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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Population genomics provides insights into the genetic basis of adaptive evolution in the mushroom-forming fungus Lentinula edodes

Introduction: Mushroom-forming fungi comprise diverse species that develop complex multicellular structures. In cultivated species, both ecological adaptation and artificial selection have driven genome evolution. However, little is known about the connections among genotype, phenotype and adaptation in mushroom-forming fungi. Objectives: This study aimed to (1) uncover the population structure and demographic history of Lentinula edodes, (2) dissect the genetic basis of adaptive evolution in L. edodes, and (3) determine if genes related to fruiting body development are involved in adaptive evolution. Methods: We analyzed genomes and fruiting body-related traits (FBRTs) in 133 L. edodes strains and conducted RNA-seq analysis of fruiting body development in the YS69 strain. Combined methods of genomic scan for divergence, genome-wide association studies (GWAS), and RNA-seq were used to dissect the genetic basis of adaptive evolution. Results: We detected three distinct subgroups of L. edodes via single nucleotide polymorphisms, which showed robust phenotypic and temperature response differentiation and correlation with geographical distribution. Demographic history inference suggests that the subgroups diverged 36,871 generations ago. Moreover, L. edodes cultivars in China may have originated from the vicinity of Northeast China. A total of 942 genes were found to be related to genetic divergence by genomic scan, and 719 genes were identified to be candidates underlying FBRTs by GWAS. Integrating results of genomic scan and GWAS, 80 genes were detected to be related to phenotypic differentiation. A total of 364 genes related to fruiting body development were involved in genetic divergence and phenotypic differentiation. Conclusion: Adaptation to the local environment, especially temperature, triggered genetic divergence and phenotypic differentiation of L. edodes. A general model for genetic divergence and phenotypic differentiation during adaptive evolution in L. edodes, which involves in signal perception and transduction, transcriptional regulation, and fruiting body morphogenesis, was also integrated here.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Root hairs vs. trichomes: Not everyone is straight!

Trichomes show 47 morphological phenotypes, while literature reports only two root hair phenotypes in all plants. However, could hair-like structures exist below-ground in a similar wide range of morphologies like trichomes? Genetic mutants and root hair stress phenotypes point to the possibility of uncharacterized morphological variation existing belowground. For example, such root hairs in Arabidopsis (Arabidopsis thaliana) can be wavy, curled, or branched. We found hints in the literature about hair-like structures that emerge before root hairs belowground. As such, these early emerging hair structures can be potential exceptions to the contrasting morphological variation between trichomes and root hairs. Here, in this work, we show a previously unreported ‘hooked’ hair structure growing below-ground in common bean. The unique ‘hooking’ shape distinguishes the ‘hooked hair’ morphologically from root hairs. Currently, we cannot fully characterize the phenotype of our observation due to the lack of automated methods for phenotyping root hairs. This phenotyping bottleneck also handicaps the discovery of more morphology types that might exist below-ground as manual screening across species is slower than computer-assisted high-throughput screening.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Systematic characterization of gene function in the photosynthetic alga Chlamydomonas reinhardtii

Most genes in photosynthetic organisms remain functionally uncharacterized. Here, using a barcoded mutant library of the model eukaryotic alga Chlamydomonas reinhardtii, we determined the phenotypes of more than 58,000 mutants under more than 121 different environmental growth conditions and chemical treatments. A total of 59% of genes are represented by at least one mutant that showed a phenotype, providing clues to the functions of thousands of genes. Mutant phenotypic profiles place uncharacterized genes into functional pathways such as DNA repair, photosynthesis, the CO 2 -concentrating mechanism and ciliogenesis. We illustrate the value of this resource by validating phenotypes and gene functions, including three new components of an actin cytoskeleton defense pathway. The data also inform phenotype discovery in land plants; mutants in Arabidopsis thaliana genes exhibit phenotypes similar to those we observed in their Chlamydomonas homologs. We anticipate that this resource will guide the functional characterization of genes across the tree of life.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Characterizing the gene–environment interaction underlying natural morphological variation in Neurospora crassa conidiophores using high-throughput phenomics and transcriptomics

