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1.
Proc Natl Acad Sci U S A ; 121(21): e2316497121, 2024 May 21.
Article in English | MEDLINE | ID: mdl-38739807

ABSTRACT

Decreased production of crops due to climate change has been predicted scientifically. While climate-resilient crops are necessary to ensure food security and support sustainable agriculture, predicting crop growth under future global warming is challenging. Therefore, we aimed to assess the impact of realistic global warming conditions on rice cultivation. We developed a crop evaluation platform, the agro-environment (AE) emulator, which generates diverse environments by implementing the complexity of natural environmental fluctuations in customized, fully artificial lighting growth chambers. We confirmed that the environmental responsiveness of rice obtained in the fluctuation of artificial environments is similar to those exhibited in natural environments by validating our AE emulator using publicly available meteorological data from multiple years at the same location and multiple locations in the same year. Based on the representative concentration pathway, real-time emulation of severe global warming unveiled dramatic advances in the rice life cycle, accompanied by a 35% decrease in grain yield and an 85% increase in quality deterioration, which is higher than the recently reported projections. The transcriptome dynamism showed that increasing temperature and CO2 concentrations synergistically changed the expression of various genes and strengthened the induction of flowering, heat stress adaptation, and CO2 response genes. The predicted severe global warming greatly alters rice environmental adaptability and negatively impacts rice production. Our findings offer innovative applications of artificial environments and insights for enhancing varietal potential and cultivation methods in the future.


Subject(s)
Global Warming , Oryza , Oryza/growth & development , Oryza/genetics , Climate Change , Crops, Agricultural/growth & development , Carbon Dioxide/metabolism , Carbon Dioxide/analysis , Agriculture/methods , Gene Expression Regulation, Plant , Temperature , Transcriptome
2.
Am J Hum Genet ; 110(9): 1522-1533, 2023 09 07.
Article in English | MEDLINE | ID: mdl-37607538

ABSTRACT

Population-scale biobanks linked to electronic health record data provide vast opportunities to extend our knowledge of human genetics and discover new phenotype-genotype associations. Given their dense phenotype data, biobanks can also facilitate replication studies on a phenome-wide scale. Here, we introduce the phenotype-genotype reference map (PGRM), a set of 5,879 genetic associations from 523 GWAS publications that can be used for high-throughput replication experiments. PGRM phenotypes are standardized as phecodes, ensuring interoperability between biobanks. We applied the PGRM to five ancestry-specific cohorts from four independent biobanks and found evidence of robust replications across a wide array of phenotypes. We show how the PGRM can be used to detect data corruption and to empirically assess parameters for phenome-wide studies. Finally, we use the PGRM to explore factors associated with replicability of GWAS results.


Subject(s)
Biological Specimen Banks , Data Science , Humans , Phenomics , Phenotype , Genotype
3.
Brief Bioinform ; 25(3)2024 Mar 27.
Article in English | MEDLINE | ID: mdl-38557678

ABSTRACT

Disease ontologies facilitate the semantic organization and representation of domain-specific knowledge. In the case of prostate cancer (PCa), large volumes of research results and clinical data have been accumulated and needed to be standardized for sharing and translational researches. A formal representation of PCa-associated knowledge will be essential to the diverse data standardization, data sharing and the future knowledge graph extraction, deep phenotyping and explainable artificial intelligence developing. In this study, we constructed an updated PCa ontology (PCAO2) based on the ontology development life cycle. An online information retrieval system was designed to ensure the usability of the ontology. The PCAO2 with a subclass-based taxonomic hierarchy covers the major biomedical concepts for PCa-associated genotypic, phenotypic and lifestyle data. The current version of the PCAO2 contains 633 concepts organized under three biomedical viewpoints, namely, epidemiology, diagnosis and treatment. These concepts are enriched by the addition of definition, synonym, relationship and reference. For the precision diagnosis and treatment, the PCa-associated genes and lifestyles are integrated in the viewpoint of epidemiological aspects of PCa. PCAO2 provides a standardized and systematized semantic framework for studying large amounts of heterogeneous PCa data and knowledge, which can be further, edited and enriched by the scientific community. The PCAO2 is freely available at https://bioportal.bioontology.org/ontologies/PCAO, http://pcaontology.net/ and http://pcaontology.net/mobile/.


