, the development of genetically encoded fluorescent biosensors has allowed real time visualization of glucose dynamics from individual neurons and astrocytes. A major difficulty for this approach, even for ratiometric sensors, is the lack of a practical method to convert such measurements into actual concentrations in ex vivo brain tissue or in vivo. Fluorescence lifetime imaging provides a strategy to overcome this. In a previous study, we reported the lifetime glucose sensor iGlucoSnFR-TS (then called SweetieTS) for monitoring changes in neuronal glucose levels in response to stimulation. This genetically encoded sensor was generated by combining the Thermus thermophilus glucose-binding protein with a circularly permuted variant of the monomeric fluorescent protein T-Sapphire. Here, we provide more details on iGlucoSnFR-TS design and characterization, as well as pH and temperature sensitivities. For accurate estimation of glucose concentrations, the sensor must be calibrated at the same temperature as the experiments. We find that when the extracellular glucose concentration is in the range 2-10&nbsp;mM, the intracellular glucose concentration in hippocampal neurons from acute brain slices is ~20% of the nominal external glucose concentration (~0.4-2&nbsp;mM). We also measured the cytosolic neuronal glucose concentration in vivo, finding a range of ~0.7-2.5&nbsp;mM in cortical neurons from awake mice