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At least 1,099 records · Page 61

Developing Open-Source Training Materials for AI/ML and Space Biological Sciences Using NASA Cloud-Based Data

Artificial Intelligence (AI) and Machine Learning (ML) has gained significant traction in the biological and biomedical research fields in the last two decades, in part thanks to an increasing culture of open data sharing and reuse. Due to its capability for identifying complex relationships and patterns, AI/ML methodology is particularly well suited to recognize and predict biological patterns from high-dimensional next-generation sequencing data (e.g. whole genome sequencing, transcriptomic sequencing), as well as from biological or medical imaging data (e.g. microscopy, computed tomography, ultrasound, magnetic resonance imaging, radiography). These methodologies hold particular promise for space biosciences research and automated space health monitoring systems. However, there are many key considerations for properly training, validating, and testing a machine learning model in biological research or clinical application. Even with the positive culture of Open Science and data sharing, inexperienced researchers working quickly without proper checks can produce models that perform poorly outside of the immediate training dataset. Lessons learned from biological AI/ML research indicate that Open Science principles such as data sharing and open-source code must go hand-in-hand with publicly available, high-quality training curricula in best practices, with modules centered on real-life scientific use cases and data so future AI/ML practitioners gain experience on real problems. Here we present the development of open-source training materials for AI/ML and space biosciences, as part of the NASA Transform to Open Science Training (TOPST) initiative. We develop 4 independent training programs, focused on the following topics: 1) Fundamentals of Machine Learning and Space Biosciences Domain, 2) Open Science, Artificial Intelligence, and Ethical Best Practices for Data Sharing and Analysis, 3) Using AI/ML Classification to Identify Gene Networks Affected By Space Exposure in Mouse Liver, and 4) Using Neural Networks to Find DNA Damage Patterns in Immune Cells after Radiation. All programs leverage cloud-based NASA biological datasets. The curriculum we present will enable worldwide access to training in AI/ML and scientific analysis.

James Andrew Casaletto↗

Saccharomyces cerevisiae gene expression changes during rotating wall vessel suspension culture

This study utilizes Saccharomyces cerevisiae to study genetic responses to suspension culture. The suspension culture system used in this study is the high-aspect-ratio vessel, one type of the rotating wall vessel, that provides a high rate of gas exchange necessary for rapidly dividing cells. Cells were grown in the high-aspect-ratio vessel, and DNA microarray and metabolic analyses were used to determine the resulting changes in yeast gene expression. A significant number of genes were found to be up- or downregulated by at least twofold as a result of rotational growth. By using Gibbs promoter alignment, clusters of genes were examined for promoter elements mediating these genetic changes. Candidate binding motifs similar to the Rap1p binding site and the stress-responsive element were identified in the promoter regions of differentially regulated genes. This study shows that, as in higher order organisms, S. cerevisiae changes gene expression in response to rotational culture and also provides clues for investigations into the signaling pathways involved in gravitational response.

Non-NASA Center↗

Microarray analysis identifies Salmonella genes belonging to the low-shear modeled microgravity regulon

The low-shear environment of optimized rotation suspension culture allows both eukaryotic and prokaryotic cells to assume physiologically relevant phenotypes that have led to significant advances in fundamental investigations of medical and biological importance. This culture environment has also been used to model microgravity for ground-based studies regarding the impact of space flight on eukaryotic and prokaryotic physiology. We have previously demonstrated that low-shear modeled microgravity (LSMMG) under optimized rotation suspension culture is a novel environmental signal that regulates the virulence, stress resistance, and protein expression levels of Salmonella enterica serovar Typhimurium. However, the mechanisms used by the cells of any species, including Salmonella, to sense and respond to LSMMG and identities of the genes involved are unknown. In this study, we used DNA microarrays to elucidate the global transcriptional response of Salmonella to LSMMG. When compared with identical growth conditions under normal gravity (1 x g), LSMMG differentially regulated the expression of 163 genes distributed throughout the chromosome, representing functionally diverse groups including transcriptional regulators, virulence factors, lipopolysaccharide biosynthetic enzymes, iron-utilization enzymes, and proteins of unknown function. Many of the LSMMG-regulated genes were organized in clusters or operons. The microarray results were further validated by RT-PCR and phenotypic analyses, and they indicate that the ferric uptake regulator is involved in the LSMMG response. The results provide important insight about the Salmonella LSMMG response and could provide clues for the functioning of known Salmonella virulence systems or the identification of uncharacterized bacterial virulence strategies.

