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At least 595 records · Page 33

Hybrid finite element and Brownian dynamics method for charged particles

Diffusion is often the rate-determining step in many biological processes. Currently, the two main computational methods for studying diffusion are stochastic methods, such as Brownian dynamics, and continuum methods, such as the finite element method. A previous study introduced a new hybrid diffusion method that couples the strengths of each of these two methods, but was limited by the lack of interactions among the particles; the force on each particle had to be from an external field. This study further develops the method to allow charged particles. The method is derived for a general multidimensional system and is presented using a basic test case for a one-dimensional linear system with one charged species and a radially symmetric system with three charged species.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

On the advantages of exploiting memory in Markov state models for biomolecular dynamics

Biomolecular dynamics play an important role in numerous biological processes. Markov State Models (MSMs) provide a powerful approach to study these dynamic processes by predicting long time scale dynamics based on many short molecular dynamics (MD) simulations. In an MSM, protein dynamics are modeled as a kinetic process consisting of a series of Markovian transitions between different conformational states at discrete time intervals (called “lag time”). To achieve this, a master equation must be constructed with a sufficiently long lag time to allow interstate transitions to become truly Markovian. This imposes a major challenge for MSM studies of proteins since the lag time is bound by the length of relatively short MD simulations available to estimate the frequency of transitions. Here, we show how one can employ the generalized master equation formalism to obtain an exact description of protein conformational dynamics both at short and long time scales without the time resolution restrictions imposed by the MSM lag time. Using a simple kinetic model, alanine dipeptide, and WW domain, we demonstrate that it is possible to construct these quasi-Markov State Models (qMSMs) using MD simulations that are 5–10 times shorter than those required by MSMs. These qMSMs only contain a handful of metastable states and, thus, can greatly facilitate the interpretation of mechanisms associated with protein dynamics. A qMSM opens the door to the study of conformational changes of complex biomolecules where a Markovian model with a few states is often difficult to construct due to the limited length of available MD simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Strong attractions and repulsions mediated by monovalent salts

Significance The physical properties of proteins and polyions in electrolyte solutions are of crucial importance for understanding biological processes and for controlling biotechnological processes. The concentration of salt controls the range and strength of the interactions in these complex electrolytes. Here, multiscale coarse-grained molecular dynamics simulations reveal long-range interactions between nanoparticles in aqueous solutions at high monovalent salt concentrations. The simulations explain the crystallization of nanoparticles even when they are strongly charged and explain the reentrant attractive to repulsive to attractive interactions as the nanoparticle charge density increases in high monovalent salt-concentration conditions.

Li, Yaohua↗

Photoelectric conversion on Earth’s surface via widespread Fe- and Mn-mineral coatings

Sunlight drives photosynthesis and associated biological processes, and also influences inorganic processes that shape Earth’s climate and geochemistry. Bacterial solar-to-chemical energy conversion on this planet evolved to use an intricate intracellular process of phototrophy. However, a natural nonbiological counterpart to phototrophy has yet to be recognized. In this work, we reveal the inherent “phototrophic-like” behavior of vast expanses of natural rock/soil surfaces from deserts, red soils and karst environments, all of which can drive photon-to-electron conversions. Using scanning electron microscopy, transmission electron microscopy, micro-Raman spectroscopy and X-ray absorption spectroscopy, Fe and Mn (oxyhydr)oxide-rich coatings were found in rock varnishes, as were Fe (oxyhydr)oxides on red soil surfaces and minute amounts of Mn oxides on karst rock surfaces. By directly fabricating a photoelectric detection device on the thin section of a rock varnish sample, we have recorded the first in situ photocurrent micromapping of the coatings, which behave as highly sensitive and stable photoelectric systems. Additional measurements of red soil and powder separated from the outermost surface of karst rocks yielded photocurrents that are also sensitive to irradiation. The prominent solar-responsive capability of the phototrophic-like rocks/soils is ascribed to the semiconducting Fe and Mn (oxyhydr)oxide mineral coatings. The native semiconducting Fe/Mn-rich coatings may play a role similar in part to photosynthetic systems and thus provide a distinctive driving force for redox (bio)geochemistry on Earth’s surfaces.

Lu, Anhuai↗

Nutrient availability and senescence spatially structure the dynamics of a foundation species

Significance Landscapes are spatially heterogeneous, and the measurement of spatial pattern is dependent upon observation scale. Understanding plant populations requires assessing their extrinsic interactions with the environment as well as intrinsic biological processes and has been difficult because of the inability to track both plant abundance and health on appropriate scales. We introduce remote sensing observations that assess the abundance and health of giant kelp, an important ecosystem-structuring species, over regional and local scales. We find that both extrinsic nutrient availability and intrinsic senescence processes regulate population dynamics but on regional and local scales, respectively. This suggests that future satellite missions will be able to assess plant abundance and health and their interactions with the environment on local to global scales.

