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At least 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Tonoplast Sucrose Transporter SUT4-Dependent Sugar Partitioning Modulates Phenological Transitions and Reproductive Success in Poplar

Climate uncertainty is intensifying the need for greater plasticity in carbohydrate reserve utilization to support winter survival and spring growth in woody perennials. In poplar, the single-copy SUT4, which encodes a tonoplast-localized sucrose transporter, and the SUT5/SUT6 genome duplicates, which encode plasma membrane-localized transporters, are expressed year-round, with SUT4 showing the highest expression during cool seasons. Given its role in vacuolar sucrose efflux and winter-predominant expression, SUT4 may play a key role in modulating seasonal carbohydrate dynamics. While SUT4-knockdown and knockout effects have been studied under greenhouse conditions, their impact under field conditions remains unexplored. Here, we report a field-based study comparing CRISPR knockout mutants of winter-expressed SUT4 and SUT5/SUT6 in Populus tremula x alba. We show that sut4, but not sut5/6, mutants exhibited earlier autumn leaf senescence, delayed spring bud flush, reduced stem growth, and altered sugar partitioning in winter xylem and bark relative to controls. After 2 years in the field, all genotypes flowered before leaf flush in early spring; however, sut4 mutants produced sterile ovules despite developing normal-looking catkins. Metabolic profiling revealed disrupted sucrose and raffinose dynamics in elongating sut4 catkins. This was accompanied by transcriptomic signatures of elevated stress and downregulation of proanthocyanidin biosynthesis and circadian clock genes. These findings highlight the critical role of SUT4 in coordinating sugar allocation, stress responses, and seasonal development in poplar.

09 BIOMASS FUELS↗
DOE OSTI2026

Convergent evolution of aerobic fermentation through divergent mechanisms acting on the same key glycolytic genes

Expression profiling by high throughput sequencing The model yeast Saccharomyces cerevisiae has evolved aerobic fermentation in part through a whole genome duplication and subsequent retention of glycolytic genes. To identify independent yeast lineages with a high glycolytic rate phenotype we developed an assay measuring extracellular acidification rates (ECAR) to evaluate the glycolytic rates across diverse yeast species. This assay identified a novel group of yeasts in the genus Saturnispora with rapid glycolytic rates. Through comparative approaches, we found that several glycolytic genes encoding hexokinases and enzymes in lower glycolysis had higher expression and modifications in promoter sequences in rapid ECAR species. Intriguingly, many of the upregulated genes are the same genes that are duplicated in S. cerevisiae. When the transcription factor required for their activation was deleted, the mutants had a slow glycolytic rate and more respiratory phenotype. This work shows how the aerobic fermentation phenotype has convergently evolved in Saturnispora through transcriptional rewiring. This divergent mechanism nevertheless impacts the same glycolytic genes, which suggests that there are evolutionary constraints on how aerobic fermentation can arise.

Horianopoulos, Linda C. [Department of Food Scienc↗
DOE OSTI2025

Characterizing and controlling CRISPR repair outcomes in nondividing human cells

Genome editing is poised to revolutionize treatment of genetic diseases, but poor understanding and control of DNA repair outcomes hinders its therapeutic potential. DNA repair is especially understudied in nondividing cells like neurons, limiting the efficiency and precision of genome editing in many clinically relevant tissues. Here, we address this barrier by using induced pluripotent stem cells (iPSCs) and iPSC-derived neurons to examine how postmitotic human neurons repair Cas9-induced DNA damage. CRISPR editing outcomes differ dramatically in neurons compared to genetically identical dividing cells: neurons take longer to fully resolve this damage, and upregulate non-canonical DNA repair factors in the process. Manipulating this response with chemical or genetic perturbations allows us to direct DNA repair toward desired editing outcomes in nondividing human neurons, cardiomyocytes, and primary T cells. By studying DNA repair in clinically relevant cells, we reveal unforeseen challenges and opportunities for precise therapeutic editing.

