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At least 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Identifying impacts of contact tracing on HIV epidemiological inference from phylogenetic data

Abstract Robust sampling methods are foundational to inferences using phylogenies. Yet the impact of using contact tracing, a type of non-uniform sampling used in public health applications such as infectious disease outbreak investigations, has not been investigated in the molecular epidemiology field. To understand how contact tracing influences a recovered phylogeny, we developed a new simulation tool called SEEPS (Sequence Evolution and Epidemiological Process Simulator) that allows for the simulation of contact tracing and the resulting transmission tree, pathogen phylogeny, and corresponding virus genetic sequences. Importantly, SEEPS takes within-host evolution into account when generating pathogen phylogenies and sequences from transmission histories. Using SEEPS, we demonstrate that contact tracing can significantly impact the structure of the resulting tree, as described by popular tree statistics. Contact tracing generates phylogenies that are less balanced than the underlying transmission process, less representative of the larger epidemiological process, and affects the internal/external branch length ratios that characterize specific epidemiological scenarios. We also examined real data from a 2007–2008 Swedish HIV-1 outbreak and the broader 1998–2010 European HIV-1 epidemic to highlight the differences in contact tracing and expected phylogenies. Aided by SEEPS, we show that the data collection of the Swedish outbreak was strongly influenced by contact tracing even after downsampling, while the broader European Union epidemic showed little evidence of universal contact tracing, agreeing with the known epidemiological information about sampling and spread. Overall, our results highlight the importance of including possible non-uniform sampling schemes when examining phylogenetic trees. For that, SEEPS serves as a useful tool to evaluate such impacts, thereby facilitating better phylogenetic inferences of the characteristics of a disease outbreak. SEEPS is available at https://github.com/MolEvolEpid/SEEPS.

Virology↗
DOE OSTI2021

The Switchgrass Microbiome: A Review of Structure, Function, and Taxonomic Distribution

Switchgrass (Panicum virgatum L.) has been championed as a promising bioenergy crop due to its high productivity across a wide environmental range. The switchgrass microbiome—including bacteria, archaea, fungi, and other microbiota inhabiting soil and plant tissues—can influence plant function substantially. We conducted a review of the literature investigating switchgrass microbiome structure, key functional roles, and taxa isolated from field-grown plants. Although site conditions and plant compartment (i.e., location within shoots, roots, or root-influenced soil) appear to be the strongest drivers of switchgrass microbiome structure, the microbiome is also shaped by climate, season, and host genotype. Studies comparing across plant species show that the switchgrass microbiome is more similar to the microbiomes of other perennial plants than to the microbiomes of annual plants. Members of the switchgrass microbiome confer several benefits to their host. Most notably, mycorrhizal fungi can increase plant biomass many-fold, associative nitrogen-fixing bacteria can provide a substantial portion of the plant’s nitrogen demand, and fungal endophytes can improve plant tolerance to drought. Although the fungi and bacteria cultured from switchgrass represent only a portion of the microbiome, these serve as a valuable resource for researchers interested in investigating functional outcomes of the switchgrass microbiome. We highlight areas where additional research is necessary for a more comprehensive understanding of switchgrass microbiome structure, function, and potential to enhance sustainable bioenergy production. Key gaps include the role of understudied organisms (e.g., viruses, microeukaryotes, and nonmycorrhizal fungi), multitrophic relationships, mechanisms underpinning switchgrass–microbiome interactions, and field-scale validation of experimental findings.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Crystal structures of ‘ALternative Isoinformational ENgineered’ DNA in B-form

