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At least 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Challenges of COVID-19 Case Forecasting in the US, 2020–2021

During the COVID-19 pandemic, forecasting COVID-19 trends to support planning and response was a priority for scientists and decision makers alike. In the United States, COVID-19 forecasting was coordinated by a large group of universities, companies, and government entities led by the Centers for Disease Control and Prevention and the US COVID-19 Forecast Hub ( https://covid19forecasthub.org ). We evaluated approximately 9.7 million forecasts of weekly state-level COVID-19 cases for predictions 1–4 weeks into the future submitted by 24 teams from August 2020 to December 2021. We assessed coverage of central prediction intervals and weighted interval scores (WIS), adjusting for missing forecasts relative to a baseline forecast, and used a Gaussian generalized estimating equation (GEE) model to evaluate differences in skill across epidemic phases that were defined by the effective reproduction number. Overall, we found high variation in skill across individual models, with ensemble-based forecasts outperforming other approaches. Forecast skill relative to the baseline was generally higher for larger jurisdictions (e.g., states compared to counties). Over time, forecasts generally performed worst in periods of rapid changes in reported cases (either in increasing or decreasing epidemic phases) with 95% prediction interval coverage dropping below 50% during the growth phases of the winter 2020, Delta, and Omicron waves. Ideally, case forecasts could serve as a leading indicator of changes in transmission dynamics. However, while most COVID-19 case forecasts outperformed a naïve baseline model, even the most accurate case forecasts were unreliable in key phases. Further research could improve forecasts of leading indicators, like COVID-19 cases, by leveraging additional real-time data, addressing performance across phases, improving the characterization of forecast confidence, and ensuring that forecasts were coherent across spatial scales. In the meantime, it is critical for forecast users to appreciate current limitations and use a broad set of indicators to inform pandemic-related decision making.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Comparative genomic and phenotypic characterization of invasive non-typhoidal Salmonella isolates from Siaya, Kenya

Non-typhoidal Salmonella (NTS) is a major global health concern that often causes bloodstream infections in areas of the world affected by malnutrition and comorbidities such as HIV and malaria. Developing a strategy to control the emergence and spread of highly invasive and antimicrobial resistant NTS isolates requires a comprehensive analysis of epidemiological factors and molecular pathogenesis. Here, we characterize 11 NTS isolates that caused bloodstream infections in pediatric patients in Siaya, Kenya from 2003–2010. Nine isolates were identified as S . Typhimurium sequence type 313 while the other two were S . Enteritidis. Comprehensive genotypic and phenotypic analyses were performed to compare these isolates to those previously identified in sub-Saharan Africa. We identified a S . Typhimurium isolate referred to as UGA14 that displayed novel plasmid, pseudogene and resistance features as compared to other isolates reported from Africa. Notably, UGA14 is able to ferment both lactose and sucrose due to the acquisition of insertion elements on the pKST313 plasmid. These findings show for the first time the co-evolution of plasmid-mediated lactose and sucrose metabolism along with cephalosporin resistance in NTS further elucidating the evolutionary mechanisms of invasive NTS phenotypes. These results further support the use of combined genomic and phenotypic approaches to detect and characterize atypical NTS isolates in order to advance biosurveillance efforts that inform countermeasures aimed at controlling invasive and antimicrobial resistant NTS.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Macrolides: From Toxins to Therapeutics

Macrolides are a diverse class of hydrophobic compounds characterized by a macrocyclic lactone ring and distinguished by variable side chains/groups. Some of the most well characterized macrolides are toxins produced by marine bacteria, sea sponges, and other species. Many marine macrolide toxins act as biomimetic molecules to natural actin-binding proteins, affecting actin polymerization, while other toxins act on different cytoskeletal components. The disruption of natural cytoskeletal processes affects cell motility and cytokinesis, and can result in cellular death. While many macrolides are toxic in nature, others have been shown to display therapeutic properties. Indeed, some of the most well known antibiotic compounds, including erythromycin, are macrolides. In addition to antibiotic properties, macrolides have been shown to display antiviral, antiparasitic, antifungal, and immunosuppressive actions. Here, we review each functional class of macrolides for their common structures, mechanisms of action, pharmacology, and human cellular targets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Adverse Neurological Effects of Wildfire Smoke