Ramadoss, Gokul N. [Gladstone Institutes, San Fran↗
NASA NTRS1999

Radiation-Induced Cytogenetic Damage as a Predictor of Cancer Risk for Protons and Fe Ions

We have successfully completed the series of experiments planned for year 1 and the first part of year 2 measuring the induction of chromosome aberrations induced in multiple cell types by three model space radiations: Fe-ions, protons and photons. Most of these data have now been compiled and a significant part subjected to detailed data analyses, although continuing data analysis is an important part of our current and future efforts. These analyses are directed toward defining the patterns of chromosomal damage induction by the three radiations and the extent to which such patterns are dependent on the type of cell irradiated. Our studies show significant differences, both quantitatively and qualitatively, between response of different cell types to these radiations however there is an overall pattern that characterizes each type of radiation in most cell lines. Thus our data identifies general dose-response patterns for each radiation for induction of multiple types of chromosomal aberrations but also identifies significant differences in response between some cell types. Specifically, we observe significant resistance for induction of aberrations in rat mammary epithelial cells when they are irradiated in vivo and assayed in vitro. Further, we have observed some remarkable differences in susceptibility to certain radiation-induced aberrations in cells whose genome has been modulated for two cancer- relevant genes, TP53 and CDKNIA. This data, if confirmed, may represent the first evidence of gene-specific differences in cellular metabolism of damage induced by densely-ionizing radiation that confers substantial sensitivity to protons compared to photons.

Williams, Jerry R.↗
DOE OSTI2024

Engineering Novosphingobium aromaticivorans to produce cis,cis -muconic acid from biomass aromatics

ABSTRACT The platform chemical cis,cis- muconic acid ( cc MA) provides facile access to a number of monomers used in the synthesis of commercial plastics. It is also a metabolic intermediate in the β-ketoadipic acid pathway of many bacteria and, therefore, a current target for microbial production from abundant renewable resources via metabolic engineering. This study investigates Novosphingobium aromaticivorans DSM12444 as a chassis for the production of cc MA from biomass aromatics. The N. aromaticivorans genome predicts that it encodes a previously uncharacterized protocatechuic acid (PCA) decarboxylase and a catechol 1,2-dioxygenase, which would be necessary for the conversion of aromatic metabolic intermediates to cc MA. This study confirmed the activity of these two enzymes in vitro and compared their activity to ones that have been previously characterized and used in cc MA production. From these results, we generated one strain that is completely derived from native genes and a second that contains genes previously used in microbial engineering synthesis of this compound. Both of these strains exhibited stoichiometric production of cc MA from PCA and produced greater than 100% yield of cc MA from the aromatic monomers that were identified in liquor derived from alkaline pretreated biomass. Our results show that a strain completely derived from native genes and one containing homologs from other hosts are both capable of stoichiometric production of cc MA from biomass aromatics. Overall, this work combines previously unknown aspects of aromatic metabolism in N. aromaticivorans and the genetic tractability of this organism to generate strains that produce cc MA from deconstructed biomass. IMPORTANCE The production of commodity chemicals from renewable resources is an important goal toward increasing the environmental and economic sustainability of industrial processes. The aromatics in plant biomass are an underutilized and abundant renewable resource for the production of valuable chemicals. However, due to the chemical composition of plant biomass, many deconstruction methods generate a heterogeneous mixture of aromatics, thus making it difficult to extract valuable chemicals using current methods. Therefore, recent efforts have focused on harnessing the pathways of microorganisms to convert a diverse set of aromatics into a single product. Novosphingobium aromaticivorans DSM12444 has the native ability to metabolize a wide range of aromatics and, thus, is a potential chassis for conversion of these abundant compounds to commodity chemicals. This study reports on new features of N. aromaticivorans that can be used to produce the commodity chemical cis,cis -muconic acid from renewable and abundant biomass aromatics.

