Migratory Flyways May Affect Population Structure in Double-Crested Cormorants
Not provided.
SEARCH · Search NASA
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Not provided.
Denitrification is an important global N cycle process. The gene encoding NosZ that converts nitrous oxide (N 2 O) to N 2 has been widely used as a biomarker to study denitrifying communities. However, conventional PCR primers target a limited range of the genetically diverse Clade I nosZ, and the amplicons are too long for sequencing on current NGS platforms. To address these issues, here we developed a new PCR primer set that amplifies a 355-bp region of Clade I nosZ and captures broader taxonomic coverage than conventional primers in in silico tests. When compared with the widely used nosZF_nosZR_Rich_2003 set using the same soil samples and the same sequencing depth, the new set retrieved genes from four times more unique species, with consistently higher general diversity-based metrics. The new primer set performed well with different sequencing platforms (Ion Torrent and Illumina), and among a wide variety of soils from polar to tropical, desert to agricultural, and surface to a very low biomass subsoil, with significant differences in denitrifying community diversity and composition. This new primer set for Clade I together with the primers recently reported for Clade II by Chee-Sanford et al. provides a more comprehensive assessment of denitrifier gene hosts, their ecological patterns, and the degree of novelty in retrieved gene sequences.
Long-term production of a few species of Eucheuma and Kappaphycus from the Indo-Pacific Ocean supports the global carrageenan industry. The widespread use of vegetative propagation has resulted in low genetic diversity among farmed populations, making these crops increasingly vulnerable to diseases and environmental stressors, and resulting in declining yields and reduced biomass production over time. Insufficient efforts to develop and select new native cultivars, combined with the ecological risks posed by introducing nonindigenous species, underscore the urgent need to enhance cultivar diversification in eucheumatoid farming. Eucheumatopsis isiformis , a native carrageenophyte to the Atlantic Ocean, has potential for its cultivation in the Yucatán peninsula, Mexico. This study evaluated the growth and biochemical composition (pigments, elemental C and N, kappa/iota carrageenan ratio) of E. isiformis under different irradiance conditions in an indoor cultivation system. Specimens were collected in a subtidal population in Yucatán, Mexico, characterized, acclimatized to laboratory conditions, and exposed to five irradiance levels (71 ± 10.59 –1014 ± 65.85 µmol quanta m −2 s −1 ; 23.4 °C, salinity 33–34). Growth was measured weekly for six weeks, and elemental C and N content, pigment composition, and the kappa/iota-carrageenan ratio were evaluated. Growth and chromatic photoacclimation to light conditions were observed in all treatments. Highest growth rates (3.1–3.2% day −1 ) were registered between 238 ± 28.3 – 518 ± 44.3 µmol quanta m −2 s −1 , with a predominant iota-type carrageenan (0.97 ± 0.02) observed in all treatments. This study aims to provide guidelines for the successful development of the aquaculture of this carrageenophyte.
Microalgae, including cyanobacteria, are a genetically diverse and biochemically diverse group of mostly photosynthetic organisms that can be found in nearly every ecosystem. They produce a broad range of compounds, including structural and bioactive lipids with various roles in the metabolism of the cell and potential applications in biotechnology. Here, the majority of lipids are synthesized in the chloroplast using acetate to produce fatty acids and terpenoids via the acetate pathway and methylerythritol phosphate deoxy-xylulose phosphate pathway, respectively. This review will highlight the major groups of microalgal lipids as well as their applications in food, fuels, and specialty chemicals. Future directions include the development of microalgal chassis organisms and molecular tools to manipulate lipid synthesis for the enhanced production of target metabolites.
