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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Characterizing Long COVID: Deep Phenotype of a Complex Condition

Background: Numerous publications describe the clinical manifestations of post-acute sequelae of SARS-CoV-2 (PASC or "long COVID"), but they are difficult to integrate because of heterogeneous methods and the lack of a standard for denoting the many phenotypic manifestations. Patient-led studies are of particular importance for understanding the natural history of COVID-19, but integration is hampered because they often use different terms to describe the same symptom or condition. This significant disparity in patient versus clinical characterization motivated the proposed ontological approach to specifying manifestations, which will improve capture and integration of future long COVID studies. Methods: The Human Phenotype Ontology (HPO) is a widely used standard for exchange and analysis of phenotypic abnormalities in human disease but has not yet been applied to the analysis of COVID-19. Funding: We identified 303 articles published before April 29, 2021, curated 59 relevant manuscripts that described clinical manifestations in 81 cohorts three weeks or more following acute COVID-19, and mapped 287 unique clinical findings to HPO terms. We present layperson synonyms and definitions that can be used to link patient self-report questionnaires to standard medical terminology. Long COVID clinical manifestations are not assessed consistently across studies, and most manifestations have been reported with a wide range of synonyms by different authors. Across at least 10 cohorts, authors reported 31 unique clinical features corresponding to HPO terms; the most commonly reported feature was Fatigue (median 45.1%) and the least commonly reported was Nausea (median 3.9%), but the reported percentages varied widely between studies. Interpretation: Translating long COVID manifestations into computable HPO terms will improve analysis, data capture, and classification of long COVID patients. If researchers, clinicians, and patients share a common language, then studies can be compared/pooled more effectively. Furthermore, mapping lay terminology to HPO will help patients assist clinicians and researchers in creating phenotypic characterizations that are computationally accessible, thereby improving the stratification, diagnosis, and treatment of long COVID.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Tradeoffs between phenotypic plasticity and local adaptation influence the ecophysiology of the moss, Sphagnum magellanicum

Bryophytes are a diverse plant group and are functionally different from vascular plants. Yet, their peculiarities are rarely considered in the theoretical frameworks for plants. Currently, we lack information about the magnitude and the importance of intraspecific variability in the ecophysiology of bryophytes and how these might translate to local adaptation—a prerequisite for adaptive evolution. Capitalizing on two ecologically distinct (hummock and hollow) phenotypes of Sphagnum magellanicum, we explored the magnitude and pattern of intraspecific variability in this species and asked whether the environmental-mediated changes in shoot and physiological traits are due to phenotypic plasticity or local adaptation. Size, pigmentation, and habitat type that distinguished the phenotypes in the field did not influence the trait responses under a transplant and factorial experiment. In addition, the magnitude and pattern of trait variability (e.g., branch, stem and capitulum mass) changed with the treatments, which suggest that trait responses were due largely to phenotypic plasticity. The trait responses also suggest that the ecophysiological needs for mosses to grow in clumps, where they maintain a uniform growth may have an overriding effect over the potential for a fixed adaptive response to environmental heterogeneity, which would constrain local adaptation. In this paper, we conclude that extending the trait-based framework to mosses or making comparisons between mosses and vascular plants under any theoretical framework would only be meaningful to the extent that growth form and dispersal strategies are considered.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Monocyte-lymphocyte fusion induced by the HIV-1 envelope generates functional heterokaryons with an activated monocyte-like phenotype