The first structural model of duplex DNA reported in 1953 by Watson & Crick presented the double helix in B-form, the form that genomic DNA exists in much of the time. Thus, artificial DNA seeking to mimic the properties of natural DNA should also be able to adopt B-form. Using a host–guest system in which Moloney murine leukemia virus reverse transcriptase serves as the host and DNA as the guests, we determined high-resolution crystal structures of three complexes including 5'-CTTBPPBBSSZZSAAG, 5'-CTTSSPBZPSZBBAAG and 5'-CTTZZPBSBSZPPAAG with 10 consecutive unnatural nucleobase pairs in B-form within self-complementary 16 bp duplex oligonucleotides. We refer to this ALternative Isoinformational ENgineered (ALIEN) genetic system containing two nucleobase pairs (P:Z, pairing 2-amino-imidazo-[1,2-a]-1,3,5-triazin-(8H)-4-one with 6-amino-5-nitro-(1H)-pyridin-2-one, and B:S, 6-amino-4-hydroxy-5-(1H)-purin-2-one with 3-methyl-6-amino-pyrimidin-2-one) as ALIEN DNA. We characterized both position- and sequence-specific helical, nucleobase pair and dinucleotide step parameters of P:Z and B:S pairs in the context of B-form DNA. We conclude that ALIEN DNA exhibits structural features that vary with sequence. Further, Z can participate in alternative stacking modes within a similar sequence context as captured in two different structures. This finding suggests that ALIEN DNA may have a larger repertoire of B-form structures than natural DNA.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Mediation of Colloidal Encounter Dynamics by Surface Roughness

Rigorous understanding on the self-assembly of colloidal nanocrystals is crucial to develop tailored nanostructured materials for energy storage, sensing, and optical fields. Despite extensive studies on the self-assembly, a mechanistic understanding of self-assembly under an external field still remains an ongoing challenge. Here, in this work, we used optical tweezers that impose an external attractive force field, resulting in the self-assembly of alpha-phase sodium yttrium fluoride nanocrystals. The dynamic force that is strongly dependent on the surface roughness of the nanocrystals is shown to be a decisive factor for a direct contact between the nanocrystals, manifested by the roughness-dependent hydrodynamic resistivity and Langevin dynamic simulations. Our study provides direct evidence that the role of dynamics is equally important in understanding the self-assembly, which has been rarely observed in the self-assembly in contrast with many studies on the equilibrium forces. These results may have further impact in other fields, such as having explanatory power for the probability of nonclassical crystal growth or the structure of viral spike proteins that affect the probability of viruses binding with cells.

Felsted, Robert G. [Univ. of Washington, Seattle, ↗
DOE OSTI2021

Bayesian estimations of orientation distribution functions from small-angle scattering enable direct prediction of mechanical stress in anisotropic materials

Properties of soft materials are influenced by their anisotropic structuring under nonequilibrium fields. Although anisotropic structure-property relationships have been extensively explored theoretically, comparison to experiments requires determination of the microstructural orientation probability distribution function (OPDF) of microstructural elements. Small angle scattering (SAS) measurements encode information about the OPDF, but tools to navigate this connection are incomplete. Here, we develop and validate an explicit framework to link arbitrary OPDFs to SAS measurements. Specifically, we propose, validate, and apply a method, maximum a posteriori scattering inference (MAPSI), whereby the OPDF may be obtained from SAS measurements using a Bayesian estimation method. Using this method, we obtain estimates of the full 3D OPDF for two model semidilute fd-virus (rodlike) dispersions at concentrations that are approximately equal to and twice the overlap concentration. From the OPDF, we calculate its second and fourth moments and compare these to predictions for a dilute suspension of rigid rods and to a recent theory for semidilute suspensions. Finally, we use both the theoretical and measured moments to calculate the stress, both for dilute and semidilute suspensions. These predictions are not only compared to each other, but also to measured values of the shear stress, and point to new insights into the behavior of suspensions of highly elongated particles in the transition between dilute and semidilute behavior. We also use this new framework to provide perspective on the connection between scalar parameterizations of scattering and the OPDF that have frequently been used in the past. Here, the new tools developed in this work provide an unprecedented path toward experimental validation of dynamical theories of rodlike colloids and polymers, and for measurement of nonequilibrium structures and stresses of other complex fluids and soft materials with SAS.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Coordinate-based simulation of pair distance distribution functions for small and large molecular assemblies: implementation and applications