The respiratory and cardiovascular effects of smoke exposure are well documented from cigarette smoking and particulate matter (PM) associated with air-pollution studies, but epidemiological data also suggests exposure to high levels of woodsmoke correlate with central-nervous-system (CNS) dysfunction, including elevated rates of Alzheimer’s disease (AD) and dementia. Neuro-inflammation is believed to initiate the majority of Alzheimer’s and other neurodegenerative diseases attributed to environmental factors. We investigated whether inhaled PM and specific classes of compounds in wildfire smoke condensate extract (WSE) reach the brain and cause neuro-inflammation that can lead to progressive neurological degeneration, using isotope tracing of labeled particulate matter and major compound classes, biomarkers of blood-brain barrier (BBB) integrity, and biomarkers of neuro-inflammation. This project showed that inhalation exposure to PM and major compound classes present in WSE reached the brain through absorption in the nasal cavity and systemic circulation across the BBB. Twenty-four exposures of WSE to brain endothelial cells that form the main physical barrier of the BBB produced dose-dependent increases in biomarkers of inflammation and decreases in tight junction markers between cells. Intranasal exposure to WSE caused inflammatory disfunction in lung and brain. Biomarkers of inflammation increased and an enzyme inhibiting inflammation decreased. Similar patterns of chemical-induced changes in the lung and brain suggest either: (1) chemicals may act through shared molecular pathways upon entering lung and brain, or (2) that mediators originating in the lung circulate systemically to the brain and drive neuroinflammation. These findings warrant further mechanistic studies to delineate the temporal sequence of events to establish the lung-brain axis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Assessing the evolution of research topics in a biological field using plant science as an example

Scientific advances due to conceptual or technological innovations can be revealed by examining how research topics have evolved. But such topical evolution is difficult to uncover and quantify because of the large body of literature and the need for expert knowledge in a wide range of areas in a field. Using plant biology as an example, we used machine learning and language models to classify plant science citations into topics representing interconnected, evolving subfields. The changes in prevalence of topical records over the last 50 years reflect shifts in major research trends and recent radiation of new topics, as well as turnover of model species and vastly different plant science research trajectories among countries. Our approaches readily summarize the topical diversity and evolution of a scientific field with hundreds of thousands of relevant papers, and they can be applied broadly to other fields.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

MIDAS2: Metagenomic Intra-species Diversity Analysis System

The Metagenomic Intra-Species Diversity Analysis System (MIDAS) is a scalable metagenomic pipeline that identifies single nucleotide variants (SNVs) and gene copy number variants in microbial populations. Here, we present MIDAS2, which addresses the computational challenges presented by increasingly large reference genome databases, while adding functionality for building custom databases and leveraging paired-end reads to improve SNV accuracy. This fast and scalable reengineering of the MIDAS pipeline enables thousands of metagenomic samples to be efficiently genotyped.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Can fractal dimensions objectivize gastropod shell morphometrics? A case study from Lake Lugu (SW China)

1. Morphometrics are fundamental for the analysis of size and shape in fossils, particularly because soft parts or DNA are rarely preserved and hard parts such as shells are commonly the only source of information. Geometric morphometrics, that is, landmark analysis, is well established for the description of shape but it exhibits a couple of shortcomings resulting from subjective choices during landmarking (number and position of landmarks) and from difficulties in resolving shape at the level of micro-sculpture. 2. With the aid of high-resolution 3D scanning technology and analyses of fractal dimensions, we test whether such shortcomings of linear and landmark morphometrics can be overcome. As a model group, we selected a clade of modern viviparid gastropods from Lake Lugu, with shells that show a high degree of sculptural variation. Linear and landmark analyses were applied to the same shells in order to establish the fractal dimensions. 3. The genetic diversity of the gastropod clade was assessed. The genetic results suggest that the gastropod clade represents a single species. The results of all morphometric methods applied are in line with the genetic results, which is that no specific morphotype could be delimited. Apart from this overall agreement, landmark and fractal dimension analyses do not correspond to each other but represent data sets with different information. Generally, the fractal dimension values quantify the roughness of the shell surface, the resolution of the 3D scans determining the level. In our approach, we captured the micro-sculpture but not the first-order sculptural elements, which explains that fractal dimension and landmark data are not in phase. 4. We can show that analyzing fractal dimensions of gastropod shells opens a window to more detailed information that can be considered in evolutionary and ecological contexts. We propose that using low-resolution 3D scans may successfully substitute landmark analyses because it overcomes the subjective landmarking. Analyses of 3D scans with higher resolution than used in this study will provide surface roughness information at the mineralogical level. We suggest that fractal dimension analyses of a combination of differently resolved 3D models will significantly improve the quality of shell morphometrics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Modeling the distribution of the endangered Jemez Mountains salamander (Plethodon neomexicanus) in relation to geology, topography, and climate