Background: Deeper insights into ERBB2-driven cancers are essential to develop new treatment approaches for ERBB2+ breast cancers (BCs). We employed the Collaborative Cross (CC) mouse model to unearth genetic factors underpinning Erbb2-driven mammary tumour development and metastasis. Methods: 732 F1 hybrid female mice between FVB/N MMTV-Erbb2 and 30 CC strains were monitored for mammary tumour phenotypes. GWAS pinpointed SNPs that influence various tumour phenotypes. Multivariate analyses and models were used to construct the polygenic score and to develop a mouse tumour susceptibility gene signature (mTSGS), where the corresponding human ortholog was identified and designated as hTSGS. The importance and clinical value of hTSGS in human BC was evaluated using public datasets, encompassing TCGA, METABRIC, GSE96058, and I-SPY2 cohorts. The predictive power of mTSGS for response to chemotherapy was validated in vivo using genetically diverse MMTV-Erbb2 mice. Findings: Distinct variances in tumour onset, multiplicity, and metastatic patterns were observed in F1-hybrid female mice between FVB/N MMTV-Erbb2 and 30 CC strains. Besides lung metastasis, liver and kidney metastases emerged in specific CC strains. GWAS identified specific SNPs significantly associated with tumour onset, multiplicity, lung metastasis, and liver metastasis. Multivariate analyses flagged SNPs in 20 genes (Stx6, Ramp1, Traf3ip1, Nckap5, Pfkfb2, Trmt1l, Rprd1b, Rer1, Sepsecs, Rhobtb1, Tsen15, Abcc3, Arid5b, Tnr, Dock2, Tti1, Fam81a, Oxr1, Plxna2, and Tbc1d31) independently tied to various tumour characteristics, designated as a mTSGS. hTSGS scores (hTSGSS) based on their transcriptional level showed prognostic values, superseding clinical factors and PAM50 subtype across multiple human BC cohorts, and predicted pathological complete response independent of and superior to MammaPrint score in I-SPY2 study. The power of mTSGS score for predicting chemotherapy response was further validated in an in vivo mouse MMTV-Erbb2 model, showing that, like findings in human patients, mouse tumours with low mTSGS scores were most likely to respond to treatment. Interpretation: Our investigation has unveiled many new genes predisposing individuals to ERBB2-driven cancer. Translational findings indicate that hTSGS holds promise as a biomarker for refining treatment strategies for patients with BC.
Accurately predicting drought tolerance in woody perennial bioenergy crops is critical for sustainable biomass production under fluctuating precipitation. Hyperspectral imaging (HSI) in the visible-near-infrared (VNIR) and shortwave-infrared (SWIR) ranges offers a promising approach for predicting plant biochemical traits, yet its application in metabolite profiling remains underexplored. We integrated VNIR+SWIR HSI with untargeted metabolomics to investigate drought-induced metabolic shifts in Populus leaves from eight Populus genotypes. Metabolite profiling identified 127 compounds, with 73 showing significant drought responses spanning amino acids (AA), carbohydrates (CHO), phenolic glycosides (PG), organic acids (OA), fatty acids and alcohols (FA), terpenes (T), phenolic metabolites (P), and unclassified metabolites. Spectral analysis revealed consistently higher reflectance across VNIR and SWIR wavelengths in drought-stressed plants, corresponding with increased accumulation of AA and reduced CHO and PG levels. Least absolute shrinkage and selection operator (LASSO) regression modeling identified robust spectral predictors of metabolite concentrations, associating VNIR wavelengths (500–700 nm) predominantly with AA and P, whereas SWIR wavelengths (1680–1700 nm) reliably predicted CHO, OA, and T. Several stable spectral-metabolite associations persisted across the two watering regimes (drought vs. well-watered), highlighting their potential as spectral biomarkers for non-destructive stress monitoring. Minimal genotype-specific variation suggests that observed spectral and metabolic responses were driven primarily by environmental factors, likely reflecting limited genetic diversity among the commercial Populus genotypes examined. This work establishes VNIR+SWIR hyperspectral imaging as a powerful, non-destructive phenotyping tool for precision monitoring and targeted improvement of drought resilience in bioenergy crops.
The high genetic diversity of hepatitis C virus (HCV) complicates effective vaccine development. We screened a cohort of 435 HCV-infected individuals and found that 2%–5% demonstrated outstanding HCV-neutralizing activity. From four of these patients, we isolated 310 HCV antibodies, including neutralizing antibodies with exceptional breadth and potency. High neutralizing activity was enabled by the use of the VH1-69 heavy-chain gene segment, somatic mutations within CDRH1, and CDRH2 hydrophobicity. Structural and mutational analyses revealed an important role for mutations replacing the serines at positions 30 and 31, as well as the presence of neutral and hydrophobic residues at the tip of the CDRH3. Based on these characteristics, we computationally created a de novo antibody with a fully synthetic VH1-69 heavy chain that efficiently neutralized multiple HCV genotypes. Finally, our findings provide a deep understanding of the generation of broadly HCV-neutralizing antibodies that can guide the design of effective vaccine candidates.