Non-NASA Center↗

Alteration of gene expression profiles in skeletal muscle of rats exposed to microgravity during a spaceflight

To clarify the mechanism of skeletal muscle wasting during spaceflights, we investigated whether intramuscular gene expression profiles are affected, by using DNA microarray methods. Male rats sent on the 17-day NASA STS-90 Neurolab spaceflight were sacrificed 24 hours after return to earth (MG group). Ground control rats were maintained for 17 days in flight-simulated cages (CS group). Spaceflight induced a 19% and 23% loss of tibialis anterior and gastrocnemius muscle mass, respectively, as compared to ground controls. Muscle RNA was analyzed by the Clontech Atlas DNA expression array in four rats, with two MG/ CS pairs for the tibialis anterior, and one pair for the gastrocnemius. Alterations in gene expression were verified for selected genes by reverse-transcription PCR. In both muscles of MG rats, mRNAs for 12 genes were up-regulated by over 2-fold, and 38 were down-regulated compared to controls. There was inhibition of genes for cell proliferation and growth factor cascades, including cell cycle genes and signal transduction proteins, such as p21 Cip1, retinoblastoma (Rb), cyclins G1/S, -E and -D3, MAP kinase 3, MAD3, and ras related protein RAB2. These data indicate that following exposure to microgravity, there is downregulation of genes involved in regulation of muscle satellite cell replication.

NASA Program Fundamental Space Biology↗

Essential amino acids in the Plant-Conserved and Class-Specific Regions of cellulose synthases

The Plant-Conserved Region (P-CR) and the Class-Specific Region (CSR) are two plant-unique sequences in the catalytic core of cellulose synthases (CESAs) for which specific functions have not been established. Here, we used site-directed mutagenesis to replace amino acids and motifs within these sequences predicted to be essential for assembly and function of CESAs. We developed an in vivo method to determine the ability of mutated CesA1 transgenes to complement an Arabidopsis (Arabidopsis thaliana) temperature-sensitive root-swelling1 (rsw1) mutant. Replacement of a Cys residue in the CSR, which blocks dimerization in vitro, rendered the AtCesA1 transgene unable to complement the rsw1 mutation. Examination of the CSR sequences from 33 diverse angiosperm species showed domains of high-sequence conservation in a class-specific manner but with variation in the degrees of disorder, indicating a nonredundant role of the CSR structures in different CESA isoform classes. The Cys residue essential for dimerization was not always located in domains of intrinsic disorder. Expression of AtCesA1 transgene constructs, in which Pro417 and Arg453 were substituted for Ala or Lys in the coiled-coil of the P-CR, were also unable to complement the rsw1 mutation. Despite an expected role for Arg457 in trimerization of CESA proteins, AtCesA1 transgenes with Arg457Ala mutations were able to fully restore the wild-type phenotype in rsw1. Our data support that Cys662 within the CSR and Pro417 and Arg453 within the P-CR of Arabidopsis CESA1 are essential residues for functional synthase complex formation, but our data do not support a specific role for Arg457 in trimerization in native CESA complexes.

59 BASIC BIOLOGICAL SCIENCES↗

Genelab: Scientific Partnerships and an Open-Access Database to Maximize Usage of Omics Data from Space Biology Experiments

