Latest Publications
Ceg1 depletion reveals mechanisms governing degradation of non-capped RNAs in Saccharomyces cerevisiae
Onofrio Zanin, Matthew Eastham, Kinga Winczura, Mark Ashe, Rocio T. Martinez-Nunez, Daniel Hebenstreit and Pawel Grzechnik
Most functional eukaryotic mRNAs contain a 5’ 7-methylguanosine (m7 G) cap. Although capping is essential for many biological processes,the fate of uncapped transcripts has not been studied extensively. Here, we employed fast nuclear depletion of the capping enzymes in Saccharomyces cerevisiae to uncover the turnover of the transcripts that failed to be capped. We show that although the degradation of cap-deficient mRNA is dominant, the levels of hundreds of non-capped mRNAs increase upon depletion of the capping enzymes. Overall, the abundance of non-capped mRNAs is inversely correlated to the expression levels, altogether resembling the effects observed in cells lacking the cytoplasmic 5’-3’ exonuclease Xrn1 and indicating differential degradation fates of non-capped mRNAs. Our data indicate that the cap presence is essential to initiate the Xrn1-dependent degradation of mRNAs underpinning the role of 5’ cap in the Xrn1-dependent buffering of the cellular mRNA levels.
Spatiotemporal Variations of Soil Reactive Nitrogen Oxide Fluxes across the Anthropogenic Landscape
Megan L. Purchase, Gary D. Bending and Ryan M. Mushinski
Volatile reactive nitrogen oxides (NOy) are significant atmospheric pollutants, including NOx (nitric oxide [NO] + nitrogen dioxide [NO2]) and NOz (nitrous acid [HONO] + nitric acid [HNO3] + nitrogen trioxide [NO3] + ...). NOy species are products of nitrogen (N) cycle processes, particularly nitrification and denitrification. Biogenic sources, including soil, account for over 50% of natural NOy emissions to the atmosphere, yet emissions from soils are generally not included in atmospheric models as a result of a lack of mechanistic data. This work is a unique investigation of NOy fluxes on a landscape scale, taking a comprehensive set of land-use types, human influence, and seasonality into account to determine large-scale heterogeneity to provide a basis for future modeling and hypothesis generation
Exploration of phyllosphere microbiomes in wheat varieties with differing aphid resistance
Xinan Li, Chao Wang, Xun Zhu, Vardis Ntoukakis, Tomislav Cernava & Decai Jin
Leaf-associated microbes play an important role in plant development and response to exogenous stress. Insect herbivores are known to alter the phyllosphere microbiome. However, whether the host plant’s defense against insects is related to the phyllosphere microbiome remains mostly elusive. Here, we investigated bacterial communities in the phyllosphere and endosphere of eight wheat cultivars with differing aphid resistance, grown in the same farmland. Communities of leaf-associated microbes in wheat plants were mainly driven by the host genotype. Members of the genus Exiguobacterium may have adverse effects on wheat aphids. Our findings provide new clues supporting the development of aphid control strategies based on phyllosphere microbiome engineering.
Genomic Based Analysis of The Biocontrol Species Trichoderma harzianum: A Model Resource of Structurally Diverse Pharmaceuticals and Biopesticides
Suhad AA Al-Salihi and Fabrizio Alberti
Fungi represents a rich repository of taxonomically restricted, yet chemically diverse, secondary metabolites that are synthesised via specific metabolic pathways. An enzyme’s specificity and biosynthetic gene clustering are the bottleneck of secondary metabolite evolution. Trichoderma harzianum M10 v1.0 produces many pharmaceutically important molecules; however, their specific biosynthetic pathways remain uncharacterised. Our genomic-based analysis of this species reveals the biosynthetic diversity of its specialised secondary metabolites, where over 50 BGCs were predicted, most of which were listed as polyketide-like compounds associated clusters. Revealing the biogenetic background of these natural molecules is a step forward towards the expansion of their chemical diversification via engineering their biosynthetic genes heterologously, and the identification of their role in the interaction between this fungus and its biotic/abiotic conditions as well as its role as bio-fungicide.
Bayesian inference of polymerase dynamics over the exclusion process
Cavallaro, Massimo, Wang, Yuexuan, Hebenstreit, Daniel and Dutta, Ritabrata
Transcription is a complex phenomenon that permits the conversion of genetic information into phenotype by means of an enzyme called RNA polymerase, which erratically moves along and scans the DNA template. We perform Bayesian inference over a paradigmatic mechanistic model of non-equilibrium statistical physics, i.e. the asymmetric exclusion processes in the hydrodynamic limit, assuming a Gaussian process prior for the polymerase progression rate as a latent variable. Our framework allows us to infer the speed of polymerases during transcription given their spatial distribution, while avoiding the explicit inversion of the system’s dynamics. The results, which show processing rates strongly varying with genomic position and minor role of traffic-like congestion, may have strong implications for the understanding of gene expression.
Can Single Cell Respiration be Measured by Scanning Electrochemical Microscopy (SECM)?
Kelsey Cremin, Gabriel N Meloni, Dimitrios Valavanis, Orkun S Soyer and Patrick R Unwin
Ultramicroelectrode (UME), or, equivalently, microelectrode, probes are increasingly used for single-cell measurements of cellular properties and processes, including physiological activity, such as metabolic fluxes and respiration rates. Major challenges for the sensitivity of such measurements include: (i) the relative magnitude of cellular and UME fluxes (manifested in the current); and (ii) issues around the stability of the UME response over time. To explore the extent to which these factors impact the precision of electrochemical cellular measurements, we undertake a systematic analysis of measurement conditions and experimental parameters for determining single cell respiration rates via the oxygen consumption rate (OCR) in single HeLa cells. We provide a set of model-based suggestions for improving these measurements in the future but highlight that extraordinary improvements in the stability and precision of SECM measurements will be required if single cell OCR measurements are to be realized.