Enveloped viruses induce cell-cell fusion when infected cells expressing viral envelope proteins interact with target cells, or through the contact of cell-free viral particles with adjoining target cells. CD4{sup +} T lymphocytes and cells from the monocyte-macrophage lineage express receptors for HIV envelope protein. We have previously reported that lymphoid Jurkat T cells expressing the HIV-1 envelope protein (Env) can fuse with THP-1 monocytic cells, forming heterokaryons with a predominantly myeloid phenotype. This study shows that the expression of monocytic markers in heterokaryons is stable, whereas the expression of lymphoid markers is mostly lost. Like THP-1 cells, heterokaryons exhibited FcγR-dependent phagocytic activity and showed an enhanced expression of the activation marker ICAM-1 upon stimulation with PMA. In addition, heterokaryons showed morphological changes compatible with maturation, and high expression of the differentiation marker CD11b in the absence of differentiation-inducing agents. No morphological change nor increase in CD11b expression were observed when an HIV-fusion inhibitor blocked fusion, or when THP-1 cells were cocultured with Jurkat cells expressing a non-fusogenic Env protein, showing that differentiation was not induced merely by cell-cell interaction but required cell-cell fusion. Inhibition of TLR2/TLR4 signaling by a TIRAP inhibitor greatly reduced the expression of CD11b in heterokaryons. Thus, lymphocyte-monocyte heterokaryons induced by HIV-1 Env are stable and functional, and fusion prompts a phenotype characteristic of activated monocytes via intracellular TLR2/TLR4 signaling. - Highlights: • Jurkat T cells expressing the HIV-1 envelope fuse with THP-1 monocytes. • Heterokaryons display a dominant myeloid phenotype and monocyte function. • Heterokaryons exhibit activation features in the absence of activation agents. • Activation is not due to cell-cell interaction but requires cell-cell fusion. • The activated monocyte-like phenotype is mediated by TLR2/TLR4 signaling.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Interactive Effects of Microbes and Nitrogen on Panicum virgatum Root Functional Traits and Patterns of Phenotypic Selection

Premise of research. Plants in natural and agricultural systems are influenced in myriad ways by their microbial communities, particularly by providing goods and services that change plant functional traits. Microbes are considered an influential part of the environmental context that change plant trait expression, but often, microbe-mediated effects are contingent on local resources, such as nitrogen. Here, we ask how microbes and nitrogen affect belowground functional traits and patterns of phenotypic selection. Methodology. We performed a fully factorial greenhouse experiment with switchgrass (Panicum virgatum), manipulating microbial community composition and nitrogen availability. We measured plant performance and belowground functional traits and performed 16S amplicon sequencing of the root-associated microbial communities. We looked for correlations between microbial taxa and root functional traits, and we performed phenotypic selection analysis on five belowground functional traits to determine how traits affect plant relative performance across biotic and abiotic contexts. Pivotal results. All belowground plant functional traits except root tissue density were affected by adding nitrogen. We found that a microbial taxon (amplicon sequence variant [ASV]) in the genus Micromonospora correlated with shorter root lengths. We also found strong positive selection for longer roots regardless of the abiotic or biotic environment. In contrast, selection favored lower root-to-shoot ratios in high-nitrogen conditions, and selection on root tissue density was highest in treatments that had high nitrogen levels and perturbed microbial communities. Conclusions. We did not detect microbial effects on the expression of plant traits (ecological effects); however, patterns of phenotypic selection (evolutionary effects) on root tissue density differed depending on the biotic and abiotic environment. Additionally, we detected strong selection for increased root length across treatments; we also found that one ASV correlated with decreased root length, indicating potential conflict between root microbiome components and plant fitness. Future work would be to include microbial taxa in phenotypic selection analysis and to conduct manipulations of the microbes correlated with functional traits to determine causality.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

VipariNama: RNA viral vectors to rapidly elucidate the relationship between gene expression and phenotype

Synthetic transcription factors have great promise as tools to help elucidate relationships between gene expression and phenotype by allowing tunable alterations of gene expression without genomic alterations of the loci being studied. However, the years-long timescales, high cost, and technical skill associated with plant transformation have limited their use. In this work, we developed a technology called VipariNama (ViN) in which vectors based on the tobacco rattle virus are used to rapidly deploy Cas9-based synthetic transcription factors and reprogram gene expression in planta. We demonstrate that ViN vectors can implement activation or repression of multiple genes systemically and persistently over several weeks in Nicotiana benthamiana, Arabidopsis (Arabidopsis thaliana), and tomato (Solanum lycopersicum). By exploring strategies including RNA scaffolding, viral vector ensembles, and viral engineering, we describe how the flexibility and efficacy of regulation can be improved. We also show how this transcriptional reprogramming can create predictable changes to metabolic phenotypes, such as gibberellin biosynthesis in N. benthamiana and anthocyanin accumulation in Arabidopsis, as well as developmental phenotypes, such as plant size in N. benthamiana, Arabidopsis, and tomato. These results demonstrate how ViN vector-based reprogramming of different aspects of gibberellin signaling can be used to engineer plant size in a range of plant species in a matter of weeks. In summary, ViN accelerates the timeline for generating phenotypes from over a year to just a few weeks, providing an attractive alternative to transgenesis for synthetic transcription factor-enabled hypothesis testing and crop engineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