09 BIOMASS FUELS↗
DOE OSTI2021

Dissecting the metabolic reprogramming of maize root under nitrogen-deficient stress conditions

The growth and development of maize (Zea mays L.) largely depends on its nutrient uptake through the root. Hence, studying its growth, response, and associated metabolic reprogramming to stress conditions is becoming an important research direction. A genome-scale metabolic model (GSM) for the maize root was developed to study its metabolic reprogramming under nitrogen stress conditions. The model was reconstructed based on the available information from KEGG, UniProt, and MaizeCyc. Transcriptomics data derived from the roots of hydroponically grown maize plants were used to incorporate regulatory constraints in the model and simulate nitrogen-non-limiting (N+) and nitrogen-deficient (N-) condition. Model-predicted flux-sum variability analysis achieved 70% accuracy compared with the experimental change of metabolite levels. In addition to predicting important metabolic reprogramming in central carbon, fatty acid, amino acid, and other secondary metabolism, maize root GSM predicted several metabolites (l-methionine, l-asparagine, l-lysine, cholesterol, and l-pipecolate) playing a regulatory role in the root biomass growth. Furthermore, this study revealed eight phosphatidylcholine and phosphatidylglycerol metabolites which, even though not coupled with biomass production, played a key role in the increased biomass production under N-deficient conditions. Overall, the omics-integrated GSM provides a promising tool to facilitate stress condition analysis for maize root and engineer better stress-tolerant maize genotypes.

Plant Sciences↗
NASA NTRS2001

Induction and repair of HZE induced cytogenetic damage

Wistar rats were exposed to high-mass, high energy (HZE) 56Fe particles (1000 GeV/AMU) using the Alternating Gradient Synchrotron (AGS). The animals were sacrificed at 1-5 hours or after a 30-day recovery period. The frequency of micronuclei in the tracheal and the deep lung epithelial cells were evaluated. The relative effectiveness of 56Fe, for the induction of initial chromosome damage in the form of micronuclei, was compared to damage produced in the same biological system exposed to other types of high and low-LET radiation. It was demonstrated that for animals sacrificed at short times after exposure, the tracheal and lung epithelial cells, the 56Fe particles were 3.3 and 1.3 times as effective as 60Co in production of micronuclei, respectively. The effectiveness was also compared to that for exposure to inhaled radon. With this comparison, the 56Fe exposure of the tracheal epithelial cells and the lung epithelial cells were only 0.18 and 0.20 times as effective as radon in the production of the initial cytogenetic damage. It was suggested that the low relative effectiveness was related to potential for 'wasted energy' from the core of the 56Fe particles. When the animals were sacrificed after 30 days, the slopes of the dose-response relationships, which reflect the remaining level of damage, decreased by a factor of 10 for both the tracheal and lung epithelial cells. In both cases, the slope of the dose-response lines were no longer significantly different from zero, and the r2 values were very high. Lung epithelial cells, isolated from the animals sacrificed hours after exposure, were maintained in culture, and the micronuclei frequency evaluated after 4 and 6 subcultures. These cells were harvested at 24 and 36 days after the exposure. There was no dose-response detected in these cultures and no signs of genomic instability at either sample time.

Non-NASA Center↗
DOE OSTI2020

Morphological Characters Can Strongly Influence Early Animal Relationships Inferred from Phylogenomic Data Sets

There are considerable phylogenetic incongruencies between morphological and phylogenomic data for the deep evolution of animals. This has contributed to a heated debate over the earliest-branching lineage of the animal kingdom: the sister to all other Metazoa (SOM). Here, we use published phylogenomic data sets ($\sim $45,000–400,000 characters in size with $\sim $15–100 taxa) that focus on early metazoan phylogeny to evaluate the impact of incorporating morphological data sets ($\sim $15–275 characters). We additionally use small exemplar data sets to quantify how increased taxon sampling can help stabilize phylogenetic inferences. We apply a plethora of common methods, that is, likelihood models and their “equivalent” under parsimony: character weighting schemes. Our results are at odds with the typical view of phylogenomics, that is, that genomic-scale data sets will swamp out inferences from morphological data. Instead, weighting morphological data 2–10$\times $ in both likelihood and parsimony can in some cases “flip” which phylum is inferred to be the SOM. This typically results in the molecular hypothesis of Ctenophora as the SOM flipping to Porifera (or occasionally Placozoa). However, greater taxon sampling improves phylogenetic stability, with some of the larger molecular data sets ($>$200,000 characters and up to $\sim $100 taxa) showing node stability even with $\geqq100\times $ upweighting of morphological data. Accordingly, our analyses have three strong messages. 1) The assumption that genomic data will automatically “swamp out” morphological data is not always true for the SOM question. Morphological data have a strong influence in our analyses of combined data sets, even when outnumbered thousands of times by molecular data. Morphology therefore should not be counted out a priori. 2) We here quantify for the first time how the stability of the SOM node improves for several genomic data sets when the taxon sampling is increased. 3) The patterns of “flipping points” (i.e., the weighting of morphological data it takes to change the inferred SOM) carry information about the phylogenetic stability of matrices. The weighting space is an innovative way to assess comparability of data sets that could be developed into a new sensitivity analysis tool.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRSDate not supplied