Subject(s)
Biological Ontologies , Prostatic Neoplasms , Humans , Male , Artificial Intelligence , Semantics , Prostatic Neoplasms/genetics
4.
Mol Cell ; 69(2): 321-333.e3, 2018 01 18.
Article in English | MEDLINE | ID: mdl-29351850

ABSTRACT

We have developed a highly parallel strategy, systematic gene-to-phenotype arrays (SGPAs), to comprehensively map the genetic landscape driving molecular phenotypes of interest. By this approach, a complete yeast genetic mutant array is crossed with fluorescent reporters and imaged on membranes at high density and contrast. Importantly, SGPA enables quantification of phenotypes that are not readily detectable in ordinary genetic analysis of cell fitness. We benchmark SGPA by examining two fundamental biological phenotypes: first, we explore glucose repression, in which SGPA identifies a requirement for the Mediator complex and a role for the CDK8/kinase module in regulating transcription. Second, we examine selective protein quality control, in which SGPA identifies most known quality control factors along with U34 tRNA modification, which acts independently of proteasomal degradation to limit misfolded protein production. Integration of SGPA with other fluorescent readouts will enable genetic dissection of a wide range of biological pathways and conditions.


Subject(s)
High-Throughput Nucleotide Sequencing/methods , High-Throughput Screening Assays/methods , Cyclin-Dependent Kinase 8/genetics , Gene Regulatory Networks , Genotype , Mediator Complex/genetics , Oligonucleotide Array Sequence Analysis , Phenotype , Saccharomyces cerevisiae/genetics , Saccharomyces cerevisiae Proteins/genetics
5.
Proc Natl Acad Sci U S A ; 120(44): e2310134120, 2023 Oct 31.
Article in English | MEDLINE | ID: mdl-37878725

ABSTRACT

Plants exude specialized metabolites from their roots, and these compounds are known to structure the root microbiome. However, the underlying mechanisms are poorly understood. We established a representative collection of maize root bacteria and tested their tolerance against benzoxazinoids (BXs), the dominant specialized and bioactive metabolites in the root exudates of maize plants. In vitro experiments revealed that BXs inhibited bacterial growth in a strain- and compound-dependent manner. Tolerance against these selective antimicrobial compounds depended on bacterial cell wall structure. Further, we found that native root bacteria isolated from maize tolerated the BXs better compared to nonhost Arabidopsis bacteria. This finding suggests the adaptation of the root bacteria to the specialized metabolites of their host plant. Bacterial tolerance to 6-methoxy-benzoxazolin-2-one (MBOA), the most abundant and selective antimicrobial metabolite in the maize rhizosphere, correlated significantly with the abundance of these bacteria on BX-exuding maize roots. Thus, strain-dependent tolerance to BXs largely explained the abundance pattern of bacteria on maize roots. Abundant bacteria generally tolerated MBOA, while low abundant root microbiome members were sensitive to this compound. Our findings reveal that tolerance to plant specialized metabolites is an important competence determinant for root colonization. We propose that bacterial tolerance to root-derived antimicrobial compounds is an underlying mechanism determining the structure of host-specific microbial communities.


Subject(s)
Anti-Infective Agents , Arabidopsis , Microbiota , Zea mays/metabolism , Plant Roots/metabolism , Bacteria/metabolism , Plants/metabolism , Rhizosphere , Benzoxazines/pharmacology , Benzoxazines/metabolism , Arabidopsis/metabolism , Anti-Infective Agents/metabolism , Soil Microbiology
6.
Plant J ; 117(2): 632-646, 2024 Jan.
Article in English | MEDLINE | ID: mdl-37871136