The genotype-phenotype landscape of an allosteric protein

Allostery is a fundamental biophysical mechanism that underlies cellular sensing, signaling, and metabolism. Yet a quantitative understanding of allosteric genotype-phenotype relationships remains elusive. Here, we report the large-scale measurement of the genotype-phenotype landscape for an allosteric protein: the lac repressor from Escherichia coli , LacI. Using a method that combines long-read and short-read DNA sequencing, we quantitatively measure the dose-response curves for nearly 10 5 variants of the LacI genetic sensor. The resulting data provide a quantitative map of the effect of amino acid substitutions on LacI allostery and reveal systematic sequence-structure-function relationships. We find that in many cases, allosteric phenotypes can be quantitatively predicted with additive or neural-network models, but unpredictable changes also occur. For example, we were surprised to discover a new band-stop phenotype that challenges conventional models of allostery and that emerges from combinations of nearly silent amino acid substitutions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Rays for Roots - Integrating Backscatter X-Ray Phenotyping, Modeling and Genetics to Increase Carbon Sequestration and Switchgrass Resource Use (Final Report)

To increase carbon (C) deposition in the soil and enhance crop resource use efficiency, characterizing root form and function is essential. Several root and soil traits have been linked to increased root-to-soil C transfer. Technology that could provide high-resolution characterization of many of these traits in field conditions would revolutionize our ability to study and understand how to increase C sequestration. In this effort, we developed an initial early prototype backscatter X-ray system for non-destructive imaging of root traits. We collected initial backscatter X-ray data in field and lab settings and carried out early analysis of these data. Along with this prototype, we also developed a suite of root phenotyping approaches including advanced minirhizotron image analysis, soil core imaging, and mesocosm imaging. Minirhizotron (MR) tubes are clear tubes inserted into the soil in the field and used to image roots and the surrounding soil. Our team has developed deep learning-based methods that can segment roots from soil that can learn from imprecise image-level labels. The ability to learn or fine-tune our deep learning algorithms from image-level labels allows easier and faster application of these approaches to new locations and new plant species. We have successfully implemented and applied our MR analysis approaches to thousands of switchgrass MR images collected across geographical regions. An advantage of MR imaging is the ability to collect root and soil images over time. Our soil core analysis included collecting hundreds of soil core samples from harvested switchgrass fields and imaging these cores with both X-ray CT and backscatter X-ray imaging. Initial segmentation approaches for the X-ray CT images of these cores have been developed and applied. An advantage of soil core analysis is that it preserves the three-dimensional structures of the roots and soil in the core collected. Our group also developed photogrammetry-based mesocosm root imaging and phenotyping approaches. In this approach, a plant was grown in a large mesocosm with a three-dimensional grid of thin supporting lines inserted throughout the mesocosm. After the plant (and, correspondingly, the root architecture is grown and established) the soil media was removed and the supporting lines approximately preserved the three-dimensional root architecture. Then, we applied photogrammetry techniques to create a three-dimensional digital representation of the root architecture for which we developed analysis algorithms including skeletonization. We carried out our phenotyping development with powerful switchgrass resources and physiological and agroecosystem modeling to deliver novel technology. This project contributes to multiple ARPA-E missions including reduction of foreign imports of energy, reduction of energy-related emissions including greenhouse gases, and ensuring that the United States maintains a technological lead in developing and deploying advanced energy technology. Furthermore, the developed tools could transform public and private plant breeding and could be broadly applicable to other crops and, potentially, other application areas. Our team of engineers, plant and soil scientists, and modelers i) developed an early prototype backscatter X-ray platform that can operate in field conditions; ii) developed a suite of root phenotyping and characterization approaches as described above; iii) developed and carried out plant biology and physiology roots studies and; iv) developed and implemented mechanistic physiological modeling.

