Biology subjects

Lewandowski, M.

Publications and source records attributed to Lewandowski, M..

11 recordsLinked to original sources

bioRxiv2026

Biotic niche expansion constrains the fundamental abiotic niche: Evidence from experimental evolution

In an ever-changing world, organisms are subject to selective pressures that shape their ecological niches. Niche theory predicts that environmental heterogeneity selects for niche expansion, yet niches are inherently multidimensional, and expansion in one dimension may impose severe constrains on others. In this study, we employed rigorous experimental evolution to investigate these cross-dimensional trade-offs in the wheat curl mite, Aceria tosichella. By adapting replicated lineages to either stable (single-host) or alternating (two-host) environments for hundreds of generations, we successfully expanded the mites fundamental biotic host niche, enabling lineages to exploit diverse host species, including those unencountered during their evolutionary history. Crucially, however, this biotic generalization incurred a significant cost in the abiotic niche dimension. Lineages adapted to alternating hosts exhibited significantly reduced thermal tolerance compared to host specialists, which maintained superior performance across a wider thermal range. This trade-off appears to be driven by a combination of genetically based metabolic constraints and behavioral dispersal strategies. Our results provide compelling experimental evidence for the "Jack-of-all-trades is master of none" hypothesis across niche dimensions. We demonstrate that physiological trade-offs between biotic versatility and abiotic resilience strictly constrain the evolution of the multidimensional niche, with critical implications for forecasting species distributions and invasion potential under climate change.

ecology↗

bioRxiv2026

Genomic basis of adaptation to constant and fluctuating environments in a global pest of cereals

In agricultural systems, spatially and temporally heterogeneous environments are expected to favour the evolution of generalist pests and pathogens, yet the genomic mechanisms underlying niche-breadth expansion remain poorly understood. Here, we address this gap by assembling one of the smallest known eukaryotic genomes--from the global cereal pest Aceria tosichella--and by resequencing generalist and specialist populations which evolved in the lab on constant versus fluctuating hosts. A previous study demonstrated that generalist populations retained a wider niche, including the ability to exploit a refuge host, compared to specialist populations that showed a narrowing of the ecological niche. Genomic scans identified 640 SNPs that significantly differed in frequency between treatments, including a single highly differentiated 120-kbp region containing 13 genes. Allele-frequency shifts across many SNPs in this region paralleled phenotypic divergence in the ability to utilise refuge hosts, and gene annotations suggested their roles in starvation resistance and nutrient signalling. However, experimental validation of the top candidate gene did not support its strong direct effect on survival on the refuge host, implying a more complex, likely polygenic basis for adaptation. Consistent with this interpretation, numerous significant SNPs occurred outside the focal region, with enrichment for genes involved in xenobiotic transport, detoxification pathways, and ABC transporters. Together, these results indicate that generalism in A. tosichella relies on complex molecular mechanisms that enable survival on suboptimal or refuge hosts, relying to a considerable extent on the ability to deal with stress arising, for example, from toxic compounds present in suboptimal hosts.

evolutionary biology↗

bioRxiv2025

Is passive dispersal informed? - Experimental evidence for decision-making in phytophagous arthropods

Animals must acquire and decode information to make the right decisions. While active dispersers can evaluate habitats en route, passive dispersers can only control their departure timing. Although the passive strategy is ubiquitous among arthropods, the mechanisms behind their take-off decisions remain poorly understood. We tested whether host niche breadth shapes passive dispersal in phytophagous mites by exposing them to host-derived kairomones and measuring departure rates. Using experimentally evolved specialist and generalist lineages, we found that dispersal depends more on the context in which cues are encountered that on the kairomones themselves. Host specialisation strongly shaped responses: mites left plants more readily when exposed to unfamiliar hosts, with generalists dispersing over twice as often as specialists. Increased number of unfamiliar kairomones strongly inhibited generalists dispersal but barely affected specialists. This suggests specialists use environmental novelty to trigger exploration, whereas generalists need multiple cues to confirm host suitability, revealing a trade-off between host range and environmental sensitivity.

ecology↗

bioRxiv2025

Click. Screen. Degrade. A Miniaturized D2B Workflow for rapid PROTAC Discovery

Targeted protein degradation is one of the fastest developing fields in medicinal chemistry and chemical biology. Despite significant development in assay technologies and inhibitor discovery, the development of PROTACs remains a challenging endeavor since rational design approaches remain widely elusive. Our workflow eliminates the rate-limiting step of classic synthesis, namely compound purification, and pairs it with high-throughput, semi-automated plate-based synthesis, and direct cellular assay evaluation. We applied this direct-to-biology approach to four diverse targets demonstrating the general applicability of this technology. PROTAC synthesis was realized by using the highly efficient copper-catalyzed azide-alkyne cycloaddition reaction. This simplified reaction setup allowed synthesis in the nanomole scale with reaction volumes as low as 5 L. This high throughput approach enables the synthesis and testing of hundreds of PROTACs within a few days, allowing for a comprehensive assessment of target degradability and the identification of the most suitable E3 ligase for degrader development.

