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At least 145 records · Page 8

A Systems Biology Approach to Identify Essential Epigenetic Regulators for Specific Biological Processes in Plants

Upon sensing developmental or environmental cues, epigenetic regulators transform the chromatin landscape of a network of genes to modulate their expression and dictate adequate cellular and organismal responses. Knowledge of the specific biological processes and genomic loci controlled by each epigenetic regulator will greatly advance our understanding of epigenetic regulation in plants. To facilitate hypothesis generation and testing in this domain, we present EpiNet, an extensive gene regulatory network (GRN) featuring epigenetic regulators. EpiNet was enabled by (i) curated knowledge of epigenetic regulators involved in DNA methylation, histone modification, chromatin remodeling, and siRNA pathways; and (ii) a machine-learning network inference approach powered by a wealth of public transcriptome datasets. We applied GENIE3, a machine-learning network inference approach, to mine public Arabidopsis transcriptomes and construct tissue-specific GRNs with both epigenetic regulators and transcription factors as predictors. The resultant GRNs, named EpiNet, can now be intersected with individual transcriptomic studies on biological processes of interest to identify the most influential epigenetic regulators, as well as predicted gene targets of the epigenetic regulators. We demonstrate the validity of this approach using case studies of shoot and root apical meristem development.

root apical meristem↗

Protist diversity and community complexity in the rhizosphere of switchgrass are dynamic as plants develop

Abstract Background Despite their widespread distribution and ecological importance, protists remain one of the least understood components of the soil and rhizosphere microbiome. Knowledge of the roles that protists play in stimulating organic matter decomposition and shaping microbiome dynamics continues to grow, but there remains a need to understand the extent to which biological and environmental factors mediate protist community assembly and dynamics. We hypothesize that protists communities are filtered by the influence of plants on their rhizosphere biological and physicochemical environment, resulting in patterns of protist diversity and composition that mirror previously observed diversity and successional dynamics in rhizosphere bacterial communities. Results We analyzed protist communities associated with the rhizosphere and bulk soil of switchgrass (SG) plants ( Panicum virgatum ) at different phenological stages, grown in two marginal soils as part of a large-scale field experiment. Our results reveal that the diversity of protists is lower in rhizosphere than bulk soils, and that temporal variations depend on soil properties but are less pronounced in rhizosphere soil. Patterns of significantly prevalent protists groups in the rhizosphere suggest that most protists play varied ecological roles across plant growth stages and that some plant pathogenic protists and protists with omnivorous diets reoccur over time in the rhizosphere. We found that protist co-occurrence network dynamics are more complex in the rhizosphere compared to bulk soil. A phylogenetic bin-based null model analysis showed that protists’ community assembly in our study sites is mainly controlled by homogenous selection and dispersal limitation, with stronger selection in rhizosphere than bulk soil as SG grew and senesced. Conclusions We demonstrate that environmental filtering is a dominant determinant of overall protist community properties and that at the rhizosphere level, plant control on the physical and biological environment is a critical driver of protist community composition and dynamics. Since protists are key contributors to plant nutrient availability and bacterial community composition and abundance, mapping and understanding their patterns in rhizosphere soil is foundational to understanding the ecology of the root-microbe-soil system.

54 ENVIRONMENTAL SCIENCES↗

Designing sequence-defined peptoids for fibrillar self-assembly and silicification

In the biological environment, mineral crystals exquisitely controlled by biomacromolecules often show intricate hierarchical structures and superior mechanical properties. Among these biominerals, spicules, hybrid silica/protein superstructures serving as skeletal elements in demosponges, represent an excellent example for motivating the synthesis of silica materials. Herein, by designing sequence-defined peptoids containing side chains with a strong binding to silica, we demonstrated that self-assembly of these peptoids into fiber structures enables the mimicking of both biocatalytic and templating functions of silicatein filaments for the formation of silica fibers at near-neutral pH and ambient temperature. We further showed that the presence of amino groups is significant for the nucleation of silica on self-assembled peptoid nanofibers. Molecular dynamics simulation further confirmed that having silica-binding of amino side chains is critical for self-assembled peptoid fibers in triggering silica formation. Here, we demonstrated that tuning inter-peptoid interactions by varying carboxyl and amino side chains significantly influences the assembly kinetics and final morphologies of peptoid assemblies as scaffolds for directing silica mineralization to form silica spheres, fibers, and sheets. The formation of silica shell on peptoid fibers increased the mechanical property of peptoid hydrogel materials by nearly 1000-fold, highlighting the great potential of using silicification to enhance the mechanical property of hydrogel materials for applications including tissue engineering. Since peptoids are highly robust and programmable, we expect that self-assembly of peptoids containing solid-binding side chains into hierarchical materials opens new opportunities in the design and synthesis of highly tunable scaffolds that direct the formation of composite nanomaterials.