54 ENVIRONMENTAL SCIENCES↗

Facile and dynamic cleavage of every iron–sulfide bond in cuboidal iron–sulfur clusters

Nature employs weak-field metalloclusters to support a wide range of biological processes. The most ubiquitous metalloclusters are the cuboidal Fe–S clusters, which are comprised of Fe sites with locally high-spin electronic configurations. Such configurations enhance rates of ligand exchange and imbue the clusters with a degree of structural plasticity that is increasingly thought to be functionally relevant. Here, we examine this phenomenon using isotope tracing experiments. Specifically, we demonstrate that synthetic [Fe 4 S 4 ] and [MoFe 3 S 4 ] clusters exchange their Fe atoms with Fe 2+ ions dissolved in solution, a process that involves the reversible cleavage and reformation of every Fe–S bond in the cluster core. This exchange is facile—in most cases occurring at room temperature on the timescale of minutes—and documented over a range of cluster core oxidation states and terminal ligation patterns. In addition to suggesting a highly dynamic picture of cluster structure, these results provide a method for isotopically labeling pre-formed clusters with spin-active nuclei, such as 57 Fe. Such a protocol is demonstrated for the radical S -adenosyl- l -methionine enzyme, RlmN.

Science & Technology - Other Topics↗

Design and fabrication of a differential scanning nanocalorimeter

This paper describes the design, fabrication, and characterization of a differential scanning nanocalorimeter that significantly reduces the sample volume to microliters and can potentially improve the temperature sensitivity to 10 µK. The nanocalorimeter consists of a polymeric freestanding membrane, four high-sensitive low-noise thermistors based on silicon carbide (SiC), and a platinum heater and temperature sensor. With the integrated heater and sensors, temperature scanning and power compensation can be achieved for calorimetric measurement. Temperature sensing SiC film was prepared by using sintered SiC target and DC magnetron sputtering under different gas pressures and sputtering power. The SiC sensing material is characterized through the measurement of current–voltage curves and noise levels. The thermal performance of a fabricated nanocalorimeter is studied in simulation and experiment. The experiment results show the device has excellent thermal isolation to hold thermal energy. As a result, the noise test together with the simulation show the device is promising for micro 10 µK temperature sensitivity and nanowatt resolution which will lead to low-volume ultra-sensitive nanocalorimetry for biological processes, such as protein folding and ligand binding.

42 ENGINEERING↗

Glycan Reader is improved to recognize most sugar types and chemical modifications in the Protein Data Bank

Motivation: Glycans play a central role in many essential biological processes. Glycan Reader was originally developed to simplify the reading of Protein Data Bank (PDB) files containing glycans through the automatic detection and annotation of sugars and glycosidic linkages between sugar units and to proteins, all based on atomic coordinates and connectivity information. Carbohydrates can have various chemical modifications at different positions, making their chemical space much diverse. Unfortunately, current PDB files do not provide exact annotations for most carbohydrate derivatives and more than 50% of PDB glycan chains have at least one carbohydrate derivative that could not be correctly recognized by the original Glycan Reader. Results: Glycan Reader has been improved and now identifies most sugar types and chemical modifications (including various glycolipids) in the PDB, and both PDB and PDBx/mmCIF formats are supported. CHARMM-GUI Glycan Reader is updated to generate the simulation system and input of various glycoconjugates with most sugar types and chemical modifications. It also offers a new functionality to edit the glycan structures through addition/deletion/modification of glycosylation types, sugar types, chemical modifications, glycosidic linkages, and anomeric states. The simulation system and input files can be used for CHARMM, NAMD, GROMACS, AMBER, GENESIS, LAMMPS, Desmond, OpenMM, and CHARMM/OpenMM. Glycan Fragment Database in GlycanStructure. Org is also updated to provide an intuitive glycan sequence search tool for complex glycan structures with various chemical modifications in the PDB.

