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At least 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Structural characterization and computational analysis of PDZ domains in Monosiga brevicollis

Abstract Identification of the molecular networks that facilitated the evolution of multicellular animals from their unicellular ancestors is a fundamental problem in evolutionary cellular biology. Choanoflagellates are recognized as the closest extant nonmetazoan ancestors to animals. These unicellular eukaryotes can adopt a multicellular‐like “rosette” state. Therefore, they are compelling models for the study of early multicellularity. Comparative studies revealed that a number of putative human orthologs are present in choanoflagellate genomes, suggesting that a subset of these genes were necessary for the emergence of multicellularity. However, previous work is largely based on sequence alignments alone, which does not confirm structural nor functional similarity. Here, we focus on the PDZ domain, a peptide‐binding domain which plays critical roles in myriad cellular signaling networks and which underwent a gene family expansion in metazoan lineages. Using a customized sequence similarity search algorithm, we identified 178 PDZ domains in the Monosiga brevicollis proteome. This includes 11 previously unidentified sequences, which we analyzed using Rosetta and homology modeling. To assess conservation of protein structure, we solved high‐resolution crystal structures of representative M. brevicollis PDZ domains that are homologous to human Dlg1 PDZ2, Dlg1 PDZ3, GIPC, and SHANK1 PDZ domains. To assess functional conservation, we calculated binding affinities for mbGIPC, mbSHANK1, mbSNX27, and mbDLG‐3 PDZ domains from M. brevicollis . Overall, we find that peptide selectivity is generally conserved between these two disparate organisms, with one possible exception, mbDLG‐3. Overall, our results provide novel insight into signaling pathways in a choanoflagellate model of primitive multicellularity.

Gao, Melody↗
DOE OSTI2021

cGAS-like receptors sense RNA and control 3'2'-cGAMP signalling in Drosophila

Cyclic GMP–AMP synthase (cGAS) is a cytosolic DNA sensor that produces the second messenger cG[2'–5']pA[3'–5']p (2'3'-cGAMP) and controls activation of innate immunity in mammalian cells. Animal genomes typically encode multiple proteins with predicted homology to cGAS, but the function of these uncharacterized enzymes is unknown. Here we show that cGAS-like receptors (cGLRs) are innate immune sensors that are capable of recognizing divergent molecular patterns and catalysing synthesis of distinct nucleotide second messenger signals. Crystal structures of human and insect cGLRs reveal a nucleotidyltransferase signalling core shared with cGAS and a diversified primary ligand-binding surface modified with notable insertions and deletions. We demonstrate that surface remodelling of cGLRs enables altered ligand specificity and used a forward biochemical screen to identify cGLR1 as a double-stranded RNA sensor in the model organism Drosophila melanogaster. We show that RNA recognition activates Drosophila cGLR1 to synthesize the novel product cG[3'–5']pA[2'–5']p (3'2'-cGAMP). A crystal structure of Drosophila stimulator of interferon genes (dSTING) in complex with 3'2'-cGAMP explains selective isomer recognition, and 3'2'-cGAMP induces an enhanced antiviral state in vivo that protects from viral infection. Similar to radiation of Toll-like receptors in pathogen immunity, our results establish cGLRs as a diverse family of metazoan pattern recognition receptors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

