Trends Plant Sci , IF:18.313 , 2022 Sep , V27 (9) : P922-935 doi: 10.1016/j.tplants.2022.01.008
Transcriptional regulatory network of plant cold-stress responses.
Graduate School of Agricultural and Life Sciences, The University of Tokyo, Bunkyo-ku, Tokyo 113-8657, Japan. Electronic address: akido@g.ecc.u-tokyo.ac.jp.; Gene Discovery Research Group, RIKEN Center for Sustainable Resource Science, Tsukuba, Ibaraki 305-0074, Japan.; Graduate School of Agricultural and Life Sciences, The University of Tokyo, Bunkyo-ku, Tokyo 113-8657, Japan; Research Institute for Agricultural and Life Sciences, Tokyo University of Agriculture, Setagaya-ku, Tokyo 156-8502, Japan. Electronic address: akys@g.ecc.u-tokyo.ac.jp.
Recent studies have revealed the complex and flexible transcriptional regulatory network involved in cold-stress responses. Focusing on two major signaling pathways that respond to cold stress, we outline current knowledge of the transcriptional regulatory network and the post-translational regulation of transcription factors in the network. Cold-stress signaling pathways are closely associated with other signaling pathways such as those related to the circadian clock, and large amounts of data on their crosstalk and tradeoffs are available. However, it remains unknown how plants sense and transmit cold-stress signals to regulate gene expression. We discuss recent reports on cold-stress sensing and associated signaling pathways that regulate the network. We also emphasize future directions for developing abiotic stress-tolerant crop plants.
PMID: 35210165
Proc Natl Acad Sci U S A , IF:11.205 , 2022 Aug , V119 (35) : Pe2204400119 doi: 10.1073/pnas.2204400119
The generality of cryptic dietary niche differences in diverse large-herbivore assemblages.
Department of Ecology & Evolutionary Biology, Princeton University, Princeton, NJ, 08544.; Institut de Sciences de l'Evolution de Montpellier, University of Montpellier, CNRS, Institut de Recherche pour le Developpement, Montpellier, 34095, France.; Department of Biology, Wake Forest University, Winston-Salem, NC, 27109.; Copernicus Institute of Sustainable Development, Utrecht University, Utrecht, 3584 CB, The Netherlands.; Centre for African Conservation Ecology, Nelson Mandela University, Port Elizabeth, 6031, South Africa.; Niassa Carnivore Project, Niassa National Reserve, Mozambique.; Laboratoire d'Ecologie Alpine, Universite Grenoble Alpes, Centre National de la Recherche Scientifique, Grenoble, F-38000, France.; Argaly, Batiment Cleanspace, F-73800 Sainte Helene du Lac, France.; School of Natural Resources, Department of Zoology & Aquatic Sciences, Copperbelt University, Kitwe, Zambia.; Centre d'Ecologie Fonctionnelle et Evolutive, University of Montpellier, Centre National de la Recherche Scientifique, Ecole Pratique des Hautes Etudes, IRD, Montpellier, 34293, France.; Mammal Research Institute, Department of Zoology & Entomology, University of Pretoria, Pretoria, Hatfield 0028, South Africa.; Department of Wildlife, Fish & Environmental Studies, Swedish University of Agricultural Sciences, Umea, SE-901 83, Sweden.; Odum School of Ecology, University of Georgia, Athens, GA, 30602.; Department of National Parks and Wildlife, Lilongwe, 3, Malawi.; Mpala Research Centre, Nanyuki, 10400, Kenya.; Department of Fish and Wildlife Sciences, University of Idaho, Moscow, ID, 83844.; Serengeti Wildlife Research Institute, Seronera, Tanzania.; School of Environmental Sciences, University of Liverpool, Liverpool, L3 5DA, United Kingdom.; Department of Zoology and Entomology, University of Pretoria, Pretoria, Hatfield 0028, South Africa.; School of Animal, Plant and Environmental Sciences, University of the Witwatersrand, Wits, Braamfontein 2000, Johannesburg, South Africa.; Tromso Museum, UiT The Arctic University of Norway, Tromso, Langnes N-9037, Norway.; Department of Ecology, Evolution, and Organismal Biology, Brown University, Providence, RI, 02912.; Institute at Brown for Environment and Society, Brown University, Providence, RI, 02912.
Ecological niche differences are necessary for stable species coexistence but are often difficult to discern. Models of dietary niche differentiation in large mammalian herbivores invoke the quality, quantity, and spatiotemporal distribution of plant tissues and growth forms but are agnostic toward food plant species identity. Empirical support for these models is variable, suggesting that additional mechanisms of resource partitioning may be important in sustaining large-herbivore diversity in African savannas. We used DNA metabarcoding to conduct a taxonomically explicit analysis of large-herbivore diets across southeastern Africa, analyzing approximately 4,000 fecal samples of 30 species from 10 sites in seven countries over 6 y. We detected 893 food plant taxa from 124 families, but just two families-grasses and legumes-accounted for the majority of herbivore diets. Nonetheless, herbivore species almost invariably partitioned food plant taxa; diet composition differed significantly in 97% of pairwise comparisons between sympatric species, and dissimilarity was pronounced even between the strictest grazers (grass eaters), strictest browsers (nongrass eaters), and closest relatives at each site. Niche differentiation was weakest in an ecosystem recovering from catastrophic defaunation, indicating that food plant partitioning is driven by species interactions, and was stronger at low rainfall, as expected if interspecific competition is a predominant driver. Diets differed more between browsers than grazers, which predictably shaped community organization: Grazer-dominated trophic networks had higher nestedness and lower modularity. That dietary differentiation is structured along taxonomic lines complements prior work on how herbivores partition plant parts and patches and suggests that common mechanisms govern herbivore coexistence and community assembly in savannas.
PMID: 35994662
Proc Natl Acad Sci U S A , IF:11.205 , 2022 Aug , V119 (35) : Pe2208795119 doi: 10.1073/pnas.2208795119
Regulators of early maize leaf development inferred from transcriptomes of laser capture microdissection (LCM)-isolated embryonic leaf cells.
Biodiversity Research Center, Academia Sinica, Taipei 115, Taiwan.; Department of Plant Biology, Michigan State University, East Lansing, MI 48824.; Department of Computational Mathematics, Science, and Engineering, Michigan State University, East Lansing, MI 48824.; Department of Bioagricultural Science, National Chiayi University, Chiayi 600, Taiwan.; School of Biological Sciences, Washington State University, Pullman, WA 99164.; Institute of Plant and Microbial Biology, Academia Sinica, Taipei 115, Taiwan.; Department of Ecology and Evolution, University of Chicago, Chicago, IL 60637.
The superior photosynthetic efficiency of C4 leaves over C3 leaves is owing to their unique Kranz anatomy, in which the vein is surrounded by one layer of bundle sheath (BS) cells and one layer of mesophyll (M) cells. Kranz anatomy development starts from three contiguous ground meristem (GM) cells, but its regulators and underlying molecular mechanism are largely unknown. To identify the regulators, we obtained the transcriptomes of 11 maize embryonic leaf cell types from five stages of pre-Kranz cells starting from median GM cells and six stages of pre-M cells starting from undifferentiated cells. Principal component and clustering analyses of transcriptomic data revealed rapid pre-Kranz cell differentiation in the first two stages but slow differentiation in the last three stages, suggesting early Kranz cell fate determination. In contrast, pre-M cells exhibit a more prolonged transcriptional differentiation process. Differential gene expression and coexpression analyses identified gene coexpression modules, one of which included 3 auxin transporter and 18 transcription factor (TF) genes, including known regulators of Kranz anatomy and/or vascular development. In situ hybridization of 11 TF genes validated their expression in early Kranz development. We determined the binding motifs of 15 TFs, predicted TF target gene relationships among the 18 TF and 3 auxin transporter genes, and validated 67 predictions by electrophoresis mobility shift assay. From these data, we constructed a gene regulatory network for Kranz development. Our study sheds light on the regulation of early maize leaf development and provides candidate leaf development regulators for future study.