Abstract Neurospora crassa propagates through dissemination of conidia, which develop through specialized structures called conidiophores. Recent work has identified striking variation in conidiophore morphology, using a wild population collection from Louisiana, United States of America to classify 3 distinct phenotypes: Wild-Type, Wrap, and Bulky. Little is known about the impact of these phenotypes on sporulation or germination later in the N. crassa life cycle, or about the genetic variation that underlies them. In this study, we show that conidiophore morphology likely affects colonization capacity of wild N. crassa isolates through both sporulation distance and germination on different carbon sources. We generated and crossed homokaryotic strains belonging to each phenotypic group to more robustly fit a model for and estimate heritability of the complex trait, conidiophore architecture. Our fitted model suggests at least 3 genes and 2 epistatic interactions contribute to conidiophore phenotype, which has an estimated heritability of 0.47. To uncover genes contributing to these phenotypes, we performed RNA-sequencing on mycelia and conidiophores of strains representing each of the 3 phenotypes. Our results show that the Bulky strain had a distinct transcriptional profile from that of Wild-Type and Wrap, exhibiting differential expression patterns in clock-controlled genes (ccgs), the conidiation-specific gene con-6, and genes implicated in metabolism and communication. Combined, these results present novel ecological impacts of and differential gene expression underlying natural conidiophore morphological variation, a complex trait that has not yet been thoroughly explored.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Predicting Antimicrobial Resistance Using Partial Genome Alignments

Antimicrobial resistance (AMR) is an important global health threat that impacts millions of people worldwide each year. Developing methods that can detect and predict AMR phenotypes can help to mitigate the spread of AMR by informing clinical decision making and appropriate mitigation strategies. Many bioinformatic methods have been developed for predicting AMR phenotypes from whole-genome sequences and AMR genes, but recent studies have indicated that predictions can be made from incomplete genome sequence data. In order to more systematically understand this, we built random forest-based machine learning classifiers for predicting susceptible and resistant phenotypes for Klebsiella pneumoniae (1,640 strains), Mycobacterium tuberculosis (2,497 strains), and Salmonella enterica (1,981 strains). We started by building models from alignments that were based on a reference chromosome for each species. We then subsampled each chromosomal alignment and built models for the resulting subalignments, finding that very small regions, representing approximately 0.1 to 0.2% of the chromosome, are predictive. In K. pneumoniae, M. tuberculosis, and S. enterica, the subalignments are able to predict multiple AMR phenotypes with at least 70% accuracy, even though most do not encode an AMR-related function. We used these models to identify regions of the chromosome with high and low predictive signals. Finally, subalignments that retain high accuracy across larger phylogenetic distances were examined in greater detail, revealing genes and intergenic regions with potential links to AMR, virulence, transport, and survival under stress conditions. IMPORTANCE Antimicrobial resistance causes thousands of deaths annually worldwide. Understanding the regions of the genome that are involved in antimicrobial resistance is important for developing mitigation strategies and preventing transmission. Machine learning models are capable of predicting antimicrobial resistance phenotypes from bacterial genome sequence data by identifying resistance genes, mutations, and other correlated features. They are also capable of implicating regions of the genome that have not been previously characterized as being involved in resistance. In this study, we generated global chromosomal alignments for Klebsiella pneumoniae, Mycobacterium tuberculosis, and Salmonella enterica and systematically searched them for small conserved regions of the genome that enable the prediction of antimicrobial resistance phenotypes. In addition to known antimicrobial resistance genes, this analysis identified genes involved in virulence and transport functions, as well as many genes with no previous implication in antimicrobial resistance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Data for "Genetics of flooding tolerance in an F2 Miscanthus sacchariflorus ssp. lutarioriparius × M. sinensis population"

This dataset contains all data and supplementary materials from "Genetics of flooding tolerance in an F2 Miscanthus sacchariflorus ssp. lutarioriparius × M. sinensis population". 1. The dataset S1 table contains the raw phenotypic data collected during the experiment. 2. The dataset S2 table contains the LSmean values for the 24 traits studied. 3. The dataset S3 table contains the TASSEL GBSv2 map, marker information, and genotype data used for mapping. 4. The dataset S4 table contains information on candidate genes found in each of the QTL intervals. 5. The dataset S5 table contains the GO annotations and KEGG enrichment analyses for those candidate genes. 6. The dataset S6 table contains information on the sequences used to classify AP2 ERF transcription factors. 7. The dataset S7 table contains information on AP2 ERF orthologs between Miscanthus and rice based on synteny. 8. Supplementary file 1 contains the ANOVA results using the raw phenotypic data collected from protocol "A". 9. Supplementary file 2 contains the ANOVA results using the raw phenotypic data collected from protocol "B". 10. Supplementary file 3 contains notes on the comparison of SNP calling methods. 11. Supplementary file 4 is a script for analyzing candidate genes found in QTL intervals.

