scholarly journals Spatial resolution of an integrated C4+CAM photosynthetic metabolism

2021 ◽  
Author(s):  
Jose J Moreno-Villena ◽  
Haoran Zhou ◽  
Ian S Gilman ◽  
S. Lori Tausta ◽  
C. Y. Maurice Cheung

C4 and CAM photosynthesis have repeatedly evolved in plants over the past 30 million years. Because both repurpose the same set of enzymes but differ in their spatial and temporal deployment, they have long been considered as distinct and incompatible adaptations. Remarkably, Portulaca contains multiple C4 species that perform CAM when droughted. Spatially explicit analyses of gene expression reveal that C4 and CAM systems are completely integrated in P. oleracea, with CAM and C4 carbon fixation occurring in the same cells and CAM-generated metabolites likely incorporated directly into the C4 cycle. Flux balance analysis corroborates the gene expression and predicts an integrated C4+CAM system under drought. This first spatially explicit description of a C4+CAM photosynthetic metabolism presents a new blueprint for crop improvement.

2020 ◽  
Vol 80 (20) ◽  
pp. 4565-4577
Author(s):  
B. Bishal Paudel ◽  
Joshua E. Lewis ◽  
Keisha N. Hardeman ◽  
Corey E. Hayford ◽  
Charles J. Robbins ◽  
...  

2021 ◽  
Author(s):  
Karolina Heyduk ◽  
Edward McAssey ◽  
James Leebens-Mack

CAM photosynthesis has evolved repeatedly across the plant tree of life, yet our understanding of the genetic convergence across independent origins remains hampered by the lack of comparative studies. CAM is furthermore thought to be closely linked to the circadian clock in order to achieve temporal separation of carboxylation and sugar production. Here, we explore gene expression profiles in eight species from the Agavoideae (Asparagaceae) encompassing three independent origins of CAM. Using comparative physiology and transcriptomics, we examined the variable modes of CAM in this subfamily and the changes in gene expression across time of day and between well-watered and drought-stressed treatments. We further assessed gene expression and molecular evolution of genes encoding phosphoenolpyruvate carboxylase (PPC), an enzyme required for primary carbon fixation in CAM. Most time-of-day expression profiles are largely conserved across all eight species and suggest that large perturbations to the central clock are not required for CAM evolution. In contrast, transcriptional response to drought is highly lineage specific. Yucca and Beschorneria have CAM-like expression of PPC2, a copy of PPC that has never been shown to be recruited for CAM in angiosperms, and evidence of positive selection in PPC genes implicates mutations that may have facilitated the recruitment for CAM function early in the evolutionary history of the Agavoideae. Together the physiological and transcriptomic comparison of closely related C3 and CAM species reveals similar gene expression profiles, with the notable exception of differential recruitment of carboxylase enzymes for CAM function.


2020 ◽  
Vol 48 (5) ◽  
pp. 1889-1903
Author(s):  
Fernando Cruz ◽  
José P. Faria ◽  
Miguel Rocha ◽  
Isabel Rocha ◽  
Oscar Dias

The current survey aims to describe the main methodologies for extending the reconstruction and analysis of genome-scale metabolic models and phenotype simulation with Flux Balance Analysis mathematical frameworks, via the integration of Transcriptional Regulatory Networks and/or gene expression data. Although the surveyed methods are aimed at improving phenotype simulations obtained from these models, the perspective of reconstructing integrated genome-scale models of metabolism and gene expression for diverse prokaryotes is still an open challenge.