PMID: 36001691
Plant Biotechnol J , IF:9.803 , 2022 Aug doi: 10.1111/pbi.13918
Single-cell RNA-seq reveals fate determination control of an individual fiber cell initiation in cotton (Gossypium hirsutum).
National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, Hubei Province, 430070, China.; Department of Biosciences, Durham University, Durham, UK.
Cotton fiber is a unicellular seed trichome, and lint fiber initials per seed as a factor determines fiber yield. However, the mechanisms controlling fiber initiation from ovule epidermis are not understood well enough. Here, with single-cell RNA sequencing (scRNA-seq), a total of 14,535 cells were identified from cotton ovule outer integument of Xu142_LF line at four developmental stages (1.5, 1, 0.5 days before anthesis and the day of anthesis). Three major cell types, fiber, non-fiber epidermis and outer pigment layer were identified and then verified by RNA in situ hybridization. A comparative analysis on scRNA-seq data between Xu142 and its fiberless mutant Xu142 fl further confirmed fiber cluster definition. The developmental trajectory of fiber cell was reconstructed, and fiber cell was identified differentiated at 1 day before anthesis. Gene regulatory networks at four stages revealed the spatiotemporal pattern of core transcription factors, and MYB25-like and HOX3 were demonstrated played key roles as commanders in fiber differentiation and tip-biased diffuse growth, respectively. A model for early development of a single fiber cell was proposed here, which sheds light on further deciphering mechanism of plant trichome and the improvement of cotton fiber yield.
PMID: 36053965
Environ Int , IF:9.621 , 2022 Aug , V168 : P107457 doi: 10.1016/j.envint.2022.107457
Storm promotes the dissemination of antibiotic resistome in an urban lagoon through enhancing bio-interactions.
CAS Key Laboratory of Urban Pollutant Conversion, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Department of Bacteriology, University of Wisconsin-Madison, Madison, WI 53706, USA.; CAS Key Laboratory of Urban Pollutant Conversion, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China; Fujian Key Laboratory of Watershed Ecology, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China.; Yundang Lake Management Center, Xiamen, Fujian 361004, China.; Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, Fujian 361021, China.; CAS Key Laboratory of Urban Pollutant Conversion, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Fujian Key Laboratory of Watershed Ecology, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Water Pollution Research Department, National Research Centre, Giza 12622, Egypt.; CSIRO Land and Water, Ecosciences Precinct, 41 Boggo Road, Qld 4102, Australia.; CAS Key Laboratory of Urban Pollutant Conversion, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Graduate Institute of Environmental Engineering, National Taiwan University, Taipei 106, Taiwan.; CAS Key Laboratory of Urban Pollutant Conversion, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Fujian Key Laboratory of Watershed Ecology, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China. Electronic address: ayhu@iue.ac.cn.
Antibiotic-resistance genes (ARGs) and resistant bacteria (ARB) are abundant in stormwater that could cause serious infections, posing a potential threat to public health. However, there is no inference about how stormwater contributes to ARG profiles as well as the dynamic interplay between ARGs and bacteria via vertical gene transfer (VGT) or horizontal gene transfer (HGT) in urban water ecosystems. In this study, the distribution of ARGs, their host communities, and the source and community assembly process of ARGs were investigated in Yundang Lagoon (China) via high-throughput quantitative PCR, 16S rRNA gene amplicon sequencing, and application of SourceTracker before, after and recovering from an extreme precipitation event (132.1 mm). The abundance of ARGs and mobile genetic elements (MGEs) was the highest one day after precipitation and then decreased 2 days after precipitation and so on. Based on SourceTracker and NMDS analysis, the ARG and bacterial communities in lagoon surface water from one day after precipitation were mainly contributed by the wastewater treatment plant (WWTP) influent and effluent. However, the contribution of WWTP to ARG communities was minor 11 days after the precipitation, suggesting that the storm promoted the ARG levels by introducing the input of ARGs, MGEs, and ARB from point and non-point sources, such as sewer overflow and land-applied manure. Based on a novel microbial network analysis framework, the contribution of positive biological interactions between ARGs and MGEs or bacteria was the highest one day after precipitation, indicating a promoted VGT and HGT for ARG dissemination. The microbial networks deconstructed 11 days after precipitation, suggesting the stormwater practices (e.g., tide gate opening, diversion channels, and pumping) alleviated the spread of ARGs. These results advanced our understanding of the distribution and transport of ARGs associated with their source in urban stormwater runoff.
PMID: 35963060
Elife , IF:8.14 , 2022 Sep , V11 doi: 10.7554/eLife.77058
A unified view of low complexity regions (LCRs) across species.
Department of Biology, Massachusetts Institute of Technology, Cambridge, United States.; David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, United States.
Low complexity regions (LCRs) play a role in a variety of important biological processes, yet we lack a unified view of their sequences, features, relationships, and functions. Here, we use dotplots and dimensionality reduction to systematically define LCR type/copy relationships and create a map of LCR sequence space capable of integrating LCR features and functions. By defining LCR relationships across the proteome, we provide insight into how LCR type and copy number contribute to higher order assemblies, such as the importance of K-rich LCR copy number for assembly of the nucleolar protein RPA43 in vivo and in vitro. With LCR maps, we reveal the underlying structure of LCR sequence space, and relate differential occupancy in this space to the conservation and emergence of higher order assemblies, including the metazoan extracellular matrix and plant cell wall. Together, LCR relationships and maps uncover and identify scaffold-client relationships among E-rich LCR-containing proteins in the nucleolus, and revealed previously undescribed regions of LCR sequence space with signatures of higher order assemblies, including a teleost-specific T/H-rich sequence space. Thus, this unified view of LCRs enables discovery of how LCRs encode higher order assemblies of organisms.
PMID: 36098382
Elife , IF:8.14 , 2022 Sep , V11 doi: 10.7554/eLife.73031
Computational modeling and quantitative physiology reveal central parameters for brassinosteroid-regulated early cell physiological processes linked to elongation growth of the Arabidopsis root.
BioQuant, Heidelberg University, Heidelberg, Germany.; Center for Molecular Biology of Plants, University of Tubingen, Tubingen, Germany.; Centre for Organismal Studies, Heidelberg University, Heidelberg, Germany.; Tasmanian Institute for Agriculture, University of Tasmania, Hobard, Australia.; Tasmanian Institute for Agriculture, University of Tasmania, Hobart, Australia.
Brassinosteroids (BR) are key hormonal regulators of plant development. However, whereas the individual components of BR perception and signaling are well characterized experimentally, the question of how they can act and whether they are sufficient to carry out the critical function of cellular elongation remains open. Here, we combined computational modeling with quantitative cell physiology to understand the dynamics of the plasma membrane (PM)-localized BR response pathway during the initiation of cellular responses in the epidermis of the Arabidopsis root tip that are be linked to cell elongation. The model, consisting of ordinary differential equations, comprises the BR induced hyperpolarization of the PM, the acidification of the apoplast and subsequent cell wall swelling. We demonstrate that the competence of the root epidermal cells for the BR response predominantly depends on the amount and activity of H+-ATPases in the PM. The model further predicts that an influx of cations is required to compensate for the shift of positive charges caused by the apoplastic acidification. A potassium channel was subsequently identified and experimentally characterized, fulfilling this function. Thus, we established the landscape of components and parameters for physiological processes potentially linked to cell elongation, a central process in plant development.
PMID: 36069528
Environ Pollut , IF:8.071 , 2022 Aug , V307 : P119516 doi: 10.1016/j.envpol.2022.119516
Effects of soil protists on the antibiotic resistome under long term fertilization.
Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, 1799 Jimei Road, Xiamen, 361021, China; University of Chinese Academy of Sciences, 19A Yuquan Road, Beijing, 100049, China.; Key Laboratory of Urban Environment and Health, Ningbo Urban Environment Observation and Research Station, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China. Electronic address: dongzhu@rcees.ac.cn.; Key Laboratory for Humid Subtropical Ecogeographical Processes of the Ministry of Education, School of Geographical Sciences, Fujian Normal University, Fuzhou, 350007, China.; Department of Plant and Environmental Sciences, Faculty of Science, University of Copenhagen, 1871, Frederiksberg, Denmark; Sino-Danish Center for Education and Research, Beijing, China.; Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, 1799 Jimei Road, Xiamen, 361021, China.
Soil protists are key in regulating soil microbial communities. However, our understanding on the role of soil protists in shaping antibiotic resistome is limited. Here, we considered the diversity and composition of bacteria, fungi and protists in arable soils collected from a long-term field experiment with multiple fertilization treatments. We explored the effects of soil protists on antibiotic resistome using high-throughput qPCR. Our results showed that long term fertilization had stronger effect on the composition of protists than those of bacteria and fungi. The detected number and relative abundance of antibiotic resistance genes (ARGs) were elevated in soils amended with organic fertilizer. Co-occurrence network analysis revealed that changes in protists may contribute to the changes in ARGs composition, and the application of different fertilizers altered the communities of protistan consumers, suggesting that effects of protistan communities on ARGs might be altered by the top-down impact on bacterial composition. This study demonstrates soil protists as promising agents in monitoring and regulating ecological risk of antibiotic resistome associated with organic fertilizers.
PMID: 35609845
Sci Total Environ , IF:7.963 , 2022 Sep , V838 (Pt 3) : P156426 doi: 10.1016/j.scitotenv.2022.156426
The combined effect of an integrated reclaimed water system on the reduction of antibiotic resistome.
Engineering Research Center of Ministry of Education on Groundwater Pollution Control and Remediation, College of Water Sciences, Beijing Normal University, Beijing 100875, China.; Beijing BHZQ Environmental Engineering Technology Co., LTD, Beijing 100176, China.; Engineering Research Center of Ministry of Education on Groundwater Pollution Control and Remediation, College of Water Sciences, Beijing Normal University, Beijing 100875, China. Electronic address: chen.haiyang@bnu.edu.cn.
The reuse of urban reclaimed water is conducive to alleviate the current serious shortage of water resources. However, antibiotic resistance genes (ARGs) in reclaimed water have received widespread attention due to their potential risks to public health. Deciphering the fate of ARGs in reclaimed water benefits the development of effective strategies to control resistome risk and guarantees the safety of water supply of reclaimed systems. In this study, the characteristics of ARGs in an integrated reclaimed water system (sewage treatment plant-constructed wetland, STP-CW) in Beijing (China) have been identified using metagenomic assembly-based analysis, as well as the combined effect of the STP-CW system on the reduction of antibiotic resistome. Results showed a total of 29 ARG types and 813 subtypes were found in the reclaimed water system. As expected, the STP-CW system improved the removal of ARGs, and about 58% of ARG subtypes were removed from the effluent of the integrated STP-CW system, which exceeded 43% for the STP system and 37% for the CW system. Although the STP-CW system had a great removal on ARGs, abundant and diverse ARGs were still found in the downstream river. Importantly, network analysis revealed the co-occurrence of ARGs, mobile genetic elements and virulence factors in the downstream water, implying potential resistome dissemination risk in the environment. Source identification with SourceTracker showed the STP-effluent was the largest contributor of ARGs in the downstream river, with a contribution of 45%. Overall, the integrated STP-CW system presented a combined effect on the reduction of antibiotic resistome, however, the resistome dissemination risk was still non-negligible in the downstream reclaimed water. This study provides a comprehensive analysis on the fate of ARGs in the STP-CW-river system, which would benefit the development of effective strategies to control resistome risk for the reuse of reclaimed water.
PMID: 35660592
Psychol Med , IF:7.723 , 2022 Aug : P1-12 doi: 10.1017/S003329172200232X
Prospective network analysis of proinflammatory proteins, lipid markers, and depression components in midlife community women.
Department of Health Care Policy, Harvard Medical School, Boston, MA, USA.; Department of Psychology, The Pennsylvania State University, State College, PA, USA.
BACKGROUND: Vulnerability theories propose that suboptimal levels of lipid markers and proinflammatory proteins predict future heightened depression. Scar models posit the reverse association. However, most studies that tested relationships between non-specific immune/endocrine markers and depression did not separate temporal inferences between people and within-person and how different immunometabolism markers related to unique depression symptoms. We thus used cross-lagged prospective network analyses (CLPN) to investigate this topic. METHODS: Community midlife women (n = 2224) completed the Center for Epidemiologic Studies-Depression scale and provided biomarker samples across five time-points spanning 9 years. CLPN identified significant relations (edges) among components (nodes) of depression (depressed mood, somatic symptoms, interpersonal issues), lipid markers [insulin, fasting glucose, triglycerides, low-density lipoprotein-cholesterol (LDL), high-density lipoprotein-cholesterol (HDL)], and proinflammatory proteins [C-reactive protein (CRP), fibrinogen], within and across time-points. All models adjusted for age, estradiol, follicle-stimulating hormone, and menopausal status. RESULTS: In within-person temporal networks, higher CRP and HDL predicted all three depression components (d = 0.131-2.112). Increased LDL preceded higher depressed mood and interpersonal issues (v. somatic symptoms) (d = 0.251-0.327). Elevated triglycerides predicted more somatic symptoms (v. depressed mood and interpersonal problems) (d = 0.131). More interpersonal problems forecasted elevated fibrinogen and LDL levels (d = 0.129-0.331), and stronger somatic symptoms preceded higher fibrinogen levels (d = 0.188). CONCLUSIONS: Results supported both vulnerability and scar models. Long-term dysregulated immunometabolism systems, social disengagement, and related patterns are possible mechanistic accounts. Cognitive-behavioral therapies that optimize nutrition and physical activity may effectively target depression.
PMID: 35924730
Plant J , IF:6.417 , 2022 Sep , V111 (6) : P1527-1538 doi: 10.1111/tpj.15905
Unsupervised and semi-supervised learning: the next frontier in machine learning for plant systems biology.
Frontiers Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100094, China.; National Maize Improvement Center, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100094, China.
Advances in high-throughput omics technologies are leading plant biology research into the era of big data. Machine learning (ML) performs an important role in plant systems biology because of its excellent performance and wide application in the analysis of big data. However, to achieve ideal performance, supervised ML algorithms require large numbers of labeled samples as training data. In some cases, it is impossible or prohibitively expensive to obtain enough labeled training data; here, the paradigms of unsupervised learning (UL) and semi-supervised learning (SSL) play an indispensable role. In this review, we first introduce the basic concepts of ML techniques, as well as some representative UL and SSL algorithms, including clustering, dimensionality reduction, self-supervised learning (self-SL), positive-unlabeled (PU) learning and transfer learning. We then review recent advances and applications of UL and SSL paradigms in both plant systems biology and plant phenotyping research. Finally, we discuss the limitations and highlight the significance and challenges of UL and SSL strategies in plant systems biology.
PMID: 35821601
Int J Mol Sci , IF:5.923 , 2022 Sep , V23 (17) doi: 10.3390/ijms23179980
Multiomics Molecular Research into the Recalcitrant and Orphan Quercus ilex Tree Species: Why, What for, and How.