Miscanthus, flood, partial submergence, complete s↗
DOE OSTI2022

A Phenome-Wide Association Study of genes associated with COVID-19 severity reveals shared genetics with complex diseases in the Million Veteran Program

The study aims to determine the shared genetic architecture between COVID-19 severity with existing medical conditions using electronic health record (EHR) data. We conducted a Phenome-Wide Association Study (PheWAS) of genetic variants associated with critical illness (n = 35) or hospitalization (n = 42) due to severe COVID-19 using genome-wide association summary data from the Host Genetics Initiative. PheWAS analysis was performed using genotype-phenotype data from the Veterans Affairs Million Veteran Program (MVP). Phenotypes were defined by International Classification of Diseases (ICD) codes mapped to clinically relevant groups using published PheWAS methods. Among 658,582 Veterans, variants associated with severe COVID-19 were tested for association across 1,559 phenotypes. Variants at the ABO locus (rs495828, rs505922) associated with the largest number of phenotypes (n rs495828 = 53 and n rs505922 = 59); strongest association with venous embolism, odds ratio (OR rs495828 1.33 (p = 1.32 x 10 –199 ), and thrombosis OR rs505922 1.33, p = 2.2 x10 -265 . Among 67 respiratory conditions tested, 11 had significant associations including MUC5B locus (rs35705950) with increased risk of idiopathic fibrosing alveolitis OR 2.83, p = 4.12 × 10 –191 ; CRHR1 (rs61667602) associated with reduced risk of pulmonary fibrosis, OR 0.84, p = 2.26× 10 –12 . The TYK2 locus (rs11085727) associated with reduced risk for autoimmune conditions, e.g., psoriasis OR 0.88, p = 6.48 x10 -23 , lupus OR 0.84, p = 3.97 x 10 –06 . PheWAS stratified by ancestry demonstrated differences in genotype-phenotype associations. LMNA (rs581342) associated with neutropenia OR 1.29 p = 4.1 x 10 –13 among Veterans of African and Hispanic ancestry but not European. Overall, we observed a shared genetic architecture between COVID-19 severity and conditions related to underlying risk factors for severe and poor COVID-19 outcomes. Differing associations between genotype-phenotype across ancestries may inform heterogenous outcomes observed with COVID-19. Divergent associations between risk for severe COVID-19 with autoimmune inflammatory conditions both respiratory and non-respiratory highlights the shared pathways and fine balance of immune host response and autoimmunity and caution required when considering treatment targets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Temporal responsiveness of adipose-derived stem/stromal cell immune plasticity

Highlights: • Adipose-derived stem cells modulate immune responses in a plastic manner. • The persistence of pro- and anti-inflammatory phenotypes was explored over time. • IL-6 was present at all time points; IDO1 was induced after cytokine stimulation. • Phenotypes persisted 96–168 h after returning to control conditions. • Macrophages showed reaction to ASC culture but without time effect. We determined the role of time in adipose-derived stem/stromal cell (ASC) response to a model inflammatory environment. ASCs and other mesenchymal stem/stromal cells exhibit immune plasticity. We evaluated the persistence of pro- and anti-inflammatory phenotypes for ASCs exposed to a sustained or pulse inflammatory stimulus. Using qPCR, flow cytometry, and immunocytochemistry, we monitored the temporal expression and up-regulation patterns of a pro-inflammatory gene (caspase 1), a pleiotropic gene/protein (interleukin 6, IL-6), and an anti-inflammatory gene/protein (indoleamine 2, 3-dioxygenase, IDO1) after exposing ASCs to the cytokines tumor necrosis factor-α and interferon-γ. In response to sustained cytokine stimulation, we discovered that time played a role in the balance of pro- and anti-inflammatory ASC phenotypes. IL-6 was present at all time points for both cytokine-stimulated and non-stimulated conditions, whereas IDO1 was heterogeneously up-regulated in stimulated conditions at later time points. After a pulse stimulus, ASC immunoresponse remained consistent for 96–168 h. As a final measure of immune plasticity, we cultured cytokine-stimulated ASCs with blood-derived macrophages to observe macrophage polarization. While the presence of ASCs altered macrophage phenotype, there was no dependency on the length of ASC cytokine exposure time.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