2020 ◽  
Author(s):  
Lungwani Muungo

The purpose of this review is to evaluate progress inmolecular epidemiology over the past 24 years in canceretiology and prevention to draw lessons for futureresearch incorporating the new generation of biomarkers.Molecular epidemiology was introduced inthe study of cancer in the early 1980s, with theexpectation that it would help overcome some majorlimitations of epidemiology and facilitate cancerprevention. The expectation was that biomarkerswould improve exposure assessment, document earlychanges preceding disease, and identify subgroupsin the population with greater susceptibility to cancer,thereby increasing the ability of epidemiologic studiesto identify causes and elucidate mechanisms incarcinogenesis. The first generation of biomarkers hasindeed contributed to our understanding of riskandsusceptibility related largely to genotoxic carcinogens.Consequently, interventions and policy changes havebeen mounted to reduce riskfrom several importantenvironmental carcinogens. Several new and promisingbiomarkers are now becoming available for epidemiologicstudies, thanks to the development of highthroughputtechnologies and theoretical advances inbiology. These include toxicogenomics, alterations ingene methylation and gene expression, proteomics, andmetabonomics, which allow large-scale studies, includingdiscovery-oriented as well as hypothesis-testinginvestigations. However, most of these newer biomarkershave not been adequately validated, and theirrole in the causal paradigm is not clear. There is a needfor their systematic validation using principles andcriteria established over the past several decades inmolecular cancer epidemiology.


2020 ◽  
Vol 117 (10) ◽  
pp. 3006-3017 ◽  
Author(s):  
Carolina Shene ◽  
Paris Paredes ◽  
Liset Flores ◽  
Allison Leyton ◽  
Juan A. Asenjo ◽  
...  

2020 ◽  
Vol 22 (1) ◽  
pp. 253
Author(s):  
Venura Herath ◽  
Jeanmarie Verchot

The basic region-leucine zipper (bZIP) transcription factors (TFs) form homodimers and heterodimers via the coil–coil region. The bZIP dimerization network influences gene expression across plant development and in response to a range of environmental stresses. The recent release of the most comprehensive potato reference genome was used to identify 80 StbZIP genes and to characterize their gene structure, phylogenetic relationships, and gene expression profiles. The StbZIP genes have undergone 22 segmental and one tandem duplication events. Ka/Ks analysis suggested that most duplications experienced purifying selection. Amino acid sequence alignments and phylogenetic comparisons made with the Arabidopsis bZIP family were used to assign the StbZIP genes to functional groups based on the Arabidopsis orthologs. The patterns of introns and exons were conserved within the assigned functional groups which are supportive of the phylogeny and evidence of a common progenitor. Inspection of the leucine repeat heptads within the bZIP domains identified a pattern of attractive pairs favoring homodimerization, and repulsive pairs favoring heterodimerization. These patterns of attractive and repulsive heptads were similar within each functional group for Arabidopsis and S. tuberosum orthologs. High-throughput RNA-seq data indicated the most highly expressed and repressed genes that might play significant roles in tissue growth and development, abiotic stress response, and response to pathogens including Potato virus X. These data provide useful information for further functional analysis of the StbZIP gene family and their potential applications in crop improvement.


Microbiome ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Jack Jansma ◽  
Sahar El Aidy

AbstractThe human gut harbors an enormous number of symbiotic microbes, which is vital for human health. However, interactions within the complex microbiota community and between the microbiota and its host are challenging to elucidate, limiting development in the treatment for a variety of diseases associated with microbiota dysbiosis. Using in silico simulation methods based on flux balance analysis, those interactions can be better investigated. Flux balance analysis uses an annotated genome-scale reconstruction of a metabolic network to determine the distribution of metabolic fluxes that represent the complete metabolism of a bacterium in a certain metabolic environment such as the gut. Simulation of a set of bacterial species in a shared metabolic environment can enable the study of the effect of numerous perturbations, such as dietary changes or addition of a probiotic species in a personalized manner. This review aims to introduce to experimental biologists the possible applications of flux balance analysis in the host-microbiota interaction field and discusses its potential use to improve human health.