Agroforestry and Plant Biochemistry, Proteomics and Systems Biology, Department of Biochemistry and Molecular Biology, University of Cordoba, UCO-CeiA3, 14014 Cordoba, Spain.; Cardiovascular Proteomics Laboratory, Centro Nacional de Investigaciones Cardiovasculares (CNIC), 28029 Madrid, Spain.; Plant Physiology, Department of Organisms and Systems Biology, University Institute of Biotechnology of Asturias (IUBA), University of Oviedo, 33006 Asturias, Spain.; Evaluation and Restoration of Agronomic and Forest Systems ERSAF, Department of Forest Engineering, University of Cordoba, 14014 Cordoba, Spain.
The holm oak (Quercus ilex L.) is the dominant tree species of the Mediterranean forest and the Spanish agrosilvopastoral ecosystem, "dehesa." It has been, since the prehistoric period, an important part of the Iberian population from a social, cultural, and religious point of view, providing an ample variety of goods and services, and forming the basis of the economy in rural areas. Currently, there is renewed interest in its use for dietary diversification and sustainable food production. It is part of cultural richness, both economically (tangible) and environmentally (intangible), and must be preserved for future generations. However, a worrisome degradation of the species and associated ecosystems is occurring, observed in an increase in tree decline and mortality, which requires urgent action. Breeding programs based on the selection of elite genotypes by molecular markers is the only plausible biotechnological approach. To this end, the authors' group started, in 2004, a research line aimed at characterizing the molecular biology of Q. ilex. It has been a challenging task due to its biological characteristics (long life cycle, allogamous, high phenotypic variability) and recalcitrant nature. The biology of this species has been characterized following the central dogma of molecular biology using the omics cascade. Molecular responses to biotic and abiotic stresses, as well as seed maturation and germination, are the two main objectives of our research. The contributions of the group to the knowledge of the species at the level of DNA-based markers, genomics, epigenomics, transcriptomics, proteomics, and metabolomics are discussed here. Moreover, data are compared with those reported for Quercus spp. All omics data generated, and the genome of Q. ilex available, will be integrated with morphological and physiological data in the systems biology direction. Thus, we will propose possible molecular markers related to resilient and productive genotypes to be used in reforestation programs. In addition, possible markers related to the nutritional value of acorn and derivate products, as well as bioactive compounds (peptides and phenolics) and allergens, will be suggested. Subsequently, the selected molecular markers will be validated by both genome-wide association and functional genomic analyses.
PMID: 36077370
Int J Mol Sci , IF:5.923 , 2022 Sep , V23 (18) doi: 10.3390/ijms231810596
Integrated Analysis of Transcriptome and Small RNAome Reveals the Regulatory Network for Rapid Growth in Mikania micrantha.
Guangdong Provincial Key Laboratory for Plant Epigenetics, Longhua Bioindustry and Innovation Research Institute, College of Life Sciences and Oceanography, Shenzhen University, Shenzhen 518060, China.
M. micrantha has caused huge ecological damage and economic losses worldwide due to its rapid growth and serious invasion. However, the underlying molecular mechanisms of its rapid growth and environmental adaption remain unclear. Here, we performed transcriptome and small RNA sequencing with five tissues of M. micrantha to dissect miRNA-mediated regulation in M. micrantha. WGCNA and GO enrichment analysis of transcriptome identified the gene association patterns and potential key regulatory genes for plant growth in each tissue. The genes highly correlated with leaf and stem tissues were mainly involved in the chlorophyll synthesis, response to auxin, the CAM pathway and other photosynthesis-related processes, which promoted the fast growth of M. micrantha. Importantly, we identified 350 conserved and 192 novel miRNAs, many of which displayed differential expression patterns among tissues. PsRNA target prediction analysis uncovered target genes of both conserved and novel miRNAs, including GRFs and TCPs, which were essential for plant growth and development. Further analysis revealed that miRNAs contributed to the regulation of tissue-specific gene expression in M. micrantha, such as mmi-miR396 and mmi-miR319. Taken together, our study uncovered the miRNA-mRNA regulatory networks and the potential vital roles of miRNAs in modulating the rapid growth of M. micrantha.
PMID: 36142547
Int J Mol Sci , IF:5.923 , 2022 Aug , V23 (16) doi: 10.3390/ijms23168986
Transcriptomics and Genomics Analysis Uncover the Differentially Expressed Chlorophyll and Carotenoid-Related Genes in Celery.
Center for Informational Biology, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China.; Center for Genomics and Bio-Computing, School of Life Sciences, North China University of Science and Technology, Tangshan 063210, China.; Beijing Vegetable Research Center, Beijing Academy of Agriculture and Forestry Sciences, Key Laboratory of Biology and Genetic Improvement of Horticultural Crops (North China), Beijing 100097, China.; Department of Food Science, Aarhus University, 8200 Aarhus, Denmark.; Fredericton Research and Development Centre, Agriculture and Agri-Food Canada, Fredericton, NB E3B 4Z7, Canada.
Celery (Apium graveolens L.), a plant from Apiaceae, is one of the most important vegetables and is grown worldwide. Carotenoids can capture light energy and transfer it to chlorophyll, which plays a central role in photosynthesis. Here, by performing transcriptomics and genomics analysis, we identified and conducted a comprehensive analysis of chlorophyll and carotenoid-related genes in celery and six representative species. Significantly, different contents and gene expression patterns were found among three celery varieties. In total, 237 and 290 chlorophyll and carotenoid-related genes were identified in seven species. No notable gene expansion of chlorophyll biosynthesis was detected in examined species. However, the gene encoding zeta-carotene desaturase (ZDS) enzyme in carotenoid was expanded in celery. Comparative genomics and RNA-seq analyses revealed 16 and 5 key genes, respectively, regulating chlorophyll and carotenoid. An intriguing finding is that chlorophyll and carotenoid-related genes were coordinately regulated by transcriptional factors, which could be distinctively classified into positive- and negative-regulation groups. Six CONSTANS (CO)-like transcription factors co-regulated chlorophyll and carotenoid-related genes were identified in celery. In conclusion, this study provides new insights into the regulation of chlorophyll and carotenoid by transcription factors.
PMID: 36012264
Int J Mol Sci , IF:5.923 , 2022 Aug , V23 (15) doi: 10.3390/ijms23158665
Role of a ZF-HD Transcription Factor in miR157-Mediated Feed-Forward Regulatory Module That Determines Plant Architecture in Arabidopsis.
Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, NY 11724, USA.; Institute of Plasma Technology, Korea Institute of Fusion Energy, 37, Dongjangsan-ro, Gunsan-si 54004, Korea.; Division of Biological Sciences, University of California-San Diego, La Jolla, CA 92093, USA.; USDA-ARS, Robert W. Holley Center, Ithaca, NY 14853, USA.
In plants, vegetative and reproductive development are associated with agronomically important traits that contribute to grain yield and biomass. Zinc finger homeodomain (ZF-HD) transcription factors (TFs) constitute a relatively small gene family that has been studied in several model plants, including Arabidopsis thaliana L. and Oryza sativa L. The ZF-HD family members play important roles in plant growth and development, but their contribution to the regulation of plant architecture remains largely unknown due to their functional redundancy. To understand the gene regulatory network controlled by ZF-HD TFs, we analyzed multiple loss-of-function mutants of ZF-HD TFs in Arabidopsis that exhibited morphological abnormalities in branching and flowering architecture. We found that ZF-HD TFs, especially HB34, negatively regulate the expression of miR157 and positively regulate SQUAMOSA PROMOTER BINDING-LIKE 10 (SPL10), a target of miR157. Genome-wide chromatin immunoprecipitation sequencing (ChIP-Seq) analysis revealed that miR157D and SPL10 are direct targets of HB34, creating a feed-forward loop that constitutes a robust miRNA regulatory module. Network motif analysis contains overrepresented coherent type IV feedforward motifs in the amiR zf-HD and hbq mutant background. This finding indicates that miRNA-mediated ZF-HD feedforward modules modify branching and inflorescence architecture in Arabidopsis. Taken together, these findings reveal a guiding role of ZF-HD TFs in the regulatory network module and demonstrate its role in plant architecture in Arabidopsis.