NASA's mission includes expanding our understanding of biological systems to improve life on Earth and to enable long-duration human exploration of space. The GeneLab Data System (GLDS) is NASA's premier open-access omics data platform for biological experiments. GLDS houses standards-compliant, high-throughput sequencing and other omics data from spaceflight-relevant experiments. The GeneLab project at NASA-Ames Research Center is developing the database, and also partnering with spaceflight projects through sharing or augmentation of experiment samples to expand omics analyses on precious spaceflight samples. The partnerships ensure that the maximum amount of data is garnered from spaceflight experiments and made publically available as rapidly as possible via the GLDS. GLDS Version 1.0, went online in April 2015. Software updates and new data releases occur at least quarterly. As of October 2016, the GLDS contains 80 datasets and has search and download capabilities. Version 2.0 is slated for release in September of 2017 and will have expanded, integrated search capabilities leveraging other public omics databases (NCBI GEO, PRIDE, MG-RAST). Future versions in this multi-phase project will provide a collaborative platform for omics data analysis. Data from experiments that explore the biological effects of the spaceflight environment on a wide variety of model organisms are housed in the GLDS including data from rodents, invertebrates, plants and microbes. Human datasets are currently limited to those with anonymized data (e.g., from cultured cell lines). GeneLab ensures prompt release and open access to high-throughput genomics, transcriptomics, proteomics, and metabolomics data from spaceflight and ground-based simulations of microgravity, radiation or other space environment factors. The data are meticulously curated to assure that accurate experimental and sample processing metadata are included with each data set. GLDS download volumes indicate strong interest of the scientific community in these data. To date GeneLab has partnered with multiple experiments including two plant (Arabidopsis thaliana) experiments, two mice experiments, and several microbe experiments. GeneLab optimized protocols in the rodent partnerships for maximum yield of RNA, DNA and protein from tissues harvested and preserved during the SpaceX-4 mission, as well as from tissues from mice that were frozen intact during spaceflight and later dissected on the ground. Analysis of GeneLab data will contribute fundamental knowledge of how the space environment affects biological systems, and as well as yield terrestrial benefits resulting from mitigation strategies to prevent effects observed during exposure to space environments.

bioinformatics↗

GeneLab: Scientific Partnerships and an Open-Access Database to Maximize Usage of Omics Data from Space Biology Experiments

NASA's mission includes expanding our understanding of biological systems to improve life on Earth and to enable long-duration human exploration of space. The GeneLab Data System (GLDS) is NASAs premier open-access omics data platform for biological experiments. GLDS houses standards-compliant, high-throughput sequencing and other omics data from spaceflight-relevant experiments. The GeneLab project at NASA-Ames Research Center is developing the database, and also partnering with spaceflight projects through sharing or augmentation of experiment samples to expand omics analyses on precious spaceflight samples. The partnerships ensure that the maximum amount of data is garnered from spaceflight experiments and made publically available as rapidly as possible via the GLDS. GLDS Version 1.0, went online in April 2015. Software updates and new data releases occur at least quarterly. As of October 2016, the GLDS contains 80 datasets and has search and download capabilities. Version 2.0 is slated for release in September of 2017 and will have expanded, integrated search capabilities leveraging other public omics databases (NCBI GEO, PRIDE, MG-RAST). Future versions in this multi-phase project will provide a collaborative platform for omics data analysis. Data from experiments that explore the biological effects of the spaceflight environment on a wide variety of model organisms are housed in the GLDS including data from rodents, invertebrates, plants and microbes. Human datasets are currently limited to those with anonymized data (e.g., from cultured cell lines). GeneLab ensures prompt release and open access to high-throughput genomics, transcriptomics, proteomics, and metabolomics data from spaceflight and ground-based simulations of microgravity, radiation or other space environment factors. The data are meticulously curated to assure that accurate experimental and sample processing metadata are included with each data set. GLDS download volumes indicate strong interest of the scientific community in these data. To date GeneLab has partnered with multiple experiments including two plant (Arabidopsis thaliana) experiments, two mice experiments, and several microbe experiments. GeneLab optimized protocols in the rodent partnerships for maximum yield of RNA, DNA and protein from tissues harvested and preserved during the SpaceX-4 mission, as well as from tissues from mice that were frozen intact during spaceflight and later dissected on the ground. Analysis of GeneLab data will contribute fundamental knowledge of how the space environment affects biological systems, and as well as yield terrestrial benefits resulting from mitigation strategies to prevent effects observed during exposure to space environments.

spaceflight↗

Evidence for a role in growth and salt resistance of a plasma membrane H+-ATPase in the root endodermis

