Biology subjects

Diehl, S.

Publications and source records attributed to Diehl, S..

6 recordsLinked to original sources

bioRxiv2026

Contrasting relationships between evolved consumer diversity and productivity for essential vs. substitutable resources

Any mechanistic biodiversity-ecosystem functioning theory must explain how biodiversity in natural communities arises, which requires an evolutionary metacommunity perspective. Using a model of adaptive evolution of competitive metacommunities in landscapes with spatially heterogeneous supply of two resources, we studied the evolution of resource-uptake specialization as a function of resource type (substitutable/essential) and trade-off shape between resource-uptake affinities (generalist-/specialist-favouring). We identified "critical essentiality" as a key phenomenon separating parameter regions with fundamentally different biodiversity--ecosystem function relationships. Specifically, while greater spatial heterogeneity in resource supply increases biodiversity, this comes at the cost of reduced productivity when resources are essential. Moreover, when resources are essential, both generalist- and specialist-favoring trade-offs select for phenotypes that prevent efficient resource partitioning, leading to low resource use efficiency and consumer biomass - despite often high species richness. In contrast, when resources are substitutable, a specialist-favoring affinity trade-off selects for phenotypes that partition resources efficiently, promoting a metacommunity of only two species characterized by high functional diversity, resource use efficiency, and biomass. Overall, our analyses thus suggest that conditions promoting the evolution of diverse consumer communities often do not engender higher functional richness, consumer biomass, or resource use efficiency.

ecology↗

bioRxiv2025

On the influence of stratification and lake size on pelagic and benthic algal dynamics: A modelling study using 'Lake2D'

This study investigates the influence of mixed layer depth and lake size on the dynamics of pelagic and benthic algae in stratified lakes using a two-dimensional, spatially explicit modeling approach. To this end, we modified the process-based, two-dimensional model Lake2D to account for stratification in lakes by simulating a shallow layer with fast turbulent mixing, and a deep layer with slow turbulent mixing, separated by a sharp boundary. Using this modified version of Lake2D we comprehensively explored pelagic and benthic algal dynamics across a wide range of ecological conditions by varying lake mean depth, total nutrient content, lake size, and mixing depth in a full-factorial manner. Our results reveal distinct regimes of whole-lake algal dynamics: In shallow, nutrient-poor lakes, pelagic algae are nutrient-limited and sparse, while benthic algae thrive and constitute the majority of the total biomass, with no notable influence of mixed layer depth on algal dynamics. As lakes become deeper or more nutrient-rich, pelagic biomass increases and can become the dominant constituent of total biomass. For deep lakes, the model shows a characteristic L-shaped pattern in algal biomass for varying lake size and mixing depth. Pelagic algae exhibit low biomass in small lakes with a deep mixed layer, and high biomass otherwise. Benthic algae show the opposite pattern, exhibiting high biomass in small, deep lakes with a deep mixed layer, and significantly lower biomass otherwise. The study also uncovers a novel phenomenon, a benthic deep chlorophyll maximum, where the benthic algal biomass peaks at an intermediate depth along the lake bottom. This phenomenon arises in lakes of moderate depth and nutrient content, where a shallow mixed layer enables opposing vertical gradients of light and nutrients. These findings highlight the role of mixed layer depth and horizontal transport in structuring the spatial distribution and overall composition of algal biomass in lakes, underscoring the importance of vertical mixing and lake size for understanding lake primary production.

ecology↗

bioRxiv2025

Physical drivers of benthic and pelagic algal biomass dynamics in lakes: a conceptual exploration with 'Lake2D'