A shift between mineral and nonmineral sources of iron and sulfur causes proteome-wide changes in Methanosarcina barkeri

ABSTRACT Iron (Fe) and sulfur (S) are required elements for life, and changes in their availability can limit the ecological distribution and function of microorganisms. In anoxic environments, soluble Fe typically exists as ferrous iron [Fe(II)] and S as sulfide (HS − ). These species exhibit a strong affinity that ultimately drives the formation of sedimentary pyrite (FeS 2 ). Recently, paradigm-shifting studies indicate that Fe and S in FeS 2 can be made bioavailable by methanogens through a reductive dissolution process. However, the impact of the utilization of FeS 2 , as opposed to canonical Fe and S sources, on the phenotype of cells is not fully understood. Here, shotgun proteomics was utilized to measure changes in the phenotype of Methanosarcina barkeri MS grown with FeS 2 , Fe(II)/HS − , or Fe(II)/cysteine. Shotgun proteomics tracked 1,019 proteins overall, with 307 observed to change between growth conditions. Functional characterization and pathway analyses revealed these changes to be systemic and largely tangential to Fe/S metabolism. As a final step, the proteomics data were viewed with respect to previously collected transcriptomics data to deepen the analysis. Presented here is evidence that M. barkeri adopts distinct phenotypes to exploit specific sources of Fe and S in its environment. This is supported by observed protein abundance changes across broad categories of cellular biology. DNA adjacent metabolism, central carbon metabolism methanogenesis, metal trafficking, quorum sensing, and porphyrin biosynthesis pathways are all features in the phenotypic differentiation. Differences in trace metal availability attributed to complexation with HS − , either as a component of the growth medium [Fe(II)/HS − ] or generated through reduction of FeS 2 , were likely a major factor underpinning these phenotypic differences. IMPORTANCE The methanogenic archaeon Methanosarcina barkeri holds great potential for industrial bio-mining and energy generation technologies. Much of the biochemistry of this microbe is poorly understood, and its characterization will provide a glimpse into biological processes that evolved close to life’s origin. The discovery of its ability to extract iron and sulfur from bulk, solid-phase minerals shifted a longstanding paradigm that these elements were inaccessible to biological systems. The full elucidation of this process has the potential to help scientists and engineers extract valuable metals from low-grade ore and mine waste generating energy in the form of methane while doing so.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

The Ontology of Biological Attributes (OBA)—computational traits for the life sciences

Abstract Existing phenotype ontologies were originally developed to represent phenotypes that manifest as a character state in relation to a wild-type or other reference. However, these do not include the phenotypic trait or attribute categories required for the annotation of genome-wide association studies (GWAS), Quantitative Trait Loci (QTL) mappings or any population-focussed measurable trait data. The integration of trait and biological attribute information with an ever increasing body of chemical, environmental and biological data greatly facilitates computational analyses and it is also highly relevant to biomedical and clinical applications. The Ontology of Biological Attributes (OBA) is a formalised, species-independent collection of interoperable phenotypic trait categories that is intended to fulfil a data integration role. OBA is a standardised representational framework for observable attributes that are characteristics of biological entities, organisms, or parts of organisms. OBA has a modular design which provides several benefits for users and data integrators, including an automated and meaningful classification of trait terms computed on the basis of logical inferences drawn from domain-specific ontologies for cells, anatomical and other relevant entities. The logical axioms in OBA also provide a previously missing bridge that can computationally link Mendelian phenotypes with GWAS and quantitative traits. The term components in OBA provide semantic links and enable knowledge and data integration across specialised research community boundaries, thereby breaking silos.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Five amino acid mismatches in the zinc-finger domains of Cellulose Synthase 5 and Cellulose Synthase 6 cooperatively modulate their functional properties by controlling homodimerization in Arabidopsis