The Jemez Mountains salamander (Plethodon neomexicanus; hereafter JMS) is an endangered salamander restricted to the Jemez Mountains in north-central New Mexico, United States. This strictly terrestrial and lungless species requires moist surface conditions for activities such as mating and foraging. Threats to its current habitat include fire suppression and ensuing severe fires, changes in forest composition, habitat fragmentation, and climate change. Forest composition changes resulting from reduced fire frequency and increased tree density suggest that its current aboveground habitat does not mirror its historically successful habitat regime. However, because of its limited habitat area and underground behavior, we hypothesized that geology and topography might play a significant role in the current distribution of the salamander. We modeled the distribution of the JMS using a machine learning algorithm to assess how geology, topography, and climate variables influence its distribution. The best habitat suitability model indicates that geology type and maximum winter temperature (November to March) were most important in predicting the distribution of the salamander (23.5% and 50.3% permutation importance, respectively). Minimum winter temperature was also an important variable (21.4%), suggesting this also plays a role in salamander habitat. Our habitat suitability map reveals low uncertainty in model predictions, and we found slight discrepancies between the designated critical habitat and the most suitable areas for the JMS. Because geological features are important to its distribution, we recommend that geological and topographical data are considered, both during survey design and in the description of localities of JMS records once detected.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Extracellular electron uptake by autotrophic microbes: physiological, ecological, and evolutionary implications

Abstract Microbes exchange electrons with their extracellular environment via direct or indirect means. This exchange is bidirectional and supports essential microbial oxidation–reduction processes, such as respiration and photosynthesis. The microbial capacity to use electrons from insoluble electron donors, such as redox-active minerals, poised electrodes, or even other microbial cells is called extracellular electron uptake (EEU). Autotrophs with this capability can thrive in nutrient and soluble electron donor-deficient environments. As primary producers, autotrophic microbes capable of EEU greatly impact microbial ecology and play important roles in matter and energy flow in the biosphere. In this review, we discuss EEU-driven autotrophic metabolisms, their mechanism and physiology, and highlight their ecological, evolutionary, and biotechnological implications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Tailoring Microbial Fitness Through Computational Steering and CRISPRi-Driven Robustness Regulation

The widespread application of genetically modified microorganisms (GMMs) across diverse sectors underscores the pressing need for robust strategies to mitigate the risks associated with their potential uncontrolled escape. This study merges computational modeling with CRISPR interference (CRISPRi) to refine GMM metabolic robustness. Utilizing ensemble modeling, we achieved high-throughput in silico screening for enzymatic targets susceptible to expression alterations. Translating these insights, we developed functional CRISPRi, boosting fitness control via multiplexed gene knockdown. Our method, enhanced by an insulator-improved gRNA structure and an off-switch circuit controlling a compact Cas12m, resulted in rationally engineered strains with escape frequencies below National Institutes of Health standards. The effectiveness of this approach was confirmed under various conditions, showcasing its ability for secure GMM management. This research underscores the resilience of microbial metabolism, strategically modifying key nodes to halt growth without provoking significant resistance, thereby enabling more reliable and precise GMM control. A record of this paper's transparent peer review process is included in the supplemental information.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Microalgal and bacterial auxin biosynthesis: implications for algal biotechnology

Optimization of microalgal growth and high-value metabolite production are key steps in microalgal mass culture for the algae industry. An emerging technology is the use of phytohormones, like indole-3-acetic acid (IAA), to promote microalgal growth. This requires an understanding of the biosynthesis of IAA in microalgae-bacteria associations and its function in regulating algal physiology and metabolite production. We review the current advances in understanding of microalgal and bacterial auxin biosynthesis and their implications for algal biotechnology.

