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At least 703 records · Page 39

Diversity, taxonomy, and evolution of archaeal viruses of the class Caudoviricetes

The archaeal tailed viruses (arTV), evolutionarily related to tailed double-stranded DNA (dsDNA) bacteriophages of the class Caudoviricetes , represent the most common isolates infecting halophilic archaea. Only a handful of these viruses have been genomically characterized, limiting our appreciation of their ecological impacts and evolution. Here, we present 37 new genomes of haloarchaeal tailed virus isolates, more than doubling the current number of sequenced arTVs. Analysis of all 63 available complete genomes of arTVs, which we propose to classify into 14 new families and 3 orders, suggests ancient divergence of archaeal and bacterial tailed viruses and points to an extensive sharing of genes involved in DNA metabolism and counterdefense mechanisms, illuminating common strategies of virus–host interactions with tailed bacteriophages. Coupling of the comparative genomics with the host range analysis on a broad panel of haloarchaeal species uncovered 4 distinct groups of viral tail fiber adhesins controlling the host range expansion. The survey of metagenomes using viral hallmark genes suggests that the global architecture of the arTV community is shaped through recurrent transfers between different biomes, including hypersaline, marine, and anoxic environments.

59 BASIC BIOLOGICAL SCIENCES↗

Diverse signatures of convergent evolution in cactus-associated yeasts

Many distantly related organisms have convergently evolved traits and lifestyles that enable them to live in similar ecological environments. However, the extent of phenotypic convergence evolving through the same or distinct genetic trajectories remains an open question. Here, we leverage a comprehensive dataset of genomic and phenotypic data from 1,049 yeast species in the subphylum Saccharomycotina (Kingdom Fungi, Phylum Ascomycota) to explore signatures of convergent evolution in cactophilic yeasts, ecological specialists associated with cacti. We inferred that the ecological association of yeasts with cacti arose independently approximately 17 times. Using a machine learning–based approach, we further found that cactophily can be predicted with 76% accuracy from both functional genomic and phenotypic data. The most informative feature for predicting cactophily was thermotolerance, which we found to be likely associated with altered evolutionary rates of genes impacting the cell envelope in several cactophilic lineages. We also identified horizontal gene transfer and duplication events of plant cell wall–degrading enzymes in distantly related cactophilic clades, suggesting that putatively adaptive traits evolved independently through disparate molecular mechanisms. Notably, we found that multiple cactophilic species and their close relatives have been reported as emerging human opportunistic pathogens, suggesting that the cactophilic lifestyle—and perhaps more generally lifestyles favoring thermotolerance—might preadapt yeasts to cause human disease. This work underscores the potential of a multifaceted approach involving high-throughput genomic and phenotypic data to shed light onto ecological adaptation and highlights how convergent evolution to wild environments could facilitate the transition to human pathogenicity.

59 BASIC BIOLOGICAL SCIENCES↗

Enrichment of root-associated Streptomyces strains in response to drought is driven by diverse functional traits and does not predict beneficial effects on plant growth

The genus Streptomyces has consistently been found enriched in drought-stressed plant root microbiomes, yet the ecological basis and functional variation underlying this enrichment at the strain and isolate level remain unclear. Using two 16S rRNA sequencing methods with different levels of taxonomic resolution, we confirmed drought-associated enrichment (DE) of Streptomyces in field-grown sorghum roots and identified five closely related but distinct amplicon sequence variants (ASVs) belonging to the genus with variable drought enrichment patterns. From a culture collection of sorghum root endophytes, we selected 12 Streptomyces isolates representing these ASVs for phenotypic and genomic characterization. Whole-genome sequencing revealed substantial variation in gene content, even among closely related isolates, and exometabolomic profiling showed distinct metabolic responses to media supplemented with drought- versus well-watered root tissue. Traits linked to drought survival, including osmotic stress tolerance, siderophore production, and carbon utilization, varied widely among isolates and were not phylogenetically conserved. Using a broader panel of 48 Streptomyces, we demonstrate that DE scores, determined through mono-association experiments in gnotobiotic sorghum systems, showed high variability and lacked correlation with plant growth promotion. Pangenome-wide association identified orthogroups involved in osmolyte transport (e.g., proP) and membrane biosynthesis (e.g., fabG) as positively associated with DE, though most associations lacked phylogenetic signal. Collectively, these results demonstrate that Streptomyces DE is not a conserved genus-level trait but is instead strain-specific and functionally heterogeneous. Furthermore, DE in the root microbiome was shown not to predict beneficial effects on plant growth. This work underscores the need to resolve functional traits at the strain level and highlights the complexity of microbe-host-environment interactions under abiotic stress.

