A quantitative RT-PCR platform for high-throughput expression profiling of 2500 rice transcription factors

<p>Abstract</p> <p>Background</p> <p>Quantitative reverse transcription – polymerase chain reaction (qRT-PCR) has been demonstrated to be particularly suitable for the analysis of weakly expressed genes, such as those encoding transcription factors. Rice (<it>Oryza sativa </it>L.) is an important crop and the most advanced model for monocotyledonous species; its nuclear genome has been sequenced and molecular tools are being developed for functional analyses. However, high-throughput methods for rice research are still limited and a large-scale qRT-PCR platform for gene expression analyses has not been reported.</p> <p>Results</p> <p>We established a qRT-PCR platform enabling the multi-parallel determination of the expression levels of more than 2500 rice transcription factor genes. Additionally, using different rice cultivars, tissues and physiological conditions, we evaluated the expression stability of seven reference genes. We demonstrate this resource allows specific and reliable detection of the expression of transcription factor genes in rice.</p> <p>Conclusion</p> <p>Multi-parallel qRT-PCR allows the versatile and sensitive transcriptome profiling of large numbers of rice transcription factor genes. The new platform complements existing microarray-based expression profiling techniques, by allowing the analysis of lowly expressed transcription factor genes to determine their involvement in developmental or physiological processes. We expect that this resource will be of broad utility to the scientific community in the further development of rice as an important model for plant science.</p

A quantitative RT-PCR platform for high-throughput expression profiling of 2500 rice transcription factors

<p>Abstract</p> <p>Background</p> <p>Quantitative reverse transcription – polymerase chain reaction (qRT-PCR) has been demonstrated to be particularly suitable for the analysis of weakly expressed genes, such as those encoding transcription factors. Rice (<it>Oryza sativa </it>L.) is an important crop and the most advanced model for monocotyledonous species; its nuclear genome has been sequenced and molecular tools are being developed for functional analyses. However, high-throughput methods for rice research are still limited and a large-scale qRT-PCR platform for gene expression analyses has not been reported.</p> <p>Results</p> <p>We established a qRT-PCR platform enabling the multi-parallel determination of the expression levels of more than 2500 rice transcription factor genes. Additionally, using different rice cultivars, tissues and physiological conditions, we evaluated the expression stability of seven reference genes. We demonstrate this resource allows specific and reliable detection of the expression of transcription factor genes in rice.</p> <p>Conclusion</p> <p>Multi-parallel qRT-PCR allows the versatile and sensitive transcriptome profiling of large numbers of rice transcription factor genes. The new platform complements existing microarray-based expression profiling techniques, by allowing the analysis of lowly expressed transcription factor genes to determine their involvement in developmental or physiological processes. We expect that this resource will be of broad utility to the scientific community in the further development of rice as an important model for plant science.</p

Interaction with Diurnal and Circadian Regulation Results in Dynamic Metabolic and Transcriptional Changes during Cold Acclimation in Arabidopsis

In plants, there is a large overlap between cold and circadian regulated genes and in Arabidopsis, we have shown that cold (4°C) affects the expression of clock oscillator genes. However, a broader insight into the significance of diurnal and/or circadian regulation of cold responses, particularly for metabolic pathways, and their physiological relevance is lacking. Here, we performed an integrated analysis of transcripts and primary metabolites using microarrays and gas chromatography-mass spectrometry. As expected, expression of diurnally regulated genes was massively affected during cold acclimation. Our data indicate that disruption of clock function at the transcriptional level extends to metabolic regulation. About 80% of metabolites that showed diurnal cycles maintained these during cold treatment. In particular, maltose content showed a massive night-specific increase in the cold. However, under free-running conditions, maltose was the only metabolite that maintained any oscillations in the cold. Furthermore, although starch accumulates during cold acclimation we show it is still degraded at night, indicating significance beyond the previously demonstrated role of maltose and starch breakdown in the initial phase of cold acclimation. Levels of some conventional cold induced metabolites, such as γ-aminobutyric acid, galactinol, raffinose and putrescine, exhibited diurnal and circadian oscillations and transcripts encoding their biosynthetic enzymes often also cycled and preceded their cold-induction, in agreement with transcriptional regulation. However, the accumulation of other cold-responsive metabolites, for instance homoserine, methionine and maltose, did not have consistent transcriptional regulation, implying that metabolic reconfiguration involves complex transcriptional and post-transcriptional mechanisms. These data demonstrate the importance of understanding cold acclimation in the correct day-night context, and are further supported by our demonstration of impaired cold acclimation in a circadian mutant

Adjustment of the Arabidopsis circadian oscillator by sugar signalling dictates the regulation of starch metabolism.