A Nonlinear Viscoelastic-Viscoplastic Constitutive Model for Epoxy Polymers

The objective of this paper is to develop a nonlinear viscoelastic–viscoplastic constitutive model for epoxy polymers. The classic nonlinear viscoelasticity model is reformulated to yield a closed-form incremental constitutive relation, which relates the stress increments to the viscoelastic strain increments. A viscoplasticity model, which consists of the Drucker–Prager yield function, nonlinear isotropic and kinematic hardening laws, and the Perzyna viscosity function, is subsequently developed. The nonlinear viscoelasticity and the vis-coplasticity models are then implemented in a radial return algorithm. A closed-form algorithmic tangent operator is derived to facilitate model implementation. The nonlinear viscoelasticity model is validated by reproducing the test data for polymethyl methacrylate(PMMA). The present constitutive model’s capabilities are demonstrated through modeling viscoelastic–viscoplastic PMMA loaded at different strain rates. The mechanics of structure genome-based micromechanics approach, embedded with the present constitutive model, is used to homogenize a unidirectional fiber-reinforced composite with a PMMA matrix, subjected to uniaxial and shear loading at different strain rates. The viscoelastic characterization of PMT-F7 epoxy is evaluated by comparing the predicted creep–recovery responses by the present constitutive model with the experimental ones.

Liang Zhang↗
NASA NTRS1995

Repair of x-ray-induced DNA double-strand breaks in specific Not I restriction fragments in human fibroblasts: joining of correct and incorrect ends

An assay that allows measurement of absolute induction frequencies for DNA double-strand breaks (dsbs) in defined regions of the genome and that quantitates rejoining of correct DNA ends has been used to study repair of dsbs in normal human fibroblasts after x-irradiation. The approach involves hybridization of single-copy DNA probes to Not I restriction fragments separated according to size by pulsed-field gel electrophoresis. Induction of dsbs is quantitated from the decrease in the intensity of the hybridizing restriction fragment and an accumulation of a smear below the band. Rejoining of dsbs results in reconstitution of the intact restriction fragment only if correct DNA ends are joined. By comparing results from this technique with results from a conventional electrophoresis assay that detects all rejoining events, it is possible to quantitate the misrejoining frequency. Three Not I fragments on the long arm of chromosome 21 were investigated with regard to dsb induction, yielding an identical induction rate of 5.8 X 10(-3) break per megabase pair per Gy. Correct dsb rejoining was measured for two of these Not I fragments after initial doses of 80 and 160 Gy. The misrejoining frequency was about 25% for both fragments and was independent of dose. This result appears to be representative for the whole genome as shown by analysis of the entire Not I fragment distribution. The correct rejoining events primarily occurred within the first 2 h, while the misrejoining kinetics included a much slower component, with about half of the events occurring between 2 and 24 h. These misrejoining kinetics are similar to those previously reported for production of exchange aberrations in interphase chromosomes.