High-throughput mapping of the phage resistance landscape in E. coli

Bacteriophages (phages) are critical players in the dynamics and function of microbial communities and drive processes as diverse as global biogeochemical cycles and human health. Phages tend to be predators finely tuned to attack specific hosts, even down to the strain level, which in turn defend themselves using an array of mechanisms. However, to date, efforts to rapidly and comprehensively identify bacterial host factors important in phage infection and resistance have yet to be fully realized. Here, we globally map the host genetic determinants involved in resistance to 14 phylogenetically diverse double-stranded DNA phages using two model Escherichia coli strains (K-12 and BL21) with known sequence divergence to demonstrate strain-specific differences. Using genome-wide loss-of-function and gain-of-function genetic technologies, we are able to confirm previously described phage receptors as well as uncover a number of previously unknown host factors that confer resistance to one or more of these phages. We uncover differences in resistance factors that strongly align with the susceptibility of K-12 and BL21 to specific phage. We also identify both phage specific mechanisms, such as the unexpected role of cyclic-di-GMP in host sensitivity to phage N4, and more generic defenses, such as the overproduction of colanic acid capsular polysaccharide that defends against a wide array of phages. Our results indicate that host responses to phages can occur via diverse cellular mechanisms. Our systematic and high-throughput genetic workflow to characterize phage-host interaction determinants can be extended to diverse bacteria to generate datasets that allow predictive models of how phage-mediated selection will shape bacterial phenotype and evolution. The results of this study and future efforts to map the phage resistance landscape will lead to new insights into the coevolution of hosts and their phage, which can ultimately be used to design better phage therapeutic treatments and tools for precision microbiome engineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Dead but Not Forgotten: How Extracellular DNA, Moisture, and Space Modulate the Horizontal Transfer of Extracellular Antibiotic Resistance Genes in Soil

Antibiotic-resistant bacteria and the spread of antibiotic resistance genes (ARGs) pose a serious risk to human and veterinary health. While many studies focus on the movement of live antibiotic-resistant bacteria to the environment, it is unclear whether extracellular ARGs (eARGs) from dead cells can transfer to live bacteria to facilitate the evolution of antibiotic resistance in nature. Here, we use eARGs from dead, antibiotic-resistant Pseudomonas stutzeri cells to track the movement of eARGs to live P. stutzeri cells via natural transformation, a mechanism of horizontal gene transfer involving the genomic integration of eARGs. In sterile, antibiotic-free agricultural soil, we manipulated the eARG concentration, soil moisture, and proximity to eARGs. We found that transformation occurred in soils inoculated with just 0.25 μg of eDNA g –1 soil, indicating that even low concentrations of soil eDNA can facilitate transformation (previous estimates suggested ~2 to 40 μg eDNA g –1 soil). When eDNA was increased to 5 μg g –1 soil, there was a 5-fold increase in the number of antibiotic-resistant P. stutzeri cells. We found that eARGs were transformed under soil moistures typical of terrestrial systems (5 to 30% gravimetric water content) but inhibited at very high soil moistures (>30%). Altogether, this work demonstrates that dead bacteria and their eARGs are an overlooked path to antibiotic resistance. More generally, the spread of eARGs in antibiotic-free soil suggests that transformation allows genetic variants to establish in the absence of antibiotic selection and that the soil environment plays a critical role in regulating transformation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Molecular basis of hemoglobin binding and heme removal in Corynebacterium diphtheriae

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

NMR↗
DOE OSTI2022

Characterization of a 2016-2017 Human Seasonal H3 Influenza A Virus Spillover Now Endemic to U.S. Swine

In 2017, the Iowa State University Veterinary Diagnostic Laboratory detected a reverse-zoonotic transmission of a human seasonal H3 influenza A virus into swine (IAV-S) in Oklahoma. Pairwise comparison between the recently characterized human seasonal H3 IAV-S (H3.2010.2) hemagglutinin (HA) sequences detected in swine and the most similar 2016–2017 human seasonal H3 revealed 99.9% nucleotide identity. To elucidate the origin of H3.2010.2 IAV-S, 45 HA and 27 neuraminidase (NA) sequences from 2017 to 2020 as well as 11 whole-genome sequences (WGS) were genetically characterized. Time to most recent common human ancestor was estimated between August and September 2016. The N2 NA was of human origin in all but one strain from diagnostic submissions with NA sequences, and the internal gene segments from WGS consisted of matrix genes originating from the 2009 pandemic H1N1 and another 5 internal genes of triple reassortant swine origin (TTTTPT). Pigs experimentally infected with H3.2010.2 demonstrated efficient nasal shedding and replication in the lungs, mild pneumonia, and minimal microscopic lung lesions and transmitted the virus to indirect contact swine. Antigenically, H3.2010.2 viruses were closer to a human seasonal vaccine strain, A/Hong Kong/4801/2014, than to the H3.2010.1 human seasonal H3 viruses detected in swine in 2012. This was the second sustained transmission of a human seasonal IAV into swine from the 2010 decade after H3.2010.1. Monitoring the spillover and detection of novel IAV from humans to swine may help vaccine antigen selection and could impact pandemic preparedness.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Integration of genome-scale metabolic model with biorefinery process model reveals market-competitive carbon-negative sustainable aviation fuel utilizing microbial cell mass lipids and biogenic CO 2

