Biology subjects

Grigaitis, P.

Publications and source records attributed to Grigaitis, P..

8 recordsLinked to original sources

bioRxiv2026

Genomic insights into bacterial isolates dominating honeypot ant crop microbiomes reveal metabolically distinct Fructilactobacillus sp.

Honeypot ants engage in a convergently-evolved phenotype called repletism, where specialized workers expand their crops and gasters to store vast amounts of food internally. They then store that food for months to support colonies during times of food scarcity. This fascinating phenotype is not well-understood and very little is known about the microbial interactions happening within the fructose-rich replete crop. Previous research using amplicon sequencing showed that Fructilactobacillus makes up nearly 100% of the crop microbiomes of Myrmecocystus mexicanus repletes. This striking result and successful isolation of those strains led to the present investigation into the phylogenetic diversity of these strains and any clues to the nature of the symbiotic relationship between them and the ant host. We find that the isolates from these repletes represented two evolutionary lineages, both most closely related to F. fructivorans. One of those lineages was also found to be phylogenetically and metabolically distinct from all other Fructilactobacillus reference genomes used in this study. This discovery in a genus of bacteria that are highly relevant for fermented human foods and will also lay the groundwork for future understanding of the convergent evolutionary mechanisms of repletism in ants. 3. Impact statementThese analyses add to the literature by identifying a new microbe within a genus that is relevant to food systems. In addition, the host phenotype is convergently evolved and likely microbe-mediated (or at least highly exposed). Understanding this system allows for the testing of ideas of coevolutionary hypotheses with natural replicates. We expect interest to come from food safety and probiotics researchers, evolutionary biologists that think about the impacts of microbes, microbial ecologists interested in novel systems, and those interested in bacteria that may display unique metabolic possibilities. This output allows for the clear future examination of this system with many clear hypotheses. Our analysis allows for the creation of a new and unique model system of host-microbe symbiosis. 4. Data summaryNew genomes assembled in this work can be found under BioProject ID PRJNA1449409. https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA1449409. Reference bacterial genomes were obtained from NCBI at the following accession numbers: SAMN20557570, SAMN28081009, SAMN28081010, SAMN02597458, SAMN43111088, SAMN28081011, SAMN28535231, SAMN04505734, SAMN28081013, SAMN33452149, SAMN37926504, SAMN02849426, SAMN02470196, SAMN02369432, SAMN02797779, SAMN02797782, SAMN02797768, SAMN09762388, SAMN12785275, SAMEA117660288. The honeypot ant genome was obtained from SAMN37666067. Raw proteomics files will be uploaded to ProteomeXchange with a unique identifier upon manuscript acceptance.

genomics↗

bioRxiv2025

A stochastic ratchet during genome streamlining can commit insect endosymbionts to a parasitic or mutualistic fate

Many arthropods, including insects, harbor endosymbiotic bacteria. As bacteria transitioned to live inside host cells, free-living bacterial ancestors of endosymbionts reduced their genomes in a process known as streamlining. Contemporary endosymbioses represent at least two distinct life strategies: endosymbionts either become unilaterally dependent on host-derived resources (uni-obligate) or enter bidirectionally obligate mutualistic relationships (bi-obligate endosymbiosis). It is an open question whether these paths taken by free-living bacteria can be sequential, or alternatively, if commitment takes place early, making these strategies mutually exclusive. In this study, we quantified metabolic capacity of different endosymbionts to contextualize genome streamlining in terms of organismal function. We show that uni-obligate endosymbionts of insects have lost substantial parts of their metabolic capacity that are present both in free-living bacteria and bi-obligate endosymbionts. On the contrary, genomes of uni-obligate endosymbionts contain more genes which can be attributed to scavenging host resources. In sum, we challenge the existing notion that bi-obligate endosymbionts have emerged from uni-obligate ones, and rather, propose a stochastic ratchet model: in early stages of endosymbiosis, bacteria get locked into either a more mutualistic or more parasitic relationship with the host depending on the first losses during streamlining.

systems biology↗

bioRxiv2024

Mitochondrial efficiency determines Crabtree effect across yeasts

Under excess glucose conditions, many yeasts switch from high-yield respiratory metabolism to low-yield fermentation, a phenomenon called the Crabtree effect in yeast, or the Warburg effect in mammalian cells. Cellular constraints and limited resources are generally believed to govern the metabolic strategies of cells to adapt to environmental conditions, but which constraints drive this switch is still under debate. Here we study the Crabtree-negative, fully respiratory yeast Pichia kluyveri and compare it to the Crabtree-positive yeast Saccharomyces cerevisiae from a resource allocation perspective. By integrating quantitative physiology and proteomics into whole-cell proteome-constrained models, we find that the Crabtree effect is determined by the composition and catalytic efficiency of the electron transport chain. We find that the subsequent proteome efficiency of respiration versus fermentation varies between these species. The variation in parameters and composition of the respiratory machinery likely reflects the evolutionary and ecological history of these yeast species. This study advances our understanding of the role of proteome constraints and proteome efficiency in governing cellular metabolism of yeasts, and that of eukaryotic cells at large.

systems biology↗

bioRxiv2022

Elevated energy costs of biomass production in mitochondrial-respiration deficient Saccharomyces cerevisiae