09 BIOMASS FUELS↗
DOE OSTI2025

Beneath the surface: Unsolved questions in soil virus ecology

Soil virus ecology is an exciting but still nascent field of research in soil microbiology. While there has been a recent surge in soil virus research studies, many fundamental questions remain unanswered, and a range of technical and bioinformatic challenges need to be overcome. In this perspective article, we present a series of key questions that highlight fruitful research areas for ongoing and future efforts. These include describing the challenges involved in understanding soil viral abundance and activity, spatiotemporal dynamics, life strategy prevalence, virus-mediated biogeochemical impacts, viral protein function, host prediction, and soil RNA virus discovery. In the near term, combining approaches (e.g., cultivation-based, meta-omics, biogeochemical, experimental, and bioinformatic) will be key to assessing the ecological and biogeochemical impacts of soil viruses from the microscopic to the field and global scales. Still, we stress that results must be tempered by current methodological limitations and highlight knowledge gaps that are most pressing to fill via new methods or measurements, such as the prevalence of different viral replication strategies across soils, the fate of microbial necromass carbon after viral lysis, the frequency of virus-host encounters that do not lead to successful infections yet could be bioinformatically mistaken as infections, and the diversity and ecological impacts of RNA viruses in soil.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Phosphate amendment drives bloom of RNA viruses after soil wet-up

Soil rewetting after a dry period results in a surge of activity and succession in both microbial and DNA virus communities. Less is known about the response of RNA viruses to soil rewetting—while they are highly diverse and widely distributed in soil, they remain understudied. We hypothesized that RNA viruses would show temporal succession following rewetting and that phosphate amendment would influence their trajectory, as viral proliferation may cause phosphorus limitation. Using 39 time-resolved metatranscriptomes and amplicon data, 2190 RNA viral populations were identified across five phyla, with 26 % of these predicted to infect bacteria, and 11 % fungi. Only 1.2 % of viral populations had annotated capsid genes, suggesting most persist via intracellular replication without a free virion phase. Phosphate amendment altered RNA viral community composition within the first week and amended vs. unamended communities remained distinguishable for up to three weeks. While the overall host community remained stable, certain bacterial populations showed reduced abundance in phosphate-amended soils, likely due to increased viral lysis, as RNA bacteriophages proliferated significantly. Notably, 60 % of the viruses with increased abundance under phosphate amendment belonged to basal Lenarviricota clades rather than well-known groups like Leviviricetes. We estimate RNA bacteriophage infections may affect 10 7 –10 9 bacteria per gram of soil, aligning with the total bacterial population (10 7 –10 10 g -1 soil), suggesting that RNA phages significantly influence bacterial communities post-wet-up, with phosphorus availability modulating this effect.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Netting and pan traps fail to identify the pollinator guild of an agricultural crop

Pollinator decline is expected to cause significant reductions in food production and plant reproduction. Quantifying the impact of pollinator decline on food production requires survey methods that can identify insect and bee species responsible for pollination of specific crops. To address this issue, we compared the effectiveness of two survey methods, netting and pan traps, at capturing the pollinators of alfalfa, Medicago sativa. Alfalfa is a major component of forage for cows and an important ingredient in chicken feed. We also examined bee species richness and diversity with these two survey methods, and compared these measures among three different colors of pan traps. Netting was more effective at capturing known pollinators of alfalfa, especially those belonging to the Bombus and Apis genera. Pan traps captured a higher bee diversity relative to netting and, like previous studies, each survey method and each trap color was more efficient at capturing certain bee genera. However, without a priori knowledge of pollinators, neither survey method could identify which of the bee species captured could pollinate alfalfa. We therefore recommend direct observations when the goal of a study is to identify pollinators or link pollinator decline to food production.

54 ENVIRONMENTAL SCIENCES↗