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At least 757 records · Page 42

Investigating the mechanism of chloroplast singlet oxygen signaling in the Arabidopsis thaliana accelerated cell death 2 mutant

As sessile organisms, plants have evolved complex signaling mechanisms to sense stress and acclimate. This includes the use of reactive oxygen species (ROS) generated during dysfunctional photosynthesis to initiate signaling. One such ROS, singlet oxygen ( 1 O 2 ), can trigger retrograde signaling, chloroplast degradation, and programmed cell death. However, the signaling mechanisms are largely unknown. Several proteins (e.g. PUB4, OXI1, EX1) are proposed to play signaling roles across three Arabidopsis thaliana mutants that conditionally accumulate chloroplast 1 O 2 (fluorescent in blue light (flu), chlorina 1 (ch1), and plastid ferrochelatase 2 (fc2)). We previously demonstrated that these mutants reveal at least two chloroplast 1 O 2 signaling pathways (represented by flu and fc2/ch1). Here, we test if the 1 O 2 -accumulating lesion mimic mutant, accelerated cell death 2 (acd2), also utilizes these pathways. The pub4–6 allele delayed lesion formation in acd2 and restored photosynthetic efficiency and biomass. Conversely, an oxi1 mutation had no measurable effect on these phenotypes. acd2 mutants were not sensitive to excess light (EL) stress, yet pub4–6 and oxi1 both conferred EL tolerance within the acd2 background, suggesting that EL-induced 1 O 2 signaling pathways are independent from spontaneous lesion formation. Thus, 1 O 2 signaling in acd2 may represent a third (partially overlapping) pathway to control cellular degradation.

59 BASIC BIOLOGICAL SCIENCES↗

Sequence, structure prediction, and epitope analysis of the polymorphic membrane protein family in Chlamydia trachomatis

The polymorphic membrane proteins (Pmps) are a family of autotransporters that play an important role in infection, adhesion and immunity in Chlamydia trachomatis. Here we show that the characteristic GGA(I,L,V) and FxxN tetrapeptide repeats fit into a larger repeat sequence, which correspond to the coils of a large beta-helical domain in high quality structure predictions. Analysis of the protein using structure prediction algorithms provided novel insight to the chlamydial Pmp family of proteins. While the tetrapeptide motifs themselves are predicted to play a structural role in folding and close stacking of the beta-helical backbone of the passenger domain, we found many of the interesting features of Pmps are localized to the side loops jutting out from the beta helix including protease cleavage, host cell adhesion, and B-cell epitopes; while T-cell epitopes are predominantly found in the beta-helix itself. This analysis more accurately defines the Pmp family of Chlamydia and may better inform rational vaccine design and functional studies.

59 BASIC BIOLOGICAL SCIENCES↗

In Silico Insights into Protein–Protein Interaction Disruptive Mutations in the PCSK9-LDLR Complex

Gain-of-function mutations in PCSK9 (proprotein convertase subtilisin/kexin type 9) lead to reduced uptake of LDL (low density lipoprotein) cholesterol and, therefore, increased plasma LDL levels. However, the mechanism by which these mutants reduce LDL reuptake is not fully understood. Here, we have used molecular dynamics simulations, MM/PBSA (Molecular Mechanics/Poisson–Boltzmann Surface Area) binding affinity calculations, and residue interaction networks, to investigate the protein–protein interaction (PPI) disruptive effects of two of PCSK9's gain-of-function mutations, Ser127Arg and Asp374Tyr on the PCSK9 and LDL receptor complex. In addition to these PPI disruptive mutants, a third, non-interface mutation (Arg496Trp) is included as a positive control. Our results indicate that Ser127Arg and Asp374Tyr confer significantly improved binding affinity, as well as different binding modes, when compared to the wild-type. These PPI disruptive mutations lie between the EGF(A) (epidermal growth factor precursor homology domain A) of the LDL receptor and the catalytic domain of PCSK9 (Asp374Tyr) and between the prodomain of PCSK9 and the β-propeller of the LDL receptor (Ser127Arg). The interactions involved in these two interfaces result in an LDL receptor that is sterically inhibited from entering its closed conformation. This could potentially implicate the prodomain as a target for small molecule inhibitors.

