CMT2N-causing aminoacylation domain mutants enable Nrp1 interaction with AlaRS

Through dominant mutations, aminoacyl-tRNA synthetases constitute the largest protein family linked to Charcot-Marie-Tooth disease (CMT). An example is CMT subtype 2N (CMT2N), caused by individual mutations spread out in AlaRS, including three in the aminoacylation domain, thereby suggesting a role for a tRNA-charging defect. However, here we found that two are aminoacylation defective but that the most widely distributed R329H is normal as a purified protein in vitro and in unfractionated patient cell samples. Remarkably, in contrast to wild-type (WT) AlaRS, all three mutant proteins gained the ability to interact with neuropilin 1 (Nrp1), the receptor previously linked to CMT pathogenesis in GlyRS. The aberrant AlaRS-Nrp1 interaction is further confirmed in patient samples carrying the R329H mutation. However, CMT2N mutations outside the aminoacylation domain do not induce the Nrp1 interaction. Detailed biochemical and biophysical investigations, including X-ray crystallography, small-angle X-ray scattering, hydrogen-deuterium exchange (HDX), switchSENSE hydrodynamic diameter determinations, and protease digestions reveal a mutation-induced structural loosening of the aminoacylation domain that correlates with the Nrp1 interaction. The b1b2 domains of Nrp1 are responsible for the interaction with R329H AlaRS. The results suggest Nrp1 is more broadly associated with CMT-associated members of the tRNA synthetase family. Moreover, we revealed a distinct structural loosening effect induced by a mutation in the editing domain and a lack of conformational impact with C-Ala domain mutations, indicating mutations in the same protein may cause neuropathy through different mechanisms. Our results show that, as with other CMT-associated tRNA synthetases, aminoacylation per se is not relevant to the pathology

CMT2N-causing aminoacylation domain mutants enable Nrp1 interaction with AlaRS.

Through dominant mutations, aminoacyl-tRNA synthetases constitute the largest protein family linked to Charcot-Marie-Tooth disease (CMT). An example is CMT subtype 2N (CMT2N), caused by individual mutations spread out in AlaRS, including three in the aminoacylation domain, thereby suggesting a role for a tRNA-charging defect. However, here we found that two are aminoacylation defective but that the most widely distributed R329H is normal as a purified protein in vitro and in unfractionated patient cell samples. Remarkably, in contrast to wild-type (WT) AlaRS, all three mutant proteins gained the ability to interact with neuropilin 1 (Nrp1), the receptor previously linked to CMT pathogenesis in GlyRS. The aberrant AlaRS-Nrp1 interaction is further confirmed in patient samples carrying the R329H mutation. However, CMT2N mutations outside the aminoacylation domain do not induce the Nrp1 interaction. Detailed biochemical and biophysical investigations, including X-ray crystallography, small-angle X-ray scattering, hydrogen-deuterium exchange (HDX), switchSENSE hydrodynamic diameter determinations, and protease digestions reveal a mutation-induced structural loosening of the aminoacylation domain that correlates with the Nrp1 interaction. The b1b2 domains of Nrp1 are responsible for the interaction with R329H AlaRS. The results suggest Nrp1 is more broadly associated with CMT-associated members of the tRNA synthetase family. Moreover, we revealed a distinct structural loosening effect induced by a mutation in the editing domain and a lack of conformational impact with C-Ala domain mutations, indicating mutations in the same protein may cause neuropathy through different mechanisms. Our results show that, as with other CMT-associated tRNA synthetases, aminoacylation per se is not relevant to the pathology

The development of HISPEC for Keck and MODHIS for TMT: science cases and predicted sensitivities

HISPEC is a new, high-resolution near-infrared spectrograph being designed for the W.M. Keck II telescope. By offering single-shot, R=100,000 between 0.98 - 2.5 um, HISPEC will enable spectroscopy of transiting and non-transiting exoplanets in close orbits, direct high-contrast detection and spectroscopy of spatially separated substellar companions, and exoplanet dynamical mass and orbit measurements using precision radial velocity monitoring calibrated with a suite of state-of-the-art absolute and relative wavelength references. MODHIS is the counterpart to HISPEC for the Thirty Meter Telescope and is being developed in parallel with similar scientific goals. In this proceeding, we provide a brief overview of the current design of both instruments, and the requirements for the two spectrographs as guided by the scientific goals for each. We then outline the current science case for HISPEC and MODHIS, with focuses on the science enabled for exoplanet discovery and characterization. We also provide updated sensitivity curves for both instruments, in terms of both signal-to-noise ratio and predicted radial velocity precision.Comment: 25 pages, 9 figures. To appear in the Proceedings of SPIE: Techniques and Instrumentation for Detection of Exoplanets XI, vol. 12680 (2023