ABSTRACT

Plants are sessile organisms that constantly adapt to their changing environment. The root is exposed to numerous environmental signals ranging from nutrients and water to microbial molecular patterns. These signals can trigger distinct responses including the rapid increase or decrease of root growth. Consequently, using root growth as a readout for signal perception can help decipher which external cues are perceived by roots, and how these signals are integrated. To date, studies measuring root growth responses using large numbers of roots have been limited by a lack of high-throughput image acquisition, poor scalability of analytical methods, or low spatiotemporal resolution. Here, we developed the Root Walker pipeline, which uses automated microscopes to acquire time-series images of many roots exposed to controlled treatments with high spatiotemporal resolution, in conjunction with fast and automated image analysis software. We demonstrate the power of Root Walker by quantifying root growth rate responses at different time and throughput scales upon treatment with natural auxin and two mitogen-associated protein kinase cascade inhibitors. We find a concentration-dependent root growth response to auxin and reveal the specificity of one MAPK inhibitor. We further demonstrate the ability of Root Walker to conduct genetic screens by performing a genome-wide association study on 260 accessions in under 2 weeks, revealing known and unknown root growth regulators. Root Walker promises to be a useful toolkit for the plant science community, allowing large-scale screening of root growth dynamics for a variety of purposes, including genetic screens for root sensing and root growth response mechanisms.


Subject(s)
Genome-Wide Association Study , Plant Roots , Plant Roots/metabolism , Indoleacetic Acids/metabolism , Signal Transduction , Image Processing, Computer-Assisted/methods
7.
Plant J ; 117(3): 713-728, 2024 Feb.
Article in English | MEDLINE | ID: mdl-37964699

ABSTRACT

Genome-wide association studies (GWAS) identified thousands of genetic loci associated with complex plant traits, including many traits of agronomical importance. However, functional interpretation of GWAS results remains challenging because of large candidate regions due to linkage disequilibrium. High-throughput omics technologies, such as genomics, transcriptomics, proteomics and metabolomics open new avenues for integrative systems biological analyses and help to nominate systems information supported (prime) candidate genes. In the present study, we capitalise on a diverse canola population with 477 spring-type lines which was previously analysed by high-throughput phenotyping of growth-related traits and by RNA sequencing and metabolite profiling for multi-omics-based hybrid performance prediction. We deepened the phenotypic data analysis, now providing 123 time-resolved image-based traits, to gain insight into the complex relations during early vegetative growth and reanalysed the transcriptome data based on the latest Darmor-bzh v10 genome assembly. Genome-wide association testing revealed 61 298 robust quantitative trait loci (QTL) including 187 metabolite QTL, 56814 expression QTL and 4297 phenotypic QTL, many clustered in pronounced hotspots. Combining information about QTL colocalisation across omics layers and correlations between omics features allowed us to discover prime candidate genes for metabolic and vegetative growth variation. Prioritised candidate genes for early biomass accumulation include A06p05760.1_BnaDAR (PIAL1), A10p16280.1_BnaDAR, C07p48260.1_BnaDAR (PRL1) and C07p48510.1_BnaDAR (CLPR4). Moreover, we observed unequal effects of the Brassica A and C subgenomes on early biomass production.


Subject(s)
Genome-Wide Association Study , Multiomics , Quantitative Trait Loci/genetics , Genomics , Phenotype
8.
Plant J ; 119(4): 2080-2095, 2024 Aug.
Article in English | MEDLINE | ID: mdl-38860937

ABSTRACT

Stem is important for assimilating transport and plant strength; however, less is known about the genetic basis of its structural characteristics. In this study, a high-throughput method, "LabelmeP rice" was developed to generate 14 traits related to stem regions and vascular bundles, which allows the establishment of a stem cross-section phenotype dataset containing anatomical information of 1738 images from hand-cut transections of stems collected from 387 rice germplasm accessions grown over two successive seasons. Then, the phenotypic diversity of the rice accessions was evaluated. Genome-wide association studies identified 94, 83, and 66 significant single nucleotide polymorphisms (SNPs) for the assayed traits in 2 years and their best linear unbiased estimates, respectively. These SNPs can be integrated into 29 quantitative trait loci (QTL), and 11 of them were common in 2 years, while correlated traits shared 19. In addition, 173 candidate genes were identified, and six located at significant SNPs were repeatedly detected and annotated with a potential function in stem development. By using three introgression lines (chromosome segment substitution lines), four of the 29 QTLs were validated. LOC_Os01g70200, located on the QTL uq1.4, is detected for the area of small vascular bundles (SVB) and the rate of large vascular bundles number to SVB number. Besides, the CRISPR/Cas9 editing approach has elucidated the function of the candidate gene LOC_Os06g46340 in stem development. In conclusion, the results present a time- and cost-effective method that provides convenience for extracting rice stem anatomical traits and the candidate genes/QTL, which would help improve rice.


