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Macroautophagy (hereafter referred to as autophagy) is a homeostatic process that preserves cellular integrity. In mice, autophagy regulates pancreatic ductal adenocarcinoma (PDAC) development in a manner dependent on the status of the tumor suppressor gene Trp53. Studies published so far have investigated the impact of autophagy blockage in tumors arising from Trp53-hemizygous or -homozygous tissue. In contrast, in human PDACs the tumor suppressor gene TP53 is mutated rather than allelically lost, and TP53 mutants retain pathobiological functions that differ from complete allelic loss. In order to better represent the patient situation, we have investigated PDAC development in a well-characterized genetically engineered mouse model (GEMM) of PDAC with mutant Trp53 (Trp53\(^{R172H}\)) and deletion of the essential autophagy gene Atg7. Autophagy blockage reduced PDAC incidence but had no impact on survival time in the subset of animals that formed a tumor. In the absence of Atg7, non-tumor-bearing mice reached a similar age as animals with malignant disease. However, the architecture of autophagy-deficient, tumor-free pancreata was effaced, normal acinar tissue was largely replaced with low-grade pancreatic intraepithelial neoplasias (PanINs) and insulin expressing islet β-cells were reduced. Our data add further complexity to the interplay between Atg7 inhibition and Trp53 status in tumorigenesis.
Cellular stress can induce DNA lesions that threaten the stability of genes. The DNA damage response (DDR) recognises and repairs broken DNA to maintain genome stability. Intriguingly, components of nuclear paraspeckles like the non-POU domain containing octamer-binding protein (NONO) participate in the repair of DNA double-strand breaks (DSBs). NONO is a multifunctional RNA-binding protein (RBP) that facilitates the retention and editing of messenger (m)RNA as well as pre-mRNA processing. However, the role of NONO in the DDR is poorly understood. Here, we establish a novel human U2OS cell line that expresses NONO fused to the engineered ascorbate peroxidase 2 (U2OS:NONO-APEX2-HA). We show that NONO-APEX2-HA accumulates in the nucleolus in response to DNA damage. Combining viability assays, subcellular localisation studies, coimmunoprecipitation experiments and in vivo proximity labeling, we demonstrate that NONO-APEX2-HA is a stably expressed fusion protein that mimics endogenous NONO in terms of expression, localisation and bona fide interactors. We propose that in vivo proximity labeling in U2OS:NONO-APEX2-HA cells is capable for the assessment of NONO interactomes by downstream assays. U2OS:NONO-APEX2-HA cells will likely be a valuable resource for the investigation of NONO interactome dynamics in response to DNA damage and other stimuli.
Background
Bacterial meningitis is a life-threatening disease that occurs when pathogens such as Neisseria meningitidis cross the meningeal blood cerebrospinal fluid barrier (mBCSFB) and infect the meninges. Due to the human-specific nature of N. meningitidis, previous research investigating this complex host–pathogen interaction has mostly been done in vitro using immortalized brain endothelial cells (BECs) alone, which often do not retain relevant barrier properties in culture. Here, we developed physiologically relevant mBCSFB models using BECs in co-culture with leptomeningeal cells (LMCs) to examine N. meningitidis interaction.
Methods
We used BEC-like cells derived from induced pluripotent stem cells (iBECs) or hCMEC/D3 cells in co-culture with LMCs derived from tumor biopsies. We employed TEM and structured illumination microscopy to characterize the models as well as bacterial interaction. We measured TEER and sodium fluorescein (NaF) permeability to determine barrier tightness and integrity. We then analyzed bacterial adherence and penetration of the cell barrier and examined changes in host gene expression of tight junctions as well as chemokines and cytokines in response to infection.
Results
Both cell types remained distinct in co-culture and iBECs showed characteristic expression of BEC markers including tight junction proteins and endothelial markers. iBEC barrier function as determined by TEER and NaF permeability was improved by LMC co-culture and remained stable for seven days. BEC response to N. meningitidis infection was not affected by LMC co-culture. We detected considerable amounts of BEC-adherent meningococci and a relatively small number of intracellular bacteria. Interestingly, we discovered bacteria traversing the BEC-LMC barrier within the first 24 h post-infection, when barrier integrity was still high, suggesting a transcellular route for N. meningitidis into the CNS. Finally, we observed deterioration of barrier properties including loss of TEER and reduced expression of cell-junction components at late time points of infection.
Conclusions
Here, we report, for the first time, on co-culture of human iPSC derived BECs or hCMEC/D3 with meningioma derived LMCs and find that LMC co-culture improves barrier properties of iBECs. These novel models allow for a better understanding of N. meningitidis interaction at the mBCSFB in a physiologically relevant setting.