The plasma membrane of plant cells is energized by an electrochemical gradient produced by P-type H+-ATPases (proton pumps). These pumps are encoded by at least 12 genes in Arabidopsis. Here we provide evidence that isoform AHA4 contributes to solute transport through the root endodermis. AHA4 is expressed most strongly in the root endodermis and flowers, as suggested by promoter-GUS reporter assays. A disruption of this pump (aha4-1) was identified as a T-DNA insertion in the middle of the gene (after VFP(574)). Truncated aha4-1 transcripts accumulate to approximately 50% of the level observed for AHA4 mRNA in wild-type plants. Plants homozygous for aha4-1 (-/-) show a subtle reduction in root and shoot growth compared with wild-type plants when grown under normal conditions. However, a mutant phenotype is very clear in plants grown under salt stress (e.g., 75 or 110 mM NaCl). In leaves of mutant plants subjected to Na stress, the ratio of Na to K increased 4-5-fold. Interestingly, the aha4-1 mutation appears to be semidominant and was only partially complemented by the introduction of additional wild-type copies of AHA4. These results are consistent with the hypothesis that aha4-1 may produce a dominant negative protein or RNA that partially disrupts the activity of other pumps or functions in the root endodermal tissue, thereby compromising the function of this cell layer in controlling ion homeostasis and nutrient transport.

NASA Discipline Plant Biology↗

Bone morphogenic protein 4 produced in endothelial cells by oscillatory shear stress stimulates an inflammatory response

Atherosclerosis is now viewed as an inflammatory disease occurring preferentially in arterial regions exposed to disturbed flow conditions, including oscillatory shear stress (OS), in branched arteries. In contrast, the arterial regions exposed to laminar shear (LS) are relatively lesion-free. The mechanisms underlying the opposite effects of OS and LS on the inflammatory and atherogenic processes are not clearly understood. Here, through DNA microarrays, protein expression, and functional studies, we identify bone morphogenic protein 4 (BMP4) as a mechanosensitive and pro-inflammatory gene product. Exposing endothelial cells to OS increased BMP4 protein expression, whereas LS decreased it. In addition, we found BMP4 expression only in the selective patches of endothelial cells overlying foam cell lesions in human coronary arteries. The same endothelial patches also expressed higher levels of intercellular cell adhesion molecule-1 (ICAM-1) protein compared with those of non-diseased areas. Functionally, we show that OS and BMP4 induced ICAM-1 expression and monocyte adhesion by a NFkappaB-dependent mechanism. We suggest that BMP4 is a mechanosensitive, inflammatory factor playing a critical role in early steps of atherogenesis in the lesion-prone areas.

NASA Program Fundamental Space Biology↗

Drosophila atonal fully rescues the phenotype of Math1 null mice: new functions evolve in new cellular contexts

Many genes share sequence similarity between species, but their properties often change significantly during evolution. For example, the Drosophila genes engrailed and orthodenticle and the onychophoran gene Ultrabithorax only partially substitute for their mouse or Drosophila homologs. We have been analyzing the relationship between atonal (ato) in the fruit fly and its mouse homolog, Math1. In flies, ato acts as a proneural gene that governs the development of chordotonal organs (CHOs), which serve as stretch receptors in the body wall and joints and as auditory organs in the antennae. In the fly CNS, ato is important not for specification but for axonal arborization. Math1, in contrast, is required for the specification of cells in both the CNS and the PNS. Furthermore, Math1 serves a role in the development of secretory lineage cells in the gut, a function that does not parallel any known to be served by ato. We wondered whether ato and Math1 might be more functionally homologous than they appear, so we expressed Math1 in ato mutant flies and ato in Math1 null mice. To our surprise, the two proteins are functionally interchangeable.

Non-NASA Center↗

Hyporheic zone, river, and groundwater metagenome resolved genomes and rpS3 genes in East River Watershed, Colorado USA Summer 2020, 2021

Here we present metagenome assembled genomes (MAGs) for the bacterial and archaeal communities from water filter collected across 8 locations along the East River Watershed, CO, and 1 nearby groundwater well. The purpose was to look for connectivity and similarities across the network and to see the impact of the groundwater. As a part of Lawrence Berkeley National Laboratory (LBNL) Watershed Science Focus Area (SFA), we assessed community composition and strain similarities between the sites and we also compared it to previous metagenomic studies within the watershed looking at floodplain (Matheus Carnevali et al. 2021) and hillslope (Lavy et al. 2019) microbiomes. Here we present metagenome assembled genomes (MAGs) for the bacterial and archaeal communities from filters across 8 locations during August 2020 and July 2021. This resulted in 32 samples. The groundwater sample was sequenced at UC Berkley's QB3. The other 31 samples were sequenced at University of Maryland. Metagenomes were assembled using four autobinners and the best bins were selected using dasTool. The genomes were dereplicated at 95% with dRep and the subset of winning genomes were manually curated based on visual inspection of taxonomic profile, GC content, coverage, and a set of 51 bacterial single copy genes (BSCG), and 38 archaeal signal copy genes (ASCG). The dataset includes a zip file of 311 genomes (HZ_River_SW_MAGS_Dereplicated_95.zip). The dataset additionally includes a zipped file of ribosomal protein small subunit 3 (rpS3) proteins from the hyporheic zone and river data (rpS3_Proteins_HZ_River.zip), a metadata file used to register associated samples with IGSNs (International Generic Sample Numbers) (samples.csv), a location metadata file (locations.csv). This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