Fonseca-Garcia, Citlali↗

Distinctiveness of genes contributing to growth of Pseudomonas syringae in diverse host plant species

A variety of traits are necessary for bacterial colonization of the interior of plant hosts, including well-studied virulence effectors as well as other phenotypes contributing to bacterial growth and survival within the apoplast. High-throughput methods such as transposon sequencing (TnSeq) are powerful tools to identify such genes in bacterial pathogens. However, there is little information as to the distinctiveness of traits required for bacterial colonization of different hosts. Here, we utilize randomly barcoded TnSeq (RB-TnSeq) to identify the genes that contribute to the ability of Pseudomonas syringae strain B728a to grow within common bean (Phaseolus vulgaris), lima bean (Phaseolus lunatus), and pepper (Capsicum annuum); species representing two different plant families. The magnitude of contribution of most genes to apoplastic fitness in each of the plant hosts was similar. However, 50 genes significantly differed in their fitness contributions to growth within these species. These genes encoded proteins in various functional categories including polysaccharide synthesis and transport, amino acid metabolism and transport, cofactor metabolism, and phytotoxin synthesis and transport. Six genes that encoded unannotated, hypothetical proteins also contributed differentially to growth in these hosts. The genetic repertoire of a relatively promiscuous pathogen such as P. syringae may thus be shaped, at least in part, by the conditional contribution of some fitness determinants.

59 BASIC BIOLOGICAL SCIENCES↗

Rapid estimation of photosynthetic leaf traits of tropical plants in diverse environmental conditions using reflectance spectroscopy

Tropical forests are one of the main carbon sinks on Earth, but the magnitude of CO 2 absorbed by tropical vegetation remains uncertain. Terrestrial biosphere models (TBMs) are commonly used to estimate the CO 2 absorbed by forests, but their performance is highly sensitive to the parameterization of processes that control leaf-level CO 2 exchange. Direct measurements of leaf respiratory and photosynthetic traits that determine vegetation CO 2 fluxes are critical, but traditional approaches are time-consuming. Reflectance spectroscopy can be a viable alternative for the estimation of these traits and, because data collection is markedly quicker than traditional gas exchange, the approach can enable the rapid assembly of large datasets. However, the application of spectroscopy to estimate photosynthetic traits across a wide range of tropical species, leaf ages and light environments has not been extensively studied. Here, we used leaf reflectance spectroscopy together with partial least-squares regression (PLSR) modeling to estimate leaf respiration ( R dark25 ), the maximum rate of carboxylation by the enzyme Rubisco ( V cmax25 ), the maximum rate of electron transport ( J max25 ), and the triose phosphate utilization rate ( T p25 ), all normalized to 25°C. We collected data from three tropical forest sites and included leaves from fifty-three species sampled at different leaf phenological stages and different leaf light environments. Our resulting spectra-trait models validated on randomly sampled data showed good predictive performance for V cmax25 , J max25 , T p25 and R dark25 (RMSE of 13, 20, 1.5 and 0.3 μmol m -2 s -1 , and R 2 of 0.74, 0.73, 0.64 and 0.58, respectively). The models showed similar performance when applied to leaves of species not included in the training dataset, illustrating that the approach is robust for capturing the main axes of trait variation in tropical species. We discuss the utility of the spectra-trait and traditional gas exchange approaches for enhancing tropical plant trait studies and improving the parameterization of TBMs.

54 ENVIRONMENTAL SCIENCES↗

Deciphering the microbial and molecular responses of geographically diverse Setaria accessions grown in a nutrient-poor soil

The microbial and molecular characterization of the ectorhizosphere is an important step towards developing a more complete understanding of how the cultivation of biofuel crops can be undertaken in nutrient poor environments. The ectorhizosphere of Setaria is of particular interest because the plant component of this plant-microbe system is an important agricultural grain crop and a model for biofuel grasses. Importantly, Setaria lends itself to high throughput molecular studies. As such, we have identified important intra- and interspecific microbial and molecular differences in the ectorhizospheres of three geographically distant Setaria italica accessions and their wild ancestor S . viridis . All were grown in a nutrient-poor soil with and without nutrient addition. To assess the contrasting impact of nutrient deficiency observed for two S . italica accessions, we quantitatively evaluated differences in soil organic matter, microbial community, and metabolite profiles. Together, these measurements suggest that rhizosphere priming differs with Setaria accession, which comes from alterations in microbial community abundances, specifically Actinobacteria and Proteobacteria populations. When globally comparing the metabolomic response of Setaria to nutrient addition, plants produced distinctly different metabolic profiles in the leaves and roots. With nutrient addition, increases of nitrogen containing metabolites were significantly higher in plant leaves and roots along with significant increases in tyrosine derived alkaloids, serotonin, and synephrine. Glycerol was also found to be significantly increased in the leaves as well as the ectorhizosphere. These differences provide insight into how C 4 grasses adapt to changing nutrient availability in soils or with contrasting fertilization schemas. Gained knowledge could then be utilized in plant enhancement and bioengineering efforts to produce plants with superior traits when grown in nutrient poor soils.