Park, Sang-Jun↗

Lighting up yeast: overview of optogenetics in yeast and their applications to yeast biotechnology

Abstract Optogenetics is an empowering technology that uses light-responsive proteins to control biological processes. Because of its genetic tractability, abundance of genetic tools, and robust culturing conditions, Saccharomyces cerevisiae has served for many years as an ideal platform in which to study, develop, and apply a wide range of optogenetic systems. In many instances, yeast has been used as a steppingstone in which to characterize and optimize optogenetic tools to later be deployed in higher eukaryotes. More recently, however, optogenetic tools have been developed and deployed in yeast specifically for biotechnological applications, including in nonconventional yeasts. In this review, we summarize various optogenetic systems responding to different wavelengths of light that have been demonstrated in diverse yeast species. We then describe various applications of these optogenetic tools in yeast, particularly in metabolic engineering and recombinant protein production. Finally, we discuss emerging applications in yeast cybergenetics—the interfacing of yeast and computers for closed-loop controls of yeast bioprocesses—and the potential impact of optogenetics in other future biotechnological applications.

Biotechnology & Applied Microbiology↗

Transcript and metabolite network perturbations in lignin biosynthetic mutants of Arabidopsis

Abstract Lignin, one of the most abundant polymers in plants, is derived from the phenylpropanoid pathway, which also gives rise to an array of metabolites that are essential for plant fitness. Genetic engineering of lignification can cause drastic changes in transcription and metabolite accumulation with or without an accompanying development phenotype. To understand the impact of lignin perturbation, we analyzed transcriptome and metabolite data from the rapidly lignifying stem tissue in 13 selected phenylpropanoid mutants and wild-type Arabidopsis (Arabidopsis thaliana). Our dataset contains 20,974 expressed genes, of which over 26% had altered transcript levels in at least one mutant, and 18 targeted metabolites, all of which displayed altered accumulation in at least one mutant. We found that lignin biosynthesis and phenylalanine supply via the shikimate pathway are tightly co-regulated at the transcriptional level. The hierarchical clustering analysis of differentially expressed genes (DEGs) grouped the 13 mutants into 5 subgroups with similar profiles of mis-regulated genes. Functional analysis of the DEGs in these mutants and correlation between gene expression and metabolite accumulation revealed system-wide effects on transcripts involved in multiple biological processes.

Plant Sciences↗

Locoregional Treatment of Glioblastoma With Targeted α Therapy: [213Bi]Bi-DOTA–Substance P Versus [225Ac]Ac-DOTA–Substance P—Analysis of Influence Parameters

Background Glioblastoma (GB) is the most malignant primary brain tumor. Therefore, introduction of new treatment options is critically important. The aim of this study was to assess local treatment with α emitters [ 213 Bi]Bi-DOTA–substance P (SP) and [ 225 Ac]Ac-DOTA-SP. Methods Treatment was performed as salvage therapy in patients with recurrent primary and secondary GB. [ 213 Bi]Bi-DOTA-SP with injected activity 1.85 GBq per cycle was used in 20 primary (48.2 ± 11.8 years old) and in 9 secondary (38.8 ± 10.8 years old) GB patients and [ 225 Ac]Ac-DOTA-SP in 15 primary (45.1 ± 9.9 years old) and in 6 secondary (37.8 ± 6.4 years old) GB patients with a dose escalation scheme (10, 20, and 30 MBq). Results Local treatment with [ 213 Bi]Bi-DOTA-SP and [ 225 Ac]Ac-DOTA-SP was well tolerated with only few adverse effects. There was no statistically significant difference between [ 213 Bi]Bi-DOTA-SP and [ 225 Ac]Ac-DOTA-SP groups in survival parameters. For primary GB, survival parameters of patients treated with [ 213 Bi]Bi-DOTA-SP and [ 225 Ac]Ac-DOTA-SP were as follows(in months): progression-free survival time, 2.7 versus 2.4; OS-d (overall survival from time of diagnosis to death from any cause), 23.6 versus 21.0; OS-t (overall survival from the start of treatment to death from any cause), 7.5 versus 5.0; and OS-r (overall survival from recurrence in primary tumors to death from any cause), 10.9 versus 12.0. Survival parameters of secondary GB patients treated with [ 213 Bi]Bi-DOTA-SP and [ 225 Ac]Ac-DOTA-SP were as follows (in months): progression-free survival time, 5.8 versus 2.4; OS-d, 52.3 versus 65.0; OS-t, 16.4 versus 16.0; and OS-c (overall survival from conversion into secondary GB multiforme to death from any cause), 18.4 versus 36.0. Conclusions The similarity results of 213 Bi or 225 Ac may suggest that the local treatment of brain tumors can be greatly simplified. The experience to date shows that local radioisotope treatment of brain tumors requires further dosimetry studies, taking into account the complexity of biological processes.