DNA↗

Integration of ultra-low coverage whole-genome sequences for reconstructing the evolutionary history of Galapagos giant tortoises

Genomic data from contemporary and historical samples often need to be coupled for evolutionary reconstructions of multitaxon complexes. However, the genetic data recovered from historical samples may result only in ultra-low coverage whole-genome sequences (ulcWGS; <0.15× depth), leading to inaccurate evolutionary inferences given a preponderance of missing data. Using the Galapagos giant tortoise radiation as a study system (Chelonoidis spp., composed of 13 extant and four extinct lineages), we assembled a novel methodological pipeline that removes potential noise introduced by the missing data and enhances the evolutionary signal from ulcWGS samples. We leveraged existing tools for phylogenomic placement (EPA-ng), population genomic structure (smartsnp) and admixture (Admixfrog, NGSadmix) to demonstrate that the evolutionary history of samples can be uncovered with sequencing depths as low as 0.008–0.139×. Importantly, these approaches do not use genotype imputation of the ulcWGS samples, which would require extensive reference datasets. Our application to two cases of extinct lineages of Galapagos giant tortoises, with and without references from the same lineage, demonstrates the general value of the approach. We confirm where the extinct lineages from San Cristóbal and Santa Fe islands fit into the Galapagos giant tortoise radiation, and that these lineages were evolutionarily distinct entities.

ancient DNA↗

Montane Conifer, Aspen, Meadow, and Sagebrush Metagenome Resolved Genomes and Traits in East River Watershed, Colorado, USA

Climate change is driving vegetation shifts in mountain watersheds, with unknown impacts on biogeochemical cycles. We hypothesize that these shifts will reshape soil microbiomes and associated biogeochemical processes. As a part of Lawrence Berkeley National Laboratory (LBNL) Watershed Science Focus Area (SFA), we assessed microbiome and microbial functional trait differences between soils under conifer, aspen, forby meadows, and sagebrush across the East River Watershed, CO, controlling for elevation and aspect.Here we present metagenome assembled genomes (MAGs) for the bacterial and archaeal communities from soils 0-20cm in depth across three locations in the watershed—Headwaters, Upper Reaches, and Lower Reaches from August 3-11th 2016. Each location was further subdivided into two blocks, with one block on a west facing aspect, and two on the east aspect of the valley. Within blocks, two samples per vegetation type were taken (one at each depth). This resulted in 66 samples, which were sequenced at JGI and can be found under the Joint Genome Institute (JGI) Genomes Online Database (GOLD) sequencing project Gs0118068. Metagenomes were assembled through an inhouse pipeline (see methods), binned using four autobinners (concoct, maxbin2, metabat2, and vamb) and consolidated using dastool. The consolidated bins from all metagenomes were pooled, filtered by completeness (>75%) and contamination (<25%), and dereplicated at 95% ANI using drep. The dataset includes a zip file of 687 genomes (Vegtype_MAGS.zip), the accession numbers for the underlying metagenomes, a csv file with MAG quality metrics and taxonomy from Genome Taxonomy Database (GTDB) and National Center for Biotechnology Information (NCBI) taxonomic representative genome proteins (EastRiver_Vegtype_drep_genome_info.csv), and a file containing MAG quality metrics and taxonomy (gtdb_drep_bin_taxonomy.csv). The dataset additionally includes a sample metadata file (EastRiver_Vegtype_sample_metadata.csv), a metadata file used to register associated samples with IGSNs (International Generic Sample Numbers) (samples.csv), a Google KML file for the sampled locations (sample_collection_sites.kml), a location metadata file (locations.csv), a file-level metadata file (flmd.csv), and a data dictionary (dd.csv) file.This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

54 ENVIRONMENTAL SCIENCES↗

Molecular evolution inferred from small subunit rRNA sequences: what does it tell us about phylogenetic relationships and taxonomy of the parabasalids?