59 BASIC BIOLOGICAL SCIENCES↗

A synthetic cell density signal can drive proliferation in chick embryonic tendon cells and tendon cells from a full size rooster can produce high levels of procollagen in cell culture

Cell density signaling drives tendon morphogenesis by regulating both procollagen production and cell proliferation. The signal is composed of a small, highly conserved protein (SNZR P) tightly bound to a tissue-specific, unique lipid (SNZR L). This allows the complex (SNZR PL) to bind to the membrane of the cell and locally diffuse over a radius of ~1 mm. The cell produces low levels of this signal but the binding to the membrane increases with the number of tendon cells in the local environment. In this article SNZR P was produced in E.coli and SNZR L was chemically synthesized. The two bind together when heated to 60 °C in the presence of Ca ++ and Mg ++ and the synthesized SNZR PL at ng/ml levels can replace serum. Adding SNZR PL to the medium was also tested on primary tendon cells from adult roosters. The older cells were in a maintenance state in vivo and in cell culture they proliferate more slowly than embryonic cells. Nevertheless, after reaching a moderately high cell density, they produced high levels of procollagen similar to the embryonic cells. This data was not expected from older cells but suggests that adult tendon cells can regenerate the tissue after injury when given the correct signals.

59 BASIC BIOLOGICAL SCIENCES↗

Enhancing Biopreparedness through a Model System to Understand the Molecular Mechanisms that Lead to Pathogenesis and Disease Transmission: NW-BRaVE

The science of biopreparedness to counter biological threats hinges on understanding the fundamental principles and molecular mechanisms that lead to pathogenesis and disease transmission. Our vision to address this challenge is to create a powerful and user-friendly platform to elucidate the fundamental principles of how molecular interactions drive pathogen-host relationships and host shifts. We will enable groundbreaking discoveries by integrating a wide range of structural, genomics, proteomics, and other advanced omics measurements, along with evolutionary and artificial intelligence predictions. To make sure the system is applicable to real-world problems, we will develop it in the context of a tractable model system, the small, abundant, and accessible photosynthetic cyanobacteria and their constantly co-adapting viral pathogens, cyanophages. This model will maintain the system’s applicability to real-world problems and techniques, but the overall focus will be on elucidating general principles of detecting, assessing, and surveilling molecular interaction, adaptation, and coevolution that are system agnostic and therefore extensible to other viral-host interactions. Our overall objectives are to (1) identify the molecular complexes that comprise the cyanobacteria redox macromolecular subsystem and how they dynamically change with bacteriophage infection in situ, using cryo-electron tomography; (2) profile regulatory changes during infection using proteomics, multiomics, and experimental validation, and integrate the data with in situ structures; (3) use genomics and metagenomics to determine environmental and population factors across time scales that impact the interactions between marine cyanobacteria and their cyanophage parasites, predicting the evolutionary origins of in situ structural and functional interactions, convergence and coevolution; and (4) develop a data integration and transformation platform that facilitates the integration of in situ, proteomic, and evolutionary measurements of molecular interactions to surveil diverse hosts and parasites in various environmental contexts. These objectives address Focus Area 2 Reveal Molecular Interactions Across Biological Scales for Design of Targeted Interventions. Our powerful and user-friendly platform will enhance connections between the often-siloed fields of structure, molecular phenotype, and evolutionary genomics that are key to biopreparedness, but in need of integration (Figure 1). We will build an integrated navigation tool to facilitate the effective use of globally distributed experimental data for integrated analysis and predictive modeling. The project will develop, implement, and test a platform to assess host-pathogen molecular interactions, adaptation to hosts and host shifts, and coevolution between hosts and pathogens, successfully impacting the research community by revolutionizing abilities to study any host-pathogen interaction, encourage diverse community contributions, and gain fundamental insights into how proteins adapt to new contexts. This ability will be critical for designing early interventions to address future threats. We will build surveillance training capability, aiming for a fair and equitable response to future pandemics and biothreats.

59 BASIC BIOLOGICAL SCIENCES↗

RhizoNet segments plant roots to assess biomass and growth for enabling self-driving labs

Abstract Flatbed scanners are commonly used for root analysis, but typical manual segmentation methods are time-consuming and prone to errors, especially in large-scale, multi-plant studies. Furthermore, the complex nature of root structures combined with noisy backgrounds in images complicates automated analysis. Addressing these challenges, this article introduces RhizoNet, a deep learning-based workflow to semantically segment plant root scans. Utilizing a sophisticated Residual U-Net architecture, RhizoNet enhances prediction accuracy and employs a convex hull operation for delineation of the primary root component. Its main objective is to accurately segment root biomass and monitor its growth over time. RhizoNet processes color scans of plants grown in a hydroponic system known as EcoFAB, subjected to specific nutritional treatments. The root detection model using RhizoNet demonstrates strong generalization in the validation tests of all experiments despite variable treatments. The main contributions are the standardization of root segmentation and phenotyping, systematic and accelerated analysis of thousands of images, significantly aiding in the precise assessment of root growth dynamics under varying plant conditions, and offering a path toward self-driving labs.

