Biology subjects

Dietze, M.

Publications and source records attributed to Dietze, M..

7 recordsLinked to original sources

bioRxiv2026

Bx42 directs neural stem cell exit from quiescence through Prospero

Microcephaly is a rare neurodevelopmental disorder characterized by a severely reduced head and brain size in children and is accompanied by a myriad of debilitating side effects including cognitive and developmental impairments. While many cases of microcephaly arise from genetic mutations, the molecular mechanism linking variants to disease remain poorly understood. We previously identified Bx42 as a microcephaly-causing gene from a patient-informed study using human brain organoid modeling and functional studies in Drosophila melanogaster. Here, we demonstrate that loss of Bx42 leads to microcephaly by reducing neural stem cell proliferation early in development. Mechanistically, our data suggest that Bx42 promotes the transition from quiescence to proliferation through regulation of the neural differentiation factor Prospero. Reduction of Bx42 results in reduced neural stem cell division due to a prolonged quiescent state. Importantly, we demonstrate that two patient-derived variants in the human ortholog, SNW1, are nonfunctional or hypomorphic, providing strong evidence that these variants are pathogenic and causative of microcephaly. Together, our findings define a previously unrecognized role for the Bx42/SNW1 pathway in regulating neural stem cell activation and brain growth, offering new mechanistic insight into the pathogenesis of genetically driven microcephaly.

developmental biology↗

bioRxiv2024

Mechanistic pathways of tick exposure risk in native and invaded plant communities

Plant invasions may alter disease vector abundance by several mechanistic pathways, including modifying microclimates that influence vector survival or changing habitats to influence host use. Here, we used a field experiment and observational data to evaluate multiple mechanistic pathways (tick survival and host abundance) by which plant invasions may alter vector-borne disease risk using the common disease vector lone star tick (Amblyomma americanum), its preeminent host white-tailed deer (Odocoileus virginianus), and the widespread invasive cogongrass (Imperata cylindrica) in the southeastern USA. In the field experiment, ticks survived over 50% longer in areas dominated by the invasive plant compared to those with only native plant species. Invaded areas had lower temperatures and higher relative humidity, yielding a lower vapor pressure deficit (VPD) that likely reduced tick desiccation. The observational study showed similar average tick abundance in native and invaded plant communities and no difference in wildlife host (white-tailed deer) activity between plant communities. However, there was a positive relationship between tick abundance and white-tailed deer activity, but only in native areas. Together, these results suggest that more favorable microclimate conditions resulting in greater tick longevity are the dominant driver of tick abundance in invaded areas, while tick abundance in native-dominated areas may be promoted, at least in part, by white-tailed deer activity. Our results demonstrate that plant invasions can affect multiple, potentially counteracting mechanistic pathways that contribute to tick exposure risk. The complexity of these relationships highlights the need for better understanding of how invasive species and other global change drivers influence disease vectors and, ultimately, disease transmission.

ecology↗

bioRxiv2024

Identification of CNTN2 as a genetic modifier of PIGA-CDG through pedigree analysis of a family with incomplete penetrance and functional testing in Drosophila

Loss of function mutations in the X-linked PIGA gene lead to PIGA-CDG, an ultra-rare congenital disorder of glycosylation (CDG), typically presenting with seizures, hypotonia, and neurodevelopmental delay. We identified two brothers (probands) with PIGA-CDG, presenting with epilepsy and mild developmental delay. Both probands carry PIGAS132C, an ultra-rare variant predicted to be damaging. Strikingly, the maternal grandfather and a great-uncle also carry PIGAS132C, but neither presents with symptoms associated with PIGA-CDG. We hypothesized genetic modifiers may contribute to this reduced penetrance. Using whole genome sequencing and pedigree analysis, we identified possible susceptibility variants found in the probands and not in carriers and possible protective variants found in the carriers and not in the probands. Candidate variants included heterozygous, damaging variants in three genes also involved directly in GPI-anchor biosynthesis and a few genes involved in other glycosylation pathways or encoding GPI-anchored proteins. We functionally tested the predicted modifiers using a Drosophila eye-based model of PIGA-CDG. We found that loss of CNTN2, a predicted protective modifier, rescues loss of PIGA in Drosophila eye-based model, like what we predict in the family. Further testing found that loss of CNTN2 also rescues patient-relevant phenotypes, including seizures and climbing defects in Drosophila neurological models of PIGA-CDG. By using pedigree information, genome sequencing, and in vivo testing, we identified CNTN2 as a strong candidate modifier that could explain the incomplete penetrance in this family. Identifying and studying rare disease modifier genes in human pedigrees may lead to pathways and targets that may be developed into therapies.

genetics↗

bioRxiv2023

A Zika virus protein expression screen in Drosophila to investigate targeted host pathways during development

In the past decade, Zika virus (ZIKV) emerged as a global public health concern. While adult infections are typically mild, maternal infection can lead to adverse fetal outcomes. Understanding how ZIKV proteins disrupt development can provide insights into the molecular mechanisms of symptoms caused by this virus including microcephaly. In this study, we generated a toolkit to ectopically express Zika viral proteins in vivo in Drosophila melanogaster in a tissue-specific manner using the GAL4/UAS system. We use this toolkit to identify phenotypes and host pathways targeted by the virus. Our work identified that expression of most ZIKV proteins cause scorable phenotypes, such as overall lethality, gross morphological defects, reduced brain size, and neuronal function defects. We further use this system to identify strain-dependent phenotypes that may contribute to the increased pathogenesis associated with the more recent outbreak of ZIKV in the Americas. Our work demonstrates Drosophilas use as an efficient in vivo model to rapidly decipher how pathogens cause disease and lays the groundwork for further molecular study of ZIKV pathogenesis in flies.