PMID: 35955798
Front Plant Sci , IF:5.753 , 2022 , V13 : P928718 doi: 10.3389/fpls.2022.928718
Dynamic modeling of ABA-dependent expression of the Arabidopsis RD29A gene.
Department of Biological Sciences, Louisiana State University, Baton Rouge, LA, United States.; Donald Danforth Plant Science Center, St. Louis, MO, United States.
The abscisic acid (ABA) signaling pathway is the key defense mechanism against drought stress in plants. In the pathway, signal transduction among four core proteins, pyrabactin resistance (PYR), protein phosphatase 2C (PP2C), sucrose-non-fermenting-1-related protein kinase 2 (SnRK2), and ABRE binding factor (ABF) leads to altered gene expression kinetics that is driven by an ABA-responsive element (ABRE). A most recent and comprehensive study provided data suggesting that ABA alters the expression kinetics in over 6,500 genes through the ABF-ABRE associations in Arabidopsis. Of these genes, termed ABA gene regulatory network (GRN), over 50% contain a single ABRE within 4 kb of the gene body, despite previous findings suggesting that a single copy of ABRE is not sufficient to drive the gene expression. To understand the expression system of the ABA GRN by the single ABRE, a dynamic model of the gene expression for the desiccation 29A (RD29A) gene was constructed with ordinary differential equations. Parameter values of molecular-molecular interactions and enzymatic reactions in the model were implemented from the data obtained by previously conducted in vitro experiments. On the other hand, parameter values of gene expression and translation were determined by comparing the kinetics of gene expression in the model to the expression kinetics of RD29A in real plants. The optimized model recapitulated the trend of gene expression kinetics of RD29A in ABA dose-response that were previously investigated. Further analysis of the model suggested that a single ABRE controls the time scale and dynamic range of the ABA-dependent gene expression through the PP2C feedback regulation even though an additional cis-element is required to drive the expression. The model construed in this study underpins the importance of a single ABRE in the ABA GRN.
PMID: 36092424
Front Plant Sci , IF:5.753 , 2022 , V13 : P852047 doi: 10.3389/fpls.2022.852047
The flowering transition pathways converge into a complex gene regulatory network that underlies the phase changes of the shoot apical meristem in Arabidopsis thaliana.
Laboratorio de Genetica Molecular, Desarrollo y Evolucion de Plantas, Departamento de Ecologia Funcional, Instituto de Ecologia, Universidad Nacional Autonoma de Mexico, Mexico City, Mexico.; Centro de Ciencias de la Complejidad, Universidad Nacional Autonoma de Mexico, Mexico City, Mexico.
Post-embryonic plant development is characterized by a period of vegetative growth during which a combination of intrinsic and extrinsic signals triggers the transition to the reproductive phase. To understand how different flowering inducing and repressing signals are associated with phase transitions of the Shoot Apical Meristem (SAM), we incorporated available data into a dynamic gene regulatory network model for Arabidopsis thaliana. This Flowering Transition Gene Regulatory Network (FT-GRN) formally constitutes a dynamic system-level mechanism based on more than three decades of experimental data on flowering. We provide novel experimental data on the regulatory interactions of one of its twenty-three components: a MADS-box transcription factor XAANTAL2 (XAL2). These data complement the information regarding flowering transition under short days and provides an example of the type of questions that can be addressed by the FT-GRN. The resulting FT-GRN is highly connected and integrates developmental, hormonal, and environmental signals that affect developmental transitions at the SAM. The FT-GRN is a dynamic multi-stable Boolean system, with 2(23) possible initial states, yet it converges into only 32 attractors. The latter are coherent with the expression profiles of the FT-GRN components that have been experimentally described for the developmental stages of the SAM. Furthermore, the attractors are also highly robust to initial states and to simulated perturbations of the interaction functions. The model recovered the meristem phenotypes of previously described single mutants. We also analyzed the attractors landscape that emerges from the postulated FT-GRN, uncovering which set of signals or components are critical for reproductive competence and the time-order transitions observed in the SAM. Finally, in the context of such GRN, the role of XAL2 under short-day conditions could be understood. Therefore, this model constitutes a robust biological module and the first multi-stable, dynamical systems biology mechanism that integrates the genetic flowering pathways to explain SAM phase transitions.
PMID: 36017258
Front Microbiol , IF:5.64 , 2022 , V13 : P970477 doi: 10.3389/fmicb.2022.970477
Meta-analysis of fungal plant pathogen Fusarium oxysporum infection-related gene profiles using transcriptome datasets.
Key Laboratory of Molecular and Cytogenetics, Heilongjiang Province, College of Life Science and Technology, Harbin Normal University, Harbin, China.
Fusarium oxysporum is a serious soil-borne fungal pathogen that affects the production of many economically important crops worldwide. Recent reports suggest that this fungus is becoming the dominant species in soil and could become the main infectious fungus in the future. However, the infection mechanisms employed by F. oxysporum are poorly understood. In the present study, using a network meta-analysis technique and public transcriptome datasets for different F. oxysporum and plant interactions, we aimed to explore the common molecular infection strategy used by this fungus and to identify vital genes involved in this process. Principle component analysis showed that all the fungal culture samples from different datasets were clustered together, and were clearly separated from the infection samples, suggesting the feasibility of an integrated analysis of heterogeneous datasets. A total of 335 common differentially expressed genes (DEGs) were identified among these samples, of which 262 were upregulated and 73 were downregulated significantly across the datasets. The most enriched functional categories of the common DEGs were carbohydrate metabolism, amino acid metabolism, and lipid metabolism. Nine co-expression modules were identified, and two modules, the turquoise module and the blue module, correlated positively and negatively with all the infection processes, respectively. Co-expression networks were constructed for these two modules and hub genes were identified and validated. Our results comprise a cross fungal-host interaction resource, highlighting the use of a network biology approach to gain molecular insights.
PMID: 36090060
Front Microbiol , IF:5.64 , 2022 , V13 : P949152 doi: 10.3389/fmicb.2022.949152
Microbiome and pathobiome analyses reveal changes in community structure by foliar pathogen infection in rice.
Plant Microbiology Laboratory, Tokyo University of Agriculture and Technology, Tokyo, Japan.; Department of Plant Pathology, Bangladesh Agricultural University, Mymensingh, Bangladesh.
Increasing evidence suggests that the plant rhizosphere may recruit beneficial microbes to suppress soil-borne pathogens, but microbiome assembly due to foliar pathogen infection and ecological mechanisms that govern microbiome assembly and functions in the diseased host are not fully understood. To provide a comprehensive view of the rice-associated microbiome, we compared bacterial and fungal communities of healthy rice and those infected with Magnaporthe oryzae, the causal agent of blast disease. We found that the soil had a greater diversity of bacterial and fungal communities than plant endospheric communities. There was no significant dysbiosis of bacterial and fungal microbiome diversity due to disease, but it caused a substantial alteration of bacterial community structure in the root and rhizosphere compartments. The pathobiome analysis showed that the microbiome community structure of leaf and grain tissues was changed markedly at the pathogen infection site, although the alpha diversity did not change. Correspondingly, the relative abundances of some bacteria and fungi were clearly altered in symptomatic tissues. We noted an increase in Rhizobium bacteria and a decline of Tylospora, Clohesyomyces, and Penicillium fungi in the symptomatic leaf and grain tissues from both locations. According to the inferred microbial network, several direct interactions between M. oryzae and other microbes were identified. The majority of edges in the interaction network were positive in diseased samples; contrastingly, the number of edges was much lower in the healthy samples. With source tracking analysis, we observed a sharp contrast in the source of root endosphere bacteria due to Magnaporthe infection. Whereas the majority (71%) of healthy root bacteria could be tracked from the soil, only a very small portion (17%) could be tracked from the soil for diseased samples. These results advanced our understanding and provided potential ideas and a theoretical basis for studying pathobiome and exploiting the microbiome for sustainable agriculture.
