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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Predicting Pulsed-Laser Deposition SrTiO 3 Homoepitaxy Growth Dynamics Using High-Speed Reflection High-Energy Electron Diffraction

Pulsed-laser deposition (PLD) is a powerful technique for growing complex oxides with controlled stoichiometry. To understand growth dynamics therein, it is common to leverage in situ spectroscopies, such as reflection high-energy electron diffraction (RHEED), to monitor surface crystallinity. Most commercial systems rely on video-rate cameras operating at 60-120 Hz that lack sufficient temporal resolution to capture growth dynamics at practical deposition frequencies. Here, a high-speed platform to record in situ dynamics via RHEED at >500 Hz is implemented. An open-source analysis package is designed to fit diffraction spots to 2D Gaussians, allowing single-pulse surface reconstruction kinetics extraction. Using homoepitaxially deposited (001)-oriented SrTiO 3 as a model system, we demonstrate how high-speed RHEED can provide real-time insight into growth processes obscured by slower acquisition systems. By fitting the single-pulse intensity to a set of exponential functions, we observe changes in the characteristic decay time and mechanism correlated to the substrate step width and surface termination. We observe distinct surface effects, with diffraction intensity decaying on lower-energy TiO 2 -terminated surfaces and stabilizing on SrO- or mixed-terminated surfaces. Similarly, using an exponential model, the extracted characteristic time of adatom deposition decreases with increased density of bonding sites associated with mixed termination and narrower step widths. Ultimately, this work shows how increasing RHEED temporal resolution can uncover new insights into growth processes, with practical implications for the design and control of PLD processes. This experimental platform provides new capabilities to enable data-driven machine learning analysis and autonomous control systems to enhance the complexity and fecundity of PLD.

(SrO)↗
DOE OSTI2024

Molecular basis of hemoglobin binding and heme removal in Corynebacterium diphtheriae

To successfully mount infections, nearly all bacterial pathogens must acquire iron, a key metal cofactor that primarily resides within human hemoglobin. Corynebacterium diphtheriae causes the life-threatening respiratory disease diphtheria and captures hemoglobin for iron scavenging using the surface-displayed receptor HbpA. Here, we show using X-ray crystallography, NMR, and in situ binding measurements that C. diphtheriae selectively captures iron-loaded hemoglobin by partially ensconcing the heme molecules of its α subunits. Quantitative growth and heme release measurements are compatible with C. diphtheriae acquiring heme passively released from hemoglobin’s β subunits. We propose a model in which HbpA and heme-binding receptors collectively function on the C. diphtheriae surface to capture hemoglobin and its spontaneously released heme. Acquisition mechanisms that exploit the propensity of hemoglobin’s β subunit to release heme likely represent a common strategy used by bacterial pathogens to obtain iron during infections.

NMR↗
DOE OSTI2023

Upgrade of the Graphical User Interface (GUI) of otsdaq

otsdaq is a data acquisition software. The purpose of this project was to improve the design and the functionality of some features on the Graphical User Interface of otsdaq. The GUI interface is developed in HTML and JavaScript. The code is maintained on GitHub and developed by different users working on a remote machine environment.