Subject(s)
Genome-Wide Association Study , Oryza , Phenotype , Plant Stems , Polymorphism, Single Nucleotide , Quantitative Trait Loci , Oryza/genetics , Oryza/growth & development , Quantitative Trait Loci/genetics , Plant Stems/genetics , Plant Stems/growth & development , Plant Stems/anatomy & histology , Genome, Plant/genetics
9.
Plant J ; 119(5): 2514-2537, 2024 Sep.
Article in English | MEDLINE | ID: mdl-38970620

ABSTRACT

Soil salinity is a major environmental stressor affecting agricultural productivity worldwide. Understanding plant responses to salt stress is crucial for developing resilient crop varieties. Wild relatives of cultivated crops, such as wild tomato, Solanum pimpinellifolium, can serve as a useful resource to further expand the resilience potential of the cultivated germplasm, S. lycopersicum. In this study, we employed high-throughput phenotyping in the greenhouse and field conditions to explore salt stress responses of a S. pimpinellifolium diversity panel. Our study revealed extensive phenotypic variations in response to salt stress, with traits such as transpiration rate, shoot mass, and ion accumulation showing significant correlations with plant performance. We found that while transpiration was a key determinant of plant performance in the greenhouse, shoot mass strongly correlated with yield under field conditions. Conversely, ion accumulation was the least influential factor under greenhouse conditions. Through a Genome Wide Association Study, we identified candidate genes not previously associated with salt stress, highlighting the power of high-throughput phenotyping in uncovering novel aspects of plant stress responses. This study contributes to our understanding of salt stress tolerance in S. pimpinellifolium and lays the groundwork for further investigations into the genetic basis of these traits, ultimately informing breeding efforts for salinity tolerance in tomato and other crops.


Subject(s)
Genome-Wide Association Study , Phenotype , Salt Stress , Solanum , Solanum/genetics , Solanum/physiology , Salt Tolerance/genetics , Salt Tolerance/physiology
10.
Plant J ; 117(6): 1676-1701, 2024 Mar.
Article in English | MEDLINE | ID: mdl-37483133

ABSTRACT

The demand for agricultural production is becoming more challenging as climate change increases global temperature and the frequency of extreme weather events. This study examines the phenotypic variation of 149 accessions of Brachypodium distachyon under drought, heat, and the combination of stresses. Heat alone causes the largest amounts of tissue damage while the combination of stresses causes the largest decrease in biomass compared to other treatments. Notably, Bd21-0, the reference line for B. distachyon, did not have robust growth under stress conditions, especially the heat and combined drought and heat treatments. The climate of origin was significantly associated with B. distachyon responses to the assessed stress conditions. Additionally, a GWAS found loci associated with changes in plant height and the amount of damaged tissue under stress. Some of these SNPs were closely located to genes known to be involved in responses to abiotic stresses and point to potential causative loci in plant stress response. However, SNPs found to be significantly associated with a response to heat or drought individually are not also significantly associated with the combination of stresses. This, with the phenotypic data, suggests that the effects of these abiotic stresses are not simply additive, and the responses to the combined stresses differ from drought and heat alone.