Producing scalable, economically viable, low-carbon biofuels or biochemicals hinges on more efficient bioconversion processes. While microbial conversion can offer robust solutions, the native microbial growth process often redirects a large fraction of carbon to CO 2 and cell mass. By integrating genome-scale metabolic models with techno-economic and life cycle assessment models, this study analyzes the effects of converting cell mass lipids to hydrocarbon fuels, and CO 2 to methanol on the facility’s costs and life-cycle carbon footprint. Results show that upgrading microbial lipids or both microbial lipids and CO 2 using renewable hydrogen produces carbon-negative bisabolene. Additionally, on-site electrolytic hydrogen production offers a supply of pure oxygen to use in place of air for bioconversion and fuel combustion in the boiler. To reach cost parity with conventional jet fuel, renewable hydrogen needs to be produced at less than $\$2.2$ to $\$3.1$/kg, with a bisabolene yield of 80% of the theoretical yield, along with cell mass and CO 2 yields of 22 wt% and 54 wt%, respectively. The economic combination of cell mass, CO 2 , and bisabolene yields demonstrated in this study provides practical insights for prioritizing research, selecting suitable hosts, and determining necessary engineered production levels.

09 BIOMASS FUELS↗
NASA NTRS2006

Computer Modeling of Protocellular Functions: Peptide Insertion in Membranes

Lipid vesicles became the precursors to protocells by acquiring the capabilities needed to survive and reproduce. These include transport of ions, nutrients and waste products across cell walls and capture of energy and its conversion into a chemically usable form. In modem organisms these functions are carried out by membrane-bound proteins (about 30% of the genome codes for this kind of proteins). A number of properties of alpha-helical peptides suggest that their associations are excellent candidates for protobiological precursors of proteins. In particular, some simple a-helical peptides can aggregate spontaneously and form functional channels. This process can be described conceptually by a three-step thermodynamic cycle: 1 - folding of helices at the water-membrane interface, 2 - helix insertion into the lipid bilayer and 3 - specific interactions of these helices that result in functional tertiary structures. Although a crucial step, helix insertion has not been adequately studied because of the insolubility and aggregation of hydrophobic peptides. In this work, we use computer simulation methods (Molecular Dynamics) to characterize the energetics of helix insertion and we discuss its importance in an evolutionary context. Specifically, helices could self-assemble only if their interactions were sufficiently strong to compensate the unfavorable Free Energy of insertion of individual helices into membranes, providing a selection mechanism for protobiological evolution.

