Biology subjects

Jasinska, W.

Publications and source records attributed to Jasinska, W..

7 recordsLinked to original sources

bioRxiv2025

Metabolite correlation networks reveal complex phenotypes of adaptation-driving mutations

Living organisms are organized into hierarchical levels of increasing complexity. As mutational effects propagate through these levels, multiple phenotypes are produced. However, identifying which phenotypes influence fitness and drive selection remains a key challenge in understanding genotype-phenotype-fitness relationships. Here, we demonstrate that mutation-induced structural changes in metabolite correlation networks--an organizational level with emergent properties shaped by the cumulative effects of multiple biochemical reactions and regulatory mechanisms--constitute complex phenotypes linking mutations to bacterial fitness. We engineered a metabolically suboptimal E. coli strain by replacing the metK gene encoding methionine adenosyltransferase (MAT) with an ortholog from U. urealyticum and subjected it to laboratory evolution. Analysis of correlation networks constructed from 2,118 untargeted metabolites revealed that adaptive mutations enhanced the strains fitness by reducing network density, removing node hubs, and extensively rewiring connectivity. These changes yielded smaller, more cohesive, and better-interconnected network clusters. Moreover, evolution shifted the node representing S-adenosylmethionine (SAM), the product of the MAT-catalyzed reaction, from a peripheral role to a key connector between network clusters with a significantly increased betweenness. None of the accumulated mutations potentially driving this transition directly influenced MAT activity or SAM metabolism, indicating that the shift in SAMs role is an adaptive phenotype emerging from the metabolic systems complexity. Targeted metabolomics of key nodes displaying similar network transitions unveiled additional metabolites involved in SAM-related pathways. We propose the construction and analysis of metabolite correlation networks as an experimental and analytical framework for mapping genotype-phenotype-fitness relationships and exploring the mechanisms of metabolic adaptation.

evolutionary biology↗

bioRxiv2024

Chemoproteomic profiling of serine hydrolases reveals the dynamic role of lipases in Phaeodactylum tricornutum

Phaeodactylum tricornutum is a model oleaginous pennate diatom, widely investigated for the accumulation of triacylglycerols (TAG) in lipid droplets during nitrogen (N) starvation. However, lipid droplet breakdown, TAG catabolism, and remobilization upon N replenishment during growth restoration are less studied. Serine hydrolases (SH) constitute a diverse family encompassing proteases, amidases, esterases, and lipases. In this report, we adopted a chemoproteomic approach called Activity-Based Protein Profiling (ABPP) to explore the repertoire of active serine hydrolases to elucidate the mechanisms of lipid metabolism in P. tricornutum (strain Pt4). A superfamily-wide profile of serine hydrolases revealed a differentially active proteome (activome) during N starvation and after nutrient replenishment. We report 30 active serine hydrolases, which were broadly categorized into metabolic serine hydrolases and serine proteases. Lipases appeared to be the major metabolic linchpins prevalent during lipid remobilization. Global transcriptomics analysis provided a complementary insight into the gene expression level of the detected serine hydrolases. It revealed putative phospholipases as central players in membrane lipid turnover and remodeling involved in cellular lipid homeostasis and TAG accumulation. TAG remobilization and lipid droplet breakdown were impaired in the presence of phenyl mercuric acetate (PMA), whose activity as an SH inhibitor was validated by competitive ABPP. Lipid species profiling corroborated the impairment in TAG degradation and the buildup of structural lipids in the presence of PMA after nutrient replenishment. Collectively, our functional proteome approach, coupled with the transcriptome and lipidome data, provides a comprehensive landscape of bona fide active serine hydrolases, including lipases in this model diatom.

biochemistry↗

bioRxiv2024

Comparative analysis of the plasma metabolome of migrating passerines during stopover: Novel insights into flight metabolism

During long distance migration, many birds may experience periods of either prolonged fasting, during endurance flights, or extensive feeding during stopovers. It was previously shown that habitat selection during stopover can largely affect the migration outcome of an individual. Despite decades of research of the avian metabolism during stopover and migration, many questions have remained unanswered, as such research mainly focused on targeted metabolites and fat metabolism. Here, we examined the plasma-metabolome of migrating passerines prior to their crossing the Sahara Desert. Birds were sampled at two sites populated by Pistacia trees, bearing fat-rich fruits, and at an additional site dominated by blooming Eucalyptus trees. The blood samples were analyzed using both GC-MS and LC-MS, using an untargeted approach. We found that birds from one of the sites had a distinguish metabolic profile, suggesting recent landing. Examination of metabolic pathways activated during stopovers indicated a crucial role for cycling glucose through the Cori and Cahill cycles in resting and recovery processes. This novel perspective, conducted on free-ranging birds, suggests the evolution of avian insulin resistance due to factors such as endurance exercise, fasting, and a preference for fatty acid oxidation during migration, akin to cell trauma recovery. Additionally, we investigated inter-site variations in birds metabolic profiles. Significant variations were observed in both polar and lipophilic metabolites among the sites. Differences in polar metabolites were primarily attributed to variations in the physiological state of the birds between sites, while distinctions in the lipophilic profiles of rested birds were linked to variations in their primary food sources. This study underscores the challenge of interpreting commonly used indicators for assessing migrating birds physiological states and site quality, which are predominantly derived from lipid metabolism, in complex ecological systems.

ecology↗

bioRxiv2023

Non-consecutive enzyme interactions within TCA cycle supramolecular assembly regulate carbon-nitrogen metabolism