X-ray scattering has become a major tool in the structural characterization of nanoscale materials. Thanks to the widely available experimental and computational atomic models, coordinate-based X-ray scattering simulation has played a crucial role in data interpretation in the past two decades. However, simulation of real-space pair distance distribution functions (PDDFs) from small- and wide-angle X-ray scattering, SAXS/WAXS, has been relatively less exploited. This study presents a comparison of PDDF simulation methods, which are applied to molecular structures that range in size from β-cyclodextrin [1 kDa molecular weight (MW), 66 non-hydrogen atoms] to the satellite tobacco mosaic virus capsid (1.1 MDa MW, 81 960 non-hydrogen atoms). The results demonstrate the power of interpretation of experimental SAXS/WAXS from the real-space view, particularly by providing a more intuitive method for understanding of partial structure contributions. Furthermore, the computational efficiency of PDDF simulation algorithms makes them attractive as approaches for the analysis of large nanoscale materials and biological assemblies. The simulation methods demonstrated in this article have been implemented in stand-alone software, SolX 3.0 , which is available to download from https://12idb.xray.aps.anl.gov/solx.html.

Zuo, Xiaobing (ORCID:0000000201344804)↗
DOE OSTI2020

Crystal structures of SARS-CoV-2 ADP-ribose phosphatase: from the apo form to ligand complexes

Among 15 nonstructural proteins (Nsps), the newly emerging Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) encodes a large, multidomain Nsp3. One of its units is the ADP-ribose phosphatase domain (ADRP; also known as the macrodomain, MacroD), which is believed to interfere with the host immune response. Such a function appears to be linked to the ability of the protein to remove ADP-ribose from ADP-ribosylated proteins and RNA, yet the precise role and molecular targets of the enzyme remain unknown. Here, five high-resolution (1.07–2.01 Å) crystal structures corresponding to the apo form of the protein and its complexes with 2-(N-morpholino)ethanesulfonic acid (MES), AMP and ADP-ribose have been determined. The protein is shown to undergo conformational changes to adapt to the ligand in the manner previously observed in close homologues from other viruses. A conserved water molecule is also identified that may participate in hydrolysis. This work builds foundations for future structure-based research on ADRP, including the search for potential antiviral therapeutics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Room-temperature X-ray crystallography reveals the oxidation and reactivity of cysteine residues in SARS-CoV-2 3CL Mpro: insights into enzyme mechanism and drug design

The emergence of the novel coronavirus SARS-CoV-2 has resulted in a worldwide pandemic not seen in generations. Creating treatments and vaccines to battle COVID-19, the disease caused by the virus, is of paramount importance in order to stop its spread and save lives. The viral main protease, 3CL M pro , is indispensable for the replication of SARS-CoV-2 and is therefore an important target for the design of specific protease inhibitors. Detailed knowledge of the structure and function of 3CL M pro is crucial to guide structure-aided and computational drug-design efforts. Here, the oxidation and reactivity of the cysteine residues of the protease are reported using room-temperature X-ray crystallography, revealing that the catalytic Cys145 can be trapped in the peroxysulfenic acid oxidation state at physiological pH, while the other surface cysteines remain reduced. Only Cys145 and Cys156 react with the alkylating agent N -ethylmaleimide. It is suggested that the zwitterionic Cys145–His45 catalytic dyad is the reactive species that initiates catalysis, rather than Cys145-to-His41 proton transfer via the general acid–base mechanism upon substrate binding. The structures also provide insight into the design of improved 3CL M pro inhibitors.

3CL Mpro↗
DOE OSTI2020

FiXR : a framework to reconstruct fiber cross-sections from X-ray fiber diffraction experiments

Ab initio reconstruction methods have revolutionized the capabilities of small-angle X-ray scattering (SAXS), allowing the data-driven discovery of previously unknown molecular conformations, exploiting optimization heuristics and assumptions behind the composition of globular molecules. While these methods have been successful for the analysis of small particles, their impact on fibrillar assemblies has been more limited. The micrometre-range size of these assemblies and the complex interaction of their periodicities in their scattering profiles indicate that the discovery of fibril structures from SAXS measurements requires novel approaches beyond extending existing tools for molecular discovery. In this work, it is proposed to use SAXS measurements, together with diffraction theory, to infer the electron distribution of the average cross-section of a fiber. This cross-section is modeled as a discrete electron density with continuous support, allowing representations beyond binary distributions. Additional constraints, such as non-negativity or smoothness/connectedness, can also be added to the framework. The proposed approach is tested using simulated SAXS data from amyloid β fibril models and using measured data of Tobacco mosaic virus from SAXS experiments, recovering the geometry and density of the cross-sections in all cases. The approach is further tested by analyzing SAXS data from different amyloid β fibril assemblies, with results that are in agreement with previously proposed models from cryo-EM measurements. The limitations of the proposed method, together with an analysis of the robustness of the method and the combination with different experimental sources, are also discussed.