Cellulose synthase 5 (CESA5) and CESA6 are known to share substantial functional overlap. In the zinc-finger domain (ZN) of CESA5, there are five amino acid (AA) mismatches when compared to CESA6. These mismatches in CESA5 were replaced with their CESA6 counterparts one by one until all were replaced, generating nine engineered CESA5s. Each N-terminal enhanced yellow fluorescent protein-tagged engineered CESA5 was introduced to prc1-1, a cesa6 null mutant, and resulting mutants were subjected to phenotypic analyses. For this work, we found that five single AA-replaced CESA5 proteins partially rescue the prc1-1 mutant phenotypes to different extents. Multi-AA replaced CESA5s further rescued the mutant phenotypes in an additive manner, culminating in full recovery by CESA5 G43R + S49T+S54P+S80A+Y88F . Investigations in cellulose content, cellulose synthase complex (CSC) motility, and cellulose microfibril organization in the same mutants support the results of the phenotypic analyses. Bimolecular fluorescence complementation assays demonstrated that the level of homodimerization in every engineered CESA5 is substantially higher than CESA5. The mean fluorescence intensity of CSCs carrying each engineered CESA5 fluctuates with the degree to which the prc1-1 mutant phenotypes are rescued by introducing a corresponding engineered CESA5. Taken together, these five AA mismatches in the ZNs of CESA5 and CESA6 cooperatively modulate the functional properties of these CESAs by controlling their homodimerization capacity, which in turn imposes proportional changes on the incorporation of these CESAs into CSCs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Genetic control of root architectural plasticity in maize

Root phenotypes regulate soil resource acquisition; however, their genetic control and phenotypic plasticity are poorly understood. We hypothesized that the responses of root architectural phenes to water deficit (stress plasticity) and different environments (environmental plasticity) are under genetic control and that these loci are distinct. Root architectural phenes were phenotyped in the field using a large maize association panel with and without water deficit stress for three seasons in Arizona and without water deficit stress for four seasons in South Africa. All root phenes were plastic and varied in their plastic response. We identified candidate genes associated with stress and environmental plasticity and candidate genes associated with phenes in well-watered conditions in South Africa and in well-watered and water-stress conditions in Arizona. Few candidate genes for plasticity overlapped with those for phenes expressed under each condition. Our results suggest that phenotypic plasticity is highly quantitative, and plasticity loci are distinct from loci that control phene expression in stress and non-stress, which poses a challenge for breeding programs. To make these loci more accessible to the wider research community, we developed a public online resource that will allow for further experimental validation towards understanding the genetic control underlying phenotypic plasticity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Nonlinear drought plasticity reveals intraspecific diversity in a dominant grass species

Abstract Intraspecific diversity of dominant species in native plant communities can modulate ecosystem function under both optimal and stressful conditions. Yet, few genotype by environment interaction studies quantify differences in the shape of plasticity functions or phenotypic breakpoints across genotypes in natural populations. Using three genotypes with a history of drought selection, we performed a greenhouse study on the dominant tallgrass prairie species Andropogon gerardii . We investigated phenotypic plasticity and recovery differences among genotypes across a water availability gradient, measuring growth‐related, instantaneous and cumulative phenotypes. To further understand genotype by environment effects, we quantified plasticity functions and breakpoints among genotypes. Like other studies, we found strong evidence for phenotypic and plasticity differences among genotypes. However, we also found nonlinear plasticity functions and breakpoints were common across phenotypes, especially relative growth rates, biomass allocation and root architecture. Drought selected genotypes were also more likely to flower during recovery, but all genotypes were resilient to drought across treatments. We demonstrate that plasticity functions may help explain intraspecific diversity, patterns of selection and nonlinear community responses to more variable rainfall within an experimental population. In particular, plasticity functions can help disentangle drought/variability tolerance versus acquisitive strategies. A better understanding of intraspecific diversity in this grass species will provide more mechanistic insight into its ability to buffer ecosystem changes and provide resiliency in the tallgrass prairie under future droughts. A free Plain Language Summary can be found within the Supporting Information of this article.