Rodriquez-Gomez, D.↗
NASA NTRS2023

Molecular Identification of Microbial Contaminants

Microorganisms can have significant impacts on the success of NASA’s missions, including the integrity of materials, the reliability of scientific results, and maintenance of crew health. Robust cleaning and sterilization protocols are currently in place in NASA facilities, but agency experts agree that microbial contamination is unavoidable and its impact on NASA’s missions and science must be minimized. Therefore, it is critical to understand: 1) what specific microorganisms are present, 2) how they may impact scientific objectives, and 3) how to select appropriate mitigation strategies. The Marshall Space Flight Center (MSFC) Planetary Protection (PP) microbiology lab historically relied solely upon enumeration of culturable microbial contamination associated with spacecraft materials or cleanrooms. However, this process is time consuming, many microbes cannot be cultured, and very few can be identified with any fidelity using NASA standard microbiological methods. The work described in this white paper includes the establishment of molecular identification capabilities at MSFC, including DNA isolation, amplification, purification, and Sanger sequencing. This capability will not only improve planetary protection efforts at MSFC (i.e. by identifying contaminating microorganisms in cleanrooms or on spacecraft) but also offers a service center-wide for the identification of contaminants that arise in other projects, processing locations, or during set up and roll out of spacecraft. This work also lays the foundation for higher throughput efforts to identify large populations of microbes across the lifetime of a project and serves as the starting point for future work into whole genome sequencing, non-culture based methods, or additional characterization studies. Ultimately, accurate identification informs appropriate mitigation strategies, increasing the chances of success for NASA’s missions and objectives.

C. D. Cassilly↗
DOE OSTI2021

Ontology-Enriched Specifications Enabling Findable, Accessible, Interoperable, and Reusable Marine Metagenomic Datasets in Cyberinfrastructure Systems

Marine microbial ecology requires the systematic comparison of biogeochemical and sequence data to analyze environmental influences on the distribution and variability of microbial communities. With ever-increasing quantities of metagenomic data, there is a growing need to make datasets Findable, Accessible, Interoperable, and Reusable (FAIR) across diverse ecosystems. FAIR data is essential to developing analytical frameworks that integrate microbiological, genomic, ecological, oceanographic, and computational methods. Although community standards defining the minimal metadata required to accompany sequence data exist, they haven’t been consistently used across projects, precluding interoperability. Moreover, these data are not machine-actionable or discoverable by cyberinfrastructure systems. By making ‘omic and physicochemical datasets FAIR to machine systems, we can enable sequence data discovery and reuse based on machine-readable descriptions of environments or physicochemical gradients. In this work, we developed a novel technical specification for dataset encapsulation for the FAIR reuse of marine metagenomic and physicochemical datasets within cyberinfrastructure systems. This includes using Frictionless Data Packages enriched with terminology from environmental and life-science ontologies to annotate measured variables, their units, and the measurement devices used. This approach was implemented in Planet Microbe, a cyberinfrastructure platform and marine metagenomic web-portal. Here, we discuss the data properties built into the specification to make global ocean datasets FAIR within the Planet Microbe portal. We additionally discuss the selection of, and contributions to marine-science ontologies used within the specification. Finally, we use the system to discover data by which to answer various biological questions about environments, physicochemical gradients, and microbial communities in meta-analyses. This work represents a future direction in marine metagenomic research by proposing a specification for FAIR dataset encapsulation that, if adopted within cyberinfrastructure systems, would automate the discovery, exchange, and re-use of data needed to answer broader reaching questions than originally intended.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

classLog: Logistic regression for the classification of genetic sequences

Introduction Sequencing and phylogenetic classification have become a common task in human and animal diagnostic laboratories. It is routine to sequence pathogens to identify genetic variations of diagnostic significance and to use these data in realtime genomic contact tracing and surveillance. Under this paradigm, unprecedented volumes of data are generated that require rapid analysis to provide meaningful inference. Methods We present a machine learning logistic regression pipeline that can assign classifications to genetic sequence data. The pipeline implements an intuitive and customizable approach to developing a trained prediction model that runs in linear time complexity, generating accurate output rapidly, even with incomplete data. Our approach was benchmarked against porcine respiratory and reproductive syndrome virus (PRRSv) and swine H1 influenza A virus (IAV) datasets. Trained classifiers were tested against sequences and simulated datasets that artificially degraded sequence quality at 0, 10, 20, 30, and 40%. Results When applied to a poor-quality sequence data, the classifier achieved between >85% to 95% accuracy for the PRRSv and the swine H1 IAV HA dataset and this increased to near perfect accuracy when using the full dataset. The model also identifies amino acid positions used to determine genetic clade identity through a feature selection ranking within the model. These positions can be mapped onto a maximum-likelihood phylogenetic tree, allowing for the inference of clade defining mutations. Discussion Our approach is implemented as a python package with code available at https://github.com/flu-crew/classLog .