Subject(s)
Brachypodium , Brachypodium/metabolism , Biodiversity , Temperature , Stress, Physiological/genetics , Gene Expression Regulation, Plant , Plant Proteins/genetics , Plant Proteins/metabolism
11.
Plant J ; 2024 Sep 02.
Article in English | MEDLINE | ID: mdl-39222478

ABSTRACT

Plant hormones are chemical signals governing almost every aspect of a plant's life cycle and responses to environmental cues. They are enmeshed within complex signaling networks that can only be deciphered by using broad-scale analytical methods to capture information about several plant hormone classes simultaneously. Methods used for this purpose are all based on reversed-phase (RP) liquid chromatography and mass spectrometric detection. Hydrophilic interaction chromatography (HILIC) is an alternative chromatographic method that performs well in analyses of biological samples. We therefore developed and validated a HILIC method for broad-scale plant hormone analysis including a rapid sample preparation procedure; moreover, derivatization or fractionation is not required. The method enables plant hormone screening focused on polar and moderately polar analytes including cytokinins, auxins, jasmonates, abscisic acid and its metabolites, salicylates, indoleamines (melatonin), and 1-aminocyclopropane-1-carboxylic acid (ACC), for a total of 45 analytes. Importantly, the major pitfalls of ACC analysis have been addressed. Furthermore, HILIC provides orthogonal selectivity to conventional RP methods and displays greater sensitivity, resulting in lower limits of quantification. However, it is less robust, so procedures to increase its reproducibility were established. The method's potential is demonstrated in a case study by employing an approach combining hormonal analysis with phenomics to examine responses of three Arabidopsis ecotypes toward three abiotic stress treatments: salinity, low nutrient availability, and their combination. The case study showcases the value of the simultaneous determination of several plant hormone classes coupled with phenomics data when unraveling processes involving complex cross-talk under diverse plant-environment interactions.

12.
Plant J ; 118(2): 584-600, 2024 Apr.
Article in English | MEDLINE | ID: mdl-38141174

ABSTRACT

Phenotyping of model organisms grown on Petri plates is often carried out manually, despite the procedures being time-consuming and laborious. The main reason for this is the limited availability of automated phenotyping facilities, whereas constructing a custom automated solution can be a daunting task for biologists. Here, we describe SPIRO, the Smart Plate Imaging Robot, an automated platform that acquires time-lapse photographs of up to four vertically oriented Petri plates in a single experiment, corresponding to 192 seedlings for a typical root growth assay and up to 2500 seeds for a germination assay. SPIRO is catered specifically to biologists' needs, requiring no engineering or programming expertise for assembly and operation. Its small footprint is optimized for standard incubators, the inbuilt green LED enables imaging under dark conditions, and remote control provides access to the data without interfering with sample growth. SPIRO's excellent image quality is suitable for automated image processing, which we demonstrate on the example of seed germination and root growth assays. Furthermore, the robot can be easily customized for specific uses, as all information about SPIRO is released under open-source licenses. Importantly, uninterrupted imaging allows considerably more precise assessment of seed germination parameters and root growth rates compared with manual assays. Moreover, SPIRO enables previously technically challenging assays such as phenotyping in the dark. We illustrate the benefits of SPIRO in proof-of-concept experiments which yielded a novel insight on the interplay between autophagy, nitrogen sensing, and photoblastic response.


Subject(s)
Germination , Seedlings , Phenotype , Germination/physiology , Seeds , Image Processing, Computer-Assisted
13.
Annu Rev Genomics Hum Genet ; 23: 383-412, 2022 08 31.
Article in English | MEDLINE | ID: mdl-35483406

ABSTRACT

Variations in the form of the human face, which plays a role in our individual identities and societal interactions, have fascinated scientists and artists alike. Here, we review our current understanding of the genetics underlying variation in craniofacial morphology and disease-associated dysmorphology, synthesizing decades of progress on Mendelian syndromes in addition to more recent results from genome-wide association studies of human facial shape and disease risk. We also discuss the various approaches used to phenotype and quantify facial shape, which are of particular importance due to the complex, multipartite nature of the craniofacial form. We close by discussing how experimental studies have contributed and will further contribute to our understanding of human genetic variation and then proposing future directions and applications for the field.