Radiology, Nuclear Medicine & Medical Imaging↗

Extended families of critical and stationary droplets for nonequilibrium phase transitions in spatially discrete bistable systems

Bistable nonequilibrium systems are realized in catalytic reaction-diffusion processes, biological transport and regulation, spatial epidemics, etc. Behavior in spatially continuous formulations, described at the mean-field level by reaction-diffusion type equations (RDEs), often mimics that of classic equilibrium van der Waals type systems. When accounting for noise, similarities include a discontinuous phase transition at some value, p eq , of a control parameter, p , with metastability and hysteresis around p eq . For each p , there is a unique critical droplet of the more stable phase embedded in the less stable or metastable phase which is stationary (neither shrinking nor growing), and with size diverging as p → p eq . Spatially discrete analogs of these mean-field formulations, described by lattice differential equations (LDEs), are more appropriate for some applications, but have received less attention. It is recognized that LDEs can exhibit richer behavior than RDEs, specifically propagation failure for planar interphases separating distinct phases. Herein, we show that this feature, together with an orientation dependence of planar interface propagation also deriving from spatial discreteness, results in the occurrence of entire families of stationary droplets. The extent of these families increases approaching the transition and can be infinite if propagation failure is realized. In addition, there can exist a regime of generic two-phase coexistence where arbitrarily large droplets of either phase always shrink. Such rich behavior is qualitatively distinct from that for classic nucleation in equilibrium and spatially continuous nonequilibrium systems.

97 MATHEMATICS AND COMPUTING↗

(2 + δ)-dimensional theory of the electromechanics of lipid membranes: Electrostatics

The coupling of electric fields to the mechanics of lipid membranes gives rise to intriguing electromechanical behavior, as, for example, evidenced by the deformation of lipid vesicles in external electric fields. Electromechanical effects are relevant for many biological processes, such as the propagation of action potentials in axons and the activation of mechanically gated ion channels. Currently, a theoretical framework describing the electromechanical behavior of arbitrarily curved and deforming lipid membranes does not exist. Purely mechanical models commonly treat lipid membranes as two-dimensional surfaces, ignoring their finite thickness. While holding analytical and numerical merit, this approach cannot describe the coupling of lipid membranes to electric fields and is thus unsuitable for electromechanical models. In a sequence of articles, we derive an effective surface theory of the electromechanics of lipid membranes, called the (2 + δ)-dimensional theory, which has the advantages of surface descriptions while accounting for finite thickness effects. The present article proposes a generic dimension reduction procedure relying on low-order spectral expansions. This procedure is applied to the electrostatics of lipid membranes to obtain the (2 + δ)-dimensional theory that captures potential differences across and electric fields within lipid membranes. Finally, this model is tested on different geometries relevant for lipid membranes, showing good agreement with the corresponding three-dimensional electrostatics theory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computing Free Energies with Fluctuation Relations on Quantum Computers

As a central thermodynamic property, free energy enables the calculation of virtually any equilibrium property of a physical system, allowing for the construction of phase diagrams and predictions about transport, chemical reactions, and biological processes. Thus, methods for efficiently computing free energies, which in general is a difficult problem, are of great interest to broad areas of physics and the natural sciences. The majority of techniques for computing free energies target classical systems, leaving the computation of free energies in quantum systems less explored. Recently developed fluctuation relations enable the computation of free energy differences in quantum systems from an ensemble of dynamic simulations. While performing such simulations is exponentially hard on classical computers, quantum computers can efficiently simulate the dynamics of quantum systems. Here, we present an algorithm utilizing a fluctuation relation known as the Jarzynski equality to approximate free energy differences of quantum systems on a quantum computer. In this work we discuss under which conditions our approximation becomes exact, and under which conditions it serves as a strict upper bound. Furthermore, we successfully demonstrate a proof of concept of our algorithm using the transverse field Ising model on a real quantum processor. As quantum hardware continues to improve, we anticipate that our algorithm will enable computation of free energy differences for a wide range of quantum systems useful across the natural sciences.