Najjuma, Brenda↗
DOE OSTI2024

Status of ICARUS NUMI Interaction Cross-Section Analysis

The ICARUS experiment, utilizing Liquid Argon Time Projection Chamber (LAr TPC) technology, has been installed at Fermilab in Chicago, Illinois, following its initial operation in Italy and subsequent refurbishment at CERN. ICARUS completed commissioning in June 2022. Currently, the experiment is in the phase of analyzing data from its two runs of physics data acquisition and gearing up for the third run. While its primary objective is to function as the far detector of the Short Baseline Neutrino program (SBN), seeking sterile neutrino signatures, ICARUS also offers diverse physics capabilities, including searches beyond the standard model and measurements of cross-sections. In addition to being exposed to the common Booster Neutrino (BNB) beamline, ICARUS also receives off-axis neutrinos from the Main Injector (NuMI) beam. Due to the off-axis angle between NuMI and ICARUS, coupled with contributions from both pion and kaon decays to neutrino fluxes, interactions of NuMI neutrinos within ICARUS can be detected over a range of several GeV in energy. These interactions present opportunities for crucial cross-section measurements and model tests within an energy range that overlaps both the SBN oscillation search and a portion of the DUNE spectrum. This poster presentation will delve into our efforts to conduct a muon-neutrino cross-section measurement, where the signal is defined by events with no pions produced in the final state of the interaction, along with some preliminary muon-neutrino inclusive measurements. Additionally, it will provide updates on the current status and future plans, including reconstruction, selection, and analysis procedures.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Lifecycle Management of Nuclear Security Radiation Detection Systems: Testing and Evaluation

The lifecycle of radiation detection systems functioning within a State’s Nuclear Security Detection Architecture encompasses all activities associated with acquisition, deployment, and eventual disposal. Throughout a system’s lifecycle, testing and evaluation activities are needed to ensure requirements are continually met, as underscored by recent experiences.This paper provides:1.A discussion of reasons why testing should be part of the radiation detection equipment lifecycle before, during, and after acquisition.2.A general process for determining applicable evaluation methods.3.A discussion of issues related to integrating testing and evaluation into procurement and operational processes and mitigation strategies.

Harris, Tyrone↗
DOE OSTI2022

High repetition rate mapping of the interaction between a laser plasma and magnetized background plasma via laser induced fluorescence

In this work, the laminar coupling of energy between a laser-produced plasma and a background magnetized plasma was investigated via planar laser induced fluorescence diagnostic and magnetic flux probes. Experiments performed on the Large Plasma Device at the University of California, Los Angeles, mapped out the two-dimensional spatiotemporal evolution of the laser-plasma (debris) ion velocity distribution function (VDF) to assess debris-background coupling in a sub-Alfvénic regime. The acquisition of these data necessitates high repetition rate (1 Hz) as each dataset is the accumulation of thousands of laser shots, which would not be feasible in single-shot experiments. Fully kinetic, three-dimensional particle-in-cell simulations are compared to the measured VDFs to provide a framework in which we can understand the coupling of a sub-Alfvénic plasma flow through a preformed, magnetized plasma. The simulations display the same departure from the expected gyromotion of the debris plasma as observed in the experimental data, and in conjunction with the measured magnetic field traces, have led to the direct observation of the collisionless coupling via laminar fields.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Depth-resolved sagebrush root metabolomics, rhizosphere microbial communities, and geochemistry at the East River Watershed

This data set consists of results from soil nutrient profile, untargeted metabolomics, mass spec imaging, and amplicon sequencing. Data for soil nutrient profile includes common cations (Ca, Mg, Na, and K etc.) extracted from 3 digesting steps – ammonia acetate (for exchangeable cations), nitric acid (for acid dissolved fraction), and hydrofluoric acid/perchloric acid (HF/HClO4) for whole soil digestion. It also includes concentration of organic carbon, inorganic nitrogen (ammonia and nitrate) and phosphorus (Bray-1 P and nitric acid extract), and total nitrogen and phosphorus. Data for untargeted metabolomics includes metabolomic profile for root exudate/tissues and soil extracts from depths at surface soil to saprolite, that were measured using gas chromatography – mass spectrometry (GC-MS), and liquid chromatography – tandem mass spectrometry (LC-MS/MS). Data for mass spec imaging includes spatial distribution of metabolites that were detected and annotated with Fourier transformation ion cyclotron resonance mass spectrometer (FTICR-MS). Data for amplicon sequencing includes the base paired 16S and ITS ribosomal RNA sequences from Miseq Illumina sequencing. All samples were collected from 2 sampling campaign October 2022 and June 2023. Collectively, these datasets enable a mechanistic evaluation of how nutrient acquisition, especially nitrogen and phosphorus, differs between shallow roots operating in soil and deep roots functioning within the fractured bedrock zone. All files are provided as comma-separated values (CSV) fies (.csv) and (GZIP) file (.gz). The compressed .gz FASTQ files can be read directly in R using the dada2 package as part of the amplicon sequence analysis workflow. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. This research was performed on a project award 60563 (https://dx.doi.org/10.46936/expl.proj.2022.60563/60008727) from the Environmental Molecular Sciences Laboratory, a DOE Office of Science User Facility sponsored by the Biological and Environmental Research program under Contract No. DE-AC05-76RL01830.