NASA Discipline Radiation Health↗
DOE OSTI2025

Data imbalance in drug response prediction: multi-objective optimization approach in deep learning setting

Abstract Drug response prediction (DRP) methods tackle the complex task of associating the effectiveness of small molecules with the specific genetic makeup of the patient. Anti-cancer DRP is a particularly challenging task requiring costly experiments as underlying pathogenic mechanisms are broad and associated with multiple genomic pathways. The scientific community has exerted significant efforts to generate public drug screening datasets, giving a path to various machine learning models that attempt to reason over complex data space of small compounds and biological characteristics of tumors. However, the data depth is still lacking compared to application domains like computer vision or natural language processing domains, limiting current learning capabilities. To combat this issue and improves the generalizability of the DRP models, we are exploring strategies that explicitly address the imbalance in the DRP datasets. We reframe the problem as a multi-objective optimization across multiple drugs to maximize deep learning model performance. We implement this approach by constructing Multi-Objective Optimization Regularized by Loss Entropy loss function and plugging it into a Deep Learning model. We demonstrate the utility of proposed drug discovery methods and make suggestions for further potential application of the work to achieve desirable outcomes in the healthcare field.

Biochemistry & Molecular Biology↗
DOE OSTI2022

HT-SIP: a semi-automated stable isotope probing pipeline identifies cross-kingdom interactions in the hyphosphere of arbuscular mycorrhizal fungi

Abstract Background Linking the identity of wild microbes with their ecophysiological traits and environmental functions is a key ambition for microbial ecologists. Of many techniques that strive for this goal, Stable-isotope probing—SIP—remains among the most comprehensive for studying whole microbial communities in situ. In DNA-SIP, actively growing microorganisms that take up an isotopically heavy substrate build heavier DNA, which can be partitioned by density into multiple fractions and sequenced. However, SIP is relatively low throughput and requires significant hands-on labor. We designed and tested a semi-automated, high-throughput SIP (HT-SIP) pipeline to support well-replicated, temporally resolved amplicon and metagenomics experiments. We applied this pipeline to a soil microhabitat with significant ecological importance—the hyphosphere zone surrounding arbuscular mycorrhizal fungal (AMF) hyphae. AMF form symbiotic relationships with most plant species and play key roles in terrestrial nutrient and carbon cycling. Results Our HT-SIP pipeline for fractionation, cleanup, and nucleic acid quantification of density gradients requires one-sixth of the hands-on labor compared to manual SIP and allows 16 samples to be processed simultaneously. Automated density fractionation increased the reproducibility of SIP gradients compared to manual fractionation, and we show adding a non-ionic detergent to the gradient buffer improved SIP DNA recovery. We applied HT-SIP to 13 C-AMF hyphosphere DNA from a 13 CO 2 plant labeling study and created metagenome-assembled genomes (MAGs) using high-resolution SIP metagenomics (14 metagenomes per gradient). SIP confirmed the AMF Rhizophagus intraradices and associated MAGs were highly enriched (10–33 atom% 13 C), even though the soils’ overall enrichment was low (1.8 atom% 13 C). We assembled 212 13 C-hyphosphere MAGs; the hyphosphere taxa that assimilated the most AMF-derived 13 C were from the phyla Myxococcota, Fibrobacterota, Verrucomicrobiota, and the ammonia-oxidizing archaeon genus Nitrososphaera . Conclusions Our semi-automated HT-SIP approach decreases operator time and improves reproducibility by targeting the most labor-intensive steps of SIP—fraction collection and cleanup. We illustrate this approach in a unique and understudied soil microhabitat—generating MAGs of actively growing microbes living in the AMF hyphosphere (without plant roots). The MAGs’ phylogenetic composition and gene content suggest predation, decomposition, and ammonia oxidation may be key processes in hyphosphere nutrient cycling.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1998

PCR cloning and characterization of multiple ADP-glucose pyrophosphorylase cDNAs from tomato

Four ADP-glucose pyrophosphorylase (AGP) cDNAs were cloned from tomato fruit and leaves by the PCR techniques. Three of them (agp S1, agp S2, and agp S3) encode the large subunit of AGP, the fourth one (agp B) encodes the small subunit. The deduced amino acid sequences of the cDNAs show very high identities (96-98%) to the corresponding potato AGP isoforms, although there are major differences in tissue expression profiles. All four tomato AGP transcripts were detected in fruit and leaves; the predominant ones in fruit are agp B and agp S1, whereas in leaves they are agp B and agp S3. Genomic southern analysis suggests that the four AGP transcripts are encoded by distinct genes.