Malaria transmission-blocking vaccines (TBVs) aim to induce antibodies that interrupt malaria parasite development in the mosquito, thereby blocking onward transmission, and provide a much-needed tool for malaria control and elimination. The parasite surface protein Pfs48/45 is a leading TBV candidate. Here, we isolated and characterized a panel of 81 human Pfs48/45-specific monoclonal antibodies (mAbs) from donors naturally exposed to Plasmodium parasites. Genetically diverse mAbs against each of the three domains (D1–D3) of Pfs48/45 were identified. The most potent mAbs targeted D1 and D3 and achieved >80% transmission-reducing activity in standard membrane-feeding assays, at 10 and 2 μg/mL, respectively. Co-crystal structures of D3 in complex with four different mAbs delineated two conserved protective epitopes. Altogether, these Pfs48/45-specific human mAbs provide important insight into protective and non-protective epitopes that can further our understanding of transmission and inform the design of refined malaria transmission-blocking vaccine candidates.
Recombination events occur frequently in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), resulting in genetic diversity. Because these events contribute to altered host immune evasion and antiviral susceptibility, it is crucial to evaluate the efficacy of COVID-19 vaccines and antivirals against recombinant variants. As of March 2023, XBB.1.5, a recombinant sublineage of XBB, is currently the dominant form globally (Fig. S1A, Supplementary Appendix). XBB emerged as a result of recombination between two BA.2 descendants, BJ.1 and BM.1.1.1 (a progeny of BA.2.75). We and other groups have shown that XBB.1.5 is resistant to several therapeutic monoclonal antibodies and effectively evades humoral immunity elicited by natural infection or COVID-19 vaccination.1, 2, 3 By March 30, 2023, an additional recombinant variant, XBF, had been sampled 8966 times in 47 countries and territories in GISAID, reaching it highest prevalence in Australia and New Zealand (Fig. S2, Supplementary Appendix). XBF is still increasing in frequency, although the prevalence of XBB.1.5 appears to be increasing at a faster pace in most regions (Fig. S1B, Supplementary Appendix). XBF is a recombinant of BA.5.2.3 (a descendant of BA.5) and CJ.1 (a descendant of BA.2.75) and, like CJ.1, has an additional three substitutions (R346T, F486P, and F490S) in the receptor-binding domain (RBD) of the consensus form of its spike protein compared to baseline BA.2.75 (Fig. S3A, Supplementary Appendix). CJ.1 and its related sublineage CJ.1.1 did not expand as extensively as XBF, being sampled in GISAID only 1589 and 142 times respectively. CJ.1 was found circulating in many countries, but most commonly sampled in South Korea, where it is still increasing and has currently reached about 5% of the sampled population. CJ.1.1 was most frequently sampled in Malaysia and Singapore, but remained rare in both nations, peaking at about 1% of the sample in December of 2022. Despite the importance of these related variants, we have no information about the antiviral efficacy and immunity induced by COVID-19 vaccines against a clinical isolate of XBF.
NIR spectroscopy is a rapid and accurate green technology for high-throughput biomass characterization, including sorghum (Sorghum bicolor), a promising energy crop for the biofuel industry. This study assessed the influence of particle size on NIR spectroscopic analysis (wavelength range: 867–2535 nm) of sorghum biomass composition. Grown under field conditions, a total of 113 types of genetically diverse sorghum accessions were dried, ground, and sieved (<250, 250–600, 600–850, and > 850 µm particle size) for developing partial least square regression (PLSR) prediction models for moisture, ash, extractive, glucan, xylan, acid-soluble lignin (ASL), acid-insoluble lignin (AIL), and total lignin (ASL + AIL). Overall, smaller particle sizes provided better model performance, while no single particle size provided the best performance for all the selected components. With only 9 selected bands and 4 latent variables (LVs), the best PLSR model was obtained for moisture with particle size of 600–850 µm with the square root of the coefficient of determination (R) of 0.85, the ratio of prediction to deviation (RPD) of 2.2, and the root mean square error (RMSE) of 0.46 % in external validation. Similar model performances were also obtained for ash, extractive, glucan, and xylan. This study showed that size reduction could effectively improve NIR spectroscopic analysis for lipid-producing sorghum biomass for the biofuel industry.
Polyketide synthase (PKS) engineering is an attractive method to generate new molecules such as commodity, fine and specialty chemicals. A significant challenge is re-engineering a partially reductive PKS module to produce a saturated β-carbon through a reductive loop (RL) exchange. In this work, we sought to establish that chemoinformatics, a field traditionally used in drug discovery, offers a viable strategy for RL exchanges. We first introduced a set of donor RLs of diverse genetic origin and chemical substrates into the first extension module of the lipomycin PKS (LipPKS1). Product titers of these engineered unimodular PKSs correlated with chemical structure similarity between the substrate of the donor RLs and recipient LipPKS1, reaching a titer of 165 mg/L of short-chain fatty acids produced by the host Streptomyces albus J1074. Finally, expanding this method to larger intermediates that require bimodular communication, we introduced RLs of divergent chemosimilarity into LipPKS2 and determined triketide lactone production. Collectively, we observed a statistically significant correlation between atom pair chemosimilarity and production, establishing a new chemoinformatic method that may aid in the engineering of PKSs to produce desired, unnatural products.