97 MATHEMATICS AND COMPUTING↗

Multimodal Microchannel and Nanowell-Based Microfluidic Platforms for Bioimaging

Modern live-cell imaging approaches permit real-time visualization of biological processes. However, limitations for unicellular organism trapping, culturing and long-term imaging can preclude complete understanding of how such microorganisms respond to perturbations in their local environment or linking single-cell variability to whole population dynamics. We have developed microfluidic platforms to overcome prior technical bottlenecks to allow both chemostat and compartmentalized cellular growth conditions using the same device. Additionally, a nanowell-based platform enables a high throughput approach to scale up compartmentalized imaging optimized within the microfluidic device. These channel and nanowell platforms are complementary, and both provide fine control over the local environment as well as the ability to add/replace media components at any experimental time point.

bioimaging↗

Impacts of Sea‐Level Rise on Hypoxia and Phytoplankton Production in Chesapeake Bay: Model Prediction and Assessment

In this study, the influence of sea-level rise (SLR) on seasonal hypoxia and phytoplankton production in Chesapeake Bay is investigated using a 3D unstructured grid model. Three SLR scenarios (0.17, 0.5, and 1.0 m) were conducted from 1991 to 1995. Results show that the summer hypoxic volume (HV) increases about 2%, 8%, and 16%, respectively, for these three scenarios, compared with Base Scenario. The contributions of physical and biological processes on the increase in the HV were analyzed. With the projected SLR, enhanced gravitational circulation transports more oxygen-rich water in the bottom layer from the mouth. However, the pycnocline moves upwards along with increasing water depth, which largely prolongs the time for dissolved oxygen (DO) to be transported to the bottom. The altered physical processes contribute greatly to a larger HV bay-wide. Besides, SLR increases the whole Bay phytoplankton production, with a larger increase in shallow areas (e.g., 53% in areas with depth <1 m under SLR of 0.5 m). Enhanced light availability is suggested to be the major driver of blooming phytoplankton under SLR in shallow areas. While increased DO production over the euphotic zone is mostly released to the atmosphere and transported downstream, the increase in settled organic matter greatly promotes DO consumption in the water column. The increased respiration is another major cause of the HV increase besides the physical contributions.

54 ENVIRONMENTAL SCIENCES↗

Wildfire smoke impacts lake ecosystems

Abstract Wildfire activity is increasing globally. The resulting smoke plumes can travel hundreds to thousands of kilometers, reflecting or scattering sunlight and depositing particles within ecosystems. Several key physical, chemical, and biological processes in lakes are controlled by factors affected by smoke. The spatial and temporal scales of lake exposure to smoke are extensive and under‐recognized. We introduce the concept of the lake smoke‐day, or the number of days any given lake is exposed to smoke in any given fire season, and quantify the total lake smoke‐day exposure in North America from 2019 to 2021. Because smoke can be transported at continental to intercontinental scales, even regions that may not typically experience direct burning of landscapes by wildfire are at risk of smoke exposure. We found that 99.3% of North America was covered by smoke, affecting a total of 1,333,687 lakes ≥10 ha. An incredible 98.9% of lakes experienced at least 10 smoke‐days a year, with 89.6% of lakes receiving over 30 lake smoke‐days, and lakes in some regions experiencing up to 4 months of cumulative smoke‐days. Herein we review the mechanisms through which smoke and ash can affect lakes by altering the amount and spectral composition of incoming solar radiation and depositing carbon, nutrients, or toxic compounds that could alter chemical conditions and impact biota. We develop a conceptual framework that synthesizes known and theoretical impacts of smoke on lakes to guide future research. Finally, we identify emerging research priorities that can help us better understand how lakes will be affected by smoke as wildfire activity increases due to climate change and other anthropogenic activities.

54 ENVIRONMENTAL SCIENCES↗

Complex interactions between day length and diurnal patterns of gene expression drive photoperiodic responses in a perennial C 4 grass

Abstract Photoperiod is a key environmental cue affecting flowering and biomass traits in plants. Key components of the photoperiodic flowering pathway have been identified in many species, but surprisingly few studies have globally examined the diurnal rhythm of gene expression with changes in day length. Using a cost‐effective 3′‐Tag RNA sequencing strategy, we characterize 9,010 photoperiod responsive genes with strict statistical testing across a diurnal time series in the C 4 perennial grass, Panicum hallii . We show that the vast majority of photoperiod responses are driven by complex interactions between day length and sampling periods. A fine‐scale contrast analysis at each sampling time revealed a detailed picture of the temporal reprogramming of cis ‐regulatory elements and biological processes under short‐ and long‐day conditions. Phase shift analysis reveals quantitative variation among genes with photoperiod‐dependent diurnal patterns. In addition, we identify three photoperiod enriched transcription factor families with key genes involved in photoperiod flowering regulatory networks. Finally, coexpression networks analysis of GIGANTEA homolog predicted 1,668 potential coincidence partners, including five well‐known GI‐interacting proteins. Our results not only provide a resource for understanding the mechanisms of photoperiod regulation in perennial grasses but also lay a foundation to increase biomass yield in biofuel crops.

Weng, Xiaoyu↗