biochemistry↗

bioRxiv2025

WISER: an innovative and efficient method for correcting population structure in omics-based prediction and selection

This work introduces WISER (whitening and successive least squares estimation refinement), an innovative and efficient method designed to enhance phenotype estimation by addressing population structure. WISER outperforms traditional methods such as least squares (LS) means and best linear unbiased prediction (BLUP) in phenotype estimation, offering a more accurate approach for omics-based selection and having the potential to improve association studies. Unlike existing approaches that correct for population structure, WISER provides a generalized framework applicable across diverse experimental setups, species, and omics datasets, including single nucleotide polymorphisms (SNPs), metabolomics, and near-infrared spectroscopy (NIRS) used as phenomic predictors. Central to WISER is the concept of whitening, a statistical transformation that removes correlations between variables and standardizes their variances. Within its framework, WISER extends classical methods that use eigen-information as fixed-effect covariates to correct for population structure, by relaxing their assumptions and implementing a true whitening matrix instead of a pseudo-whitening matrix. This approach corrects fixed effects (e.g., environmental effects) for the genetic covariance structure embedded within the experimental design, thereby minimizing confounding factors between fixed and genetic effects. To support its practical application, a user-friendly R package named wiser has been developed. The WISER method has been employed in analyses for genomic prediction and heritability estimation across four species and 33 traits using multiple datasets, including rice, maize, apple, and Scots pine. Results indicate that genomic predictive abilities based on WISER-estimated phenotypes consistently outperform the LS-means and BLUP approaches for phenotype estimation, regardless of the predictive model applied. This underscores WISERs potential to advance omics analyses and related research fields by capturing stronger genetic signals.

genetics↗

bioRxiv2025

Altered Protein Phosphorylation in a Novel Midbrain Organoid Model for Bipolar Disorder

Bipolar disorder (BD) is a severe psychiatric condition marked by episodes of mania and depression, with neurotransmitter imbalance in the midbrain believed to play a critical role in its pathophysiology. Despite this, there is currently no validated midbrain model for examining BD-associated molecular changes available. Leveraging recent advances in stem cell technology, we developed a midbrain organoid model using human induced pluripotent stem cells (hiPSCs) from BD patients and healthy controls (CTR). To address issues of variability and enhance the throughput in organoid production, we implemented liquid handling and high-content imaging techniques. Quality control metrics were established to identify organoids unsuitable for further study. Electrophysiological analysis via high-density microelectrode arrays (MEAs) revealed significantly elevated neuronal properties in individual BD organoids, including increased mean amplitude, conduction velocity, and extended axonal and dendritic growth. Transcriptome and proteome analyses indicated significant dysregulation of BD-relevant signaling pathways--such as those involving phosphatidylinositol, glycogen synthase kinase-3 beta, and AKT. Notably, we identified dysregulated casein kinase 2 (CSNK2A1) and calmodulin 3 (CALM3) in BD organoids, which were reversed by lithium treatment, highlighting potential novel targets for therapeutic intervention. This study validates the midbrain organoid model as a valuable tool for exploring the molecular underpinnings of BD and identifying new treatment avenues.

cell biology↗

bioRxiv2025

WISER: an innovative and efficient method for correcting population structure in omics-based selection and association studies

This work introduces WISER (whitening and successive least squares estimation refinement), an innovative and efficient method designed to enhance phenotype estimation by addressing population structure. WISER outperforms traditional methods such as least squares (LS) means and best linear unbiased prediction (BLUP) in phenotype estimation, offering a more accurate approach for omics-based selection and association studies. Unlike existing approaches which correct for population structure, WISER offers a generalized framework that can be applied across diverse experimental setups, species, and omics datasets, such as single nucleotide polymorphisms (SNPs), near-infrared spectroscopy (NIRS), and metabolomics. Within its framework, WISER extends classical methods that use eigen-information as fixed-effect covariates to correct for population structure, by relaxing their assumptions and implementing a true whitening matrix instead of a pseudo-whitening matrix. This approach corrects fixed effects (e.g., environmental effects) for the genetic covariance structure embedded within the experimental design, thereby removing confounding factors between fixed and genetic effects. To support its practical application, a user-friendly R package named wiser has been developed. The WISER method has been employed in analyses for genomic prediction and heritability estimation across four species and 33 traits using multiple datasets, including rice, maize, apple, and Scots pine. Results indicate that genomic predictive abilities based on WISER-estimated phenotypes consistently outperform the LS-means and BLUP approaches for phenotype estimation, regardless of the predictive model applied. This underscores WISERs potential to advance omics analyses and related research fields by capturing stronger genetic signals.

genetics↗

bioRxiv2024

Control of Molecular Biochemistry and Cell Injury Responses through Highly Ordered Supramolecular Assembly of Flavonoids