Hoffman, Ava M.↗
DOE OSTI2020

Systems Analysis of NADH Dehydrogenase Mutants Reveals Flexibility and Limits of Pseudomonas taiwanensis VLB120’s Metabolism

Obligate aerobic organisms rely on a functional electron transport chain for energy conservation and NADH oxidation. Because of this essential requirement, the genes of this pathway are likely constitutively and highly expressed to avoid a cofactor imbalance and energy shortage under fluctuating environmental conditions. In this work, we investigated the essentiality of the three NADH dehydrogenases of the respiratory chain of the obligate aerobe Pseudomonas taiwanensis VLB120 and the impact of the knockouts of corresponding genes on its physiology and metabolism. While a mutant lacking all three NADH dehydrogenases seemed to be nonviable, the single or double knockout mutant strains displayed no, or only a weak, phenotype. Only the mutant deficient in both type 2 dehydrogenases showed a clear phenotype with biphasic growth behavior and a strongly reduced growth rate in the second phase. In-depth analyses of the metabolism of the generated mutants, including quantitative physiological experiments, transcript analysis, proteomics, and enzyme activity assays revealed distinct responses to type 2 and type 1 dehydrogenase deletions. An overall high metabolic flexibility enables P. taiwanensis to cope with the introduced genetic perturbations and maintain stable phenotypes, likely by rerouting of metabolic fluxes. This metabolic adaptability has implications for biotechnological applications. While the phenotypic robustness is favorable in large-scale applications with inhomogeneous conditions, the possible versatile redirecting of carbon fluxes upon genetic interventions can thwart metabolic engineering efforts. While Pseudomonas has the capability for high metabolic activity and the provision of reduced redox cofactors important for biocatalytic applications, exploitation of this characteristic might be hindered by high, constitutive activity of and, consequently, competition with the NADH dehydrogenases of the respiratory chain. The in-depth analysis of NADH dehydrogenase mutants of Pseudomonas taiwanensis VLB120 presented here provides insight into the phenotypic and metabolic response of this strain to these redox metabolism perturbations. This high degree of metabolic flexibility needs to be taken into account for rational engineering of this promising biotechnological workhorse toward a host with a controlled and efficient supply of redox cofactors for product synthesis.

36 MATERIALS SCIENCE↗
DOE OSTI2021

The role of memory in non-genetic inheritance and its impact on cancer treatment resistance

Intra-tumour heterogeneity is a leading cause of treatment failure and disease progression in cancer. While genetic mutations have long been accepted as a primary mechanism of generating this heterogeneity, the role of phenotypic plasticity is becoming increasingly apparent as a driver of intra-tumour heterogeneity. Consequently, understanding the role of this plasticity in treatment resistance and failure is a key component of improving cancer therapy. We develop a mathematical model of stochastic phenotype switching that tracks the evolution of drug-sensitive and drug-tolerant subpopulations to clarify the role of phenotype switching on population growth rates and tumour persistence. By including cytotoxic therapy in the model, we show that, depending on the strategy of the drug-tolerant subpopulation, stochastic phenotype switching can lead to either transient or permanent drug resistance. We study the role of phenotypic heterogeneity in a drug-resistant, genetically homogeneous population of non-small cell lung cancer cells to derive a rational treatment schedule that drives population extinction and avoids competitive release of the drug-tolerant sub-population. This model-informed therapeutic schedule results in increased treatment efficacy when compared against periodic therapy, and, most importantly, sustained tumour decay without the development of resistance.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Quantile-Specific Heritability of Inflammatory and Oxidative Stress Biomarkers Linked to Cardiovascular Disease