59 BASIC BIOLOGICAL SCIENCES↗

Cryo-electron Microscopy of Adeno-associated Virus

Adeno-associated virus (AAV) has a single-stranded DNA genome encapsidated in a small icosahedrally symmetric protein shell with 60 subunits. AAV is the leading delivery vector in emerging gene therapy treatments for inherited disorders, so its structure and molecular interactions with human hosts are of intense interest. A wide array of electron microscopic approaches have been used to visualize the virus and its complexes, depending on the scientific question, technology available, and amenability of the sample. Approaches range from subvolume tomographic analyses of complexes with large and flexible host proteins to detailed analysis of atomic interactions within the virus and with small ligands at resolutions as high as 1.6 Å. Analyses have led to the reclassification of glycan receptors as attachment factors, to structures with a new-found receptor protein, to identification of the epitopes of antibodies, and a new understanding of possible neutralization mechanisms. AAV is now well-enough characterized that it has also become a model system for EM methods development. Heralding a new era, cryo-EM is now also being deployed as an analytic tool in the process development and production quality control of high value pharmaceutical biologics, namely AAV vectors.

59 BASIC BIOLOGICAL SCIENCES↗

Chemically Separable Ruthenium Hydride Isomers with Distinct Hydride Transfer Properties

Transition metal hydrides are key intermediates in biological and industrial catalysis, where control over hydride donor ability (hydricity) is essential for optimizing reactivity. Herein, we report a series of isomeric ruthenium hydrides in which the ligand trans to the ruthenium hydride bond–either an N-heterocyclic carbene or pyridine–modulates the thermodynamic hydricity by up to 8 kcal mol –1 . These hydrides exhibited distinct reactivity toward CO 2 and various organic hydride acceptors, enabling detailed kinetic and mechanistic analysis. Stopped-flow experiments, isotopic labeling, and computational studies supported an outer-sphere hydride transfer mechanism. Linear free energy relationships (LFERs) and Marcus relationships were utilized to correlate the changes in thermodynamics and kinetics, revealing that ligands with strong trans effects and trans influence can disrupt conventional scaling relationships, which can be a powerful strategy for promoting new reactivity paradigms in hydride transfer reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

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↗

Effects of Surface Water Fluctuations and Sediment Movement on Hyporheic Zone Biogeochemistry and Microbial Communities

The hyporheic zone (HZ) is the region beneath and adjacent to streams, rivers, and riverine estuaries where the bidirectional exchange of groundwater (GW) and surface water (SW) occurs. The HZ is an integral component of watersheds, a biologically-active zone providing critical control of SW quality and aquatic life. Much prior work has investigated microbially-mediated biogeochemical reactions in the HZ, mainly from a steady-state perspective. Yet key unique aspects of the HZ include 1) proximity to SW fluctuations (e.g., storms, dam operations) which cyclically drive DOC and DO into the bed and banks creating biogeochemical “hot moments,” and 2) continually shifting surface sediment. Both of these controls should substantially influence microbial communities, yet remain poorly understood, and a mechanistic predictive framework does not exist.

54 ENVIRONMENTAL SCIENCES↗

Nanoscale biochemical sample preparation and analysis

Provided herein are methods and systems for biochemical analysis, including compositions and methods for processing and analysis of small cell populations and biological samples (e.g., a robotically controlled chip-based nanodroplet platform). In particular aspects, the methods described herein can reduce total processing volumes from conventional volumes to nanoliter volumes within a single reactor vessel (e.g., within a single droplet reactor) while minimizing losses, such as due to sample evaporation.

