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Metabolic reprogramming in the OPA1-deficient cells
No full textOPA1, a dynamin-related GTPase mutated in autosomal dominant optic atrophy, is essential for the fusion of the inner mitochondrial membrane. Although OPA1 deficiency leads to impaired mitochondrial morphology, the role of OPA1 in central carbon metabolism remains unclear. Here, we aim to explore the functional role and metabolic mechanism of OPA1 in cell fitness beyond the control of mitochondrial fusion. We applied [U-¹³C]glucose and [U-13C]glutamine isotope tracing techniques to OPA1-knockout (OPA1-KO) mouse embryonic fibroblasts (MEFs) compared to OPA1 wild-type (OPA1-WT) controls. Furthermore, the resulting tracing data were integrated by metabolic flux analysis to understand the underlying metabolic mechanism through which OPA1 deficiency reprograms cellular metabolism. OPA1-deficient MEFs were depleted of intracellular citrate, which was consistent with the decreased oxygen consumption rate in these cells with mitochondrial fission that is not balanced by mitochondrial fusion. Whereas oxidative glucose metabolism was impaired, OPA1-deficient cells activated glutamine-dependent reductive carboxylation and subsequently relied on this reductive metabolism to produce cytosolic citrate as a predominant acetyl-CoA source for de novo fatty acid synthesis. Prevention of cytosolic glutamine reductive carboxylation by GSK321, an inhibitor of isocitrate dehydrogenase 1 (IDH1), largely repressed lipid synthesis and blocked cell proliferation in OPA1-deficient MEFs. Our data support that, when glucose oxidation failed to support lipogenesis and proliferation in cells with unbalanced mitochondrial fission, OPA1 deficiency stimulated metabolic anaplerosis into glutamine-dependent reductive carboxylation in an IDH1-mediated manner
Trapping effects in quantum atomic arrays
No full textQuantum emitters, particularly atomic arrays with subwavelength lattice constant, have been proposed to be an ideal platform for studying the interplay between photons and electric dipoles. In this work, motivated by the recent experiment [1], we develop a microscopic quantum treatment using annihilation and creation operator of atoms in deep optical lattices. Using a diagrammatic approach on the Keldysh contour, we derive the cooperative scattering of the light and obtain the general formula for the S matrix. We apply our method to study the trapping effect, which is beyond previous treatment with spin operators. If the optical lattices are formed by light fields with magical wavelength, the result matches previous results using spin operators. When there is a mismatch between the trapping potentials for atoms in the ground state and the excited state, atomic mirrors become imperfect, with multiple resonances in the optical response. We further study the effect of recoil for large but finite trapping frequency. Our results are consistent with existing experiments
New approaches to dark matter detection
No full textDecades of searching for theoretically motivated dark matter candidates have yielded no results, so the research community is starting to adopt different strategies for detecting dark matter. Seven scientists discuss these new approaches
On the Robustness of the Velocity Anisotropy Parameter in Probing the Stellar Kinematics in Milky Way-Like Galaxies: Takeaway from TNG50 Simulation
No full textWe analyze the velocity anisotropy of stars in real and energy space for a sample of Milky Way–like galaxies in the TNG50 simulation. We employ different selection criteria, including spatial, kinematic, and metallicity cuts, and make three halo classes (A-C) that show mild-to-strong sensitivity to different selections. The above classes cover 48%, 16%, and 36% of the halos, respectively. We analyze the β radial profiles and divide them into either monotonically increasing radial profiles or ones with peaks and troughs. We demonstrate that halos with monotonically increasing β profiles are mostly from class A, while those with peaks/troughs are part of classes B and C. This means that care must be taken, as the observationally reported peaks/troughs might be a consequence of different selection criteria. We infer the anisotropy parameter β energy space and compare that against the β radial profile. It is seen than 65% of halos with very mild sensitivity to different selections in real space are those for which the β radial and energy profiles are closely related. Consequently, we propose that comparing the β radial and energy profiles might be a novel way to examine the sensitivity to different selection criteria and thus examining the robustness of the anisotropy parameter in tracing stellar kinematics. We compare simulated β radial profiles against various observations and demonstrate that, in most cases, the model diversity is comparable with the error bars from different observations, meaning that the TNG50 models are in good overall agreement with observations