Long-term climate change and periodic environmental extremes threaten food and fuel security and global crop productivity. Although molecular and adaptive breeding strategies can buffer the effects of climatic stress and improve crop resilience, these approaches require sufficient knowledge of the genes that underlie productivity and adaptation—knowledge that has been limited to a small number of well-studied model systems. Here we present the assembly and annotation of the large and complex genome of the polyploid bioenergy crop switchgrass ( Panicum virgatum ). Analysis of biomass and survival among 732 resequenced genotypes, which were grown across 10 common gardens that span 1,800 km of latitude, jointly revealed extensive genomic evidence of climate adaptation. Climate–gene–biomass associations were abundant but varied considerably among deeply diverged gene pools. Furthermore, we found that gene flow accelerated climate adaptation during the postglacial colonization of northern habitats through introgression of alleles from a pre-adapted northern gene pool. The polyploid nature of switchgrass also enhanced adaptive potential through the fractionation of gene function, as there was an increased level of heritable genetic diversity on the nondominant subgenome. In addition to investigating patterns of climate adaptation, the genome resources and gene–trait associations developed here provide breeders with the necessary tools to increase switchgrass yield for the sustainable production of bioenergy.
The long interspersed element-1 (LINE-1, hereafter L1) retrotransposon has generated nearly one-third of the human genome and serves as an active source of genetic diversity and human disease. L1 spreads through a mechanism termed target-primed reverse transcription, in which the encoded enzyme (ORF2p) nicks the target DNA to prime reverse transcription of its own or non-self RNAs. Here we purified full-length L1 ORF2p and biochemically reconstituted robust target-primed reverse transcription with template RNA and target-site DNA. We report cryo-electron microscopy structures of the complete human L1 ORF2p bound to structured template RNAs and initiating cDNA synthesis. The template polyadenosine tract is recognized in a sequence-specific manner by five distinct domains. Among them, an RNA-binding domain bends the template backbone to allow engagement of an RNA hairpin stem with the L1 ORF2p C-terminal segment. Moreover, structure and biochemical reconstitutions demonstrate an unexpected target-site requirement: L1 ORF2p relies on upstream single-stranded DNA to position the adjacent duplex in the endonuclease active site for nicking of the longer DNA strand, with a single nick generating a staggered DNA break. Our research provides insights into the mechanism of ongoing transposition in the human genome and informs the engineering of retrotransposon proteins for gene therapy.
Abstract Our ability to predict, control, or design biological function is fundamentally limited by poorly annotated gene function. This can be particularly challenging in non-model systems. Accordingly, there is motivation for new high-throughput methods for accurate functional annotation. Here, we used co mplementation of aux otrophs and DNA barcode seq uencing (Coaux-Seq) to enable high-throughput characterization of protein function. Fragment libraries from eleven genetically diverse bacteria were tested in twenty different auxotrophic strains of Escherichia coli to identify genes that complement missing biochemical activity. We recovered 41% of expected hits, with effectiveness ranging per source genome, and observed success even with distant E. coli relatives like Bacillus subtilis and Bacteroides thetaiotaomicron . Coaux-Seq provided the first experimental validation for 53 proteins, of which 11 are less than 40% identical to an experimentally characterized protein. Among the unexpected function identified was a sulfate uptake transporter, an O-succinylhomoserine sulfhydrylase for methionine synthesis, and an aminotransferase. We also identified instances of cross-feeding wherein protein overexpression and nearby non-auxotrophic strains enabled growth. Altogether, Coaux-Seq’s utility is demonstrated, with future applications in ecology, health, and engineering.
Abstract Aims Antimicrobial resistance in Pseudomonas aeruginosa represents a major global challenge in public and veterinary health, particularly from a One Health perspective. This study aimed to investigate antimicrobial resistance, the presence of virulence genes, and the genetic diversity of P. aeruginosa isolates from diverse sources. Methods and results The study utilized antimicrobial susceptibility testing, genomic analysis for resistance and virulence genes, and multilocus sequence typing to characterize a total of 737 P. aeruginosa isolates that were collected from humans, domestic animals, and aquatic environments in Northern Portugal. Antimicrobial resistance profiles were analyzed, and genomic approaches were employed to detect resistance and virulence genes. The study found a high prevalence of multidrug-resistant isolates, including high-risk clones such as ST244 and ST446, particularly in hospital sources and wastewater treatment plants. Key genes associated with resistance and virulence, including efflux pumps (e.g. MexA and MexB) and secretion systems (T3SS and T6SS), were identified. Conclusions This work highlights the intricate dynamics of multidrug-resistant P. aeruginosa across interconnected ecosystems in Northern Portugal. It underscores the importance of genomic studies in revealing the mechanisms of resistance and virulence, contributing to the broader understanding of resistance dynamics and informing future mitigation strategies.
