Browsing by Author "Yang, Shu"

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    Draft genome sequence of mortierella alpina strain LL118, isolated from an aspen (populus tremuloides) leaf litter sample
    Yang, Shu; Vinatzer, Boris A. (American Society for Microbiology, 2021-11-01)
    Mortierella alpina is a filamentous fungus commonly associated with soil and is one of very few fungal species known to include strains with ice nucleation activity. Here, we report the draft genome sequence of the ice nucleation-active M. alpina strain LL118, isolated from aspen leaf litter collected in Alberta, Canada.
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    Genomic, transcriptomic, and metagenomic approaches for detecting fungal plant pathogens and investigating the molecular basis of fungal ice nucleation activity
    Yang, Shu (Virginia Tech, 2022-02-02)
    Fungi play important roles in various environments. Some of them infect plants and cause economically important diseases. However, many fungal pathogens cause similar symptoms or are even spread asymptomatically, making it difficult to identify them morphologically. Therefore, culture-independent, sequence-based diagnostic methods that can detect and identify fungi independently of the symptoms that they cause are desirable. Whole genome metagenomic sequencing has the potential to enable rapid diagnosis of plant diseases without culturing pathogens and designing pathogen-specific probes. In my study, the MinION nanopore sequencer, a portable single‐molecule sequencing platform developed by Oxford Nanopore Technologies, was employed to detect the fungus Calonectria pseudonaviculata (Cps), the causal agent of the devastating boxwood blight disease of the popular ornamental boxwood (Buxus spp.). Various DNA extraction methods and computational tools were compared. Detection was sensitive with an extremely low false positive rate for most methods. Therefore, metagenomic sequencing is a promising technology that could be implemented in routine diagnostics of fungal diseases. Other fungi may play important roles in the atmosphere because of their ice nucleation activity (INA). INA is the capacity of some particles to induce ice formation above the temperature that pure water freezes (-38°C). Importantly, INPs affect the ratio of ice crystals to liquid droplets in clouds, which in turn affects Earth's radiation balance and the intensity and frequency of precipitation. A few fungal species can produce ice nucleating particles (INPs) that cause ice formation at temperatures ≥ –10°C and they may be present in clouds. Two such fungal genera are Fusarium and Mortierella but little is known about their INPs and the genetic basis of their INA. In my study, F. avenaceum and M. alpina were examined in detail. INPs of both species were characterized and it was found that strains within both species varied in regards to the strength of INA. Whole genome sequencing and comparative genomic studies were then performed to identify putative INA genes. Differential expression analyses at different growth temperatures were also performed. INP properties of the two species shared similarities, both appearing to consist of secreted aggregates larger than 30 kDa. Low temperatures induced INA in both species. Lists of candidate INA genes were identified based on their presence in the strains with the strongest INA and/or induction of their expression at low temperatures and because they either encode secreted proteins or enzymes that produce other molecules known to have INA in other organisms. These genes can now be characterized further to help identify the fungal INA genes in both species. This can be expected to help increase our understanding of the role of fungal INA in the atmosphere.
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    Ice nucleation in a Gram-positive bacterium isolated from precipitation depends on a polyketide synthase and non-ribosomal peptide synthetase
    Failor, Kevin C.; Liu, Haijie; Llontop, Marco E. Mechan; LeBlanc, Sophie; Eckshtain-Levi, Noam; Sharma, Parul; Reed, Austin; Yang, Shu; Tian, Long; Lefevre, Christopher; Menguy, Nicolas; Du, Liangcheng; Monteil, Caroline L.; Vinatzer, Boris A. (2021-10-23)
    Earth's radiation budget and frequency and intensity of precipitation are influenced by aerosols with ice nucleation activity (INA), i.e., particles that catalyze the formation of ice. Some bacteria, fungi, and pollen are among the most efficient ice nucleators but the molecular basis of INA is poorly understood in most of them. Lysinibacillus parviboronicapiens (Lp) was previously identified as the first Gram-positive bacterium with INA. INA of Lp is associated with a secreted, nanometer-sized, non-proteinaceous macromolecule or particle. Here a combination of comparative genomics, transcriptomics, and a mutant screen showed that INA in Lp depends on a type I iterative polyketide synthase and a non-ribosomal peptide synthetase (PKS-NRPS). Differential filtration in combination with gradient ultracentrifugation revealed that the product of the PKS-NRPS is associated with secreted particles of a density typical of extracellular vesicles and electron microscopy showed that these particles consist in "pearl chain"-like structures not resembling any other known bacterial structures. These findings expand our knowledge of biological INA, may be a model for INA in other organisms for which the molecular basis of INA is unknown, and present another step towards unraveling the role of microbes in atmospheric processes.