PMID: 35983324
Microbiol Res , IF:5.415 , 2022 Sep , V262 : P127084 doi: 10.1016/j.micres.2022.127084
Effect of the mineral-microbial complexes on the quality, soil nutrients, and microbial community of tailing substrates for growing potted Rorippa.
Key Laboratory of Ministry of Education on Safe Mining of Deep Metal Mines, Northeastern University, Shenyang 110819, PR China.; School of Life Science and Biopharmaceutics, Shenyang Pharmaceutical University, Shenyang 110016, PR China.; College of Architecture and Environment, Ningxia Institute of Science and Technology, Shizuishan 753000, PR China.; Institute for Frontier Technologies of Low-Carbon Steelmaking, Northeastern University, Shenyang 110819, PR China.; Key Laboratory of Ministry of Education on Safe Mining of Deep Metal Mines, Northeastern University, Shenyang 110819, PR China. Electronic address: hxmin_jj@163.com.
With China's industrialization and a rapidly developing coal industry, tailings have become one of the most widely distributed solid wastes, responsible for degrading available land and damaging the surrounding ecological environment. This study investigated the effect of adding mineral-microbial complexes to tailing substrates for the improvement of plant growth and substrate microbial community. The results revealed that compared with other treatments, the growth of Rorippa was considerably better after the addition of mineral-microbial complexes to the substrate, indicating that the mineral-microbial complexes promoted plant growth. After the addition of mineral-microbial complexes, the fertility indicators of the substrate showed a substantial improvement, in addition to the pH and organic matter (OM). The addition of fertilizers to the substrate plays a key role in plant growth, whereas the addition of microbial supplements to the substrate alone has little effect on plant growth. The results of high-throughput sequencing showed that the main microbial communities present in the substrate were Proteobacteria, Actinobacteria, Firmicutes, Bacteroidetes, and Nitrospirae. The results of the microbial community alpha-diversity analysis showed that the addition of the mineral-microbial complexes improved the abundance and diversity of the substrate microbial community. Results of the microbial community beta-diversity analysis indicated that the experimental group showed a higher correlation with the microbial community relative to the background group. Network analysis revealed similar correlations between microbial communities and environmental factors, and total phosphorous (TP)-pH-available potassium (AK)-available nitrogen (AN) and TP-electronic conductivity (EC)-AK-AN were the main drivers of microbial communities in the background and experimental groups, respectively. The findings of this study provide a theoretical basis for the resource utilization of tailings and vegetation restoration using tailings.
PMID: 35690045
Metabolites , IF:4.932 , 2022 Sep , V12 (9) doi: 10.3390/metabo12090871
Regulation Mechanism of Plant Pigments Biosynthesis: Anthocyanins, Carotenoids, and Betalains.
Hainan Yazhou Bay Seed Laboratory, Sanya Nanfan Research Institute of Hainan University, Sanya 572025, China.; College of Tropical Crops, Hainan University, Haikou 570228, China.
Anthocyanins, carotenoids, and betalains are known as the three major pigments in the plant kingdom. Anthocyanins are flavonoids derived from the phenylpropanoid pathway. They undergo acylation and glycosylation in the cytoplasm to produce anthocyanin derivatives and deposits in the cytoplasm. Anthocyanin biosynthesis is regulated by the MBW (comprised by R2R3-MYB, basic helix-loop-helix (bHLH) and WD40) complex. Carotenoids are fat-soluble terpenoids whose synthetic genes also are regulated by the MBW complex. As precursors for the synthesis of hormones and nutrients, carotenoids are not only synthesized in plants, but also synthesized in some fungi and bacteria, and play an important role in photosynthesis. Betalains are special water-soluble pigments that exist only in Caryophyllaceae plants. Compared to anthocyanins and carotenoids, the synthesis and regulation mechanism of betalains is simpler, starting from tyrosine, and is only regulated by MYB (myeloblastosis). Recently, a considerable amount of novel information has been gathered on the regulation of plant pigment biosynthesis, specifically with respect to aspects. In this review, we summarize the knowledge and current gaps in our understanding with a view of highlighting opportunities for the development of pigment-rich plants.
PMID: 36144275
Plant Sci , IF:4.729 , 2022 Sep , V325 : P111459 doi: 10.1016/j.plantsci.2022.111459
ZmDWF1 regulates leaf angle in maize.
State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou, China.; College of Agronomy, National Key Laboratory of Wheat and Maize Crop Science and Key Laboratory of Regulating and Controlling Crop Growth and Development Ministry of Education, Henan Agricultural University, No. 15 Longzihu University Park, Zhengdong New Area, Zhengzhou, Henan 450046, China; Henan Academy of Agricultural Science, Zhengzhou, Henan 450002, China.; College of Agronomy, National Key Laboratory of Wheat and Maize Crop Science and Key Laboratory of Regulating and Controlling Crop Growth and Development Ministry of Education, Henan Agricultural University, No. 15 Longzihu University Park, Zhengdong New Area, Zhengzhou, Henan 450046, China.; College of Agronomy, National Key Laboratory of Wheat and Maize Crop Science and Key Laboratory of Regulating and Controlling Crop Growth and Development Ministry of Education, Henan Agricultural University, No. 15 Longzihu University Park, Zhengdong New Area, Zhengzhou, Henan 450046, China. Electronic address: kulixia0371@163.com.
Leaf angle (LA) is a critical agronomic trait enhancing grain yield under high-density planting in maize. A number of researches have been conducted in recent years to investigate the quantitative trait loci/genes responsible for LA variation, while only a few genes were identified through map-based cloning. Here we cloned the ZmDWF1 gene, which was previously reported to encode Delta24-sterol reductase in the brassinosteroids (BRs) biosynthesis pathway. Overexpression of ZmDWF1 resulted in enlarged LA, indicating that ZmDWF1 is a positive regulator of LA in maize. To reveal the regulatory framework of ZmDWF1, we conducted RNA-Sequencing and yeast-two hybrid (Y2H) screening analysis. RNA-Sequencing analyzing results indicate ZmDWF1 mainly affected expression level of genes involved in cell wall associated metabolism and hormone metabolism including BR, gibberellin, and auxin. Y2H screening with Bi-FC assay confirmed three proteins (ZmPP2C-1, ZmROF1, and ZmTWD1) interacting with ZmDWF1. We revealed a new regulatory network of ZmDWF1 gene in controlling plant architecture in maize.
PMID: 36113675
Phytopathology , IF:4.025 , 2022 Aug doi: 10.1094/PHYTO-05-22-0177-R
Metabolite signature and differential expression of genes in Washington Navel oranges (Citrus sinesis Osbeck) infected by Spiroplasma citri.
UC Davis, Food Science & Technology, Davis, California, United States; cjmcneil@ucdavis.edu.; University of California Davis, Contained Research Facility, Davis, California, United States; kjaraujo@ucdavis.edu.; UC Davis, Contained Research Facility, Davis, California, United States; kegodfrey@ucdavis.edu.; UC Davis, Nutrition, One Shields Ave, Davis, California, United States, 95616-5270.; UC Davis, Food Science & Technology, One Shields Ave, Davis, California, United States, 95616-5270; cslupsky@ucdavis.edu.