Flavonoids are phytonutrients commonly found in plant-based foods and are generally known for their health benefits. However, their utility as potential therapeutics has not been explored because their presence in drug development tests can lead to false positives due to non-specific binding. Here, we employed molecular dynamic simulations (MDS) to examine flavonoid behavior and discovered that they form highly organized supramolecular assemblies that physically interact with disordered regions of enzymatic proteins and can physically interlink multiple protein molecules. These flavonoid assemblies adopt secondary structural patterns like those found in proteins and nucleic acids, and they physically influence molecular movement and tertiary protein structure, thereby modulating the biochemical activities of a diverse range of enzymes. Moreover, in the presence of flavonoids, human cells are protected against injury caused by ultraviolet radiation. These findings unveil a novel form of biochemical regulation wherein small molecules can modulate the function of larger proteins by forming supramolecular assemblies which results in enhanced molecular and cellular resilience. Single Sentence SummaryMolecular dynamic simulations led to the discovery that flavonoid phytonutrients can self-assemble into highly ordered supramolecular structures that interact with enzymatic proteins, slow biochemical activities, and protect cells against injury.

biochemistry↗

bioRxiv2023

Brain cell type specific proteomics approach to discover pathological mechanisms in the childhood CNS disorder mucolipidosis type IV

1 Mucolipidosis IV (MLIV) is an ultra-rare, recessively inherited lysosomal disorder resulting from inactivating mutations in MCOLN1, the gene encoding the lysosomal cation channel TRPML1. The disease primarily affects the central nervous system (CNS) and manifests in the first year with cognitive and motor developmental delay, followed by a gradual decline in neurological function across the second decade of life, blindness, and premature death in third or fourth decades. Brain pathology manifestations in MLIV are consistent with hypomyelinating leukodystrophy with brain iron accumulation. Presently, there are no approved or investigational therapies for MLIV, and pathogenic mechanisms remain largely unknown. The MLIV mouse model, Mcoln1-/- mice, recapitulates all major manifestations of the human disease. Here, to better understand the pathological mechanisms in the MLIV brain, we performed cell type specific LC-MS/MS proteomics analysis in the MLIV mouse model and reconstituted molecular signatures of the disease in either freshly isolated populations of neurons, astrocytes, oligodendrocytes, and neural stem cells, or whole tissue cortical homogenates from young adult symptomatic Mcoln1-/- mice. Our analysis confirmed on the molecular level major histopathological hallmarks of MLIV universally present in Mcoln1-/- tissue and brain cells, such as hypomyelination, lysosomal dysregulation, and impaired metabolism of lipids and polysaccharides. Importantly, pathway analysis in brain cells revealed mitochondria-related alterations in all Mcoln1-/- brain cells, except oligodendrocytes, that was not possible to resolve in whole tissue. We also report unique proteome signatures and dysregulated pathways for each brain cell population used in this study. These data shed new light on cell-intrinsic mechanisms of MLIV and provide new insights for biomarker discovery and validation to advance translational studies for this disease.

neuroscience↗

bioRxiv2023

Identification of a pharmaceutical biostasis inducer that slows metabolism in multiple vertebrates that do not hibernate

Drugs that induce reversible slowing of metabolic and physiological processes would have great value for organ preservation, especially for organs with high susceptibility to hypoxia-reperfusion injury, such as the heart. Using whole-organism screening of metabolism, mobility, and development in Xenopus, we identified an existing drug, SNC80, that rapidly and reversibly slows biochemical and metabolic activities while preserving cell and tissue viability. Although SNC80 was developed as a delta opioid receptor activator, we discovered that its ability to slow metabolism is independent of its opioid modulating activity as a novel SNC80 analog (WB3) with almost 1,000 times less delta opioid receptor binding activity is equally active. Metabolic suppression was also achieved using SNC80 in microfluidic human organs-on-chips, as well as in explanted whole porcine hearts and limbs, demonstrating the cross-species relevance of this approach and potential clinical relevance for surgical transplantation. Pharmacological induction of physiological slowing in combination with organ perfusion transport systems may offer a new therapeutic approach for tissue and organ preservation for transplantation, trauma management, and enhancing patient survival in remote and low-resource locations.

bioengineering↗

bioRxiv2021

Genetic architecture and genomic prediction accuracy of apple quantitative traits across environments

Implementation of genomic tools is desirable to increase the efficiency of apple breeding. The apple reference population (apple REFPOP) proved useful for rediscovering loci, estimating genomic prediction accuracy, and studying genotype by environment interactions (GxE). Here we show contrasting genetic architecture and genomic prediction accuracies for 30 quantitative traits across up to six European locations using the apple REFPOP. A total of 59 stable and 277 location-specific associations were found using GWAS, 69.2% of which are novel when compared with 41 reviewed publications. Average genomic prediction accuracies of 0.18-0.88 were estimated using single-environment univariate, single-environment multivariate, multi-environment univariate, and multi-environment multivariate models. The GxE accounted for up to 24% of the phenotypic variability. This most comprehensive genomic study in apple in terms of trait-environment combinations provided knowledge of trait biology and prediction models that can be readily applied for marker-assisted or genomic selection, thus facilitating increased breeding efficiency.

genomics↗