59 BASIC BIOLOGICAL SCIENCES↗

CovS inactivation reduces CovR promoter binding at diverse virulence factor encoding genes in group A Streptococcus

The control of virulence gene regulator (CovR), also called caspsule synthesis regulator (CsrR), is critical to how the major human pathogen group A Streptococcus fine-tunes virulence factor production. CovR phosphorylation (CovR~P) levels are determined by its cognate sensor kinase CovS, and functional abrogating mutations in CovS can occur in invasive GAS isolates leading to hypervirulence. Presently, the mechanism of CovR-DNA binding specificity is unclear, and the impact of CovS inactivation on global CovR binding has not been assessed. Thus, we performed CovR chromatin immunoprecipitation sequencing (ChIP-seq) analysis in the emm1 strain MGAS2221 and its CovS kinase deficient derivative strain 2221-CovS-E281A. We identified that CovR bound in the promoter regions of nearly all virulence factor encoding genes in the CovR regulon. Additionally, direct CovR binding was observed for numerous genes encoding proteins involved in amino acid metabolism, but we found limited direct CovR binding to genes encoding other transcriptional regulators. The consensus sequence AATRANAAAARVABTAAA was present in the promoters of genes directly regulated by CovR, and mutations of highly conserved positions within this motif relieved CovR repression of the hasA and MGAS2221_0187 promoters. Analysis of strain 2221-CovS-E281A revealed that binding of CovR at repressed, but not activated, promoters is highly dependent on CovR~P state. CovR repressed virulence factor encoding genes could be grouped dependent on how CovR~P dependent variation in DNA binding correlated with gene transcript levels. Taken together, the data show that CovR repression of virulence factor encoding genes is primarily direct in nature, involves binding to a newly-identified DNA binding motif, and is relieved by CovS inactivation. These data provide new mechanistic insights into one of the most important bacterial virulence regulators and allow for subsequent focused investigations into how CovR-DNA interaction at directly controlled promoters impacts GAS pathogenesis.

59 BASIC BIOLOGICAL SCIENCES↗

News and Notes: SSA Task Force on Diversity, Equity, and Inclusion: Toward a Changing, Inclusive Future in Earthquake Science

In the United States, a wide variety of studies show that the geoscience community does not reflect the broader societal makeup (e.g., Velasco and Jaurrieta de Velasco, 2010; Dutt, 2020; Howley, 2020). In fact, only about 10% of all Science, Technology, Engineering, Mathematics (STEM) Ph.D. degrees are awarded to people of color, although they represent more than a third of the population (Dutt, 2020). These numbers have changed little over the past 40 years (e.g., Bernard and Cooperdock, 2018; Dutt, 2020). Recent events in the United States have again raised awareness of this discrepancy in many fields; similar divergences may be present throughout the world. How this discrepancy represents a tremendous loss of talent and contributes to ongoing bias and racism is discussed.

58 GEOSCIENCES↗

Modeling Air Handling Units to Create a Diverse Fault Dataset for FDD Innovation: Lessons Learned and Recommendations

As energy management and information systems (e.g., automated fault detection and diagnostics [AFDD] tools) become more prevalent in the commercial building stock, it is important to determine the effectiveness of these technologies by benchmarking their performance. The authors have been working to develop the largest publicly available dataset of HVAC fault datasets for performance benchmarking applications, covering the most common HVAC systems and designs including chiller plants, rooftop packaged units, dual duct air handling unit and single duct air handling units. This study covers the development, modeling, and validation of a synthetic fault dataset for the air handling unit (AHU), one of the most common HVAC configurations found in the commercial building stock. Despite this being a common system, real-world time series data are scarce and usually do not span a wide range of weather conditions. Due to this limitation, two detailed AHU models, which included the single duct AHU and dual duct AHU developed in the Modelica language and HVACSIM+ were employed to carry out annual simulations of numerous common sensor faults, mechanical faults, and control sequence faults. The fault inclusive data were then validated by comparing fault effects on system performance to expected symptoms. We summarize the nature of each fault and their impacts under different weather and operation conditions. We report some lessons learnt during the efforts of validating the high volumes of the FDD data sets. Finally, we highlight considerations for FDD developers that may want to use this dataset to assess their algorithms’ performance and their improvement over time.

Casillas, Armando↗

Biologically Diverse Genetic Engineering Platform

This project focused on methods to genetically edit arbitrary prokaryotes to convert non-agricultural biomass to industrially relevant chemicals at scale and at a price point that would be competitive with petroleum. Our target chemical for this demonstration was succinic acid, a polymer precursor that could theoretically be produced at scale from biomass. We demonstrated genetic control over a selected bacterial type strain: we can make permanent and directed changes to its genome. After thoroughly characterizing its behavior, and the circumstances under which it produced the most succinic acid, the researchers found a wild-type isolate that produces at least eight times more succinic acid than the type strain.

09 BIOMASS FUELS↗

How to Actively Not be a Barrier to Diversity Efforts in Physics

Systemic racism permeates all facets of our society and the recent horrific killings of George Floyd, Breonna Taylor and many others are just one of the many reminders of this. The serious lack of underrepresented minorities (URMs) in physics is proof that our field is no exception to discrimination and racism. In light of the recent events, it is important to confront ourselves about how our own complicity and inaction have perpetuated racism and a culture that allows racist actions to thrive.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