59 BASIC BIOLOGICAL SCIENCES↗

Structure analysis of the telomere resolvase from the Lyme disease spirochete Borrelia garinii reveals functional divergence of its C-terminal domain

Borrelia spirochetes are the causative agents of Lyme disease and relapsing fever, two of the most common tick-borne illnesses. A characteristic feature of these spirochetes is their highly segmented genomes which consists of a linear chromosome and a mixture of up to approximately 24 linear and circular extrachromosomal plasmids. The complexity of this genomic arrangement requires multiple strategies for efficient replication and partitioning during cell division, including the generation of hairpin ends found on linear replicons mediated by the essential enzyme ResT, a telomere resolvase. Using an integrative structural biology approach employing advanced modelling, circular dichroism, X-ray crystallography and small-angle X-ray scattering, we have generated high resolution structural data on ResT from B. garinii. Our data provides the first high-resolution structures of ResT from Borrelia spirochetes and revealed active site positioning in the catalytic domain. We also demonstrate that the C-terminal domain of ResT is required for both transesterification steps of telomere resolution, and is a requirement for DNA binding, distinguishing ResT from other telomere resolvases from phage and bacteria. These results advance our understanding of the molecular function of this essential enzyme involved in genome maintenance in Borrelia pathogens.

59 BASIC BIOLOGICAL SCIENCES↗

Three-Dimensional Imaging Lidar for Characterizing Particle Fields and Organisms in the Mesopelagic Zone

The ocean’s mesopelagic zone is largely uncharacterized despite its vital role in sustaining ocean ecosystems. The composition, cycling, and fate of particle fields in the mesopelagic lacks an integrative multi-scale understanding of organism migration patterns, distribution, and diversity. This problem is addressed by combining complementary technologies with overlapping size spectra, including profiler mounted optical scattering sensors, profiler, and ship mounted acoustic devices, and a custom Unobtrusive Multi-Static Lidar Imager (UMSLI). This unique sensor suite can observe distributions of particles including organisms over a six order of magnitude dynamic size range, from microns to meters. Overlapping size ranges between different methods allows for cross-validation. This work focuses on the lidar imaging measurements and optical backscattering and attenuation, covering a combined particle size range of 0.1 mm to several cm. Particles at the small end of this range are sized using an existing backscattering time series inversion method after Briggs et al. (2013). Larger particles are resolved with UMSLI over an expanding volume using three-dimensional photo-realistic laser serial imaging. UMSLI’s image rectifying ability over time allows for derivation of particle concentration, size, and spatial distribution. Technical details on the development and post-processing methods for the novel UMSLI system are provided. Image resolved particle size distributions (PSDs) revealed a size shift from smaller to larger particles (>0.5 mm) as indicated by flatter slopes from dawn (slope = 2.6) to dusk (slope = 3.0). PSD trends are supported by an optical backscatter and transmissometer time series inversion analysis. Size shifts in the particle field are largely attributed to aggregation effects. Images support evidence of temporal variation between dusk and dawn stations through statistical analysis of particle concentrations for particle sizes 0.50–5.41 mm. Spatial analysis of the particle field revealed a dominantly uniform distributed marine snow background. The importance and potential of integrated approaches to studying particle and organism dynamics in ocean environments are discussed.

54 ENVIRONMENTAL SCIENCES↗

Light Regulation of Phytoplankton Growth in San Francisco Bay Studied Using a 3D Sediment Transport Model