Enzymes of the core energy metabolism pathways tend to assemble into transient supramolecular complexes, yet the functional significance of the interactions within these complexes, particularly between enzymes catalyzing non-consecutive reactions, remains unclear. Here, by co-localizing two non-consecutive enzymes of the TCA cycle from B. subtilis, malate dehydrogenase (MDH) and isocitrate dehydrogenase (ICD), in highly crowded liquid-liquid phase separated droplets we discovered that MDH-ICD interaction causes an enhancement of ICD catalytic rate and an apparent sequestration of its reaction product, 2-oxoglutarate. Theory suggests that the observed phenomena are explained by the MDH-mediating clustering of ICD molecules. In vivo validation with targeted GC-MS and 13C tracer analyses revealed that when B. subtilis is grown on glucose and ammonia, overexpression of MDH leads to accumulation of 2-oxoglutarate with a concomitant reduction of fluxes flowing through both the catabolic and anabolic branches of the carbon-nitrogen intersection occupied by 2-oxoglutarate, resulting in impeded ammonium assimilation and reduced biomass production. Our findings thus suggest that in B. subtilis the MDH-ICD interaction is an important coordinator of carbon-nitrogen metabolism, thereby expanding the list of types of functionally understood unconventional enzyme-enzyme interactions.

microbiology↗

bioRxiv2023

R2R3-MYB EVER links emission of volatiles with epicuticular wax biosynthesis in petunia petal epidermis

The epidermal cells of petunia flowers are the main site of volatile emission. However, data on the mechanisms underlying the release of volatiles into the environment are lacking. Here, using cell-layer-specific transcriptomic analysis, reverse genetics by VIGS and CRISPR, and metabolomics we identified EPIDERMIS VOLATILE EMISSION REGULATOR (EVER)--a petal adaxial epidermis-specific MYB activator that affects the emission of volatiles. Using a three-step viral-based CRISPR/Cas9 editing system, ever knockout lines were generated and together with transient suppression assays, revealed EVERs involvement in the repression of low-vapor-pressure volatiles. Internal pools and annotated scent-related genes involved in production and emission were not affected by EVER. RNA-Seq analyses of petals of ever knockout lines and EVER-overexpressing flowers revealed enrichment in wax-related biosynthesis genes. LC/GC-MS analyses of petal epicuticular waxes revealed substantial reductions in wax loads in ever petals, particularly of monomers of fatty acids and wax esters. These results implicate EVER in the emission of volatiles by fine-tuning the composition of petal epicuticular waxes. Thus, we reveal a petunia MYB regulator that interlinks epicuticular wax composition and volatile emission, thus unraveling a new regulatory layer in the scent-emission machinery in petunia flowers.

plant biology↗

bioRxiv2023

Autophagy in maternal tissues contributes to Arabidopsis thaliana seed development.

Seeds are an essential food source, providing nutrients for germination and early seedling growth. Degradation events in the seed and the mother plant accompany seed development. One degradation mechanism is autophagy, facilitating cellular component breakdown in the lytic organelle. Autophagy influences various aspects of plant physiology, specifically nutrient availability and remobilization, suggesting its involvement in source-sink interactions. During seed development, autophagy was shown to affect nutrient remobilization from mother plants and function in the embryo. Yet, these studies examined autophagy-knockout (atg mutant) plants, making it impossible to distinguish between the contribution of autophagy in the source (i.e., the mother plant) and the sink tissue (i.e., the embryo). To address this, we employed a novel approach to differentiate between autophagy in source and sink tissues. We investigated how autophagy in the maternal tissue affects seed development by performing reciprocal crosses between WT and atg mutant Arabidopsis thaliana plants. Although F1 seedlings possessed a functional autophagy mechanism, etiolated F1 plants from maternal atg mutants displayed reduced growth. This was attributed to altered protein but not lipid accumulation in the seeds, suggesting autophagy differentially regulates carbon and nitrogen remobilization. Surprisingly, F1 seeds of maternal atg mutants exhibited faster germination, resulting from different seed coat development. Our study emphasizes the significance of examining autophagy in a tissue-specific manner, revealing valuable insights into the interplay between different tissues during seed development. It sheds light on the tissue-specific functions of autophagy, offering potential for new research into the underlying mechanisms governing seed development and crop yield.

plant biology↗

bioRxiv2019

Chromosomal barcoding of E. coli populations reveals lineage diversity dynamics at high resolution

Evolutionary dynamics in large asexual populations is strongly influenced by multiple competing beneficial lineages, most of which segregate at very low frequencies. However, technical barriers to tracking a large number of these rare lineages have so far prevented a detailed elucidation of evolutionary dynamics in large bacterial populations. Here, we overcome this hurdle by developing a chromosomal barcoding technique that allows simultaneous tracking of [~]450,000 distinct lineages in E. coli. We used this technique to gather insights into the evolutionary dynamics of large (>107 cells) E. coli populations propagated for [~]420 generations in the presence of sub-inhibitory concentrations of common antibiotics. By deep sequencing the barcodes, we reconstructed trajectories of individual lineages at high frequency resolution (< 10-5). Using quantitative tools from ecology, we found that populations lost lineage diversity at distinct rates corresponding to their antibiotic regimen. Additionally, by quantifying the reproducibility of these dynamics across replicate populations, we found that some lineages had similar fates over independent experiments. Combined with an analysis of individual lineage trajectories, these results suggest how standing genetic variation and new mutations may contribute to adaptation to sub-inhibitory antibiotic levels. Altogether, our results demonstrate the power of high-resolution barcoding in studying the dynamics of bacterial evolution.

evolutionary biology↗