EARTH SCIENCE > AGRICULTURE > SOILS > CARBON↗
DOE OSTI2024

Commissioning of the Mu2e tracker DAQ, planning for the Vertical Slice Test and pre-pattern recognition studies

The primary objective of the Mu2e experiment at Fermilab is to search for the neutrino-less coherent $\mu \rightarrow e$ conversion in the field of an aluminum nucleus ($\mu^- \text{Al} \rightarrow e^- \text{Al}$). The signature of this process is a monochromatic Conversion Electron (CE) with an energy of approximately 104.97 MeV \cite{bartoszek2015mu2e}. Within the Standard Model (SM), the branching ratio for this process, including neutrino masses and oscillation, is expected to be less than $\mathcal{O}(10^{-50})$. This value is far beyond current experimental capabilities. However, models of physics beyond the SM predict much higher relative rates, approaching an observable level. The SINDRUM II experiment set an upper limit on muon conversion at $7 \times 10^{-13}$ (90\% CL) on Au target \cite{SINDRUMII:2006dvw}, and the Mu2e collaboration aims to improve this limit by four orders of magnitude. Observing this process would provide a clear evidence of physics beyond the Standard Model. A brief discussion of the theoretical and experimental aspects is provided in Chapter \ref{intr}. Mu2e adopts a sophisticated experimental setup to achieve its goals, further described in Chapter \ref{mu2echapter}. The central part of the Mu2e detector is the tracker, that consists of 18 tracking stations. The tracker must provide excellent momentum resolution, approximately 1 MeV/c, to distinguish the monochromatic CE signal from the background. To minimize the energy losses, a straw tube tracker will be used \cite{bobbb}. Chapter \ref{chaptertrk} provides an overview of the straw tracker design and its working principles. This Thesis presents a comprehensive study of the Mu2e tracker, covering complementary aspects from initial commissioning to optimization and first steps of the calibration processes. My work at Fermilab has been focused on the complete Data Acquisition (DAQ) testing from both hardware and software perspectives. I was involved in the commissioning of the Mu2e DAQ system and the Vertical Slice Test (VST) of the tracker. The VST encompasses the entire testing chain, from the straws to the readout, and to processed data on disk. I was also focused on the offline analysis, especially on pre-pattern recognition studies, to explore the best methods for identifying $\delta$-electrons during the data taking. Chapter \ref{commissioning} details the commissioning of the tracker DAQ system, emphasizing the importance of understanding of the readout process before the data acquisition. This includes validating the readout logic and firmware through Monte Carlo simulations to confirm functionality and buffering, monitoring the quality of the data from the tracker preamplifiers and front-end electronics, and assessing overall DAQ performance to ensure reliability during future calibration and data-taking. Chapter \ref{planning} discusses the initial steps towards the tracker calibration. The ultimate goal is to perform a time calibration of the first assembled station of the tracker using cosmic muons, aiming for a longitudinal hit position resolution better than 4 cm. This involves determining the signal propagation times and channel-to-channel delays. I performed a Monte Carlo study to determine the impact of the station orientation on the quality of the calibration, in particular on the cosmic track reconstruction, focusing on potential biases that could arise. These studies provide essential insights into the operation, optimization, and calibration of the Mu2e tracker system. Given the high data volume expected during Mu2e operations, estimated at approximately 7 PBytes per year, optimizing memory usage and minimizing CPU consumption are critical. A significant challenge lies in effectively flagging $\delta$-electron hits, which are the primary source of hits in the tracker, without compromising the efficiency of CE hit detection and track reconstruction. A detailed study of pre-pattern recognition and a thorough comparison of two $\delta$-electron flagging algorithms is provided in Chapter \ref{delta}. In Chapter \ref{conclusions}, the findings are concisely summarized, offering a comprehensive synthesis of the research and emphasizing the key insights derived from this study.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Machine learning assisted quantum super-resolution microscopy