Arabidopsis plants store part of the carbon fixed by photosynthesis as starch to sustain growth at night. Two competing hypotheses have been proposed to explain this diel starch turnover based on either the measurement of starch abundance with respect to circadian time, or the sensing of sugars to feedback to the circadian oscillator to dynamically adjust the timing of starch turnover. We report a phase oscillator model that permitted derivation of the ideal responses of the circadian regulation of starch breakdown to maintain sucrose homeostasis. Testing the model predictions using a sugar-unresponsive mutant of Arabidopsis demonstrated that the dynamics of starch turnover arise from the circadian clock measuring and responding to the rate of change of cellular sucrose. Our theory and experiments suggest that starch turnover is controlled by the circadian clock acting as a dynamic homeostat responding to sucrose signals to maintain carbon homeostasis

The Aspergillus nidulans pyruvate dehydrogenase kinases are essential to integrate carbon source metabolism

The pyruvate dehydrogenase complex (PDH), that converts pyruvate to acetyl-coA, is regulated by pyruvate dehydrogenase kinases (PDHK) and phosphatases (PDHP) that have been shown to be important for morphology, pathogenicity and carbon source utilization in different fungal species. The aim of this study was to investigate the role played by the three PDHKs PkpA, PkpB and PkpC in carbon source utilization in the reference filamentous fungus Aspergillus nidulans, in order to unravel regulatory mechanisms which could prove useful for fungal biotechnological and biomedical applications. PkpA and PkpB were shown to be mitochondrial whereas PkpC localized to the mitochondria in a carbon source-dependent manner. Only PkpA was shown to regulate PDH activity. In the presence of glucose, deletion of pkpA and pkpC resulted in reduced glucose utilization, which affected carbon catabolite repression (CCR) and hydrolytic enzyme secretion, due to de-regulated glycolysis and TCA cycle enzyme activities. Furthermore, PkpC was shown to be required for the correct metabolic utilization of cellulose and acetate. PkpC negatively regulated the activity of the glyoxylate cycle enzyme isocitrate lyase (ICL), required for acetate metabolism. In summary, this study identified PDHKs important for the regulation of central carbon metabolism in the presence of different carbon sources, with effects on the secretion of biotechnologically important enzymes and carbon source-related growth. This work demonstrates how central carbon metabolism can affect a variety of fungal traits and lays a basis for further investigation into these characteristics with potential interest for different applications.We would like to thank the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), the Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP, grant numbers 2016/07870-9 for GHG and 2014/00789-6 for LJA), the Science Foundation Ireland (SCI, grant number 13/CDA/2142 for OB) for providing financial support.info:eu-repo/semantics/publishedVersio

Metabolite Profiles of Sugarcane Culm Reveal the Relationship Among Metabolism and Axillary Bud Outgrowth in Genetically Related Sugarcane Commercial Cultivars

Metabolic composition is known to exert influence on several important agronomic traits, and metabolomics, which represents the chemical composition in a cell, has long been recognized as a powerful tool for bridging phenotype–genotype interactions. In this work, sixteen truly representative sugarcane Brazilian varieties were selected to explore the metabolic networks in buds and culms, the tissues involved in the vegetative propagation of this species. Due to the fact that bud sprouting is a key trait determining crop establishment in the field, the sprouting potential among the genotypes was evaluated. The use of partial least square discriminant analysis indicated only mild differences on bud outgrowth potential under controlled environmental conditions. However, primary metabolite profiling provided information on the variability of metabolic features even under a narrow genetic background, typical for modern sugarcane cultivars. Metabolite–metabolite correlations within and between tissues revealed more complex patterns for culms in relation to buds, and enabled the recognition of key metabolites (e.g., sucrose, putrescine, glutamate, serine, and myo-inositol) affecting sprouting ability. Finally, those results were associated with the genetic background of each cultivar, showing that metabolites can be potentially used as indicators for the genetic background

Predominance of the SARS-CoV-2 lineage P.1 and its sublineage P.1.2 in patients from the metropolitan region of Porto Alegre, southern Brazil in March 2021