Subject(s)
Genome-Wide Association Study , Humans , Phenotype
14.
Am J Hum Genet ; 109(8): 1353-1365, 2022 08 04.
Article in English | MEDLINE | ID: mdl-35931048

ABSTRACT

Copy-number variants and structural variants (CNVs/SVs) drive many neurodevelopmental-related disorders. While many neurodevelopmental-related CNVs/SVs give rise to complex phenotypes, the overlap in phenotypic presentation between independent CNVs can be extensive and provides a motivation for shared approaches. This confluence at the level of clinical phenotype implies convergence in at least some aspects of the underlying genomic mechanisms. With this perspective, our Commission on Novel Technologies for Neurodevelopmental CNVs asserts that the time has arrived to approach neurodevelopmental-related CNVs/SVs as a class of disorders that can be identified, investigated, and treated on the basis of shared mechanisms and/or pathways (e.g., molecular, neurological, or developmental). To identify common etiologic mechanisms among uncommon neurodevelopmental-related disorders and to potentially identify common therapies, it is paramount for teams of scientists, clinicians, and patients to unite their efforts. We bring forward novel, collaborative, and integrative strategies to translational CNV/SV research that engages diverse stakeholders to help expedite therapeutic outcomes. We articulate a clear vision for piloted roadmap strategies to reduce patient/caregiver burden and redundancies, increase efficiency, avoid siloed data, and accelerate translational discovery across CNV/SV-based syndromes.


Subject(s)
Neurodevelopmental Disorders , Patient Advocacy , DNA Copy Number Variations/genetics , Genome , Humans , Neurodevelopmental Disorders/genetics , Neurodevelopmental Disorders/therapy , Phenotype
15.
Eur J Immunol ; 54(1): e2250337, 2024 Jan.
Article in English | MEDLINE | ID: mdl-37863831

ABSTRACT

Great effort was made to characterize the bacterial communities inhabiting the human body as a factor in disease, resulting in the realization that a wide spectrum of diseases is associated with an altered composition of the microbiome. However, the identification of disease-relevant bacteria has been hindered by the high cross-sectional diversity of individual microbiomes, and in most cases, it remains unclear whether the observed alterations are cause or consequence of disease. Hence, innovative analysis approaches are required that enable inquiries of the microbiome beyond mere taxonomic cataloging. This review highlights the utility of microbiota flow cytometry, a single-cell analysis platform to directly interrogate cellular interactions, cell conditions, and crosstalk with the host's immune system within the microbiome to take into consideration the role of microbes as critical interaction partners of the host and the spectrum of microbiome alterations, beyond compositional changes. In conjunction with advanced sequencing approaches it could reveal the genetic potential of target bacteria and advance our understanding of taxonomic diversity and gene usage in the context of the microenvironment. Single-cell bacterial phenotyping has the potential to change our perspective on the human microbiome and empower microbiome research for the development of microbiome-based therapy approaches and personalized medicine.


Subject(s)
Microbiota , Humans , Cross-Sectional Studies , Bacteria/genetics , Flow Cytometry , High-Throughput Nucleotide Sequencing
16.
Biostatistics ; 2024 Sep 03.
Article in English | MEDLINE | ID: mdl-39226534

ABSTRACT

Major depressive disorder (MDD), a leading cause of years of life lived with disability, presents challenges in diagnosis and treatment due to its complex and heterogeneous nature. Emerging evidence indicates that reward processing abnormalities may serve as a behavioral marker for MDD. To measure reward processing, patients perform computer-based behavioral tasks that involve making choices or responding to stimulants that are associated with different outcomes, such as gains or losses in the laboratory. Reinforcement learning (RL) models are fitted to extract parameters that measure various aspects of reward processing (e.g. reward sensitivity) to characterize how patients make decisions in behavioral tasks. Recent findings suggest the inadequacy of characterizing reward learning solely based on a single RL model; instead, there may be a switching of decision-making processes between multiple strategies. An important scientific question is how the dynamics of strategies in decision-making affect the reward learning ability of individuals with MDD. Motivated by the probabilistic reward task within the Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study, we propose a novel RL-HMM (hidden Markov model) framework for analyzing reward-based decision-making. Our model accommodates decision-making strategy switching between two distinct approaches under an HMM: subjects making decisions based on the RL model or opting for random choices. We account for continuous RL state space and allow time-varying transition probabilities in the HMM. We introduce a computationally efficient Expectation-maximization (EM) algorithm for parameter estimation and use a nonparametric bootstrap for inference. Extensive simulation studies validate the finite-sample performance of our method. We apply our approach to the EMBARC study to show that MDD patients are less engaged in RL compared to the healthy controls, and engagement is associated with brain activities in the negative affect circuitry during an emotional conflict task.