The Parabasala are a primitive group of protists divided into two classes: the trichomonads and the hypermastigids. Until recently, phylogeny and taxonomy of parabasalids were mainly based on the comparative analysis of morphological characters primarily linked to the development of their cytoskeleton. Recent use of molecular markers, such as small subunit (SSU) rRNA has led to now insights into the systematics of the Parabasala and other groups of prolists. An updated phylogeny based on SSU rRNA is provided and compared to that inferred from ultrastructural data. The SSU rRNA phylogeny contradicts the dogma equating simple characters with pumitive characters. Hypermastigids, possessing a hyperdeveloped cytoskeleton, exhibit the most basal emergence in the parabasalid lineage. Other observations emerge from the SSU rRNA analysis, such as the secondary loss of some cytoskeleton structures in all representatives of the Monocercomonadidae, the existence of secondarily free living taxa (reversibility of parasitism) and the evidence against the co-evolution of the endobiotic parabasalids and their animal hosts. According to phylogenies based on SSU rRNA, all the trichomonad families are not monophyletic groups, putting into question the validity of current taxonomic assignments. The precise branching order of some taxa remains unclear, but this issue can possibly be addressed by the molecular analysis of additional parabasalids. The goal of such additional analyses would be to propose, in a near future, a revision of the taxonomy of this group of protists that takes into account both molecular and morphological data.

NASA Discipline Exobiology↗

Development, optimization, and application of an episomal plasmid system for Rhodotorula toruloides

Rhodotorula toruloides is an emerging oleaginous yeast with strong potential as a microbial cell factory for the production of acetyl-CoA-derived bioproducts. However, engineering of this organism has been limited by the absence of a functional episomal plasmid system, a foundational genetic tool for rapid gene expression, pathway testing, and CRISPR-based genome engineering. Here, we report the first episomal plasmid system for R. toruloides . Through systematic screening of candidate autonomously replicating sequences (ARSs) from diverse sources, we identified multiple functional ARS elements and selected C63F4, a fragment derived from Contig 63 of R. toruloides CBS14, because of its stable performance. The resulting pC63F4 plasmid was maintained episomally, supported GFP reporter expression, exhibited a copy number of 2.39 ± 0.13, and showed good stability during long term cultivation. To overcome poor transformation efficiency, we developed a Cre- loxP -mediated in vivo re-circularization strategy that enabled reliable delivery of the episomal plasmid. Using this improved system, we demonstrated functional episomal expression of metabolic engineering genes and multi-gene pathways for the production of triacetic acid lactone, fatty alcohols, and limonene. Finally, we leveraged this platform to establish a redesigned CRISPR system that enables seamless genome editing in R. toruloides for the first time, while also simplifying marker recycling. Together, this work establishes a long-needed episomal plasmid platform and associated CRISPR toolkit that will accelerate metabolic engineering, synthetic biology, and fundamental studies in R. toruloides .

CRISPR-Cas9↗

Next-generation yeast-two-hybrid analysis with Y2H-SCORES identifies novel interactors of the MLA immune receptor

Protein-protein interaction networks are one of the most effective representations of cellular behavior. In order to build these models, high-throughput techniques are required. Next-generation interaction screening (NGIS) protocols that combine yeast two-hybrid (Y2H) with deep sequencing are promising approaches to generate interactome networks in any organism. However, challenges remain to mining reliable information from these screens and thus, limit its broader implementation. Here, we present a computational framework, designated Y2H-SCORES, for analyzing high-throughput Y2H screens. Y2H-SCORES considers key aspects of NGIS experimental design and important characteristics of the resulting data that distinguish it from RNA-seq expression datasets. Three quantitative ranking scores were implemented to identify interacting partners, comprising: 1) significant enrichment under selection for positive interactions, 2) degree of interaction specificity among multi-bait comparisons, and 3) selection of in-frame interactors. Using simulation and an empirical dataset, we provide a quantitative assessment to predict interacting partners under a wide range of experimental scenarios, facilitating independent confirmation by one-to-one bait-prey tests. Simulation of Y2H-NGIS enabled us to identify conditions that maximize detection of true interactors, which can be achieved with protocols such as prey library normalization, maintenance of larger culture volumes and replication of experimental treatments. Y2H-SCORES can be implemented in different yeast-based interaction screenings, with an equivalent or superior performance than existing methods. Proof-of-concept was demonstrated by discovery and validation of novel interactions between the barley nucleotide-binding leucine-rich repeat (NLR) immune receptor MLA6, and fourteen proteins, including those that function in signaling, transcriptional regulation, and intracellular trafficking.