Purpose: Heritability (h 2 , the proportion of the phenotypic variance attributable to additive genetic effects) is traditionally assumed to be constant throughout the distribution of the phenotype. However, the heritabilities of circulating C-reactive protein, interleukin-6, plasminogen activator inhibitor type-1 (PAI-1), and monocyte chemoattractant protein-1 (MCP-1) concentrations depend upon whether the phenotype is high or low relative to their distributions (quantile-dependent expressivity), which may account for apparent gene–environment interactions. Whether the heritabilities of other inflammatory biomarkers linked to cardiovascular disease are quantile-dependent remain to be determined. Patients and Methods: Quantile-specific offspring-parent (β OP ) and full-sib regression slopes (β FS ) were estimated by applying quantile regression to the age- and sex-adjusted phenotypes of families surveyed as part of the Framingham Heart Study. Quantile-specific heritabilities were calculated as: h 2 =2β OP /(1+r spouse ) and h 2 ={(1+8r spouse β FS ) 0.5 – 1}/(2r spouse ). Results: Heritability (h 2 ± SE) of lipoprotein-associated phospholipase A2 (Lp-PLA 2 ) mass concentrations increased from 0.11 ± 0.03 at the 10 th percentile, 0.08 ± 0.03 at the 25 th , 0.12 ± 0.03 at the 50 th , 0.20 ± 0.04 at the 75 th , and 0.26 ± 0.06 at the 90 th percentile, or 0.0023 ± 0.0006 per each one-percent increase in the phenotype distribution (P linear trend = 0.0004). Similarly, h 2 increased 0.0029 ± 0.0011 (P linear trend = 0.01) for sP-selectin, 0.0032 ± 0.0009 (P linear trend = 0.0001) for soluble intercellular adhesion molecule 1 (sICAM-1), and 0.0026 ± 0.0006 for tumor necrosis factor receptor 2 (TNFR2) (P linear trend = 5.0 × 10 -6 ) per each one-percent increase in their distributions when estimated from β OP . Osteoprotegerin and soluble ST2 heritability also increased significantly with increasing percentiles of their distributions when estimated from β FS . Lp-PLA 2 activity, CD40 ligand, TNFα, interleukin-18, and myeloperoxidase heritability showed no significant quantile-dependence. Conclusion: The heritabilities of circulating Lp-PLA 2 -mass, sP-selectin, sICAM-1, TNFR2, osteoprotegerin and soluble ST2 concentrations are quantile-dependent, which may contribute to purported genetic modulations of: 1) sP-selectin’s relationships to venous thrombosis, pulmonary hypertension, type 2 diabetes and atorvastatin treatment; 2) sICAM-I’s relationships to brain abscess and atorvastatin treatment; and 3) Lp-PLA 2 ’s relationships to myocardial infarction and preeclampsia.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

CarbStor: Development, Analysis and Modification of Carbon Storing Model Soil Communities

Soil microbial communities carry out a number of key processes including plant growth promotion, bioremediation and cycling of nutrients. Carbon cycling is among the most important of these nutrients that are metabolized and processed by the soil microbial community. Many of the carbon inputs are converted to alternative organic forms of carbon that can be used by plants or act as biomass for microbial growth. However, inorganic forms of carbon can also be produced by soil microbial communities including calcium carbonate (CaCO 3 ). Production of calcium carbonate is beneficial for the ecosystem in several ways: it can stabilize soils and improve soil health, especially denser soils with high clay content, it can act as a method of bioremediation, it can serve as an alternative carbon source for plants and it can be a way to store carbon in soil in a stable, inorganic manner for the long term. While the chemistry surrounding individual species carrying out this process is well known what is lacking is an understanding of how species interact in a community to drive carbonate production. As all microbial species in soil exist in a community setting gaining this knowledge is critical to our predicting and controlling this microbial phenotype to greatly improve soil health. The CarbStor project is focused on developing, analyzing and modifying defined microbial soil consortia that express phenotypes at both the species and community level to convert carbon into recalcitrant stable sources such as precipitated carbonate or microbial necromass. To take full advantage of the soil community for this process we will need to fill several key knowledge gaps (KG), three of which are the focus of CarbStor. KG1: Whether and to what degree microbial communities can be developed that produce precipitated carbon via microbial metabolism. KG2: What interspecies interactions drive the individual member phenotypes in defined communities that lead to carbon precipitation. KG3: How can these interactions be modified to enhance carbon sequestration beyond what native communities are capable of. We hypothesize that in a carbon sequestering community only a subset of species will express phenotypes related to carbon storage processes. We also hypothesize that these phenotypes are expressed as a result of interactions with other species in the community that are not involved in carbon storage processes and that these interactions can be harnessed to enhance community carbon sequestration.

54 ENVIRONMENTAL SCIENCES↗