GigaScience ◽  
2020 ◽  
Vol 9 (11) ◽  
Author(s):  
Alexandra J Lee ◽  
YoSon Park ◽  
Georgia Doing ◽  
Deborah A Hogan ◽  
Casey S Greene

Abstract Motivation In the past two decades, scientists in different laboratories have assayed gene expression from millions of samples. These experiments can be combined into compendia and analyzed collectively to extract novel biological patterns. Technical variability, or "batch effects," may result from combining samples collected and processed at different times and in different settings. Such variability may distort our ability to extract true underlying biological patterns. As more integrative analysis methods arise and data collections get bigger, we must determine how technical variability affects our ability to detect desired patterns when many experiments are combined. Objective We sought to determine the extent to which an underlying signal was masked by technical variability by simulating compendia comprising data aggregated across multiple experiments. Method We developed a generative multi-layer neural network to simulate compendia of gene expression experiments from large-scale microbial and human datasets. We compared simulated compendia before and after introducing varying numbers of sources of undesired variability. Results The signal from a baseline compendium was obscured when the number of added sources of variability was small. Applying statistical correction methods rescued the underlying signal in these cases. However, as the number of sources of variability increased, it became easier to detect the original signal even without correction. In fact, statistical correction reduced our power to detect the underlying signal. Conclusion When combining a modest number of experiments, it is best to correct for experiment-specific noise. However, when many experiments are combined, statistical correction reduces our ability to extract underlying patterns.


2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Kiros Tsegay Deribew

AbstractThe main grassland plain of Nech Sar National Park (NSNP) is a federally managed protected area in Ethiopia designated to protect endemic and endangered species. However, like other national parks in Ethiopia, the park has experienced significant land cover change over the past few decades. Indeed, the livelihoods of local populations in such developing countries are entirely dependent upon natural resources and, as a result, both direct and indirect anthropogenic pressures have been placed on natural parks. While previous research has looked at land cover change in the region, these studies have not been spatially explicit and, as a result, knowledge gaps in identifying systematic transitions continue to exist. This study seeks to quantify the spatial extent and land cover change trends in NSNP, identify the strong signal transitions, and identify and quantify the location of determinants of change. To this end, the author classifies panchromatic aerial photographs in 1986, multispectral SPOT imagery in 2005, and Sentinel imagery in 2019. The spatial extent and trends of land cover change analysis between these time periods were conducted. The strong signal transitions were systematically identified and quantified. Then, the basic driving forces of the change were identified. The locations of these transitions were also identified and quantified using the spatially explicit statistical model. The analysis revealed that over the past three decades (1986–2019), nearly 52% of the study area experienced clear landscape change, out of which the net change and swap change attributed to 39% and 13%, respectively. The conversion of woody vegetation to grassland (~ 5%), subsequently grassland-to-open-overgrazed land (28.26%), and restoration of woody vegetation (0.76%) and grassland (0.72%) from riverine forest and open-overgrazed land, respectively, were found to be the fully systematic transitions whereas the rest transitions were recorded either partly systematic or random transitions. The location of these most systematic land cover transitions identified through the spatially explicit statistical modeling showed drivers due to biophysical conditions, accessibility, and urban/market expansions, coupled with successive government policies for biodiversity management, geo-politics, demographic, and socioeconomic factors. These findings provide important insights into biodiversity loss, land degradation, and ecosystem disruption. Therefore, the model for predicted probability generally suggests a 0.75 km and 0.72 km buffers which are likely to protect forest and grassland from conversion to grassland and open-overgrazed land, respectively.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Fernando Santos-Beneit ◽  
Vytautas Raškevičius ◽  
Vytenis A. Skeberdis ◽  
Sergio Bordel

AbstractIn this study we have developed a method based on Flux Balance Analysis to identify human metabolic enzymes which can be targeted for therapeutic intervention against COVID-19. A literature search was carried out in order to identify suitable inhibitors of these enzymes, which were confirmed by docking calculations. In total, 10 targets and 12 bioactive molecules have been predicted. Among the most promising molecules we identified Triacsin C, which inhibits ACSL3, and which has been shown to be very effective against different viruses, including positive-sense single-stranded RNA viruses. Similarly, we also identified the drug Celgosivir, which has been successfully tested in cells infected with different types of viruses such as Dengue, Zika, Hepatitis C and Influenza. Finally, other drugs targeting enzymes of lipid metabolism, carbohydrate metabolism or protein palmitoylation (such as Propylthiouracil, 2-Bromopalmitate, Lipofermata, Tunicamycin, Benzyl Isothiocyanate, Tipifarnib and Lonafarnib) are also proposed.


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