One of the main characteristics of optical imaging systems is spatial resolution, which is restricted by the diffraction limit to approximately half the wavelength of the incident light. Along with the recently developed classical super-resolution techniques, which aim at breaking the diffraction limit in classical systems, there is a class of quantum super-resolution techniques which leverage the non-classical nature of the optical signals radiated by quantum emitters, the so-called antibunching super-resolution microscopy. This approach can ensure a factor of $\sqrt{n}$ improvement in the spatial resolution by measuring the n -th order autocorrelation function. The main bottleneck of the antibunching super-resolution microscopy is the time-consuming acquisition of multi-photon event histograms. We present a machine learning-assisted approach for the realization of rapid antibunching super-resolution imaging and demonstrate 12 times speed-up compared to conventional, fitting-based autocorrelation measurements. The developed framework paves the way to the practical realization of scalable quantum super-resolution imaging devices that can be compatible with various types of quantum emitters.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Bioavailable iron titrations reveal oceanic Synechococcus ecotypes optimized for different iron availabilities

Abstract The trace metal iron (Fe) controls the diversity and activity of phytoplankton across the surface oceans, a paradigm established through decades of in situ and mesocosm experimental studies. Despite widespread Fe-limitation within high-nutrient, low chlorophyll (HNLC) waters, significant contributions of the cyanobacterium Synechococcus to the phytoplankton stock can be found. Correlations among differing strains of Synechococcus across different Fe-regimes have suggested the existence of Fe-adapted ecotypes. However, experimental evidence of high- versus low-Fe adapted strains of Synechococcus is lacking, and so we investigated the transcriptional responses of microbial communities inhabiting the HNLC, sub-Antarctic region of the Southern Ocean during the Spring of 2018. Analysis of metatranscriptomes generated from on-deck incubation experiments reflecting a gradient of Fe-availabilities reveal transcriptomic signatures indicative of co-occurring Synechococcus ecotypes adapted to differing Fe-regimes. Functional analyses comparing low-Fe and high-Fe conditions point to various Fe-acquisition mechanisms that may allow persistence of low-Fe adapted Synechococcus under Fe-limitation. Comparison of in situ surface conditions to the Fe-titrations indicate ecological relevance of these mechanisms as well as persistence of both putative ecotypes within this region. This Fe-titration approach, combined with transcriptomics, highlights the short-term responses of the in situ phytoplankton community to Fe-availability that are often overlooked by examining genomic content or bulk physiological responses alone. These findings expand our knowledge about how phytoplankton in HNLC Southern Ocean waters adapt and respond to changing Fe supply.

Gilbert, Naomi E. (ORCID:0000000256915547)↗
DOE OSTI2026

Study on Application of Distributed Network of Sensors with List Mode for NMAC Literature Review