In San Francisco Bay (SFB), light availability is largely determined by the concentration of suspended particulate matter (SPM) in the water column. SPM exhibits substantial variation with time, depth, and location. To study how SPM influences light and phytoplankton growth, we coupled a sediment transport model with a hydrodynamic model and a biogeochemical model. The coupled models were used to simulate conditions for the year of 2011 with a focus on northern SFB. For comparison, two simulations were conducted with ecosystem processes driven by SPM concentrations supplied by the sediment transport model and by applying a constant SPM concentration of 20 mg l –1 . The sediment transport model successfully reproduced the general pattern of SPM variation in northern SFB, which improved the chlorophyll-a simulation resulting from the biogeochemical model, with vertically integrated primary productivity varying greatly, from 40 g[C] m –2 year –1 over shoals to 160 g[C] m –2 year –1 in the deep channel. Primary productivity in northern SFB is influenced by euphotic zone depth ( Ze ). Our results show that Ze in shallow water regions (<2 m) is mainly determined by water depth, while Ze in deep water regions is controlled by SPM concentration. As a result, Ze has low (high) values in shallow (deep) water regions. Large (small) differences in primary productivity exist between the two simulations in deep (shallow) water regions. Furthermore, we defined a new parameter F light for “averaged light limitation” in the euphotic zone. The averaged chlorophyll-a concentration in the euphotic zone and F light share a similar distribution such that both have high (low) values in shallow (deep) water regions. Our study demonstrates that light is a critical factor in regulating the phytoplankton growth in northern SFB, and a sediment transport model improves simulation of light availability in the water column.

54 ENVIRONMENTAL SCIENCES↗

Water, Protons, and the Gating of Voltage-Gated Potassium Channels

Ion channels are ubiquitous throughout all forms of life. Potassium channels are even found in viruses. Every cell must communicate with its surroundings, so all cells have them, and excitable cells, in particular, especially nerve cells, depend on the behavior of these channels. Every channel must be open at the appropriate time, and only then, so that each channel opens in response to the stimulus that tells that channel to open. One set of channels, including those in nerve cells, responds to voltage. There is a standard model for the gating of these channels that has a section of the protein moving in response to the voltage. However, there is evidence that protons are moving, rather than protein. Water is critical as part of the gating process, although it is hard to see how this works in the standard model. Here, we review the extensive evidence of the importance of the role of water and protons in gating these channels. Our principal example, but by no means the only example, will be the Kv1.2 channel. Evidence comes from the effects of D2O, from mutations in the voltage sensing domain, as well as in the linker between that domain and the gate, and at the gate itself. There is additional evidence from computations, especially quantum calculations. Structural evidence comes from X-ray studies. The hydration of ions is critical in the transfer of ions in constricted spaces, such as the gate region and the pore of a channel; we will see how the structure of the hydrated ion fits with the structure of the channel. In addition, there is macroscopic evidence from osmotic experiments and streaming current measurements. The combined evidence is discussed in the context of a model that emphasizes the role of protons and water in gating these channels.

59 BASIC BIOLOGICAL SCIENCES↗

Sparsomycin inhibits translation through a conserved mechanism across all domains of life

Abstract Sparsomycin (SPA) is a broad-spectrum inhibitor of protein synthesis with activity across all three domains of life. Although SPA has long been known to target the ribosomal peptidyl transferase center (PTC), previous structural studies suggested that SPA binds differently to bacterial ribosomes compared to their archaeal and eukaryotic counterparts—an unexpected conclusion given the high evolutionary conservation of the ribosomal catalytic center. Here, we show that SPA inhibits a majority of elongation-competent bacterial ribosomal complexes and present X-ray crystal structures of Thermus thermophilus 70S ribosomes stalled by SPA at the initiation and early elongation stages of translation. These structures reveal that SPA binds to the bacterial ribosome in a manner essentially identical to that observed in archaeal and eukaryotic ribosomes, establishing a unified structural mechanism of SPA action across all domains of life. In this conserved binding mode, SPA occupies the A-site cleft of the PTC and forms an extensive network of interactions with universally conserved ribosomal RNA nucleotides and the CCA-end of the P-site transfer RNA (tRNA), thereby stabilizing the peptidyl-tRNA substrate while sterically blocking accommodation of an incoming aminoacyl-tRNA. By clarifying the mode of action of SPA on the bacterial ribosome, our work provides a structural framework for the rational design of SPA derivatives with improved potency and bacterial specificity.