Spiroplasma citri (S. citri) is the pathogen that causes citrus stubborn disease (CSD). Infection of citrus with S. citri has been shown to cause leaf mottling, reduce fruit yield, and stunt tree growth. Fruit from trees exhibiting symptoms of CSD are misshapen and discolored. The symptoms of CSD are easily confused with nutrient deficiencies or symptoms of citrus greening disease. In this study, young Washington navel oranges (Citrus sinensis Osbeck) were graft inoculated with budwood originating from trees confirmed infected with S. citri. Leaf samples were collected monthly for 10 months for metabolomics and differential gene expression analyses. Significant differences in the concentration of metabolites and expressed genes were observed between control and S. citri infected trees throughout the experiment. Metabolites and genes associated with important defense and stress pathways including jasmonic acid signaling, cell wall modification, amino acid biosynthesis, and the production of antioxidant and antimicrobial secondary metabolites were impacted by S. citri throughout the study, and even prior to symptom development. This work fills in a current gap in knowledge surrounding the pathogenicity of S. citri and provides a mechanistic explanation for the development of CSD symptoms in S. citri- infected plants.
PMID: 35984373
OMICS , IF:3.374 , 2022 Sep doi: 10.1089/omi.2022.0107
Systems Biology of COVID-19 and Human Diseases: Beyond a Bird's Eye View, and Toward One Health.
Department of Biotechnology, Indian Institute of Technology Hyderabad, Hyderabad, India.
As we gaze into the future beyond the current coronavirus disease 2019 (COVID-19) pandemic, there is a need to rethink our priorities in planetary health, research funding, and, importantly, the concepts and unchecked assumptions by which we attempt to understand health and prevent illness. Next-generation quantitative omics technologies promise a more profound and panoptic understanding of the dynamic pathophysiological processes and their aberrations in diverse diseased conditions. Systems biology research is highly relevant for COVID-19, a systemic disease affecting multiple organs and biological pathways. In addition, expanding the concept of health beyond humans so as to capture the importance of ecosystem health and recognizing the interdependence of human, animal, and plant health are enormously relevant and timely in the current historical moment of the pandemic. Notably, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus causing COVID-19, can affect our body clock, and the circadian aspects of this viral infection and host immunity need to be considered for its effective clinical management. Finally, we need to rethink and expand beyond the false binaries such as humans versus nature, and deploy multiomics systems biology research if we intend to design effective, innovative, and socioecological planetary health interventions to prevent future pandemics and ecological crises. We argue here that juxtaposing ecology and human health sciences scholarship is one of the key emerging tenets of 21st-century integrative biology.
PMID: 36095163
J Appl Genet , IF:3.24 , 2022 Sep doi: 10.1007/s13353-022-00722-y
Genome-wide post-transcriptional regulation of bovine mammary gland response to Streptococcus uberis.
Department of Animal Science, College of Agriculture, Isfahan University of Technology, 84156-83111, Isfahan, Iran.; Department of Animal Science, College of Agriculture, Isfahan University of Technology, 84156-83111, Isfahan, Iran. ss.sharifi2015@gmail.com.; Department of Animal Science, College of Agriculture, Isfahan University of Technology, 84156-83111, Isfahan, Iran. pakdel@iut.ac.ir.; Department of Animal and Poultry Science, College of Aburaihan, University of Tehran, Tehran, 3391653755, Iran.; Department of Plant Molecular Biotechnology, National Institute of Genetic Engineering and Biotechnology (NIGEB), Tehran, 84156-83111, Iran.; Institute of Biotechnology, Shiraz University, Shiraz, 71946-84334, Iran.; Novocraft Technologies Sdn Bhd, Petaling Jaya, Malaysia.
MicroRNAs (miRNAs) as post-transcriptionally regulators of gene expression have been shown to be critical regulators to fine-tuning immune responses, besides their criteria for being an ideal biomarker. The regulatory role of miRNAs in responses to most mastitis-causing pathogens is not well understood. Gram-positive Streptococcus uberis (Str. uberis), the leading pathogen in dairy herds, cause both clinical and subclinical infections. In this study, a system biology approach was used to better understand the main post-transcriptional regulatory functions and elements of bovine mammary gland response to Str. uberis infection. Publicly available miRNA-Seq data containing 50 milk samples of the ten dairy cows (five controls and five infected) were retrieved for this current research. Functional enrichment analysis of predicted targets revealed that highly confident responsive miRNAs (4 up- and 19 downregulated) mainly regulate genes involved in the regulation of transcription, apoptotic process, regulation of cell adhesion, and pro-inflammatory signaling pathways. Time series analysis showed that six gene clusters significantly differed in comparisons between Str. uberis-induced samples with controls. Additionally, other bioinformatic analysis, including upstream network analysis, showed essential genes, including TP53 and TGFB1 and some small molecules, including glucose, curcumin, and LPS, commonly regulate most of the downregulated miRNAs. Upregulated miRNAs are commonly controlled by the most important genes, including IL1B, NEAT1, DICER1 enzyme and small molecules including estradiol, tamoxifen, estrogen, LPS, and epigallocatechin. Our study used results of next-generation sequencing to reveal key miRNAs as the main regulator of gene expression responses to a Gram-positive bacterial infection. Furthermore, by gene regulatory network (GRN) analysis, we can introduce the common upregulator transcription factor of these miRNAs. Such milk-based miRNA signature(s) would facilitate risk stratification for large-scale prevention programs and provide an opportunity for early diagnosis and therapeutic intervention.
PMID: 36066834
G3 (Bethesda) , IF:3.154 , 2022 Aug , V12 (9) doi: 10.1093/g3journal/jkac167
Analysis of transcriptome data and quantitative trait loci enables the identification of candidate genes responsible for fiber strength in Gossypium barbadense.
College of Agronomy, Xinjiang Agricultural University, Urumqi, Xinjiang 830052, China.
Gossypium barbadense possesses a superior fiber quality because of its fiber length and strength. An in-depth analysis of the underlying genetic mechanism could aid in filling the gap in research regarding fiber strength and could provide helpful information for Gossypium barbadense breeding. Three quantitative trait loci related to fiber strength were identified from a Gossypium barbadense recombinant inbred line (PimaS-7 x 5917) for further analysis. RNA sequencing was performed in the fiber tissues of PimaS-7 x 5917 0-35 days postanthesis. Four specific modules closely related to the secondary wall-thickening stage were obtained using the weighted gene coexpression network analysis. In total, 55 genes were identified as differentially expressed from 4 specific modules. Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes were used for enrichment analysis, and Gbar_D11G032910, Gbar_D08G020540, Gbar_D08G013370, Gbar_D11G033670, and Gbar_D11G029020 were found to regulate fiber strength by playing a role in the composition of structural constituents of cytoskeleton and microtubules during fiber development. Quantitative real-time PCR results confirmed the accuracy of the transcriptome data. This study provides a quick strategy for exploring candidate genes and provides new insights for improving fiber strength in cotton.
PMID: 35881688
Biosystems , IF:1.973 , 2022 Sep , V219 : P104732 doi: 10.1016/j.biosystems.2022.104732
Data-driven dynamical modelling of a pathogen-infected plant gene regulatory network: A comparative analysis.
School of Engineering, University of Warwick, CV4 7AL, Coventry, UK. Electronic address: M.Foo@warwick.ac.uk.; Institute of Computational Biology, Helmholtz Munich, 85764, Neuherberg, Germany; Department of Translational Psychiatry, Max Planck Institute of Psychiatry, International Max Planck Research School for Translational Psychiatry (IMPRS-TP), 80804, Munich, Germany; TUM School of Life Sciences Weihenstephan, Technical University of Munich, 85354, Freising, Germany. Electronic address: leander.dony@helmholtz-munich.de.; Centre for Computational Science and Mathematical Modelling, Coventry University, CV1 2JH, Coventry, UK. Electronic address: Fei.He@coventry.ac.uk.