Nuclear material accounting and control (NMAC) for nuclear security detects, deters, and resolves questions related to unauthorized removal (i.e. theft) or misuse of nuclear material. NMAC also serves as a key insider threat mitigation measure and aids in recovery of nuclear material that is missing. Effective nuclear security depends on NMAC for timely and accurate information about nuclear material types, quantities, and locations. Bulk nuclear material processing facilities, however, present unique challenges for effective NMAC due to the presence of large quantities of material in-process and the accumulation of residual material holdup within process equipment. These holdup accumulations can obscure accurate physical inventory taking and complicate efforts to resolve NMAC irregularities at the facility level. Bulk material monitoring systems often rely on material balance calculations and indirect measurement techniques, which may mask protracted theft of smaller amounts of nuclear material. These monitoring limitations have generated increased interest in continuous monitoring technologies, including distributed non-destructive assay (NDA) sensor networks capable of providing real-time or near-real-time measurement of material movement and accumulation within bulk processing environments. Recent advancements in distributed networks of NDA radiation detectors and sensing technologies provide an opportunity to address these limitations. Although such distributed sensor networks have been implemented in select facilities for IAEA Safeguards applications, their potential for supporting NMAC functions specifically tailored to nuclear security objectives remains largely unexplored. Furthermore, emerging list-mode data acquisition technologies have reached high technology readiness levels, enabling time-correlated detection of nuclear events across multiple temporal scales. These capabilities provide enhanced opportunities for accurate holdup measurement, continuous process monitoring, and improved detection of material theft or misuse over time. The increasing global expansion of civil nuclear power and development of related bulk material processing facilities, including those supporting high-assay low-enriched uranium (HALEU) and other advanced reactor fuel fabrication, further increases the need for advanced measurement and monitoring strategies for NMAC.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Towards interpretable Cryo-EM: disentangling latent spaces of molecular conformations

Molecules are essential building blocks of life and their different conformations (i.e., shapes) crucially determine the functional role that they play in living organisms. Cryogenic Electron Microscopy (cryo-EM) allows for acquisition of large image datasets of individual molecules. Recent advances in computational cryo-EM have made it possible to learn latent variable models of conformation landscapes. However, interpreting these latent spaces remains a challenge as their individual dimensions are often arbitrary. The key message of our work is that this interpretation challenge can be viewed as an Independent Component Analysis (ICA) problem where we seek models that have the property of identifiability. That means, they have an essentially unique solution, representing a conformational latent space that separates the different degrees of freedom a molecule is equipped with in nature. Thus, we aim to advance the computational field of cryo-EM beyond visualizations as we connect it with the theoretical framework of (nonlinear) ICA and discuss the need for identifiable models, improved metrics, and benchmarks. Moving forward, we propose future directions for enhancing the disentanglement of latent spaces in cryo-EM, refining evaluation metrics and exploring techniques that leverage physics-based decoders of biomolecular systems. Moreover, we discuss how future technological developments in time-resolved single particle imaging may enable the application of nonlinear ICA models that can discover the true conformation changes of molecules in nature. The pursuit of interpretable conformational latent spaces will empower researchers to unravel complex biological processes and facilitate targeted interventions. This has significant implications for drug discovery and structural biology more broadly. More generally, latent variable models are deployed widely across many scientific disciplines. Thus, the argument we present in this work has much broader applications in AI for science if we want to move from impressive nonlinear neural network models to mathematically grounded methods that can help us learn something new about nature.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

NEON AOP Survey of Upper East River CO Watersheds: Waveform LiDAR Binary Data

The waveform Light Detection and Ranging (LiDAR) data in this package were generated through a National Ecological Observatory Network Airborne Observation Platform (NEON AOP) acquisition over watersheds of interest surrounding Crested Butte, Colorado. The remote sensing imagery acquired by the NEON AOP supports an interdisciplinary project on hydrology, biogeochemistry, and ecosystem functioning in a snow-dominated headwater environment. These waveform LiDAR data enable spatially continuous estimation of vegetation structure parameters to facilitate analyses of the major environmental drivers of structural and compositional variability. The package contains 97 compressed file archives in 7-zip (.7z) format, each corresponding to one acquisition flightpath. Within each .7z archive is a set of constituent files describing properties of the LiDAR waveforms, such as return intensity, geolocation, outgoing pulse and other behavior of the sensor and signals. Once downloaded, the files must first be unzipped using the widely distributed command-line software utility 7z, using the command '7z x \[filename\].7z \[target_directory\]'. All files within the .7z archives can be opened in IDL, MatLab, or the open-source R statistical computing environment. Further details about the data package are in the attached user guide (neon_aop_crbu_waveformlidar_userguide.pdf). This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns↗
DOE OSTI2026