Non-NASA Center↗
DOE OSTI2023

Transcriptome architecture of the three main lineages of agrobacteria

ABSTRACT Agrobacteria are a diverse, polyphyletic group of prokaryotes with multipartite genomes capable of transferring DNA into the genomes of host plants, making them an essential tool in plant biotechnology. Despite their utility in plant transformation, genome-wide transcriptional regulation is not well understood across the three main lineages of agrobacteria. Transcription start sites (TSSs) are a necessary component of gene expression and regulation. In this study, we used differential RNA-seq and a TSS identification algorithm optimized on manually annotated TSS, then validated with existing TSS to identify thousands of TSS with nucleotide resolution for representatives of each lineage. We extend upon the 356 TSSs previously reported in Agrobacterium fabrum C58 by identifying 1,916 TSSs. In addition, we completed genomes and phenotyping of Rhizobium rhizogenes C16/80 and Allorhizobium vitis T60/94, identifying 2,650 and 2,432 TSSs, respectively. Parameter optimization was crucial for an accurate, high-resolution view of genome and transcriptional dynamics, highlighting the importance of algorithm optimization in genome-wide TSS identification and genomics at large. The optimized algorithm reduced the number of TSSs identified internal and antisense to the coding sequence on average by 90.5% and 91.9%, respectively. Comparison of TSS conservation between orthologs of the three lineages revealed differences in cell cycle regulation of ctrA as well as divergence of transcriptional regulation of chemotaxis-related genes when grown in conditions that simulate the plant environment. These results provide a framework to elucidate the mechanistic basis and evolution of pathology across the three main lineages of agrobacteria. IMPORTANCE Transcription start sites (TSSs) are fundamental for understanding gene expression and regulation. Agrobacteria, a group of prokaryotes with the ability to transfer DNA into the genomes of host plants, are widely used in plant biotechnology. However, the genome-wide transcriptional regulation of agrobacteria is not well understood, especially in less-studied lineages. Differential RNA-seq and an optimized algorithm enabled identification of thousands of TSSs with nucleotide resolution for representatives of each lineage. The results of this study provide a framework for elucidating the mechanistic basis and evolution of pathology across the three main lineages of agrobacteria. The optimized algorithm also highlights the importance of parameter optimization in genome-wide TSS identification and genomics at large.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Identification and overexpression of endogenous transcription factors to enhance lipid accumulation in the biotechnologically relevant species Chlamydomonas pacifica

Sustainable low-carbon energy solutions are critical to mitigating global carbon emissions. Algae-based platforms offer potential by converting carbon dioxide into valuable products while aiding carbon sequestration. However, scaling algae cultivation faces challenges like contamination in outdoor systems. Previously, our lab evolved Chlamydomonas pacifica, an extremophile green alga, which tolerates high temperature, pH, salinity, and light, making it ideal for large-scale bioproduct production, including biodiesel. Here, we enhanced lipid accumulation in evolved C. pacifica by identifying and overexpressing key endogenous transcription factors through genome-wide in-silico analysis and in-vivo testing. These factors include Lipid Remodeling Regulator 1 (CpaLRL1), Nitrogen Response Regulator 1 (CpaNRR1), Compromised Hydrolysis of Triacylglycerols 7 (CpaCHT7), and Phosphorus Starvation Response 1 (CpaPSR1). Under nitrogen deprivation, CpaLRL1, CpaNRR1, and CpaCHT7 overexpression enhanced lipid accumulation compared to wild-type. However, CpaPSR1 increased lipid accumulation compared to wild-type in normal media and did not increase further under nitrogen deprivation, highlighting the difference in function based on media conditions. Notably, lipid analysis of CpaPSR1 under normal media conditions revealed a 2.4-fold increase in triglycerides (TAGs) compared to the wild-type, highlighting its potential for biodiesel production. This approach provides a framework for transcription factor-focused metabolic engineering in algae, advancing bioenergy and biomaterial production.