Detecting Biosignatures in Nearby Rocky Exoplanets Using High-contrast Imaging and Medium-resolution Spectroscopy with the Extremely Large Telescope

In the upcoming decades, one of the primary objectives in exoplanet science is to search for habitable planets and signs of extraterrestrial life in the Universe. Signs of life can be indicated by thermal-dynamical imbalance in terrestrial planet atmospheres. O2 and CH4 in the modern Earth's atmosphere are such signs, commonly termed biosignatures. These biosignatures in exoplanetary atmospheres can potentially be detectable through high-contrast imaging instruments on future extremely large telescopes. To quantify the signal-to-noise ratio (S/N) with extremely large telescopes, we select up to 10 nearby rocky planets and simulate medium-resolution (R ∼ 1000) direct imaging of these planets using the Mid-infrared ELT Imager and Spectrograph (ELT/METIS, 3–5.6 μm) and the High Angular Resolution Monolithic Optical and Near-infrared Integral field spectrograph (ELT/HARMONI, 0.5–2.45 μm). We calculate the S/N for the detection of biosignatures including CH4, O2, H2O, and CO2. Our results show that GJ 887 b has the highest detection of S/N for biosignatures, and Proxima Cen b exhibits the only detectable CO2 among the targets for ELT/METIS direct imaging. We also investigate the TRAPPIST-1 system, the archetype of nearby transiting rocky planet systems, and compare the biosignature detection of transit spectroscopy with JWST versus direct spectroscopy with ELT/HARMONI. Our findings indicate JWST is more suitable for detecting and characterizing the atmospheres of transiting planet systems such as TRAPPIST-1 that are relatively further away and have smaller angular separations than more nearby nontransiting planets.Undergraduate Research Apprenticeship Program (URAP) of Office of Academic Enrichment, OSUNational Science Foundation under grant No.2143400No embargoAcademic Major: Astronomy and AstrophysicsAcademic Major: Physic

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Detecting Biosignatures in Nearby Rocky Exoplanets Using High-contrast Imaging and Medium-resolution Spectroscopy with the Extremely Large Telescope

In the upcoming decades, one of the primary objectives in exoplanet science is to search for habitable planets and signs of extraterrestrial life in the Universe. Signs of life can be indicated by thermal-dynamical imbalance in terrestrial planet atmospheres. O _2 and CH _4 in the modern Earth’s atmosphere are such signs, commonly termed biosignatures. These biosignatures in exoplanetary atmospheres can potentially be detectable through high-contrast imaging instruments on future extremely large telescopes. To quantify the signal-to-noise ratio (S/N) with extremely large telescopes, we select up to 10 nearby rocky planets and simulate medium-resolution ( R ∼ 1000) direct imaging of these planets using the Mid-infrared ELT Imager and Spectrograph (ELT/METIS, 3–5.6 μ m) and the High Angular Resolution Monolithic Optical and Near-infrared Integral field spectrograph (ELT/HARMONI, 0.5–2.45 μ m). We calculate the S/N for the detection of biosignatures including CH _4 , O _2 , H _2 O, and CO _2 . Our results show that GJ 887 b has the highest detection of S/N for biosignatures, and Proxima Cen b exhibits the only detectable CO _2 among the targets for ELT/METIS direct imaging. We also investigate the TRAPPIST-1 system, the archetype of nearby transiting rocky planet systems, and compare the biosignature detection of transit spectroscopy with JWST versus direct spectroscopy with ELT/HARMONI. Our findings indicate JWST is more suitable for detecting and characterizing the atmospheres of transiting planet systems such as TRAPPIST-1 that are relatively further away and have smaller angular separations than more nearby nontransiting planets

An Indoor Fingerprint Positioning Algorithm Based on WKNN and Improved XGBoost

Considering the low indoor positioning accuracy and poor positioning stability of traditional machine-learning algorithms, an indoor-fingerprint-positioning algorithm based on weighted k-nearest neighbors (WKNN) and extreme gradient boosting (XGBoost) was proposed in this study. Firstly, the outliers in the dataset of established fingerprints were removed by Gaussian filtering to enhance the data reliability. Secondly, the sample set was divided into a training set and a test set, followed by modeling using the XGBoost algorithm with the received signal strength data at each access point (AP) in the training set as the feature, and the coordinates as the label. Meanwhile, such parameters as the learning rate in the XGBoost algorithm were dynamically adjusted via the genetic algorithm (GA), and the optimal value was searched based on a fitness function. Then, the nearest neighbor set searched by the WKNN algorithm was introduced into the XGBoost model, and the final predicted coordinates were acquired after weighted fusion. As indicated in the experimental results, the average positioning error of the proposed algorithm is 1.22 m, which is 20.26–45.58% lower than that of traditional indoor positioning algorithms. In addition, the cumulative distribution function (CDF) curve can converge faster, reflecting better positioning performance