59 BASIC BIOLOGICAL SCIENCES↗

Transportability of exogenous microbial community correlates with interwell connectivity in deep aquifers

Subsurface resource engineering operations often utilize continuous injection of externally-sourced water into geological reservoirs for formation pressure maintenance, resource recovery or energy/waste storage. Such injected water generally contains naturally occurring microbes. Little is known, however, about how the injectate microbes transport through geological media as a community, how such transportability is affected by injector-producer connectivity, and whether such knowledge can be utilized for flowpath characterization. In this study, we analyzed daily-to-weekly timeseries microbial community data from the injected- and produced-fluids of a ten-month flow test at a deep, well-characterized engineered aquifer. We found that the injectate microbial community was distinct from the indigenous community at the amplicon sequence variant (ASV) level, and that the transportability of injectate community towards a given producer, quantified by an “nASV-Overlap” metric we propose, had strong and significant positive correlation with known injector-producer connectivities at our site. This suggests that the better the connectivity, the higher the probability for more injectate species to flow through the interwell region and arrive at a producer. Because interwell connectivity is an important yet usually unknown parameter in subsurface resource engineering, such correlation in turn points to nASV-Overlap as a useful indicator of interwell connectivity for aquifer characterization and long-term monitoring. Based on our findings, an nASV-Overlap-based microbial tracing approach was developed for characterizing and monitoring the relative connectivities across multiple producers with a given injector. A side-by-side comparison between the new nASV-Overlap approach and traditional artificial tracer methods is presented, and their respective strengths and limitations are discussed.

Deep biosphere↗

Chromosome-scale Genome Assembly of the Most Abundant Ectomycorrhizal Fungus Cenococcum Geophilum Reveals Massive TE Expansion and RIP Defense Mechanism

Transposable elements (TEs) play crucial roles in genome evolution and ecological adaptation in fungi, yet their dynamics in ectomycorrhizal species remain poorly understood. Cenococcum geophilum, the most widespread ectomycorrhizal fungus in boreal and temperate forests with its large, repeat-rich genome, represents an ideal system to investigate TE-mediated adaptation to the physical environment and symbiotic lifestyle. However, previous studies have been limited by fragmented genome assemblies that prevented the resolution of repeat-rich regions. We assembled a telomere-to-telomere reference genome of C. geophilum strain 1.58 using PacBio HiFi and Hi-C datasets, resulting in a 178.54 Mbp genome with seven contiguous chromosomes. We identified 14,145 genes and over 78% of the genome consists of transposable elements (TEs). Of these, 94% are affected by repeat-induced point mutations (RIP), a genome defense mechanism that acts during the sexual reproduction phase, indicating cryptic or ancient sexual reproduction in this putatively asexual fungus. Long terminal repeat retrotransposons, LINEs, and DNA transposons dominate, with three TE families (Ty3, Ty1, and Tad1) contributing over 60% of the genome size, indicating recent transposition bursts. Screening of 15 additional C. geophilum strains revealed recent and lineage-specific TE expansions, implying that several TEs escaped the RIP machinery and retained potential activity. Supporting TE activity in the context of symbiosis, we found 56 TEs differentially transcribed between ectomycorrhizal and free-living mycelium tissues. An even higher number (n = 66) of TEs were differentially expressed between stress resistance morphology (i.e. sclerotia) and free-living mycelium. This supports that TEs are differentially regulated as a response to symbiotic and stress-related conditions. Our results demonstrate that the C. geophilum genome expansion was driven by a few lineage-specific TE families in recent history, with high RIP activity attesting to sexual reproduction. We also provide insights how TEs could respond to lifestyle transitions and traits associated with desiccation resistance.

Cenococcum geophilum↗