42 ENGINEERING↗
DOE OSTI2025

G2PDeep-v2: A Web-Based Deep-Learning Framework for Phenotype Prediction and Biomarker Discovery for All Organisms Using Multi-Omics Data

Multi-omics data offers rich insights into complex traits across organisms, yet integrating and analyzing these datasets for phenotype prediction and marker discovery remains challenging. Researchers need accessible tools that combine deep learning, hyperparameter optimization, visualization, and downstream analysis in a unified web platform. To address this, we developed G2PDeep-v2, a web-based platform powered by deep learning for phenotype prediction and marker discovery from multi-omics data across a wide range of organisms, including humans and plants. The server provides multiple services for researchers to create deep-learning models through an interactive interface and train these models using an automated hyperparameter tuning algorithm on high-performance computing resources. Users can visualize the results of phenotype and markers predictions and perform Gene Set Enrichment Analysis for the significant markers to provide insights into the molecular mechanisms underlying complex diseases, conditions and other biological phenotypes being studied.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2001

Skeletal muscle calcineurin: influence of phenotype adaptation and atrophy

Calcineurin (CaN) has been implicated as a signaling molecule that can transduce physiological stimuli (e.g., contractile activity) into molecular signals that initiate slow-fiber phenotypic gene expression and muscle growth. To determine the influence of muscle phenotype and atrophy on CaN levels in muscle, the levels of soluble CaN in rat muscles of varying phenotype, as assessed by myosin heavy chain (MHC)-isoform proportions, were determined by Western blotting. CaN levels were significantly greater in the plantaris muscle containing predominantly fast (IIx and IIb) MHC isoforms, compared with the soleus (predominantly type I MHC) or vastus intermedius (VI, contains all 4 adult MHC isoforms). Three months after a complete spinal cord transection (ST), the CaN levels in the VI muscle were significantly reduced, despite a significant increase in fast MHC isoforms. Surprisingly, the levels of CaN in the VI were highly correlated with muscle mass but not MHC isoform proportions in ST and control rats. These data demonstrate that CaN levels in skeletal muscle are highly correlated to muscle mass and that the normal relationship with phenotype is lost after ST.

NASA Discipline Musculoskeletal↗
NASA NTRS2000

A strong loss-of-function mutation in RAN1 results in constitutive activation of the ethylene response pathway as well as a rosette-lethal phenotype

A recessive mutation was identified that constitutively activated the ethylene response pathway in Arabidopsis and resulted in a rosette-lethal phenotype. Positional cloning of the gene corresponding to this mutation revealed that it was allelic to responsive to antagonist1 (ran1), a mutation that causes seedlings to respond in a positive manner to what is normally a competitive inhibitor of ethylene binding. In contrast to the previously identified ran1-1 and ran1-2 alleles that are morphologically indistinguishable from wild-type plants, this ran1-3 allele results in a rosette-lethal phenotype. The predicted protein encoded by the RAN1 gene is similar to the Wilson and Menkes disease proteins and yeast Ccc2 protein, which are integral membrane cation-transporting P-type ATPases involved in copper trafficking. Genetic epistasis analysis indicated that RAN1 acts upstream of mutations in the ethylene receptor gene family. However, the rosette-lethal phenotype of ran1-3 was not suppressed by ethylene-insensitive mutants, suggesting that this mutation also affects a non-ethylene-dependent pathway regulating cell expansion. The phenotype of ran1-3 mutants is similar to loss-of-function ethylene receptor mutants, suggesting that RAN1 may be required to form functional ethylene receptors. Furthermore, these results suggest that copper is required not only for ethylene binding but also for the signaling function of the ethylene receptors.