developmental biology↗

bioRxiv2020

Determinants of Predictability in Multi-decadal Forest Community and Carbon Dynamics

Underestimation of uncertainty in ecology runs the risk of producing precise, but inaccurate predictions. Most predictions from ecological models account for only a subset of the various components of uncertainty, making it diffcult to determine which uncertainties drive inaccurate predictions. To address this issue, we leveraged the forecast-analysis cycle and created a new state data assimilation algorithm that accommodates non-normal datasets and incorporates a commonly left-out uncertainty, process error covariance. We evaluated this novel algorithm with a case study where we assimilated 50 years of tree-ring-estimated aboveground biomass data into a forest gap model. To test assumptions about which uncertainties dominate forecasts of forest community and carbon dynamics, we partitioned hindcast variance into five uncertainty components. Contrary to the assumption that demographic stochasticity dominates forest gap dynamics, we found that demographic stochasticity alone massively underestimated forecast uncertainty (0.09% of the total uncertainty) and resulted in overconfident, biased model predictions. Similarly, despite decades of reliance on unconstrained "spin-ups" to initialize models, initial condition uncertainty declined very little over the forecast period and constraining initial conditions with data led to large increases in prediction accuracy. Process uncertainty, which up until now had been diffcult to estimate in mechanistic ecosystem model projections, dominated the prediction uncertainty over the forecast time period (49.1%), followed by meteorological uncertainty (32.5%). Parameter uncertainty, a recent focus of the modeling community, contributed 18.3%. These findings call into question our conventional wisdom about how to improve forest community and carbon cycle projections. This foundation can be used to test long standing modeling assumptions across fields in global change biology and specifically challenges the conventional wisdom regarding which aspects dominate uncertainty in the forest gap models.

ecology↗

bioRxiv2019

The influence of canopy radiation parameter uncertainty on model projections of terrestrial carbon and energy cycling

Reducing uncertainties in Earth System Model predictions requires carefully evaluating core model processes. Here we examined how canopy radiative transfer model (RTM) parameter uncertainties, in combination with canopy structure, affect terrestrial carbon and energy projections in a demographic land-surface model, the Ecosystem Demography model (ED2). Our analyses focused on temperate deciduous forests and tested canopies of varying structural complexity. The results showed a strong sensitivity of tree productivity, albedo, and energy balance projections to RTM parameters. Impacts of radiative parameter uncertainty on stand-level canopy net primary productivity ranged from ~2 to > 20% and was most sensitive to canopy clumping and leaf reflectance/transmittance in the visible spectrum (~400 - 750 nm). ED2 canopy albedo varied by ~1 to ~10% and was most sensitive to near-infrared reflectance (~800 - 1200 nm). Bowen ratio, in turn, was most sensitive to wood optical properties parameterization; this was much larger than expected based on literature, suggesting model instabilities. In vertically and spatially complex canopies the model response to RTM parameterization may show an apparent reduced sensitivity when compared to simpler canopies, masking much larger changes occurring within the canopy. Our findings highlight both the importance of constraining canopy RTM parameters in models and valuating how the canopy structure responds to those parameter values. Finally, we advocate for more model evaluation, similar to this study, to highlight possible issues with model behavior or process representations, particularly models with demographic representations, and identify potential ways to inform and constrain model predictions.\n\nKey pointsO_LIUncertainties in vegetation radiative parameter affect carbon, water and energy balances in ecosystem models.\nC_LIO_LIRadiative properties can lead to significant changes in demography and canopy structure even if aggregate model responses appear unchanged\nC_LI

ecology↗

bioRxiv2018

Climate or disturbance: temperate forest structural change and carbon sink potential

Anticipating forest responses to changing climate and disturbance regimes requires understanding long-term successional processes and aggregating these local processes into global relevance. Estimates of existing forest structure and biomass are improving globally; however, vegetation models continue to show substantial spread in predictions of future land carbon uptake and the roles of forest structural change and demography are increasingly being recognized as important. To identify mechanisms that drive change in tree size, density, and carbon, we need a better understanding of forest structural trajectories and the factors that affect those trajectories. Here we reveal a coherent, cyclic pattern of structural change in temperate forests, as predicted by successional theory, and identify significant sensitivity to climatic precipitation and temperature anomalies using large datasets and empirical modeling. For example, in the eastern US above average temperature (+1{degrees}C) was associated with a 27% (-0.4{+/-}0.1 Mg C ha-1 yr-1) reduction in productivity attributed to higher rates of disease (+23%), weather disturbance (+57%), and sapling mortality. Projections of future vegetative carbon sink potential suggests biomass would be lowest on managed lands (72{+/-}2 Mg C ha-1) and highest when larger trees survive in undisturbed conditions (153{+/-}21 Mg C ha-1). Overall, the indirect effects of disturbance and mortality were considerably larger than the direct effects of climate on productivity when predicting future vegetative carbon sinks. Results provide robust comparisons for global vegetation models, and valuable projections for management and carbon mitigation efforts.

ecology↗