Biochemistry & Molecular Biology↗
DOE OSTI2026

Deep-learning methods for contrast enhancement and artifact reduction in cryo-electron tomography: a systematic analysis of the state of the art and proposed improvements

Cryo-electron tomography (cryo-ET) has emerged as the preferred technique for visualizing the organization of macromolecular complexes in situ and resolving their structures at subnanometre resolution [Tegunov et al. (2021)View full citation, Nat. Methods, 18, 186–193]. Despite improvements in data quality as a result of advances in detector technology, microscope stability and stage precision, the analysis and interpretation of tomograms remains challenging due to a low signal-to-noise ratio and reconstruction artifacts stemming from experimental constraints in specimen tilt during data collection resulting in a missing wedge in the Fourier space. Recently, self-supervised deep-learning methods have been proposed for contrast enhancement and reduction of resolution anisotropy in reconstructed tomograms. Here, we evaluate several state-of-the-art deep-learning methods which aim to improve the interpretability of cryo-ET reconstructions, with a focus on their performance on downstream tasks of template matching, sub­tomogram averaging and segmentation. We propose new training architectures and a loss function based on Fourier shell correlation that show improved performance over the standard U-Net with L1/L2 losses. We demonstrate our analysis on four diverse experimental datasets: purified 80S ribosomes, in situ Chlamydomonas reinhardtii, immature HIV-1 virus-like particles and INS-1E cells.

contrast enhancement↗
DOE OSTI2022

How Distinct Structural Flexibility within SARS-CoV-2 Spike Protein Reveals Potential Therapeutic Targets

The emergence and rapid worldwide spread of the novel coronavirus disease, COVID-19, has prompted concerted efforts to find successful treatments. The causative virus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), uses its spike (S) protein to gain entry into host cells. Therefore, the S protein presents a viable target to develop a directed therapy. Here, we deployed an integrated artificial intelligence with all-atom molecular dynamics simulation approach to provide new details of the S protein structure. Based on a comprehensive structural analysis of S proteins from SARS-CoV-2 and previous human coronaviruses, we found that the protomer state of S proteins is structurally flexible. Without the presence of a stabilizing beta sheet from another protomer chain, two regions in the S2 domain and the hinge connecting the S1 and S2 subunits lose their secondary structures. Interestingly, the region in the S2 domain was previously identified as an immunodominant site in the SARS-CoV-1 S protein. We anticipate that the molecular details elucidated here will assist in effective therapeutic development for COVID-19.

Chen, Serena↗
DOE OSTI2021

A Remote Development Process and Platform for Power Electronic Systems

Like many areas in research and development, power electronic and distributed energy resource research and development slowed during the COVID pandemic. While the presence of the virus has reduced and workers are returning to shared offices, uncertainty of potential future challenges are still present. This work proposes a development and testing network that provides researchers the ability to operate remotely and coordinate control and debug activities for power electronic systems. This development and testing network has been demonstrated in both controller hardware-in-the-loop (C-HIL) and hardware testing.

Starke, Michael↗
DOE OSTI2021

Genome‐enabled exploration of microbial ecology and evolution in the sea: a rising tide lifts all boats

Summary As a young bacteriologist just launching my career during the early days of the ‘microbial revolution’ in the 1980s, I was fortunate to participate in some early discoveries, and collaborate in the development of cross‐disciplinary methods now commonly referred to as "metagenomics". My early scientific career focused on applying phylogenetic and genomic approaches to characterize ‘wild’ bacteria, archaea and viruses in their natural habitats, with an emphasis on marine systems. These central interests have not changed very much for me over the past three decades, but knowledge, methodological advances and new theoretical perspectives about the microbial world certainly have. In this invited ‘How we did it’ perspective, I trace some of the trajectories of my lab's collective efforts over the years, including phylogenetic surveys of microbial assemblages in marine plankton and sediments, development of microbial community gene‐ and genome‐enabled surveys, and application of genome‐guided, cultivation‐independent functional characterization of novel enzymes, pathways and their relationships to in situ biogeochemistry. Throughout this short review, I attempt to acknowledge, all the mentors, students, postdocs and collaborators who enabled this research. Inevitably, a brief autobiographical review like this cannot be fully comprehensive, so sincere apologies to any of my great colleagues who are not explicitly mentioned herein. I salute you all as well!

