Mig1 localization exhibits biphasic behavior which is controlled by both metabolic and regulatory roles of the sugar kinases

Microscopy with microfluidics in microgravity using FlightScope

With planned missions to the moon and Mars, it has never been more important to study the impact of microgravity on biological organisms. Parabolic flights are one of the most accessible microgravity research platforms but present challenges: short periods of microgravity and aircraft vibration. Live-imaging is necessary to readout any real-time phenotypes so we developed FlightScope, a new microscopy and microfluidics platform to study dynamic cellular processes in microgravity.

Exploring carbon source related localization and phosphorylation in the Snf1/Mig1 network using population and single cell-based approaches

The AMPK/SNF1 pathway governs energy balance in eukaryotic cells, notably influencing glucose de-repression. In S. cerevisiae, Snf1 is phosphorylated and hence activated upon glucose depletion. This activation is required but is not sufficient for mediating glucose de-repression, indicating further glucose-dependent regulation mechanisms. Employing fluorescence recovery after photobleaching (FRAP) in conjunction with non-linear mixed effects modelling, we explore the spatial dynamics of Snf1 as well as the relationship between Snf1 phosphorylation and its target Mig1 controlled by hexose sugars. Our results suggest that inactivation of Snf1 modulates Mig1 localization and that the kinetic of Snf1 localization to the nucleus is modulated by the presence of non-fermentable carbon sources. Our data offer insight into the true complexity of regulation of this central signaling pathway in orchestrating cellular responses to fluctuating environmental cues. These insights not only expand our understanding of glucose homeostasis but also pave the way for further studies evaluating the importance of Snf1 localization in relation to its phosphorylation state and regulation of downstream targets.

The polyHIS Tract of Yeast AMPK Coordinates Carbon Metabolism with Iron Availability

Energy status in all eukaryotic cells is sensed by AMP-kinases. We have previously found that the poly-histidine tract at the N-terminus of S. cerevisiae AMPK (Snf1) inhibits its function in the presence of glucose via a pH-regulated mechanism. We show here that in the absence of glucose, the poly-histidine tract has a second function, linking together carbon and iron metabolism. Under conditions of iron deprivation, when different iron-intense cellular systems compete for this scarce resource, Snf1 is inhibited. The inhibition is via an interaction of the poly-histidine tract with the low-iron transcription factor Aft1. Aft1 inhibition of Snf1 occurs in the nucleus at the nuclear membrane, and only inhibits nuclear Snf1, without affecting cytosolic Snf1 activities. Thus, the temporal and spatial regulation of Snf1 activity enables a differential response to iron depending upon the type of carbon source. The linkage of nuclear Snf1 activity to iron sufficiency ensures that sufficient clusters are available to support respiratory enzymatic activity and tests mitochondrial competency prior to activation of nuclear Snf1.

Rewiring regulation on respiro-fermentative metabolism relieved Crabtree effects in Saccharomyces cerevisiae

The respiro-fermentative metabolism in the yeast Saccharomyces cerevisiae, also called the Crabtree effect, results in lower energy efficiency and biomass yield which can impact yields of chemicals to be produced using this cell factory. Although it can be engineered to become Crabtree negative, the slow growth and glucose consumption rate limit its industrial application. Here the Crabtree effect in yeast can be alleviated by engineering the transcription factor Mth1 involved in glucose signaling and a subunit of the RNA polymerase II mediator complex Med2. It was found that the mutant with the MTH1^A81D&MED2*^432Y allele could grow in glucose rich medium with a specific growth rate of 0.30 h⁻¹, an ethanol yield of 0.10 g g⁻¹, and a biomass yield of 0.21 g g⁻¹, compared with a specific growth rate of 0.40 h⁻¹, an ethanol yield of 0.46 g g⁻¹, and a biomass yield of 0.11 g g⁻¹ in the wild-type strain CEN.PK 113-5D. Transcriptome analysis revealed significant downregulation of the glycolytic process, as well as the upregulation of the TCA cycle and the electron transfer chain. Significant expression changes of several reporter transcription factors were also identified, which might explain the higher energy efficiencies in the engineered strain. We further demonstrated the potential of the engineered strain with the production of 3-hydroxypropionic acid at a titer of 2.04 g L⁻¹, i.e., 5.4-fold higher than that of a reference strain, indicating that the alleviated glucose repression could enhance the supply of mitochondrial acetyl-CoA. These results suggested that the engineered strain could be used as an efficient cell factory for mitochondrial production of acetyl-CoA derived chemicals.