Sub-Decadal Volcanic Tsunamis Due To Submarine Trapdoor Faulting at Sumisu Caldera in the Izu-Bonin Arc
No full textThe main cause of tsunamis is large subduction zone earthquakes with seismic magnitudes M_w > 7, but submarine volcanic processes can also generate tsunamis. At the submarine Sumisu caldera in the Izu–Bonin arc, moderate-sized earthquakes with M_w < 6 occur almost once a decade and cause meter-scale tsunamis. The source mechanism of the volcanic earthquakes is poorly understood. Here we use tsunami and seismic data from the recent 2015 event to show that abrupt uplift of the submarine caldera, with a large brittle rupture of the ring fault system due to overpressure in its magma reservoir, caused the earthquake and tsunami. This submarine trapdoor faulting mechanism can efficiently generate tsunamis due to large vertical seafloor displacements, but it inefficiently radiates long-period seismic waves. Similar seismic radiation patterns and tsunami waveforms due to repeated earthquakes indicate that continuous magma supply into the caldera induces quasi-regular trapdoor faulting. This mechanism of tsunami generation by submarine trapdoor faulting underscores the need to monitor submarine calderas for robust assessment of tsunami hazards
Fe²⁺-Mg partitioning between olivine and liquid at low oxygen fugacity: an experimental and thermodynamic framework
No full textA set of 1-atm gas-mixing experiments (n = 31) was run using Re wire loops at low-oxygen fugacity (ƒO₂, within one half-log unit of the Fe–FeO buffer) and temperatures of 1175–1400 °C to explore the compositional dependence of the Fe²⁺–Mg olivine–liquid exchange coefficient, K^(ol/liq)_(D,Fe²⁺-Mg), under conditions where corrections for liquid Fe³⁺ are small. The bulk compositions used for these experiments include a picrite, a high-alumina basalt, and a suite of three MORB compositions with variable Fe/Mg. The K^(ol/liq)_(D,Fe²⁺-Mg) values from the n = 14 experiments run on pre-saturated Re wire loops were fit to a regular solution model that relates K^(ol/liq)_(D,Fe²⁺-Mg) to temperature, melt composition, and olivine composition. Fe²⁺–Mg exchange in the experiments is well-described using two parameters: the SiO₂ content of the liquid and the coexisting olivine composition. Combining our experiments with a literature compilation of low-pressure, low-ƒO₂ experiments (largely on non-terrestrial bulk compositions) produced a combined data set spanning a broad region of composition space (e.g., liquid TiO₂ and Na₂O + K₂O contents up to 18.4 wt% and 8.4 wt%, respectively). Fitting this expanded experimental database required two additional liquid compositional terms: Ti, and a Si-(Na + K) cross-term. Because the Fe³⁺ content of all of the experimental liquids is low, the compositional variation seen in K^(ol/liq)_(D,Fe²⁺-Mg) is effectively independent of the compositional effects on liquid Fe³⁺/Fe²⁺ ratios. Given olivine–liquid Mg or Fe²⁺ partition coefficient information, it is possible to eliminate the explicit dependence of K^(ol/liq)_(D,Fe²⁺-Mg) on olivine composition, enabling a simple iterative approach for calculating the composition of oexisting olivine given only the bulk composition (and Fe³⁺/Fe²⁺ ratio) of an olivine-saturated liquid
Cell Chromatography: Biocompatible Chromatographic Separation and Interrogation of Microbial Cells
No full textThe isolation of pure, single colonies lies at the heart of experimental microbiology. However, a microbial colony typically contains around 1 million cells at all stages of the life cycle. Here, we describe a novel cell chromatography method that facilitates the capture, purification, and interrogation of microbial cell populations from both single and mixed cultures. The method described relies on, but is not limited to, differences in surface charge to separate bacterial strains. The method is fully biocompatible, leading to no significant loss of cell viability. The chromatographic capture of cells, combined with selective elution methods, facilitates a greater level of experimental control over the sample inputs required for downstream high-throughput and high-sensitivity analytical methods. The application of the method for interrogating the antibiotic resistance of bacterial strains and for the separation of bacteria from environmental samples is illustrated
PHANGS: constraining star formation time-scales using the spatial correlations of star clusters and giant molecular clouds