Island influences on plant functional traits and trait–trait associations across species‐ and community‐scales

The island rule predicts gigantism or dwarfism in body size of island species relative to their mainland counterparts. However, whether other functional traits shift and whether trait–trait associations on islands differ between species and community levels remains unclear. We measured 13 carbon- and water-related functional traits in 37 shared tree species across 35 eastern Chinese islands and 66 nearby mainland plots. We examined species-level trait value shifts and associations under the island rule and compared trait associations between species and communities. Most size-related, wood-anatomical, and hydraulic traits shifted on islands, with large values decreasing and small values increasing; yet, their associations remained stable, aligning with the global trait spectrum and trait–trait coevolution. This stability, despite trait value shifts, suggests evolutionary integration of functional strategies. By contrast, island community-scale trait associations diverged from shared species-level patterns and sometimes reversed, such as positive relationships between wood density and resource-acquisitive traits. Community-level trait associations were stronger on islands, likely reflecting constrained environmental filtering and migration limitation. These contrasting patterns suggest that dominant species can restructure trait associations at the community level, with implications for ecosystem functioning and carbon storage, thereby advancing understanding of plant trait strategies in island systems.

Archipelagos↗
DOE OSTI2024

Bacterial population-level trade-offs between drought tolerance and resource acquisition traits impact decomposition

Microbes drive fundamental ecosystem processes, such as decomposition. Environmental stressors are known to affect microbes, their fitness, and the ecosystem functions that they perform; yet, understanding the causal mechanisms behind this influence has been difficult. We used leaf litter on soil surface as a model in situ system to assess changes in bacterial genomic traits and decomposition rates for 18 months with drought as a stressor. We hypothesized that genome-scale trade-offs due to investment in stress tolerance traits under drought reduce the capacity for bacterial populations to carry out decomposition, and that these population-level trade-offs scale up to impact emergent community traits, thereby reducing decomposition rates. We observed drought tolerance mechanisms that were heightened in bacterial populations under drought, identified as higher gene copy numbers in metagenome-assembled genomes. A subset of populations under drought had reduced carbohydrate-active enzyme genes that suggested—as a trade-off—a decline in decomposition capabilities. These trade-offs were driven by community succession and taxonomic shifts as distinct patterns appeared in populations. We show that trait–trade-offs in bacterial populations under drought could scale up to reduce overall decomposition capabilities and litter decay rates. Using a trait-based approach to assess the population ecology of soil bacteria, we demonstrate genome-level trade-offs in response to drought with consequences for decomposition rates.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Toward the Instrumentation and Data Acquisition of a Tidal Turbine in Real Site Conditions

The National Renewable Energy Laboratory manufactured, instrumented, and deployed thermoplastic composite blades and a data acquisition system (NDAQ) on one of Verdant Power’s Gen5d 5 m diameter tidal turbines in New York’s East River. The thermoplastic blades had internal strain gages, and the NDAQ was a stand-alone system for monitoring and recording the strain and angular position of the blades. The turbine with thermoplastic blades operated and produced power successfully for 3 months, contributing energy to the New York City electric grid. The NDAQ hardware, instrumentation, and structure all survived the deployment and were still functional upon retrieval of the system, but no data were collected. Even though the data retrieval was not a success, data acquisition for deployed subsea marine renewable structures is a new undertaking, and it is critical to share lessons learned from national laboratory experiences. The successful deployment of thermoplastic composite blades marks a significant advancement toward improved materials for subsea components, as well as an advancement in recyclable composite materials. This article outlines the methodology and lessons learned for the instrumentation and data acquisition system.