Kelly, Ryan T.↗

Dynamic Multiplexed Control and Modeling of Optogenetic Systems Using the High-Throughput Optogenetic Platform, Lustro

The ability to control cellular processes using optogenetics is inducer-limited, with most optogenetic systems responding to blue light. To address this limitation, we leverage an integrated framework combining Lustro, a powerful high-throughput optogenetics platform, and machine learning tools to enable multiplexed control over blue light-sensitive optogenetic systems. Specifically, we identify light induction conditions for sequential activation as well as preferential activation and switching between pairs of light-sensitive split transcription factors in the budding yeast, Saccharomyces cerevisiae. We use the high-throughput data generated from Lustro to build a Bayesian optimization framework that incorporates data-driven learning, uncertainty quantification, and experimental design to enable the prediction of system behavior and the identification of optimal conditions for multiplexed control. This work lays the foundation for designing more advanced synthetic biological circuits incorporating optogenetics, where multiple circuit components can be controlled using designer light induction programs, with broad implications for biotechnology and bioengineering.

59 BASIC BIOLOGICAL SCIENCES↗

Axion optical induction of antiferromagnetic order

Using circularly polarized light to control quantum matter is a highly intriguing topic in physics, chemistry and biology. Previous studies have demonstrated helicity-dependent optical control of chirality and magnetization, with important implications in asymmetric synthesis in chemistry; homochirality in biomolecules; and ferromagnetic spintronics. We report the surprising observation of helicity-dependent optical control of fully compensated antiferromagnetic order in two-dimensional even-layered MnBi 2 Te 4 , a topological axion insulator with neither chirality nor magnetization. Furthermore, to understand this control, we study an antiferromagnetic circular dichroism, which appears only in reflection but is absent in transmission. We show that the optical control and circular dichroism both arise from the optical axion electrodynamics. Our axion induction provides the possibility to optically control a family of PT-symmetric antiferromagnets (P, inversion; T, time-reversal) such as Cr 2 O 3 , even-layered CrI3 and possibly the pseudo-gap state in cuprates. In MnBi 2 Te 4 , this further opens the door for optical writing of a dissipationless circuit formed by topological edge states.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Synthetic Biology Toolbox for Nitrogen-Fixing Soil Microbes

The soil environment adjacent to plant roots, termed the rhizosphere, is home to a wide variety of microorganisms that can significantly affect the physiology of nearby plants. Microbes in the rhizosphere can provide nutrients, secrete signaling compounds, and inhibit pathogens. These processes could be manipulated with synthetic biology to enhance the agricultural performance of crops grown for food, energy, or environmental remediation, if methods can be implemented in these nonmodel microbes. A common first step for domesticating nonmodel organisms is the development of a set of genetic engineering tools, termed a synthetic biology toolbox. A toolbox comprises transformation protocols, replicating vectors, genome engineering (e.g., CRISPR/Cas9), constitutive and inducible promoter systems, and other gene expression control elements. Furthermore, this work validated synthetic biology toolboxes in three nitrogen-fixing soil bacteria: Azotobacter vinelandii, Stutzerimonas stutzeri (Pseudomonas stutzeri), and a new isolate of Klebsiella variicola. All three organisms were amenable to transformation and reporter protein expression, with several functional inducible systems available for each organism. S. stutzeri and K. variicola showed more reliable plasmid-based expression, resulting in successful Cas9 recombineering to create scarless deletions and insertions. Using these tools, we generated mutants with inducible nitrogenase activity and introduced heterologous genes to produce resorcinol products with relevant biological activity in the rhizosphere.