Recent advances in synthetic biology have enabled the design of genetic feedback control circuits that could be implemented to build resilient plants against pathogen attacks. To facilitate the proper design of these genetic feedback control circuits, an accurate model that is able to capture the vital dynamical behaviour of the pathogen-infected plant is required. In this study, using a data-driven modelling approach, we develop and compare four dynamical models (i.e. linear, Michaelis-Menten with Hill coefficient (Hill Function), standard S-System and extended S-System) of a pathogen-infected plant gene regulatory network (GRN). These models are then assessed across several criteria, i.e. ease of identifying the type of gene regulation, the predictive capability, Akaike Information Criterion (AIC) and the robustness to parameter uncertainty to determine its viability of balancing between biological complexity and accuracy when modelling the pathogen-infected plant GRN. Using our defined ranking score, we obtain the following insights to the modelling of GRN. Our analyses show that despite commonly used and provide biological relevance, the Hill Function model ranks the lowest while the extended S-System model ranks highest in the overall comparison. Interestingly, the performance of the linear model is more consistent throughout the comparison, making it the preferred model for this pathogen-infected plant GRN when considering data-driven modelling approach.
PMID: 35781035
Front Psychol , 2022 , V13 : P983698 doi: 10.3389/fpsyg.2022.983698
The need for social network analysis for the investigation of affective variables in second language acquisition.
School of Foreign Languages, Hunan University of Arts and Science, Changde, China.; Lyceum of the Philippines University-Batangas, Batangas, Philippines.
Considering the inherent developmental nature of language learners' affective variables (e.g., their motivation, grit, foreign language enjoyment, and boredom), nuances of the development of these constructs need to be approached from a complex dynamic systems theory (CDST) perspective. Among the qualitative research methodologies compatible with the CDST is the social network analysis (SNA) with the interconnectedness and interdependence of systems within a social network at its core. In this article, an overall introduction to SNA is presented first and then followed by a review of the limited existing literature on second language acquisition (SLA) studies. Then, I argue why this innovative research method is suitable to investigate the dynamic nature of L2 learners' affective variables in the social network of classroom learning. I also suggest several relevant research questions that can potentially be formulated and answered using the SNA. The article ends with conclusive remarks on the need for a more extensive use of innovative CDST-compatible research methods such as SNA in the prospective SLA line of research.
PMID: 36003100
J Clin Psychol , 2022 Aug doi: 10.1002/jclp.23432
Using theory to guide exploratory network analyses.
Mississippi State University, Mississippi State, Mississippi, USA.; Murray State University, Murray, Kentucky, USA.; The New School for Social Research, New York, New York, USA.
The use of exploratory network analysis has increased in psychopathology research over the past decade. A benefit of exploratory network analysis is the wealth of information it can provide; however, a single analysis may generate more inferences than what can be discussed in one manuscript (e.g., centrality indices of each node). This necessitates that authors choose which results to discuss in further detail and which to omit. Without a guide for this process, the likelihood of a biased interpretation is high. We propose that the integration of theory throughout the research process makes the interpretation of exploratory networks more manageable for the researcher and more likely to result in an interpretation that advances science. The goals of this paper are to differentiate between exploratory and confirmatory network analyses, discuss the utility of exploratory work, and provide a practical framework that uses theory as a guide to interpret exploratory network analyses.
PMID: 35999793
Radiol Phys Technol , 2022 Aug doi: 10.1007/s12194-022-00670-6
Reproducibility of functional connectivity metrics estimated from resting-state functional MRI with differences in days, coils, and global signal regression.
Department of Radiological and Medical Laboratory Sciences, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan.; Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, 1-1-20 Daiko Minami, Higashi-ku, Nagoya, Aichi, 461-8673, Japan. ebagarinao@met.nagoya-u.ac.jp.; Brain and Mind Research Center, Nagoya University, Nagoya, Aichi, Japan. ebagarinao@met.nagoya-u.ac.jp.; Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, 1-1-20 Daiko Minami, Higashi-ku, Nagoya, Aichi, 461-8673, Japan.; Brain and Mind Research Center, Nagoya University, Nagoya, Aichi, Japan.; Department of Neurology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan.; Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan.; Department of Neurosurgery, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan.; Department of Radiology, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan.; Department of Psychiatry, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan.; Department of Neurology, Aichi Medical University, Nagakute, Aichi, Japan.
In multisite studies, differences in imaging acquisition systems could affect the reproducibility of the results when examining changes in brain function using resting-state functional magnetic resonance imaging (rs-fMRI). This is also important for longitudinal studies, in which changes in equipment settings can occur. This study examined the reproducibility of functional connectivity (FC) metrics estimated from rs-fMRI data acquired using scanner receiver coils with different numbers of channels. This study involved 80 rs-fMRI datasets from 20 healthy volunteers scanned in two independent imaging sessions using both 12- and 32-channel coils for each session. We used independent component analysis (ICA) to evaluate the FC of canonical resting-state networks (RSNs) and graph theory to calculate several whole-brain network metrics. The effect of global signal regression (GSR) as a preprocessing step was also considered. Comparisons within and between receiver coils were performed. Irrespective of the GSR, RSNs derived from rs-fMRI data acquired using the same receiver coil were reproducible, but not from different receiver coils. However, both the GSR and the channel count of the receiver coil have discernible effects on the reproducibility of network metrics estimated using whole-brain network analysis. The data acquired using the 32-channel coil tended to have better reproducibility than those acquired using the 12-channel coil. Our findings suggest that the reproducibility of FC metrics estimated from rs-fMRI data acquired using different receiver coils showed some level of dependence on the preprocessing method and the type of analysis performed.
PMID: 35960494
Neuropsychol Dev Cogn B Aging Neuropsychol Cogn , 2022 Sep , V29 (5) : P903-927 doi: 10.1080/13825585.2021.1965951
Neuropsychological networks in cognitively healthy older adults and dementia patients.
Experimental Psychology Department, Complutense University of Madrid, Madrid, Spain.; Center for Biomedical Technology, Universidad Politecnica De Madrid, Madrid, Spain.
Neuropsychological tests have commonly been used to determine the organization of cognitive functions by identifying latent variables. In contrast, an approach which has seldom been employed is network analysis. We characterize the network structure of a set of representative neuropsychological test scores in cognitively healthy older adults and MCI and dementia patients using network analysis. We employed the neuropsychological battery from the National Alzheimer's Coordinating Center which included healthy controls (n = 7623), mild cognitive impairment patients (n = 5981) and dementia patients (n = 2040), defined according to the Clinical Dementia Rating. The results showed that, according to several network analysis measures, the most central cognitive function is executive function followed by attention, language, and memory. At the test level, the most central test was the Trail Making Test B, which measures cognitive flexibility. Importantly, these results and most other network measures, such as the community organization and graph representation, were similar across the three diagnostic groups. Therefore, network analysis can help to establish a ranking of cognitive functions and tests based on network centrality and suggests that this organization is preserved in dementia. Central nodes might be particularly relevant both from a theoretical and clinical point of view, as they are more associated with other nodes, and their disruption is likely to have a larger effect on the overall network than peripheral nodes. The present analysis may provide a proof of principle for the application of network analysis to cognitive data.
PMID: 34415217
Sheng Wu Gong Cheng Xue Bao , 2022 Aug , V38 (8) : P2798-2810 doi: 10.13345/j.cjb.220127
[Advances in the plant multicellular network analysis].
Chongqing Key Laboratory of Plant Resource Conservation and Germplasm Innovation, College of Life Sciences, Southwest University, Chongqing 400715, China.; Key Laboratory of Eco-Environments in Three Gorges Reservoir Region (Ministry of Education), Southwest University, Chongqing 400715, China.
Multicellular network analysis is a method for topological properties analysis of cells. The functions of organs are determined by their inner cells. The arrangement of cells within organs endows higher-order functionality through a structure-function relationship, though the organizational properties of these multicellular configurations remain poorly understood. Multicellular network analysis with multicellular models established by 3D scanning of plants, will further discover the plant development mechanism, and provide clues for synthesizing plant multicellular systems. In this paper, we review the development of multicellular models, summarize the process of multicellular network analysis, and describe the development and application of multicellular network analysis in plants. In addition, this review also provides perspective on future development of plant multicellular network analysis.
PMID: 36002411