Abstract Background Reports of fluconazole-resistant Candida parapsilosis bloodstream infections are increasing. We describe a cluster of fluconazole-resistant C parapsilosis bloodstream infections identified in 2021 on routine surveillance by the Georgia Emerging Infections Program in conjunction with the Centers for Disease Control and Prevention. Methods Whole-genome sequencing was used to analyze C parapsilosis bloodstream infections isolates. Epidemiological data were obtained from medical records. A social network analysis was conducted using Georgia Hospital Discharge Data. Results Twenty fluconazole-resistant isolates were identified in 2021, representing the largest proportion (34%) of fluconazole-resistant C parapsilosis bloodstream infections identified in Georgia since surveillance began in 2008. All resistant isolates were closely genetically related and contained the Y132F mutation in the ERG11 gene. Patients with fluconazole-resistant isolates were more likely to have resided at long-term acute care hospitals compared with patients with susceptible isolates (P = .01). There was a trend toward increased mechanical ventilation and prior azole use in patients with fluconazole-resistant isolates. Social network analysis revealed that patients with fluconazole-resistant isolates interfaced with a distinct set of healthcare facilities centered around 2 long-term acute care hospitals compared with patients with susceptible isolates. Conclusions Whole-genome sequencing results showing that fluconazole-resistant C parapsilosis isolates from Georgia surveillance demonstrated low genetic diversity compared with susceptible isolates and their association with a facility network centered around 2 long-term acute care hospitals suggests clonal spread of fluconazole-resistant C parapsilosis. Further studies are needed to better understand the sudden emergence and transmission of fluconazole-resistant C parapsilosis.
Machine learning (ML) can accelerate biological research. However, the adoption of such tools to facilitate phenotyping based on sensor data has been limited by (i) the need for a large amount of human-annotated training data for each context in which the tool is used and (ii) phenotypes varying across contexts defined in terms of genetics and environment. This is a major bottleneck because acquiring training data is generally costly and time-consuming. This study demonstrates how a ML approach can address these challenges by minimizing the amount of human supervision needed for tool building. A case study was performed to compare ML approaches that examine images collected by an uncrewed aerial vehicle to determine the presence/absence of panicles (i.e. “heading”) across thousands of field plots containing genetically diverse breeding populations of 2 Miscanthus species. Automated analysis of aerial imagery enabled the identification of heading approximately 9 times faster than in-field visual inspection by humans. Leveraging an Efficiently Supervised Generative Adversarial Network (ESGAN) learning strategy reduced the requirement for human-annotated data by 1 to 2 orders of magnitude compared to traditional, fully supervised learning approaches. The ESGAN model learned the salient features of the data set by using thousands of unlabeled images to inform the discriminative ability of a classifier so that it required minimal human-labeled training data. This method can accelerate the phenotyping of heading date as a measure of flowering time in Miscanthus across diverse contexts (e.g. in multistate trials) and opens avenues to promote the broad adoption of ML tools.
Abstract By the 1980s, after decades of declining numbers in the mid‐1900s, Coho salmon ( Oncorhynchus kisutch ) were considered extirpated from the interior Columbia River. In the mid‐1990s, the Confederated Tribes of the Umatilla Indian Reservation, the Confederated Tribes and Bands of the Yakama Nation, and the Nez Perce Tribe began successful reintroduction programs of Coho salmon upstream of Bonneville Dam, but which were initially sourced from lower Columbia River hatcheries. Here we present the first Coho salmon parentage‐based tagging (PBT) baseline from seven hatchery programs located in the interior Columbia River basin, and two sites at or downstream of Bonneville Dam, composed of over 32,000 broodstock samples. Analyses of baseline collections revealed that genetic structure followed a temporal pattern based on 3‐year broodlines rather than geographic location or stocking history. Across hatchery programs, similar levels of genetic diversity was present. The PBT baseline provided multiple direct applications such as identification of origin for Coho salmon collected in a mixed stock at Priest Rapids Dam and the detection of the proportion and distribution of hatchery‐origin fish on the spawning grounds in the Methow River basin. The PBT baseline for Coho salmon is freely available for use and can be downloaded from FishGen.net .