Zeller, Michael A.↗
DOE OSTI2021

Accelerating Biological Insight for Understudied Genes

Synopsis The rapid expansion of genome sequence data is increasing the discovery of protein-coding genes across all domains of life. Annotating these genes with reliable functional information is necessary to understand evolution, to define the full biochemical space accessed by nature, and to identify target genes for biotechnology improvements. The majority of proteins are annotated based on sequence conservation with no specific biological, biochemical, genetic, or cellular function identified. Recent technical advances throughout the biological sciences enable experimental research on these understudied protein-coding genes in a broader collection of species. However, scientists have incentives and biases to continue focusing on well documented genes within their preferred model organism. This perspective suggests a research model that seeks to break historic silos of research bias by enabling interdisciplinary teams to accelerate biological functional annotation. We propose an initiative to develop coordinated projects of collaborating evolutionary biologists, cell biologists, geneticists, and biochemists that will focus on subsets of target genes in multiple model organisms. Concurrent analysis in multiple organisms takes advantage of evolutionary divergence and selection, which causes individual species to be better suited as experimental models for specific genes. Most importantly, multisystem approaches would encourage transdisciplinary critical thinking and hypothesis testing that is inherently slow in current biological research.

Zoology↗
NASA NTRS2017

The Transcriptional Response of Diverse Saccharomyces Cerevisiae Strains to Simulated Microgravity

Spaceflight imposes multiple stresses on biological systems resulting in genome-scale adaptations. Understanding these adaptations and their underlying molecular mechanisms is important to clarifying and reducing the risks associated with spaceflight. One such risk is infection by microbes present in spacecraft and their associated systems and inhabitants. This risk is compounded by results suggesting that some microbes may exhibit increased virulence after exposure to spaceflight conditions. The yeast, S. cerevisiae, is a powerful microbial model system, and its response to spaceflight has been studied for decades. However, to date, these studies have utilized common lab strains. Yet studies on trait variation in S. cerevisiae demonstrate that these lab strains are not representative of wild yeast and instead respond to environmental stimuli in an atypical manner. Thus, it is not clear how transferable these results are to the wild S. cerevisiae strains likely to be encountered during spaceflight. To determine if diverse S. cerevisiae strains exhibit a conserved response to simulated microgravity, we will utilize a collection of 100 S. cerevisiae strains isolated from clinical, environmental and industrial settings. We will place selected S. cerevisiae strains in simulated microgravity using a high-aspect rotating vessel (HARV) and document their transcriptional response by RNA-sequencing and quantify similarities and differences between strains. Our research will have a strong impact on the understanding of how genetic diversity of microorganisms effects their response to spaceflight, and will serve as a platform for further studies.

yeast↗
NASA NTRS2017

The Transcriptional Response of Diverse Saccharomyces Cerevisiae Strains to Simulated Microgravity

Spaceflight imposes multiple stresses on biological systems resulting in genome-scale adaptations. Understanding these adaptations and their underlying molecular mechanisms is important to clarifying and reducing the risks associated with spaceflight. One such risk is infection by microbes present in spacecraft and their associated systems and inhabitants. This risk is compounded by results suggesting that some microbes may exhibit increased virulence after exposure to spaceflight conditions. The yeast, S. cerevisiae, is a powerful microbial model system, and it's response to spaceflight has been studied for decades. However, to date, these studies have utilized common lab strains. Yet studies on trait variation in S. cerevisiae demonstrate that these lab strains are not representative of wild yeast and instead respond to environmental stimuli in an atypical manner. Thus, it is not clear how transferable these results are to the wild S. cerevisiae strains likely to be encountered during spaceflight. To determine if diverse S. cerevisiae strains exhibit a conserved response to simulated microgravity, we will utilize a collection of 100 S. cerevisiae strains isolated from clinical, environmental and industrial settings. We will place selected S. cerevisiae strains in simulated microgravity using a high-aspect rotating vessel (HARV) and document their transcriptional response by RNA-sequencing and quantify similarities and differences between strains. Our research will have a strong impact on the understanding of how genetic diversity of microorganisms effects their response to spaceflight, and will serve as a platform for further studies.