Microbial growth requires energy for maintaining the existing cells and producing components for the new ones. Microbes therefore invest a considerable amount of their resources into proteins needed for energy harvesting. Growth in different environments is associated with different energy demands for growth of yeast Saccharomyces cerevisiae, although the cross-condition differences remain poorly characterized. Furthermore, a direct comparison of the energy costs for the biosynthesis of the new biomass across conditions is not feasible experimentally; computational models, on the contrary, allow comparing the optimal metabolic strategies and quantify the respective costs of energy and nutrients. Thus in this study, we used a resource allocation model of S. cerevisiae to compare the optimal metabolic strategies between different conditions. We found that S. cerevisiae with respiratory-impaired mitochondria required additional energetic investments for growth, while growth on amino acid-rich media was not affected. Amino acid supplementation in anaerobic conditions also was predicted to rescue the growth reduction in mitochondrial respiratory shuttle-deficient mutants of S. cerevisiae. Collectively, these results point to elevated costs of resolving the redox imbalance caused by de novo biosynthesis of amino acids in mitochondria. To sum up, our study provides an example of how resource allocation modeling can be used to address and suggest explanations to open questions in microbial physiology.

systems biology↗

bioRxiv2022

Large excess capacity of glycolytic enzymes in Saccharomyces cerevisiae under glucose-limited conditions

In Nature, microbes live in very nutrient-dynamic environments. Rapid scavenging and consumption of newly introduced nutrients therefore offer a way to outcompete competitors. This may explain the observation that many microorganisms, including the budding yeast Saccharomyces cerevisiae, appear to keep "excess" glycolytic proteins at low growth rates, i.e. the maximal capacity of glycolytic enzymes (largely) exceeds the actual flux through the enzymes. However, such a strategy requires investment into preparatory protein expression that may come at the cost of current fitness. Moreover, at low nutrient levels, enzymes cannot operate at high saturation, and overcapacity is poorly defined without taking enzyme kinetics into account. Here we use computational modeling to suggest that in yeast the overcapacity of the glycolytic enzymes at low specific growth rates is a genuine excess, rather than the optimal enzyme demand dictated by enzyme kinetics. We found that the observed expression of the glycolytic enzymes did match the predicted optimal expression when S. cerevisiae exhibits mixed respiro-fermentative growth, while the expression of tricarboxylic acid cycle enzymes always follows the demand. Moreover, we compared the predicted metabolite concentrations with the experimental measurements and found the best agreement in glucose-excess conditions. We argue that the excess capacity of glycolytic proteins in glucose-scarce conditions is an adaptation of S. cerevisiae to fluctuations of nutrient availability in the environment.

systems biology↗

bioRxiv2022

A computational toolbox to investigate the metabolic potential and resource allocation in fission yeast

The fission yeast Schizosaccharomyces pombe is a popular eukaryal model organism for cell division and cell cycle studies. With this extensive knowledge of its cell and molecular biology, S. pombe also holds promise for use in metabolism research and industrial applications. However, unlike the bakers yeast Saccharomyces cerevisiae, a major workhorse in these areas, cell physiology and metabolism of S. pombe remain less explored. One way to advance understanding of organism-specific metabolism is construction of computational models and their use for hypothesis testing. To this end, we leverage existing knowledge of S. cerevisiae to generate a manually-curated high-quality reconstruction of S. pombes metabolic network, including a proteome-constrained version of the model. Using these models, we gain insights into the energy demands for growth, as well as ribosome kinetics in S. pombe. Furthermore, we predict proteome composition and identify growth-limiting constraints that determine optimal metabolic strategies under different glucose availability regimes, and reproduce experimentally determined metabolic profiles. Notably, we find similarities in metabolic and proteome predictions of S. pombe with S. cerevisiae, which indicate that similar cellular resource constraints operate to dictate metabolic organization. With these use cases, we show, on the one hand, how these models provide an efficient means to transfer metabolic knowledge from a well-studied to a lesser-studied organism, and on the other, how they can successfully be used to explore the metabolic behaviour and the role of resource allocation in driving different strategies in fission yeast.

systems biology↗

bioRxiv2021

Whole-cell modeling in yeast predicts compartment-specific proteome constraints that drive metabolic strategies

When conditions change, unicellular organisms rewire their metabolism to sustain cell maintenance and cellular growth. Such rewiring may be understood as resource re-allocation under cellular constraints. Eukaryal cells contain metabolically active organelles such as mitochondria, competing for cytosolic space and resources, and the nature of the relevant cellular constraints remain to be determined for such cells. Here we developed a comprehensive metabolic model of the yeast cell, based on its full metabolic reaction network extended with protein synthesis and degradation reactions (16304 reactions in total). The model predicts metabolic fluxes and corresponding protein expression by constraining compartment-specific protein pools and maximising growth rate. Comparing model predictions with quantitative experimental data revealed that under glucose limitation, a mitochondrial constraint limits growth at the onset of ethanol formation - known as the Crabtree effect. Under sugar excess, however, a constraint on total cytosolic volume dictates overflow metabolism. Our comprehensive model thus identifies condition-dependent and compartment-specific constraints that can explain metabolic strategies and protein expression profiles from growth rate optimization, providing a framework to understand metabolic adaptation in eukaryal cells.

systems biology↗

bioRxiv2021

Transcription activation is enhanced by multivalent interactions independent of liquid-liquid phase separation

Transcription factors (TFs) consist of a DNA binding and an activation domain (AD) that are considered to be independent and exchangeable modules. However, recent studies conclude that also the physico-chemical properties of the AD can control TF assembly at chromatin by driving a phase separation into transcriptional condensates. Here, we dissected transcription activation by comparing different synthetic TFs at a reporter gene array with real-time single-cell fluorescence microscopy readouts. In these experiments, binding site occupancy, residence time and co-activator recruitment in relation to multivalent TF interactions were compared. While phase separation propensity and activation strength of the AD were correlated, the actual formation of liquid-like TF droplets had a neutral or inhibitory effect on transcription activation. Rather, we conclude that multivalent AD mediated interactions increase the transcription activation capacity of a TF by stabilizing chromatin binding and mediating the recruitment of co-activators independent of phase separation.

biophysics↗