Almost a year after the COVID-19 pandemic had begun, new lineages (B.1.1.7, B.1.351, P.1, and B.1.617.2) associated with enhanced transmissibility, immunity evasion, and mortality were identified in the United Kingdom, South Africa, and Brazil. The previous most prevalent lineages in the state of Rio Grande do Sul (RS, Southern Brazil), B.1.1.28 and B.1.1.33, were rapidly replaced by P.1 and P.2, two B.1.1.28-derived lineages harboring the E484K mutation. To perform a genomic characterization from the metropolitan region of Porto Alegre, we sequenced viral samples to: (i) identify the prevalence of SARS-CoV-2 lineages in the region, the state, and bordering countries/regions; (ii) characterize the mutation spectra; (iii) hypothesize viral dispersal routes by using phylogenetic and phylogeographic approaches. We found that 96.4% of the samples belonged to the P.1 lineage and approximately 20% of them were assigned as the novel P.1.2, a P.1-derived sublineage harboring signature substitutions recently described in other Brazilian states and foreign countries. Moreover, sequences from this study were allocated in distinct branches of the P.1 phylogeny, suggesting multiple introductions in RS and placing this state as a potential diffusion core of P.1-derived clades and the emergence of P.1.2. It is uncertain whether the emergence of P.1.2 and other P.1 clades is related to clinical or epidemiological consequences. However, the clear signs of molecular diversity from the recently introduced P.1 warrant further genomic surveillance

Clinical metabolomics identifies blood serum branched chain amino acids as potential predictive biomarkers for chronic graft vs. host disease

The allogeneic hematopoietic stem cell transplantation procedure-the only curative therapy for many types of hematological cancers-is increasing, and graft vs. host disease (GVHD) is the main cause of morbidity and mortality after transplantation. Currently, GVHD diagnosis is clinically performed. Whereas, biomarker panels have been developed for acute GVHD (aGVHD), there is a lack of information about the chronic form (cGVHD). Using nuclear magnetic resonance (NMR) and gas chromatography coupled to time-of-flight (GC-TOF) mass spectrometry, this study prospectively evaluated the serum metabolome of 18 Brazilian patients who had undergone allogeneic hematopoietic stem cell transplantation (HSCT). We identified and quantified 63 metabolites and performed the metabolomic profile on day -10, day 0, day +10 and day +100, in reference to day of transplantation. Patients did not present aGVHD or cGVHD clinical symptoms at sampling times. From 18 patients analyzed, 6 developed cGVHD. The branched-chain amino acids (BCAAs) leucine and isoleucine were reduced and the sulfur-containing metabolite (cystine) was increased at day +10 and day +100. The area under receiver operating characteristics (ROC) curves was higher than 0.79. BCAA findings were validated by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) in 49 North American patients at day +100; however, cystine findings were not statistically significant in this patient set. Our results highlight the importance of multi-temporal and multivariate biomarker panels for predicting and understanding cGVHD9FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESP2011/06441-

Development of a Chlamydomonas reinhardtii metabolic network dynamic model to describe distinct phenotypes occurring at different CO2 levels

The increase in atmospheric CO2 due to anthropogenic activities is generating climate change, which has resulted in a subsequent rise in global temperatures with severe environmental impacts. Biological mitigation has been considered as an alternative for environmental remediation and reduction of greenhouse gases in the atmosphere. In fact, the use of easily adapted photosynthetic organisms able to fix CO2 with low-cost operation is revealing its high potential for industry. Among those organism, the algae Chlamydomonas reinhardtii have gain special attention as a model organism for studying CO2 fixation, biomass accumulation and bioenergy production upon exposure to several environmental conditions. In the present study, we studied the Chlamydomonas response to different CO2 levels by comparing metabolomics and transcriptomics data with the predicted results from our new-improved genomic-scale metabolic model. For this, we used in silico methods at steady dynamic state varying the levels of CO2. Our main goal was to improve our capacity for predicting metabolic routes involved in biomass accumulation. The improved genomic-scale metabolic model presented in this study was shown to be phenotypically accurate, predictive, and a significant improvement over previously reported models. Our model consists of 3726 reactions and 2436 metabolites, and lacks any thermodynamically infeasible cycles. It was shown to be highly sensitive to environmental changes under both steady-state and dynamic conditions. As additional constraints, our dynamic model involved kinetic parameters associated with substrate consumption at different growth conditions (i.e., low CO2-heterotrophic and high CO2-mixotrophic). Our results suggest that cells growing at high CO2 (i.e., photoautotrophic and mixotrophic conditions) have an increased capability for biomass production. In addition, we have observed that ATP production also seems to be an important limiting factor for growth under the conditions tested. Our experimental data (metabolomics and transcriptomics) and the results predicted by our model clearly suggest a differential behavior between low CO2-heterotrophic and high CO2-mixotrophic growth conditions. The data presented in the current study contributes to better dissect the biological response of C. reinhardtii, as a dynamic entity, to environmental and genetic changes. These findings are of great interest given the biotechnological potential of this microalga for CO2 fixation, biomass accumulation, and bioenergy production