NASA Discipline Plant Biology↗
NASA NTRS1992

Glucocorticoids promote development of the osteoblast phenotype by selectively modulating expression of cell growth and differentiation associated genes

To understand the mechanisms by which glucocorticoids promote differentiation of fetal rat calvaria derived osteoblasts to produce bone-like mineralized nodules in vitro, a panel of osteoblast growth and differentiation related genes that characterize development of the osteoblast phenotype has been quantitated in glucocorticoid-treated cultures. We compared the mRNA levels of osteoblast expressed genes in control cultures of subcultivated cells where nodule formation is diminished, to cells continuously (35 days) exposed to 10(-7) M dexamethasone, a synthetic glucocorticoid, which promotes nodule formation to levels usually the extent observed in primary cultures. Tritiated thymidine labelling revealed a selective inhibition of internodule cell proliferation and promotion of proliferation and differentiation of cells forming bone nodules. Fibronectin, osteopontin, and c-fos expression were increased in the nodule forming period. Alkaline phosphatase and type I collagen expression were initially inhibited in proliferating cells, then increased after nodule formation to support further growth and mineralization of the nodule. Expression of osteocalcin was 1,000-fold elevated in glucocorticoid-differentiated cultures in relation to nodule formation. Collagenase gene expression was also greater than controls (fivefold) with the highest levels observed in mature cultures (day 35). At this time, a rise in collagen and TGF beta was also observed suggesting turnover of the matrix. Short term (48 h) effects of glucocorticoid on histone H4 (reflecting cell proliferation), alkaline phosphatase, osteopontin, and osteocalcin mRNA levels reveal both up or down regulation as a function of the developmental stage of the osteoblast phenotype. A comparison of transcriptional levels of these genes by nuclear run-on assays to mRNA levels indicates that glucocorticoids exert both transcriptional and post-transcriptional effects. Further, the presence of glucocorticoids enhances the vitamin D3 effect on gene expression. Those genes which are upregulated by 1,25(OH)2D3 are transcribed at an increased rate by dexamethasone, while those genes which are inhibited by vitamin D3 remain inhibited in the presence of dexamethasone and D3. We propose that the glucocorticoids promote changes in gene expression involved in cell-cell and cell-extracellular matrix signaling mechanisms that support the growth and differentiation of cells capable of osteoblast phenotype development and bone tissue-like organization, while inhibiting the growth of cells that cannot progress to the mature osteoblast phenotype in fetal rat calvarial cultures.

NASA Discipline Musculoskeletal↗
DOE OSTI2024

Identifying microbial drivers in biological phenotypes with a Bayesian network regression model

Abstract In Bayesian Network Regression models, networks are considered the predictors of continuous responses. These models have been successfully used in brain research to identify regions in the brain that are associated with specific human traits, yet their potential to elucidate microbial drivers in biological phenotypes for microbiome research remains unknown. In particular, microbial networks are challenging due to their high dimension and high sparsity compared to brain networks. Furthermore, unlike in brain connectome research, in microbiome research, it is usually expected that the presence of microbes has an effect on the response (main effects), not just the interactions. Here, we develop the first thorough investigation of whether Bayesian Network Regression models are suitable for microbial datasets on a variety of synthetic and real data under diverse biological scenarios. We test whether the Bayesian Network Regression model that accounts only for interaction effects (edges in the network) is able to identify key drivers (microbes) in phenotypic variability. We show that this model is indeed able to identify influential nodes and edges in the microbial networks that drive changes in the phenotype for most biological settings, but we also identify scenarios where this method performs poorly which allows us to provide practical advice for domain scientists aiming to apply these tools to their datasets. BNR models provide a framework for microbiome researchers to identify connections between microbes and measured phenotypes. We allow the use of this statistical model by providing an easy‐to‐use implementation which is publicly available Julia package at https://github.com/solislemuslab/BayesianNetworkRegression.jl .

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Investigation of TRPV1 loss-of-function phenotypes in TRPV1 Leu206Stop mice generated by N-ethyl-N-nitrosourea mutagenesis