genetic diversity↗
DOE OSTI2025

Unraveling the influence of microbial necromass on subsurface microbiomes: metabolite utilization and community dynamics

The role of microbial necromass (nonliving microbial biomass), a significant component of belowground organic carbon, in nutrient cycling and its impact on the dynamics of microbial communities in subsurface systems remains poorly understood. It is currently unclear whether necromass metabolites from various microbes are different, whether certain groups of metabolites are preferentially utilized over others, or whether different microbial species respond to various necromass metabolites. In this study, we aimed to fill these knowledge gaps by designing enrichments with necromass as the sole nutrient source for subsurface microbial communities. We used the soluble fraction of necromass from bacterial isolates belonging to Arthrobacter, Agrobacterium, and Pseudomonas genera, and our results indicate that metabolite composition of necromass varied slightly across different strains but generally included amino acids, organic acids, and nucleic acid constituents. Arthrobacter-derived necromass appeared more recalcitrant. Necromass metabolites enriched diverse microbial genera, particularly Massilia sp. responded quickly regardless of the necromass source. Despite differences in necromass utilization, microbial community composition converged rapidly over time across the three different necromass amendments. Uracil, xanthine, valine, and phosphate-containing isomers were generally depleted over time, indicating microbial assimilation for maintenance and growth. However, numerous easily assimilable metabolites were not significantly depleted, suggesting efficient necromass recycling and the potential for necromass stabilization in systems. This study highlights the dynamic interactions between microbial necromass metabolites and subsurface microbial communities, revealing both selective utilization and rapid community and necromass convergence regardless of the necromass source.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Concurrent colonization of rodent kidneys with multiple species and serogroups of pathogenic Leptospira

ABSTRACT Rodents are important reservoir hosts of pathogenic leptospires in the US Virgin Islands. Our previous work determined that trapped rodents were colonized withLeptospira borgpeterseniiserogroup Ballum (n= 48) and/orLeptospira kirschneriserogroup Icterohaemorrhagiae (n= 3). In addition, nine rodents appeared to be colonized with a mixed population comprising more than one species/serogroup. The aim of this study was to validate this finding by characterizing clonal isolates derived from cultures of mixed species. Cultures of presumptive mixed species (designated LR1, LR5, LR37, LR57, LR60, LR61, LR68, LR70, and LR72) were propagated in different media including Hornsby-Alt-Nally (HAN) media, incubated at both 29℃ and 37℃, and T80/40/LH incubated at 29℃. Polyclonal reference antisera specific for serogroup Ballum and Icterohaemorrhagiae were used to enrich for different serogroups followed by subculture on agar plates. Individual colonies were then selected for genotyping and serotyping. Of the nine cultures of mixed species/serogroups, a single clonal isolate was separated in five of them:L. borgpeterseniiserogroup Ballum in LR1, LR5, and LR37, andL. kirschneriserogroup Icterohaemorrhagiae in LR60 and LR72. In four of the cultures with mixed species (LR57, LR61, LR68, and LR70), clonal isolates of bothL. borgpeterseniiserogroup Ballum andL. kirschneriserogroup Icterohaemorrhagiae were recovered. Our results definitively establish that rodents can be colonized with more than one species/serogroup ofLeptospiraconcurrently. The identification and characterization of multiple species/serogroups ofLeptospirafrom individual reservoir hosts of infection are essential to understand the epidemiology and transmission of disease to both human and domestic animal populations. IMPORTANCE PathogenicLeptospira, the causative agent of human and animal leptospirosis, comprise a diverse genus of species/serogroups which are inherently difficult to isolate from mammalian hosts due to fastidious growth requirements. Molecular evidence has indicated that reservoir hosts ofLeptospiramay shed multiple species concurrently. However, evidence of this phenomena by culture has been lacking. Culture is definitive and is essential for comprehensive characterization of recovered isolates by high-resolution genome sequencing and serotyping. In this work, a protocol using recently developed novel media formulations, in conjunction with reference antisera, was developed and validated to demonstrate the recovery of multiple species/serogroups of pathogenicLeptospirafrom the same host. The identification and characterization of multiple species/serogroups ofLeptospirafrom individual reservoir hosts of infection are essential to understand the epidemiology and transmission of disease to both human and domestic animal populations.