Paranjpe, Madhura N [Department of Biological Scie↗

Contrasting modes of macro and microsynteny evolution in a eukaryotic subphylum

Examination of the changes in order and arrangement of homologous genes is key for understanding the mechanisms of genome evolution in eukaryotes. Previous comparisons between eukaryotic genomes have revealed considerable conservation across species that diverged hundreds of millions of years ago (e.g., vertebrates, bilaterian animals, and filamentous fungi). However, understanding how genome organization evolves within and between eukaryotic major lineages remains underexplored. We analyzed high-quality genomes of 120 representative budding yeast species (subphylum Saccharomycotina) spanning ~400 million years of eukaryotic evolution to examine how their genome organization evolved and to compare it with the evolution of animal and plant genome organization. We, in this study, found that the decay of both macrosynteny (the conservation of homologous chromosomes) and microsynteny (the conservation of local gene content and order) was strongly associated with evolutionary divergence across budding yeast major clades. However, although macrosynteny decayed very fast, within ~100 million years, the microsynteny of many genes—especially genes in metabolic clusters (e.g., in the GAL gene cluster)—was much more deeply conserved both within major clades and across the subphylum. We further found that when genomes with similar evolutionary divergence times were compared, budding yeasts had lower macrosynteny conservation than animals and filamentous fungi but higher conservation than angiosperms. In contrast, budding yeasts had levels of microsynteny conservation on par with mammals, whereas angiosperms exhibited very low conservation. Our results provide new insight into the tempo and mode of the evolution of gene and genome organization across an entire eukaryotic subphylum.

59 BASIC BIOLOGICAL SCIENCES↗

Bio-based oxalic acid production in Issatchenkia orientalis enables sustainable rare earth recovery

The growing demand for rare earth elements (REEs) in clean energy and high-tech industries underscores the need for sustainable recovery methods and a reliable supply of processing chemicals. Here, we establish a microbial platform using the acid-tolerant yeast Issatchenkia orientalis SD108 to produce bio-oxalic acid for REE recovery. By introducing an oxaloacetate cleavage pathway and applying metabolic engineering, the engineered strain produces 39.53 g·L -1 oxalic acid at pH 4.0 in fed-batch fermentation. The crude fermentation broth, used without purification, efficiently precipitates over 99% neodymium (Nd), 99% dysprosium (Dy), and 98% lanthanum (La) from individual REE chloride solutions. Recovery from a low-grade ore leachate achieves over 99% total recovery. X-ray diffraction (XRD) and Fourier transform infrared spectroscopy (FTIR) confirm that REE oxalates precipitated with bio-oxalic acid closely resemble those obtained using commercial oxalic acid. Techno-economic analysis (TEA) and life cycle assessment (LCA) further demonstrate that bio-oxalic acid can be produced at a competitive price of $1.79·kg -1 while reducing carbon intensity (CI) by 112% to 63.5% with and without electricity displacement, respectively, relative to the fossil-based benchmark. These results highlight bio-oxalic acid as a green, economically viable alternative to synthetic oxalate for sustainable REE recovery.

59 BASIC BIOLOGICAL SCIENCES↗

GeneLab: Current and Future Omics Data Integration Between Space Biology and HRP

For the past five years, the Biological and Physical Sciences Division has pioneered Open Science in Space Biology by funding the NASA GeneLab project. Along with the Ames Life Sciences Data Archive, GeneLab has quickly become the world leader in archiving and scientifically curating spaceflight and spaceflight relevant multi-omics data. Specifically, the GeneLab Data System has become a full enterprise solution providing advanced mining capabilities, several application programming interfaces for data federation and machine learning approaches, and delivering to the world an analytical and visualization platform which has enabled collaboration within the scientific community. Over the past three years, large meta-analysis and modeling studies have been published by the GeneLab Analysis Working Groups (AWGs), which are comprised of ~200 volunteer scientists. One natural extension of GeneLab data reuse has recently turned towards linking animal data with human data, which is the next necessary step to further validate animal models for inferring biological risks to humans conducting LEO, lunar or Martian missions. As such, data from the Human Research Program are an essential component of GeneLab and ALSDA. At the moment, simulated space radiation experiments conducted at Brookhaven National Laboratory make the most of HRP GeneLab data, and the scientific community has been eager to also link their animal spaceflight results to actual Astronaut data and human analog data. We will discuss further the current status of knowledge and future approaches to accelerate our basics understanding of the impact of space stressors on humans using latest omics technology.

omics↗

D3R grand challenge 4: blind prediction of protein–ligand poses, affinity rankings, and relative binding free energies

The Drug Design Data Resource (D3R) aims to identify best practice methods for computer aided drug design through blinded ligand pose prediction and affinity challenges. Herein, we report on the results of Grand Challenge 4 (GC4). GC4 focused on proteins beta secretase 1 and Cathepsin S, and was run in an analogous manner to prior challenges. In Stage 1, participant ability to predict the pose and affinity of BACE1 ligands were assessed. Following the completion of Stage 1, all BACE1 co-crystal structures were released, and Stage 2 tested affinity rankings with co-crystal structures. Finally, we provide an analysis of the results and discuss insights into determined best practice methods.

59 BASIC BIOLOGICAL SCIENCES↗