Highlights: • N-ethyl-N-nitrosourea mutagenesis can generate mouse models for pain research. • TRPV1 Leu206Stop mice closely resemble the phenotype of TRPV1 knockout mice. • Mechanical hypersensitivity is not impaired in TRPV1 Leu206Stop mice. N-ethyl-N-nitrosourea (ENU) random mutagenesis was used to generate a mouse model for the analysis of the transient receptor potential vanilloid 1 (TRPV1) cation channel. A transversion from T→A in exon 4 led to a Leu206Stop mutation generating a loss-of-function mutant. The TRPV1 agonist capsaicin was used to analyze functional and nociceptive parameters in vitro and in vivo in TRPV1 Leu206Stop mice and congenic C3HeB/FeJ controls. Capsaicin-induced [Ca{sup 2+}]{sub i} changes in small diameter DRG neurons were significantly diminished in TRPV1 Leu206Stop mice and administration of capsaicin induced neither hypothermia nor nocifensive behaviour in vivo. TRPV1 Leu206Stop mice were tested in the spinal nerve ligation of mononeuropathic pain and developed mechanical hypersensitivity two weeks after nerve injury. In the open field test, a significant increase in spontaneous locomotion was detected in TRPV1 Leu206Stop mice as compared to wildtype controls. TRPV1 knockout mice have been reported to carry a similar phenotype regarding capsaicin-evoked responses in vitro and in vivo. However, in contrast to TRPV1 Leu206Stop mice, TRPV1 knockout mice did not differ in spontaneous locomotion as compared to congenic C57BL/6 mice, suggesting subtle ENU-dependent or independent strain differences between TRPV1 Leu206Stop mice and their wildtype controls. In summary, these data revealed a target-related (i.e. capsaicin-evoked) phenotype of TRPV1 Leu206Stop mice closely resembling that of published TRPV1 knockout mice. However, since ENU-mutant mice are congenic with the mouse strain initially used in random mutagenesis, direct phenotypic comparison with the respective wildtype controls is possible, and the time-consuming backcrossing in lines with targeted mutations is avoided.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

High phenotypic and genotypic plasticity among strains of the mushroom-forming fungus Schizophyllum commune

Schizophyllum commune is a mushroom-forming fungus notable for its distinctive fruiting bodies with split gills. It is used as a model organism to study mushroom development, lignocellulose degradation and mating type loci. It is a hypervariable species with considerable genetic and phenotypic diversity between the strains. In this study, we systematically phenotyped 16 dikaryotic strains for aspects of mushroom development and 18 monokaryotic strains for lignocellulose degradation. There was considerable heterogeneity among the strains regarding these phenotypes. The majority of the strains developed mushrooms with varying morphologies, although some strains only grew vegetatively under the tested conditions. Growth on various carbon sources showed strain-specific profiles. The genomes of seven monokaryotic strains were sequenced and analyzed together with six previously published genome sequences. Moreover, the related species Schizophyllum fasciatum was sequenced. Although there was considerable genetic variation between the genome assemblies, the genes related to mushroom formation and lignocellulose degradation were well conserved. These sequenced genomes, in combination with the high phenotypic diversity, will provide a solid basis for functional genomics analyses of the strains of S. commune.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

High throughput phenotyping to accelerate crop breeding and monitoring of diseases in the field

Effective implementation of technology that facilitates accurate and high-throughput screening of thousands of field-grown lines is critical for accelerating crop improvement and breeding strategies for higher yield and disease tolerance. Progress in the development of field-based high throughput phenotyping methods has advanced considerably in the last 10 years through technological progress in sensor development and high-performance computing. In this paper, we review recent advances in high throughput field phenotyping technologies designed to inform the genetics of quantitative traits, including crop yield and disease tolerance. Successful application of phenotyping platforms to advance crop breeding and identify and monitor disease requires: (1) high resolution of imaging and environmental sensors; (2) quality data products that facilitate computer vision, machine learning and GIS; (3) capacity infrastructure for data management and analysis; and (4) automated environmental data collection. Finally, accelerated breeding for agriculturally relevant crop traits is key to the development of improved varieties and is critically dependent on high-resolution, high-throughput field-scale phenotyping technologies that can efficiently discriminate better performing lines within a larger population and across multiple environments.