Biotechnology & Applied Microbiology↗
NASA NTRS2018

The Transcriptional Response of Diverse Saccharomyces cerevisiae Strains to Simulated Microgravity

Spaceflight imposes multiple stresses on biological systems resulting in genome-scale adaptations. Understanding these adaptations and their underlying molecular mechanisms is important to clarifying and reducing the risks associated with spaceflight. One such risk is infection by microbes present in spacecraft and their associated systems and inhabitants. This risk is compounded by results suggesting that some microbes may exhibit increased virulence after exposure to spaceflight conditions. The yeast, S. cerevisiae, is a powerful microbial model system, and it's response to spaceflight has been studied for decades. However, to date, these studies have utilized common lab strains. Yet studies on trait variation in S. cerevisiae demonstrate that these lab strains are not representative of wild yeast and instead respond to environmental stimuli in an a typical manner. Thus, it is not clear how transferable these results are to the wild S. cerevisiae strains likely to be encountered during spaceflight. To determine if diverse S. cerevisiae strains exhibit a conserved response to simulated microgravity, we will utilize a collection of 100 S. cerevisiae strains isolated from clinical, environmental and industrial settings. We will place selected S. cerevisiae strains in simulated microgravity using a high-aspect rotating vessel (HARV) and document their transcriptional response by RNA-sequencing and quantify similarities and differences between strains. Our research will have a strong impact on the understanding of how genetic diversity of microorganisms effects their response to spaceflight, and will serve as a platform for further studies.

spaceflight↗
DOE OSTI2022

Linkage map construction using limited parental genotypic information

Abstract Genetic linkage maps based on single nucleotide polymorphisms (SNPs) represent an essential tool for a variety of genomic analyses. Today, next-generation sequencing (NGS) enables rapid genotyping of different mapping populations based on thousands of SNPs and the construction of highly saturated linkage maps. Nevertheless, missing data in the genotyping of the parental lines creates a bottleneck that determines the number of SNPs that can be used for the linkage map. As a proof of concept, a highly saturated genetic linkage map was constructed using the imputed genotypic data of a recombinant inbred line (RIL) population and the limited genotypic information of its parental lines. Two ABH genotype files were created from a pseudo-parental genotypic data set that includes all the SNPs present in the RIL population. In the first ABH file pseudo-parental 1 was considered parental A, while in the second pseudo-parental 1 was considered parental B. These two duplicate ABH genotype files were merged by chromosome and subjected to linkage map analysis. Since the ABH data were duplicated, two mirrored linkage groups were generated per chromosome. The correct linkage map was identified and selected based on the partial genotypic data of the parental lines. This strategy was effective for constructing a highly saturated linkage map of 33,421 SNPs based on the genotyping of 205 RILs and a limited number of 100 SNPs present in the parental lines. This strategy enables the use of all the NGS SNP data obtained from a low-coverage sequencing experiment in the mapping population.

59 BASIC BIOLOGICAL SCIENCES↗