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    Identification of Candidate Ice Nucleation Activity (INA) Genes in Fusarium avenaceum by Combining Phenotypic Characterization with Comparative Genomics and Transcriptomics
    Yang, Shu; Rojas, Mariah; Coleman, Jeffrey J.; Vinatzer, Boris A. (MDPI, 2022-09-13)
    Ice nucleation activity (INA) is the capacity of certain particles to catalyze ice formation at temperatures higher than the temperature at which pure water freezes. INA impacts the ratio of liquid to frozen cloud droplets and, therefore, the formation of precipitation and Earth’s radiative balance. Some Fusarium strains secrete ice-nucleating particles (INPs); they travel through the atmosphere and may thus contribute to these atmospheric processes. Fusarium INPs were previously found to consist of proteinaceous aggregates. Here, we determined that in F. avenaceum, the proteins forming these aggregates are smaller than 5 nm and INA is higher after growth at low temperatures and varies among strains. Leveraging these findings, we used comparative genomics and transcriptomics to identify candidate INA genes. Ten candidate INA genes that were predicted to encode secreted proteins were present only in the strains that produced the highest number of INPs. In total, 203 candidate INA genes coding for secreted proteins were induced at low temperatures. Among them, two genes predicted to encode hydrophobins stood out because hydrophobins are small, secreted proteins that form aggregates with amphipathic properties. We discuss the potential of the candidate genes to encode INA proteins and the next steps necessary to identify the molecular basis of INA in F. avenaceum.
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    Metagenomic sequencing for detection and identification of the boxwood blight pathogen Calonectria pseudonaviculata
    Yang, Shu; Johnson, Marcela A.; Hansen, Mary Ann; Bush, Elizabeth A.; Li, Song; Vinatzer, Boris A. (Springer Nature, 2022-01-26)
    Pathogen detection and identification are key elements in outbreak control of human, animal, and plant diseases. Since many fungal plant pathogens cause similar symptoms, are difficult to distinguish morphologically, and grow slowly in culture, culture-independent, sequence-based diagnostic methods are desirable. Whole genome metagenomic sequencing has emerged as a promising technique because it can potentially detect any pathogen without culturing and without the need for pathogen-specific probes. However, efficient DNA extraction protocols, computational tools, and sequence databases are required. Here we applied metagenomic sequencing with the Oxford Nanopore Technologies MinION to the detection of the fungus Calonectria pseudonaviculata, the causal agent of boxwood (Buxus spp.) blight disease. Two DNA extraction protocols, several DNA purification kits, and various computational tools were tested. All DNA extraction methods and purification kits provided sufficient quantity and quality of DNA. Several bioinformatics tools for taxonomic identification were found suitable to assign sequencing reads to the pathogen with an extremely low false positive rate. Over 9% of total reads were identified as C. pseudonaviculata in a severely diseased sample and identification at strain-level resolution was approached as the number of sequencing reads was increased. We discuss how metagenomic sequencing could be implemented in routine plant disease diagnostics.
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    Modeling and Control of Tensegrity-Membrane Systems
    Yang, Shu (Virginia Tech, 2016-06-30)
    Tensegrity-membrane systems are a class of new bar-tendon-membrane systems. Such novel systems can be treated as extensions of tensegrity structures and are generally lightweight and deployable. These two major advantages enable tensegrity-membrane systems to become one of the most promising candidates for lightweight space structures and gossamer spacecraft. In this dissertation, modeling and control of tensegrity-membrane systems is studied. A systematic method is developed to determine the equilibrium conditions of general tensegrity-membrane systems. Equilibrium conditions can be simplified when the systems are in symmetric configurations. For one-stage symmetric systems, analytical equilibrium conditions can be determined. Three mathematical models are developed to study the dynamics of tensegrity-membrane systems. Two mathematical models are developed based on the nonlinear finite element method. The other model is a control-oriented model, which is suitable for control design. Numerical analysis is conducted using these three models to study the mechanical properties of tensegrity-membrane systems. Two control strategies are developed to regulate the deployment process of tensegrity-membrane systems. The first control strategy is to deploy the system by a nonlinear adaptive controller and use a linear H∞ controller for rapid system stabilization. The second control strategy is to regulate the dynamics of tensegrity-membrane systems using a linear parameter-varying (LPV) controller during system deployment. A gridding method is employed to discretize the system operational region in order to carry out the LPV control synthesis.
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    Strain-level identification of bacterial tomato pathogens directly from metagenomic sequences
    Mechan Llontop, Marco Enrique; Sharma, Parul; Aguilera Flores, Marcela; Yang, Shu; Pollock, Jill; Tian, Long; Huang, Chengjie; Rideout, Steven L.; Heath, Lenwood S.; Li, Song; Vinatzer, Boris A. (Scientific Societies, 2019-12-12)
    Routine strain-level identification of plant pathogens directly from symptomatic tissue could significantly improve plant disease control and prevention. Here we tested the Oxford Nanopore Technologies (ONT) MinIONTM sequencer for metagenomic sequencing of tomato plants either artificially inoculated with a known strain of the bacterial speck pathogen Pseudomonas syringae pv. tomato (Pto), or collected in the field and showing bacterial spot symptoms caused by either one of four Xanthomonas species. After species-level identification using ONT's WIMP software and the third party tools Sourmash and MetaMaps, we used Sourmash and MetaMaps with a custom database of representative genomes of bacterial tomato pathogens to attempt strain-level identification. In parallel, each metagenome was assembled and the longest contigs were used as query with the genome-based microbial identification Web service LINbase. Both the read-based and assembly-based approaches correctly identified Pto strain T1 in the artificially inoculated samples. The pathogen strain in most field samples was identified as a member of Xanthomonas perforans group 2. This result was confirmed by whole genome sequencing of colonies isolated from one of the samples. Although in our case, metagenome-based pathogen identification at the strain-level was achieved, caution still needs to be exerted when interpreting strain-level results because of the challenges inherent to assigning reads to specific strains and the error rate of nanopore sequencing.