59 BASIC BIOLOGICAL SCIENCES↗

Information-incorporated gene network construction with FDR control

Abstract Motivation Large-scale gene expression studies allow gene network construction to uncover associations among genes. To study direct associations among genes, partial correlation-based networks are preferred over marginal correlations. However, FDR control for partial correlation-based network construction is not well-studied. In addition, currently available partial correlation-based methods cannot take existing biological knowledge to help network construction while controlling FDR. Results In this paper, we propose a method called Partial Correlation Graph with Information Incorporation (PCGII). PCGII estimates partial correlations between each pair of genes by regularized node-wise regression that can incorporate prior knowledge while controlling the effects of all other genes. It handles high-dimensional data where the number of genes can be much larger than the sample size and controls FDR at the same time. We compare PCGII with several existing approaches through extensive simulation studies and demonstrate that PCGII has better FDR control and higher power. We apply PCGII to a plant gene expression dataset where it recovers confirmed regulatory relationships and a hub node, as well as several direct associations that shed light on potential functional relationships in the system. We also introduce a method to supplement observed data with a pseudogene to apply PCGII when no prior information is available, which also allows checking FDR control and power for real data analysis. Availability and implementation R package is freely available for download at https://cran.r-project.org/package=PCGII.

59 BASIC BIOLOGICAL SCIENCES↗

The Influence of Air‐Sea CO 2 Disequilibrium on Carbon Sequestration by the Ocean's Biological Pump

Abstract The ocean's biological carbon pump (BCP) affects the Earth's climate by sequestering CO 2 away from the atmosphere for decades to millennia. One primary control on the amount of carbon sequestered by the biological pump is air‐sea CO 2 disequilibrium, which is controlled by the rate of air‐sea CO 2 exchange and the residence time of CO 2 in surface waters. Here, we use a data‐assimilated model of the soft tissue BCP to quantify carbon sequestration inventories and time scales from remineralization in the water column to equilibration with the atmosphere. We find that air‐sea CO 2 disequilibrium enhances the global biogenic carbon inventory by ∼35% and its sequestration time by ∼70 years compared to identical calculations made assuming instantaneous air‐sea CO 2 exchange. Locally, the greatest enhancement occurs in the subpolar Southern Ocean, where air‐sea disequilibrium increases sequestration times by up to 600 years and the biogenic dissolved inorganic carbon inventory by >100% in the upper ocean. Contrastingly, in deep‐water formation regions of the North Atlantic and Antarctic margins, where biological production creates undersaturated surface waters which are subducted before fully equilibrating with the atmosphere, air‐sea CO 2 disequilibrium decreases the depth‐integrated sequestration inventory by up to ∼150%. The global enhancement of carbon sequestration by air‐sea disequilibrium is particularly important for carbon respired in deep waters that upwell in the Southern Ocean. These results highlight the importance of accounting for air‐sea CO 2 disequilibrium when evaluating carbon sequestration by the biological pump and for assessing the efficacy of ocean‐based CO 2 removal methods.

Environmental Sciences & Ecology↗

Term Matrix: a novel Gene Ontology annotation quality control system based on ontology term co-annotation patterns

Biological processes are accomplished by the coordinated action of gene products. Gene products often participate in multiple processes, and can therefore be annotated to multiple Gene Ontology (GO) terms. Nevertheless, processes that are functionally, temporally and/or spatially distant may have few gene products in common, and co-annotation to unrelated processes probably reflects errors in literature curation, ontology structure or automated annotation pipelines. We have developed an annotation quality control workflow that uses rules based on mutually exclusive processes to detect annotation errors, based on and validated by case studies including the three we present here: fission yeast protein-coding gene annotations over time; annotations for cohesin complex subunits in human and model species; and annotations using a selected set of GO biological process terms in human and five model species. For each case study, we reviewed available GO annotations, identified pairs of biological processes which are unlikely to be correctly co-annotated to the same gene products (e.g. amino acid metabolism and cytokinesis), and traced erroneous annotations to their sources. To date we have generated 107 quality control rules, and corrected 289 manual annotations in eukaryotes and over 52 700 automatically propagated annotations across all taxa.

59 BASIC BIOLOGICAL SCIENCES↗

Two-stage dynamic deregulation of metabolism improves process robustness & scalability in engineered E. coli.