16 TIDAL AND WAVE POWER↗
DOE OSTI2023

A previously uncharacterized divisome-associated lipoprotein, DalA, is needed for normal cell division in Rhodobacterales

ABSTRACT The bacterial cell envelope is a key subcellular compartment with important roles in antibiotic resistance, nutrient acquisition, and cell morphology. We seek to gain a better understanding of proteins that contribute to the function of the cell envelope in Alphaproteobacteria . Using Rhodobacter sphaeroides , we show that a previously uncharacterized protein, RSP_1200, is an outer membrane (OM) lipoprotein that non-covalently binds peptidoglycan (PG). Using a fluorescently tagged version of this protein, we find that RSP_1200 undergoes a dynamic repositioning during the cell cycle and is enriched at the septum during cell division. We show that the position of RSP_1200 mirrors the location of FtsZ rings, leading us to propose that RSP_1200 is a newly identified component of the R. sphaeroides ’ divisome. Additional support for this hypothesis includes the co-precipitation of RSP_1200 with FtsZ, the Pal protein, and several predicted PG L,D-transpeptidases. We also find that a ∆ RSP_1200 mutation leads to defects in cell division, sensitivity to PG-active antibiotics, and results in the formation of OM protrusions at the septum during cell division. Based on these results, we propose to name RSP_1200 DalA (for division-associated lipoprotein A) and postulate that DalA serves as a scaffold to position or modulate the activity of PG transpeptidases that are needed to form envelope invaginations during cell division. We find that DalA homologs are present in members of the Rhodobacterales order within Alphaproteobacteria . Therefore, we propose that further analysis of this and related proteins will increase our understanding of the macromolecular machinery and proteins that participate in cell division in Gram-negative bacteria. IMPORTANCE Multi-protein complexes of the bacterial cell envelope orchestrate key processes like growth, division, biofilm formation, antimicrobial resistance, and production of valuable compounds. The subunits of these protein complexes are well studied in some bacteria, and differences in their composition and function are linked to variations in cell envelope composition, shape, and proliferation. However, some envelope protein complex subunits have no known homologs across the bacterial phylogeny. We find that Rhodobacter sphaeroides RSP_1200 is a newly identified lipoprotein (DalA) and that loss of this protein causes defects in cell division and changes the sensitivity to compounds, affecting cell envelope synthesis and function. We find that DalA forms a complex with proteins needed for cell division, binds the cell envelope polymer peptidoglycan, and colocalizes with enzymes involved in the assembly of this macromolecule. The analysis of DalA provides new information on the cell division machinery in this and possibly other Alphaproteobacteria.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Genome assembly PYCC 8100

The yeast Torulaspora delbrueckii is gaining importance for biotechnology due to its ability to increase wine sensorial complexity and for enhancing pre-frozen bread dough leavening. However, little is known about its population structure, and variation in gene content, or possible domestication routes have not been investigated. Here, we address these issues and update the circumscription of T. delbrueckii, which is composed of five major clades. Among the three European clades, a lineage associated with the wild arboreal niche is sister to the two other lineages that are linked with anthropic environments, one to wine fermentations and the other one to diverse sources including dairy products and bread dough (Mix- Anthropic clade). Using 62 genomes we identified 5629 genes in the pangenome of T. delbrueckii and 270 genes in the cloud genome. A pangenome tree analysis showed that wine strains have a genome composition were more similar to European wild arboreal strains than to those of the Mix Anthropic clade, in contradiction with the phylogenetic analysis. An association of gene content and ecology gave further support to the hypothesis that the Mix - Anthropic clade has the most specialized genome content and indicated that some of the exclusive genes were implicated in galactose and maltose utilization. More detailed analyses traced the acquisition of a cluster of GAL genes in strains associated with dairy products and the expansion and functional diversification of MAL genes in strains isolated from bread dough. Contrary to S. cerevisiae, domestication in T. delbrueckii is not primed by alcoholic fermentation and appears to be a recent event.

Sampaio, Jose P.↗