17.
Proc Natl Acad Sci U S A ; 119(40): e2212199119, 2022 10 04.
Article in English | MEDLINE | ID: mdl-36161933

ABSTRACT

Plants typically orient their organs with respect to the Earth's gravity field by a dynamic process called gravitropism. To discover conserved genetic elements affecting seedling root gravitropism, we measured the process in a set of Zea mays (maize) recombinant inbred lines with machine vision and compared the results with those obtained in a similar study of Arabidopsis thaliana. Each of the several quantitative trait loci that we mapped in both species spanned many hundreds of genes, too many to test individually for causality. We reasoned that orthologous genes may be responsible for natural variation in monocot and dicot root gravitropism. If so, pairs of orthologous genes affecting gravitropism may be present within the maize and Arabidopsis QTL intervals. A reciprocal comparison of sequences within the QTL intervals identified seven pairs of such one-to-one orthologs. Analysis of knockout mutants demonstrated a role in gravitropism for four of the seven: CCT2 functions in phosphatidylcholine biosynthesis, ATG5 functions in membrane remodeling during autophagy, UGP2 produces the substrate for cellulose and callose polymer extension, and FAMA is a transcription factor. Automated phenotyping enabled this discovery of four naturally varying components of a conserved process (gravitropism) by making it feasible to conduct the same large-scale experiment in two species.


Subject(s)
Arabidopsis , Gravitropism , Arabidopsis/genetics , Cellulose , Gravitropism/genetics , Phosphatidylcholines , Plant Roots/genetics , Polymers , Quantitative Trait Loci , Transcription Factors/genetics , Zea mays/genetics
18.
J Allergy Clin Immunol ; 154(3): 807-818, 2024 Sep.
Article in English | MEDLINE | ID: mdl-38830512

ABSTRACT

BACKGROUND: Months after infection with severe acute respiratory syndrome coronavirus 2, at least 10% of patients still experience complaints. Long-COVID (coronavirus disease 2019) is a heterogeneous disease, and clustering efforts revealed multiple phenotypes on a clinical level. However, the molecular pathways underlying long-COVID phenotypes are still poorly understood. OBJECTIVES: We sought to cluster patients according to their blood transcriptomes and uncover the pathways underlying their disease. METHODS: Blood was collected from 77 patients with long-COVID from the Precision Medicine for more Oxygen (P4O2) COVID-19 study. Unsupervised hierarchical clustering was performed on the whole blood transcriptome. These clusters were analyzed for differences in clinical features, pulmonary function tests, and gene ontology term enrichment. RESULTS: Clustering revealed 2 distinct clusters on a transcriptome level. Compared with cluster 2 (n = 65), patients in cluster 1 (n = 12) showed a higher rate of preexisting cardiovascular disease (58% vs 22%), higher prevalence of gastrointestinal symptoms (58% vs 29%), shorter hospital duration during severe acute respiratory syndrome coronavirus 2 infection (median, 3 vs 8 days), lower FEV1/forced vital capacity (72% vs 81%), and lower diffusion capacity of the lung for carbon monoxide (68% vs 85% predicted). Gene ontology term enrichment analysis revealed upregulation of genes involved in the antiviral innate immune response in cluster 1, whereas genes involved with the adaptive immune response were upregulated in cluster 2. CONCLUSIONS: This study provides a start in uncovering the pathophysiological mechanisms underlying long-COVID. Further research is required to unravel why the immune response is different in these clusters, and to identify potential therapeutic targets to create an optimized treatment or monitoring strategy for the individual long-COVID patient.