09 BIOMASS FUELS↗
DOE OSTI2018

Pediatric glioblastoma cells inhibit neurogenesis and promote astrogenesis, phenotypic transformation and migration of human neural progenitor cells within cocultures

Highlights: • Interactions between human NPCs and human pediatric GBM-derived cells investigated using a coculture setup. • NPC morphology, phenotype, differentiation, neurite outgrowth, and migration patterns significantly influenced by GBMs. • Cumulative migration distance fit to Furth's formula derived formally from Ornstein-Uhlenbeck process. • Significant applications in NPC transplantation efforts to replace lesions of excised tumor sites. • Cocultures helped elucidate the underlying pathways involved in GBM-NPC interactions in a tumor microenvironment. Neural progenitor cell (NPC) fate is influenced by a variety of biological cues elicited from the surrounding microenvironment and recent studies suggest their possible role in pediatric glioblastoma multiforme (GBM) development. Since a few GBM cells also display NPC characteristics, it is not clear whether NPCs transform to tumor cell phenotype leading to the onset of GBM formation, or NPCs migrate to developing tumor sites in response to paracrine signaling from GBM cells. Elucidating the paracrine interactions between GBM cells and NPCs in vivo is challenging due to the inherent complexity of the CNS. Here, we investigated the interactions between human NPCs (ReNcell) and human pediatric GBM-derived cells (SJ-GBM2) using a Transwell{sup ®} coculture setup to assess the effects of GBM cells on ReNcells (cytokine and chemokine release, viability, phenotype, differentiation, migration). Standalone ReNcell or GBM cultures served as controls. Qualitative and quantitative results from ELISA{sup ®}, Live/Dead{sup ®} and BrdU assays, immunofluorescence labeling, western blot analysis, and scratch test suggests that although ReNcell viability remained unaffected in the presence of pediatric GBM cells, their morphology, phenotype, differentiation patterns, neurite outgrowth, migration patterns (average speed, distance, number of cells) and GSK-3β expression were significantly influenced. The cumulative distance migrated by the cells in each condition was fit to Furth's formula, derived formally from Ornstein-Uhlenbeck process. ReNcell differentiation into neural lineage was compromised and astrogenesis promoted within cocultures. Such coculture platform could be extended to identify the specific molecules contributing to the observed phenomena, to investigate whether NPCs could be transplanted to replace lesions of excised tumor sites, and to elucidate the underlying molecular pathways involved in GBM-NPC interactions within the tumor microenvironment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Detecting macroevolutionary genotype–phenotype associations using error-corrected rates of protein convergence

On macroevolutionary timescales, extensive mutations and phylogenetic uncertainty mask the signals of genotype–phenotype associations underlying convergent evolution. To overcome this problem, we extended the widely used framework of non-synonymous to synonymous substitution rate ratios and developed the novel metric ω C , which measures the error-corrected convergence rate of protein evolution. While ω C distinguishes natural selection from genetic noise and phylogenetic errors in simulation and real examples, its accuracy allows an exploratory genome-wide search of adaptive molecular convergence without phenotypic hypothesis or candidate genes. Using gene expression data, we explored over 20 million branch combinations in vertebrate genes and identified the joint convergence of expression patterns and protein sequences with amino acid substitutions in functionally important sites, providing hypotheses on undiscovered phenotypes. We further extended our method with a heuristic algorithm to detect highly repetitive convergence among computationally non-trivial higher-order phylogenetic combinations. Our approach allows bidirectional searches for genotype–phenotype associations, even in lineages that diverged for hundreds of millions of years.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Phenotypic responses to interspecies competition and commensalism in a naturally-derived microbial co-culture

The fundamental question of whether different microbial species will co-exist or compete in a given environment depends on context, composition and environmental constraints. Model microbial systems can yield some general principles related to this question. In this study we employed a naturally occurring co-culture composed of heterotrophic bacteria, Halomonas sp. HL-48 and Marinobacter sp. HL-58, to ask two fundamental scientific questions: 1) how do the phenotypes of two naturally co-existing species respond to partnership as compared to axenic growth? and 2) how do growth and molecular phenotypes of these species change with respect to competitive and commensal interactions? We hypothesized – and confirmed – that co-cultivation under glucose as the sole carbon source would result in a competitive interactions. Similarly, when glucose was swapped with xylose, the interactions became commensal because Marinobacter HL-58 was supported by metabolites derived from Halomonas HL-48. Each species responded to partnership by changing both its growth and molecular phenotype as assayed via batch growth kinetics and global transcriptomics. These phenotypic responses depended nutrient availability and so the environment ultimately controlled how they responded to each other. This simplified model community revealed that microbial interactions are context-specific and different environmental conditions dictate how interspecies partnerships will unfold.

59 BASIC BIOLOGICAL SCIENCES↗