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Community‐Level Metabolic Shifts Following Land Use Change in the Amazon Rainforest Identified by a Supervised Machine Leaning Approach

ABSTRACT The Amazon rainforest has been subjected to high rates of deforestation, mostly for pasturelands, over the last few decades. This change in plant cover is known to alter the soil microbiome and the functions it mediates, but the genomic changes underlying this response are still unresolved. In this study, we used a combination of deep shotgun metagenomics complemented by a supervised machine learning approach to compare the metabolic strategies of tropical soil microbial communities in pristine forests and long‐term established pastures in the Amazon. Machine learning‐derived metagenome analysis indicated that microbial community structures (bacteria, archaea and viruses) and the composition of protein‐coding genes were distinct in each plant cover type environment. Forest and pasture soils had different genomic diversities for the above three taxonomic groups, characterised by their protein‐coding genes. These differences in metagenome profiles in soils under forests and pastures suggest that metabolic strategies related to carbohydrate and energy metabolisms were altered at community level. Changes were also consistent with known modifications to the C and N cycles caused by long‐term shifts in aboveground vegetation and were also associated with several soil physicochemical properties known to change with land use, such as the C/N ratio, soil temperature and exchangeable acidity. In addition, our analysis reveals that these alterations in land use can also result in changes to the composition and diversity of the soil DNA virome. Collectively, our study indicates that soil microbial communities shift their overall metabolic strategies, driven by genomic alterations observed in pristine forests and long‐term established pastures with implications for the C and N cycles.

carbon and nitrogen cycles↗
DOE OSTI2020

Antibody dynamics to SARS‐CoV‐2 in asymptomatic COVID‐19 infections

Abstract Background The missing asymptomatic COVID‐19 infections have been overlooked because of the imperfect sensitivity of the nucleic acid testing (NAT). Globally understanding the humoral immunity in asymptomatic carriers will provide scientific knowledge for developing serological tests, improving early identification, and implementing more rational control strategies against the pandemic. Measure Utilizing both NAT and commercial kits for serum IgM and IgG antibodies, we extensively screened 11 766 epidemiologically suspected individuals on enrollment and 63 asymptomatic individuals were detected and recruited. Sixty‐three healthy individuals and 51 mild patients without any preexisting conditions were set as controls. Serum IgM and IgG profiles were further probed using a SARS‐CoV‐2 proteome microarray, and neutralizing antibody was detected by a pseudotyped virus neutralization assay system. The dynamics of antibodies were analyzed with exposure time or symptoms onset. Results A combination test of NAT and serological testing for IgM antibody discovered 55.5% of the total of 63 asymptomatic infections, which significantly raises the detection sensitivity when compared with the NAT alone (19%). Serum proteome microarray analysis demonstrated that asymptomatics mainly produced IgM and IgG antibodies against S1 and N proteins out of 20 proteins of SARS‐CoV‐2. Different from strong and persistent N‐specific antibodies, S1‐specific IgM responses, which evolved in asymptomatic individuals as early as the seventh day after exposure, peaked on days from 17 days to 25 days, and then disappeared in two months, might be used as an early diagnostic biomarker. 11.8% (6/51) mild patients and 38.1% (24/63) asymptomatic individuals did not produce neutralizing antibody. In particular, neutralizing antibody in asymptomatics gradually vanished in two months. Conclusion Our findings might have important implications for the definition of asymptomatic COVID‐19 infections, diagnosis, serological survey, public health, and immunization strategies.