Here, we report that two-stage dynamic control improves bioprocess robustness as a result of the dynamic deregulation of central metabolism. Dynamic control is implemented during stationary phase using combinations of CRISPR interference and controlled proteolysis to reduce levels of central metabolic enzymes. Reducing the levels of key enzymes alters metabolite pools resulting in deregulation of the metabolic network. Deregulated networks are less sensitive to environmental conditions improving process robustness. Process robustness in turn leads to predictable scalability, minimizing the need for traditional process optimization. We validate process robustness and scalability of strains and bioprocesses synthesizing the important industrial chemicals alanine, citramalate and xylitol. Predictive high throughput approaches that translate to larger scales are critical for metabolic engineering programs to truly take advantage of the rapidly increasing throughput and decreasing costs of synthetic biology.

59 BASIC BIOLOGICAL SCIENCES↗

One Electron Multiple Proton Transfer in Model Organic Donor–Acceptor Systems: Implications for High-Frequency EPR

EPR spectroscopy is an important spectroscopic method for identification and characterization of radical species involved in many biological reactions. The tyrosyl radical is one of the most studied amino acid radical intermediates in biology. Often in conjunction with histidine residues, it is involved in many fundamental biological electron and proton transfer processes, such as in the water oxidation in photosystem II. As biological processes are typically extremely complicated and hard to control, molecular bio-mimetic model complexes are often used to clarify the mechanisms of the biological reactions. In this work, we present theoretical calculations to investigate the sensitivity of magnetic resonance parameters to proton-coupled electron transfer events, as well as conformational substates of the molecular constructs which mimic the tyrosine-histidine (Tyr-His) pairs found in a large variety of proteins. Upon oxidation of the phenol, the Tyr analog, these complexes can perform not only one-electron one-proton transfer (EPT), but also one-electron two-proton transfers (E2PT). It is shown that in aprotic environment the g X -components of the electronicg-tensor are extremely sensitive to the first proton transfer from the phenoxyl oxygen to the imidazole nitrogen (EPT product), leading to a significant increase of the g X -value of up to 0.003, but are not sensitive to the second proton transfer (E2PT). In the latter case, the change of the g X -value is much smaller (ca. 0.0001), which is too small to be distinguished even by high-frequency EPR. The 14 N hyperfine values are also too similar to allow differentiation between the different protonation states in EPT and E2PT. The magnetic resonance parameters were also calculated as a function of the rotation angles around single bonds. It was demonstrated that rotation of the phenoxyl group results in large positive changes (> 0.001) in the g X -values. Analysis of the data reveals that the main source of these changes is related to the strength of the H-bond between phenoxyl oxygen and the proton(s) on N 1 and N 2 positions of the imidazole.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Three-Dimensional Mass Spectrometric Imaging of Biological Structures Using a Vacuum-Compatible Microfluidic Device

Three-dimensional (3D) molecular imaging of biological structures is important for a wide range of research. In recent decades, secondary ion mass spectrometry (SIMS) has been recognized as a powerful technique for both two-dimensional (2D) and 3D molecular imaging. Sample fixations (e. g., chemical fixation and cryogenic fixation methods) are necessary to adapt biological samples to the vacuum condition in the SIMS chamber, which has been demonstrated to be non-trivial and less controllable, thus limiting the wider application of SIMS on 3D molecular analysis of biological samples. Our group recently developed in situ liquid SIMS that offers great opportunities for the molecular study of various liquids and liquid interfaces. In this work, we demonstrate that a further development of the vacuum-compatible microfluidic device used in in situ liquid SIMS provides a convenient freeze-fixation of biological samples and leads to more controllable and convenient 3D molecular imaging. The special design of this new vacuum-compatible liquid chamber allows an easy determination of sputter rates of ice, which is critical for calibrating the depth scale of frozen biological samples. Sputter yield of a 20 keV Ar 1800 + ion on ice has been determined as 1500 (± 8%) water molecules per Ar 1800 + ion, consistent with our results from molecular dynamics simulations. Moreover, using the information of ice sputter yield, we successfully conduct 3D molecular imaging of frozen homogenized milk and observe network structures of interesting organic and inorganic species. Finally, taken together, our results will significantly benefit various research fields relying on 3D molecular imaging of biological structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