No full textIn the hierarchical view of star formation, giant molecular clouds (GMCs) undergo fragmentation to form small-scale structures made up of stars and star clusters. Here we study the connection between young star clusters and cold gas across a range of extragalactic environments by combining the high resolution (1") PHANGS–ALMA catalogue of GMCs with the star cluster catalogues from PHANGS–HST. The star clusters are spatially matched with the GMCs across a sample of 11 nearby star-forming galaxies with a range of galactic environments (centres, bars, spiral arms, etc.). We find that after 4 − 6 Myr the star clusters are no longer associated with any gas clouds. Additionally, we measure the autocorrelation of the star clusters and GMCs as well as their cross-correlation to quantify the fractal nature of hierarchical star formation. Young (≤10 Myr) star clusters are more strongly autocorrelated on kpc and smaller spatial scales than the >10 Myr stellar populations, indicating that the hierarchical structure dissolves over time
SuperSpec: On-Chip Spectrometer Design, Characterization, and Performance
No full textSuperSpec is an integrated, on-chip spectrometer for millimeter and sub-millimeter astronomy intended to pave the way for large-scale, multi-beam spectrometer instruments. SuperSpec is demonstrating a three beam, dual-polarization instrument for observing star formation in distant galaxies on the Large Millimeter Telescope , a 50 m telescope on Volcan Sierra Negra in Mexico. SuperSpec provides moderate resolution (R∼270−290) in the 1 mm atmospheric window (200–300 GHz) with a lithographically patterned filterbank on a 3.5 cm x 5.5 cm chip. The filterbank intended for deployment is implemented in niobium, fed by a lensed antenna, and using a extremely low-volume (2.6μm³) titanium nitride lumped element kinetic inductor detectors (LEKIDs) as the sensors. The small size of the spectrometer and inherent multiplexibility of the kinetic inductance detectors will allow the future use of SuperSpec in larger, multi-pixel/multi-object spectrometers far beyond the three-pixel spectrometer being demonstrated soon. We report the design of the spectrometer, laboratory characterization of devices for the upcoming SuperSpec deployment. This involves laboratory testing of the filterbank spectral response, and observing noise in the TiN KIDs
Quantifying Isotopologue Reaction Networks (QIRN): A modelling tool for predicting stable isotope fractionations in complex networks
No full textNatural-abundance stable isotope compositions are powerful tools for understanding complex processes across myriad scientific disciplines. However, quantitative interpretation of these signals often requires equally complex models. Previous stable isotope models have treated isotopic compositions as intrinsic properties of molecules or atoms (e.g. δ¹³C, ¹³R, etc.). This has proven to be a computationally efficient but inflexible approach. Here, we present a new isotope modelling software tool that combines computational strategies used in metabolic modeling with an understanding of natural isotope fractionations from the geosciences, called Quantifying Isotopologue Reaction Networks (QIRN, "churn"). QIRN treats isotopic properties as distributions of discrete isotopologues, i.e. molecules with different numbers and distributions of isotopic substitutions. This approach is remarkably generalizable and computationally tractable, enabling models of reaction networks with unprecedented complexity. QIRN parameterizes reactions as rate law equations with distinct isotopologues as the reactants and products. Isotope effects are implemented as small changes to the relevant isotopologues’ rate constants. Running this model forward in time gives the numerical solution for steady state isotopologue abundances. Different subsets of the isotopologue population can then be sampled to quantify numerous isotopic proprieties simultaneously (i.e. compound-specific, site-specific, and multiply-substituted isotope compositions). Furthermore, QIRN can model any physical, chemical or biological process as reversible or irreversible. As such, it incorporates both kinetic and equilibrium isotope effects. It can be readily applied to any isotope system (i.e. C, N, O, etc.), though at present can only track two isotopes of one element at a time. Given its generalizability, QIRN has a diverse range of applications. To demonstrate the flexibility and efficiency of QIRN, we reconstructed previous (intrinsic-property) models of sulfate reduction, abiotic amino acid synthesis, lipid biosynthesis, and photosynthesis. In these examples, QIRN consistently reproduced outputs from prior models and predicted isotopic anomalies that have been measured in nature. With its new approach to isotope modelling, QIRN will expand the potential complexity of modelled reaction networks, help predict isotopic signals that can direct experimental efforts, and provide a more efficient means of modeling emerging isotopic properties such as 'clumped isotopes'