Lei, Qing↗
DOE OSTI2020

The Potential of Low Molecular Weight Heparin to Mitigate Cytokine Storm in Severe COVID‐19 Patients: A Retrospective Cohort Study

On March 11, 2020, the World Health Organization declared its assessment of coronavirus disease 2019 (COVID‐19) as a global pandemic. However, specific anti‐severe acute respiratory syndrome‐coronavirus 2 (SARS‐CoV‐2) drugs are still under development, and patients are managed by multiple complementary treatments. We performed a retrospective analysis to compare and evaluate the effect of low molecular weight heparin (LMWH) treatment on disease progression. For this purpose, the clinical records and laboratory indicators were extracted from electronic medical records of 42 patients with COVID‐19 (21 of whom were treated with LMWH, and 21 without LMWH) hospitalized (Union Hospital of Huazhong University of Science and Technology) from February 1 to March 15, 2020. Changes in the percentage of lymphocytes before and after LMWH treatment were significantly different from those in the control group ( P = 0.011). Likewise, changes in the levels of D‐dimer and fibrinogen degradation products in the LMWH group before and after treatment were significantly different from those in the control group ( P = 0.035). Remarkably, IL‐6 levels were significantly reduced after LMWH treatment ( P = 0.006), indicating that, besides other beneficial properties, LMWH may exert an anti‐inflammatory effect and attenuate in part the “cytokine storm” induced by the virus. Our results support the use of LMWH as a potential therapeutic drug for the treatment of COVID‐19, paving the way for a subsequent well‐controlled clinical study.

Shi, Chen↗
DOE OSTI2021

Control of airborne infectious disease in buildings: Evidence and research priorities

The evolution of SARS-CoV-2 virus has resulted in variants likely to be more readily transmitted through respiratory aerosols, underscoring the increased potential for indoor environmental controls to mitigate risk. Use of tight-fitting face masks to trap infectious aerosol in exhaled breath and reduce inhalation exposure to contaminated air is of critical importance for disease control. Administrative controls including the regulation of occupancy and interpersonal spacing are also important, while presenting social and economic challenges. Indoor engineering controls including ventilation, exhaust, air flow control, filtration, and disinfection by germicidal ultraviolet irradiation can reduce reliance on stringent occupancy restrictions. However, the effects of controls-individually and in combination-on reducing infectious aerosol transfer indoors remain to be clearly characterized to the extent needed to support widespread implementation by building operators. We review aerobiologic and epidemiologic evidence of indoor environmental controls against transmission and present a quantitative aerosol transfer scenario illustrating relative differences in exposure at close-interactive, room, and building scales. We identify an overarching need for investment to implement building controls and evaluate their effectiveness on infection in well-characterized and real-world settings, supported by specific, methodological advances. Finally, improved understanding of engineering control effectiveness guides implementation at scale while considering occupant comfort, operational challenges, and energy costs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

The JA‐responsive MYC2‐ BADH ‐ like transcriptional regulatory module in Poncirus trifoliata contributes to cold tolerance by modulation of glycine betaine biosynthesis

Summary Glycine betaine (GB) is known to accumulate in plants exposed to cold, but the underlying molecular mechanisms and associated regulatory network remain unclear. Here, we demonstrated that PtrMYC2 of Poncirus trifoliata integrates the jasmonic acid (JA) signal to modulate cold‐induced GB accumulation by directly regulating PtrBADH‐l , a betaine aldehyde dehydrogenase (BADH)‐like gene. PtrBADH‐l was identified based on transcriptome and expression analysis in P. trifoliata . Overexpression and VIGS (virus‐induced gene silencing)‐mediated knockdown showed that PtrBADH‐l plays a positive role in cold tolerance and GB synthesis. Yeast one‐hybrid library screening using PtrBADH‐l promoter as baits unraveled PtrMYC2 as an interacting candidate. PtrMYC2 was confirmed to directly bind to two G‐box cis ‐acting elements within PtrBADH‐l promoter and acts as a transcriptional activator. In addition, PtrMYC2 functions positively in cold tolerance through modulation of GB synthesis by regulating PtrBADH‐l expression. Interestingly, we found that GB accumulation under cold stress was JA‐dependent and that PtrMYC2 orchestrates JA‐mediated PtrBADH‐l upregulation and GB accumulation. This study sheds new light on the roles of MYC2 homolog in modulating GB synthesis. In particular, we propose a transcriptional regulatory module PtrMYC2‐PtrBADH‐l to advance the understanding of molecular mechanisms underlying the GB accumulation under cold stress.

Ming, Ruhong↗