Scalable and flexible inference framework for stochastic dynamic single-cell models

Understanding the inherited nature of how biological processes dynamically change over time and exhibit intra- and inter-individual variability, due to the different responses to environmental stimuli and when interacting with other processes, has been a major focus of systems biology. The rise of single-cell fluorescent microscopy has enabled the study of those phenomena. The analysis of single-cell data with mechanistic models offers an invaluable tool to describe dynamic cellular processes and to rationalise cell-to-cell variability within the population. However, extracting mechanistic information from single-cell data has proven difficult. This requires statistical methods to infer unknown model parameters from dynamic, multi-individual data accounting for heterogeneity caused by both intrinsic (e.g. variations in chemical reactions) and extrinsic (e.g. variability in protein concentrations) noise. Although several inference methods exist, the availability of efficient, general and accessible methods that facilitate modelling of single-cell data, remains lacking. Here we present a scalable and flexible framework for Bayesian inference in state-space mixed-effects single-cell models with stochastic dynamic. Our approach infers model parameters when intrinsic noise is modelled by either exact or approximate stochastic simulators, and when extrinsic noise is modelled by either time-varying, or time-constant parameters that vary between cells. We demonstrate the relevance of our approach by studying how cell-to-cell variation in carbon source utilisation affects heterogeneity in the budding yeast Saccharomyces cerevisiae SNF1 nutrient sensing pathway. We identify hexokinase activity as a source of extrinsic noise and deduce that sugar availability dictates cell-to-cell variability.

Identification of genes related to hydrolysis and assimilation of Agave fructans in Candida apicola NRRL Y-50540 and Torulaspora delbrueckii NRRL Y-50541 by de novo transcriptome analysis

Fructans are the main sugar in agave pine used by yeasts during mezcal fermentation processes, from which Candida apicola NRRL Y-50540 and Torulaspora delbrueckii NRRL Y-50541 were isolated. De novo transcriptome analysis was carried out to identify genes involved in the hydrolysis and assimilation of Agave fructans (AF). We identified a transcript annotated as SUC2, which is related to β-fructofuranosidase activity, and several differential expressed genes involved in the transcriptional regulation of SUC2 such as: MIG1, MTH1, SNF1, SNF5, REG1, SSN6, SIP1, SIP2, SIP5, GPR1, RAS2, and PKA. Some of these genes were specifically expressed in some of the yeasts according to their fructans assimilation metabolism. Different hexose transporters that could be related to the assimilation of fructose and glucose were found in both the transcriptomes. Our findings provide a better understanding of AF assimilation in these yeasts and provide resources for further metabolic engineering and biotechnology applications.

Genome-Wide Insight into Profound Effect of Carbon Catabolite Repressor (Cre1) on the Insect-Pathogenic Lifecycle of Beauveriabassiana

Carbon catabolite repression (CCR) is critical for the preferential utilization of glucose derived from environmental carbon sources and regulated by carbon catabolite repressor A (Cre1/CreA) in filamentous fungi. However, a role of Cre1-mediated CCR in insect-pathogenic fungal utilization of host nutrients during normal cuticle infection (NCI) and hemocoel colonization remains explored insufficiently. Here, we report an indispensability of Cre1 for Beauveriabassiana's utilization of nutrients in insect integument and hemocoel. Deletion of cre1 resulted in severe defects in radial growth on various media, hypersensitivity to oxidative stress, abolished pathogenicity via NCI or intrahemocoel injection (cuticle-bypassing infection) but no change in conidial hydrophobicity and adherence to insect cuticle. Markedly reduced biomass accumulation in the Δcre1 cultures was directly causative of severe defect in aerial conidiation and reduced secretion of various cuticle-degrading enzymes. The majority (1117) of 1881 dysregulated genes identified from the Δcre1 versus wild-type cultures were significantly downregulated, leading to substantial repression of many enriched function terms and pathways, particularly those involved in carbon and nitrogen metabolisms, cuticle degradation, antioxidant response, cellular transport and homeostasis, and direct/indirect gene mediation. These findings offer a novel insight into profound effect of Cre1 on the insect-pathogenic lifestyle of B. bassiana.