Subject(s)
COVID-19 , Lung , SARS-CoV-2 , Transcriptome , Humans , COVID-19/immunology , COVID-19/blood , Male , Female , Middle Aged , SARS-CoV-2/immunology , Aged , Lung/immunology , Respiratory Function Tests , Post-Acute COVID-19 Syndrome
19.
J Proteome Res ; 23(4): 1313-1327, 2024 04 05.
Article in English | MEDLINE | ID: mdl-38484742

ABSTRACT

To ensure biological validity in metabolic phenotyping, findings must be replicated in independent sample sets. Targeted workflows have long been heralded as ideal platforms for such validation due to their robust quantitative capability. We evaluated the capability of liquid chromatography-mass spectrometry (LC-MS) assays targeting organic acids and bile acids to validate metabolic phenotypes of SARS-CoV-2 infection. Two independent sample sets were collected: (1) Australia: plasma, SARS-CoV-2 positive (n = 20), noninfected healthy controls (n = 22) and COVID-19 disease-like symptoms but negative for SARS-CoV-2 infection (n = 22). (2) Spain: serum, SARS-CoV-2 positive (n = 33) and noninfected healthy controls (n = 39). Multivariate modeling using orthogonal projections to latent structures discriminant analyses (OPLS-DA) classified healthy controls from SARS-CoV-2 positive (Australia; R2 = 0.17, ROC-AUC = 1; Spain R2 = 0.20, ROC-AUC = 1). Univariate analyses revealed 23 significantly different (p < 0.05) metabolites between healthy controls and SARS-CoV-2 positive individuals across both cohorts. Significant metabolites revealed consistent perturbations in cellular energy metabolism (pyruvic acid, and 2-oxoglutaric acid), oxidative stress (lactic acid, 2-hydroxybutyric acid), hypoxia (2-hydroxyglutaric acid, 5-aminolevulinic acid), liver activity (primary bile acids), and host-gut microbial cometabolism (hippuric acid, phenylpropionic acid, indole-3-propionic acid). These data support targeted LC-MS metabolic phenotyping workflows for biological validation in independent sample sets.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , Liquid Chromatography-Mass Spectrometry , Chromatography, Liquid/methods , Tandem Mass Spectrometry/methods , Phenotype , Bile Acids and Salts
20.
J Proteome Res ; 23(4): 1328-1340, 2024 04 05.
Article in English | MEDLINE | ID: mdl-38513133

ABSTRACT

Delayed diagnosis of patients with sepsis or septic shock is associated with increased mortality and morbidity. UPLC-MS and NMR spectroscopy were used to measure panels of lipoproteins, lipids, biogenic amines, amino acids, and tryptophan pathway metabolites in blood plasma samples collected from 152 patients within 48 h of admission into the Intensive Care Unit (ICU) where 62 patients had no sepsis, 71 patients had sepsis, and 19 patients had septic shock. Patients with sepsis or septic shock had higher concentrations of neopterin and lower levels of HDL cholesterol and phospholipid particles in comparison to nonsepsis patients. Septic shock could be differentiated from sepsis patients based on different concentrations of 10 lipids, including significantly lower concentrations of five phosphatidylcholine species, three cholesterol esters, one dihydroceramide, and one phosphatidylethanolamine. The Supramolecular Phospholipid Composite (SPC) was reduced in all ICU patients, while the composite markers of acute phase glycoproteins were increased in the sepsis and septic shock patients within 48 h admission into ICU. We show that the plasma metabolic phenotype obtained within 48 h of ICU admission is diagnostic for the presence of sepsis and that septic shock can be differentiated from sepsis based on the lipid profile.


Subject(s)
Sepsis , Shock, Septic , Humans , Chromatography, Liquid , Tandem Mass Spectrometry , Sepsis/diagnosis , Intensive Care Units , Phenotype , Phospholipids
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