Biofuels↗
DOE OSTI2025

DNA viruses from different stages of a wastewater treatment plant in southwest Ohio

Wastewater treatment plants (WWTPs) house diverse populations of microbial communities that are dynamic across treatment stages. Although viruses, especially non-pathogenic ones are relatively less studied compared to their bacterial counterparts, they are equally important players in WWTP microbiomes. In this study, we sampled influent, activated sludge, and effluent stages of a WWTP in southwest Ohio to sequence their viral population using multiple displacement amplification (MDA) and metagenomic approaches. We recovered 1003 viral genomes, the majority of which were ssDNA (single-stranded DNA) viruses that formed distinct clusters representing novel species and phylogenetic groups not closely related to known human gut or terrestrial viruses. Additionally, tracking viruses across treatment stages showed several persisted across multiple treatment stages. These results suggest that further studies are needed to understand the persistence of viral populations, particularly non-pathogenic ones, across different stages of WWTPs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Widespread bacterial diversity within the bacteriome of fungi

Abstract Knowledge of associations between fungal hosts and their bacterial associates has steadily grown in recent years as the number and diversity of examinations have increased, but current knowledge is predominantly limited to a small number of fungal taxa and bacterial partners. Here, we screened for potential bacterial associates in over 700 phylogenetically diverse fungal isolates, representing 366 genera, or a tenfold increase compared with previously examined fungal genera, including isolates from several previously unexplored phyla. Both a 16 S rDNA-based exploration of fungal isolates from four distinct culture collections spanning North America, South America and Europe, and a bioinformatic screen for bacterial-specific sequences within fungal genome sequencing projects, revealed that a surprisingly diverse array of bacterial associates are frequently found in otherwise axenic fungal cultures. We demonstrate that bacterial associations with diverse fungal hosts appear to be the rule, rather than the exception, and deserve increased consideration in microbiome studies and in examinations of microbial interactions.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRSDate not supplied

Benchmarking Computational Tools for Calling SNPs and Indels in Complex Microbial Populations

The NASA BioNutrients missions seek to understand the suitability of microorganisms for bioproduction during space flight. One topic of interest is the stability of microbial genomes during long-term ambient storage and subsequent rehydration and growth. To address these questions, samples from 8 species were flown to ISS for 5 years of desiccated storage at ambient temperature (Stasis Packs) and 2 species were packaged along with powdered media inside a bioreactor system to allow hydration and growth in microgravity (Production Packs). For both systems, Whole Genome Sequencing (WGS) of the DNA extracted from the returned samples and paired ground controls will be conducted to identify changes in genome stability due to time, storage conditions and growth in space. Across the technical replicates, ground controls, 10 timepoints, and multiple experimental conditions, ~300 samples have been selected for initial analysis with WGS sequencing to 100x coverage. A flexible and resource efficient mutation calling pipeline is needed to process this large dataset and allow for comparisons between species. Many bioinformatics tools for calling Indels and Single Nucleotide Variants (SNVs) are designed for use with pure isolates, where true variations from the reference genome are expected to dominate the reads aligning to the location of mutation. In contrast, DNA from the Stasis Pack (SP) samples was collected directly after recovery from desiccated storage and the Production Pack (PP) samples were collected after fermentation. In this context, reads with mutations are expected to be less frequent than reads that align with the reference genome, as each sample will include multiple lines of cells. Thus, BioNutrients samples are expected to be similar to samples from cancer cell or “pooled” sequencing approaches. In preparation for the analysis of the BioNutrients samples, we have tested three mutation calling tools (GATK for Microbes, BreSeq and DiscoSNP) designed for complex samples. A challenge of validating mutation identification pipelines is a lack of “Ground Truth” datasets, especially for complex samples. To compare these three tools, we sought to identify mutations in pre-existing WGS data collected from populations of Chlamydomonas reinhardtii that were exposed to UV mutagenesis and growth in LEO as part of the Space Algae-1 mission. Here we present a summary of these tools against the analysis originally conducted using the CRISP tool. Critical metrics are compared such as runtime, the number of SNPs, the number and size of Indels, and patterns of transversion and transitions identified by each tool are reported. By sharing these benchmarking results collected in support of the BioNutrients mission, we aim to guide others seeking to identify SNVs in similarly complex microbial samples.

Biology↗