Size, depth and basin shape are important factors controlling the physics, chemistry and, ultimately, the productivity of lakes. To our knowledge, a comprehensive theoretical investigation of the physical determinants of lake primary production from a conceptual, process-based perspective has not been performed. To address this knowledge gap, we developed and analyzed Lake2D, a process-based, reaction-advection-diffusion model that adopts a 2-dimensional modeling approach by reducing lake bathymetry to its hypsographic depth distribution under the simplifying assumption of radial symmetry of the lake basin. In simpler terms, the model assumes the lake basin is perfectly circular and uses a cross-section to represent its depth and shape. We used Lake2D to explore and analyze the dynamics of pelagic and benthic algae on a whole-lake scale in response to six environmental drivers (lake area and depth, horizontal and vertical turbulent mixing, water transparency and nutrient status), which we varied over ranges that are representative of the vast majority of the worlds lakes. Numerical analyses reveal three distinct patterns across environmental parameter space. (1) Benthic algae dominate total biomass in shallow, clear lakes with low nutrient content. In these lakes, low horizontal and vertical mixing is beneficial to benthic but detrimental to pelagic algae, which experience high sinking losses, thus liberating nutrients and minimizing shading of benthic algae. (2) Increasing mean lake depth, abiotic turbidity and/or nutrient content strongly benefits pelagic algae, which increasingly shade out benthic algae and dominate total biomass. In these lakes, increased mixing affects both algal types positively due to increased nutrient transport to shallow, well-lit areas. (3) Finally, at high lake mean depth and/or abiotic turbidity, a large fraction of the lake volume is aphotic. In such lakes, high horizontal and vertical mixing is detrimental to pelagic algae but beneficial to benthic algae, because pelagic algae are mixed to aphotic depths, liberating nutrients and minimizing shading. Moving from shallow, clear lakes via deeper and/or nutrient-rich lakes to very deep and/or turbid lakes, benthic and pelagic algae therefore show opposite gradual biomass shifts in response to vertical and horizontal mixing. Specifically, benthic biomass is highest at low and lowest at high overall mixing in shallow, nutrient-poor lakes, but shows the opposite trend in all other lakes. Conversely, pelagic biomass is highest at low and lowest at high overall mixing in very deep and/or turbid lakes, but shows the opposite trend in all other lakes.

ecology↗

bioRxiv2025

Can whole-lake algal biomass be captured by one-dimensional modeling approaches? An exploration using 'Lake2D'

Basin morphometry can strongly affect lake-internal processes relevant for productivity, such as turbulent mixing, photosynthetic energy acquisition, sedimentation, and nutrient recycling. Yet, in both empirical and theoretical studies of whole-lake primary production, lake morphometry is often simplified to a single 1-dimensional measure - lake mean depth. Using the conceptual, process-based model Lake2D, we addressed the question: To what extent can pelagic and benthic producer dynamics, integrated over a lake basin, be captured by approaches that use mean depth as the only morphometrical variable? We created two models of algal biomass dynamics in a radially symmetric, cone-shaped lake - one preserving the lakes vertical and radial dimensions and one preserving only the lakes mean depth - and compared model predictions of algal biomass dynamics across a wide range of lake sizes, mixing conditions, water transparency, and nutrient content. Our analyses reveal that model predictions differ substantially but predictably in much of the investigated parameter space, and identifies the light environment set by lake depth, water clarity and pelagic nutrients, but also lake area, as main drivers of the differences. Most commonly, the model based on mean depth underestimates benthic algal biomass and overestimates pelagic algal biomass, the net effect on total biomass being a 5-50% underestimate in shallow lakes and a 5-20% overestimate in many deeper lakes. Since gross primary production (GPP) in our model scales with algal biomass, we believe that global estimates of lake GPP should be corrected for the systematic errors inflicted by the prevailing 1-dimensional approaches.

ecology↗

bioRxiv2023

Phosphatidylinositol 4-kinase III alpha governs cytoskeletal organization for invasiveness of liver cancer cells

Background and AimsHigh expression of phosphatidylinositol 4-kinase III alpha (PI4KIII) correlates with poor survival rates in patients with hepatocellular carcinoma (HCC). In addition, Hepatitis C virus (HCV) infections activate PI4KIII and contribute to HCC progression. We aimed at mechanistically understanding the impact of PI4KIII on the progression of liver cancer and the potential contribution of HCV in this process. MethodsSeveral hepatic cell culture and mouse models were used to study functional importance of PI4KIII on liver pathogenesis. Antibody arrays, gene silencing and PI4KIII specific inhibitor were applied to identify the involved signaling pathways. The contribution of HCV was examined by using HCV infection or overexpression of its nonstructural protein. ResultsHigh PI4KIII expression and/or activity induced cytoskeletal rearrangements via increased-phosphorylation of paxillin and cofilin. This led to morphological alterations and higher migratory and invasive properties of liver cancer cells. We further identified the liver specific lipid kinase phosphatidylinositol 3-kinase C2 domain-containing subunit gamma (PIK3C2{gamma}) working downstream of PI4KIII in regulation of the cytoskeleton. PIK3C2{gamma} generates plasma membrane (PM) phosphatidylinositol 3,4-bisphosphate [PI(3,4)P2]- enriched, invadopodia-like structures which regulate cytoskeletal reorganization by promoting Akt2 phosphorylation. ConclusionsPI4KIII regulates cytoskeleton organization via PIK3C2{gamma}/Akt2/paxillin-cofilin to favor migration and invasion of liver cancer cells. These findings provide mechanistic insight into the contribution of PI4KIII and HCV to progression of liver cancer and identify promising targets for therapeutic intervention. IMPACT AND IMPLICATIONSUnderstanding mechanistically how high PI4KIII expression are associated with poor clinical outcomes of liver cancer is important to develop pharmaceutical interventions. Our study sheds light on the importance of the two lipid kinases PI4KIII and PIK3C2{gamma} as well as the contribution of HCV on liver cancer progression, unraveling the signaling pathway governing this process. This preclinical study contributes to better understanding the complex connection of phospholipids, cytoskeleton and liver cancer and suggests strategies to improve therapeutic outcomes by targeting important signaling molecules. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=161 SRC="FIGDIR/small/541742v1_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@16ba717org.highwire.dtl.DTLVardef@a6f681org.highwire.dtl.DTLVardef@181c3cdorg.highwire.dtl.DTLVardef@5df6aa_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2023

Spatial omics imaging of fresh-frozen tissue and routine FFPE histopathology on a single cancer needle core biopsy: freezing device and multimodal workflow

Complex molecular alterations underlying cancer pathophysiology are intensely studied with omics methods using bulk tissue extracts. For spatially resolved tissue diagnostics using needle biopsy cores, however, histopathological analysis using stained FFPE tissue and immuno-histochemistry (IHC) of few marker proteins is currently the main clinical focus. Today, spatial omics imaging using MSI or IRI are emerging diagnostic technologies for identification and classification of various cancer types. However, to conserve tissue-specific metabolomic states, fast, reliable and precise methods for preparation of fresh-frozen (FF) tissue sections are crucial. Such methods are often incompatible with clinical practice, since spatial metabolomics and routine histopathology of needle biopsies currently require two biopsies for FF and FFPE sampling, respectively. Therefore, we developed a device and corresponding laboratory and computational workflows for multimodal spatial omics analysis of fresh-frozen, longitudinally sectioned needle biopsies to accompany standard FFPE histopathology on the same biopsy core. As proof-of-concept, we analyzed surgical human liver cancer specimen by IRI and MSI with precise co-registration and, following FFPE processing, by sequential clinical pathology analysis on the same biopsy core. This workflow allowed spatial comparison between different spectral profiles and alterations in tissue histology, as well as direct comparison to histological diagnosis without the need of an extra biopsy. SIMPLE SUMMARYRoutine clinical approaches for cancer diagnosis demand fast, cost-efficient, and reliable methods, and their implementation within clinical settings. Currently, histopathology is the golden standard for tissue-based clinical diagnosis. Recently, spatially resolved molecular profiling techniques like mass spectrometry imaging (MSI) or infrared spectroscopy imaging (IRI) have increasingly contributed to clinical research, e.g., by differentiation of cancer subtypes using molecular fingerprints. However, adoption of the corresponding workflows in clinical routine remains challenging, especially for fresh-frozen tissue specimen. Here, we present a novel device based on 3D-printing technology, which facilitates sample preparation of needle biopsies for correlated clinical tissue analysis. It enables combination of MSI and IRI on fresh-frozen clinical samples with histopathological examination of the same needle core after formalin-fixation and paraffin-embedding (FFPE). This device and workflow can pave the way for a more profound understanding of biomolecular processes in cancer and, thus, aid more accurate diagnosis. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=180 SRC="FIGDIR/small/528125v1_ufig1.gif" ALT="Figure 1"> View larger version (55K): org.highwire.dtl.DTLVardef@1da99aborg.highwire.dtl.DTLVardef@9ee706org.highwire.dtl.DTLVardef@5153daorg.highwire.dtl.DTLVardef@1581594_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