Ovarian cancer is the second most common gynecological malignancy in women. More than 70% of the cases are diagnosed at the advanced stage, presenting as primary peritoneal metastasis, which results in a poor 5-year survival rate of around 40%. Mechanisms of peritoneal metastasis, including adhesion, migration, and invasion, are still not completely understood and therapeutic options are extremely limited. Therefore, there is a strong requirement for a 3D model mimicking the in vivo situation. In this study, we describe the establishment of a 3D tissue model of the human peritoneum based on decellularized porcine small intestinal submucosa (SIS) scaffold. The SIS scaffold was populated with human dermal fibroblasts, with LP-9 cells on the apical side representing the peritoneal mesothelium, while HUVEC cells on the basal side of the scaffold served to mimic the endothelial cell layer. Functional analyses of the transepithelial electrical resistance (TEER) and the FITC-dextran assay indicated the high barrier integrity of our model. The histological, immunohistochemical, and ultrastructural analyses showed the main characteristics of the site of adhesion. Initial experiments using the SKOV-3 cell line as representative for ovarian carcinoma demonstrated the usefulness of our models for studying tumor cell adhesion, as well as the effect of tumor cells on endothelial cell-to-cell contacts. Taken together, our data show that the novel peritoneal 3D tissue model is a promising tool for studying the peritoneal dissemination of ovarian cancer.
The idea that populations are spatially structured has become a very powerful concept in ecology, raising interest in many research areas. However, despite dispersal being a core component of the concept, it typically does not consider the movement behavior underlying any dispersal. Using individual‐based simulations in continuous space, we explored the emergence of a spatially structured population in landscapes with spatially heterogeneous resource distribution and with organisms following simple area‐concentrated search (ACS); individuals do not, however, perceive or respond to any habitat attributes per se but only to their foraging success. We investigated the effects of different resource clustering pattern in landscapes (single large cluster vs. many small clusters) and different resource density on the spatial structure of populations and movement between resource clusters of individuals. As results, we found that foraging success increased with increasing resource density and decreasing number of resource clusters. In a wide parameter space, the system exhibited attributes of a spatially structured populations with individuals concentrated in areas of high resource density, searching within areas of resources, and “dispersing” in straight line between resource patches. “Emigration” was more likely from patches that were small or of low quality (low resource density), but we observed an interaction effect between these two parameters. With the ACS implemented, individuals tended to move deeper into a resource cluster in scenarios with moderate resource density than in scenarios with high resource density. “Looping” from patches was more likely if patches were large and of high quality. Our simulations demonstrate that spatial structure in populations may emerge if critical resources are heterogeneously distributed and if individuals follow simple movement rules (such as ACS). Neither the perception of habitat nor an explicit decision to emigrate from a patch on the side of acting individuals is necessary for the emergence of such spatial structure.
Dung beetles are important actors in the self-regulation of ecosystems by driving nutrient cycling, bioturbation, and pest suppression. Urbanization and the sprawl of agricultural areas, however, destroy natural habitats and may threaten dung beetle diversity. In addition, climate change may cause shifts in geographical distribution and community composition. We used a space-for-time approach to test the effects of land use and climate on α-diversity, local community specialization (H\(_2\)′) on dung resources, and γ-diversity of dung-visiting beetles. For this, we used pitfall traps baited with four different dung types at 115 study sites, distributed over a spatial extent of 300 km × 300 km and 1000 m in elevation. Study sites were established in four local land-use types: forests, grasslands, arable sites, and settlements, embedded in near-natural, agricultural, or urban landscapes. Our results show that abundance and species density of dung-visiting beetles were negatively affected by agricultural land use at both spatial scales, whereas γ-diversity at the local scale was negatively affected by settlements and on a landscape scale equally by agricultural and urban land use. Increasing precipitation diminished dung-visiting beetle abundance, and higher temperatures reduced community specialization on dung types and γ-diversity. These results indicate that intensive land use and high temperatures may cause a loss in dung-visiting beetle diversity and alter community networks. A decrease in dung-visiting beetle diversity may disturb decomposition processes at both local and landscape scales and alter ecosystem functioning, which may lead to drastic ecological and economic damage.
Breast cancer etiology is associated with both proliferation and DNA damage induced by estrogens. Breast cancer risk factors (BCRF) such as body mass index (BMI), smoking, and intake of estrogen-active drugs were recently shown to influence intratissue estrogen levels. Thus, the aim of the present study was to investigate the influence of BCRF on estrogen-induced proliferation and DNA damage in 41 well-characterized breast glandular tissues derived from women without breast cancer. Influence of intramammary estrogen levels and BCRF on estrogen receptor (ESR) activation, ESR-related proliferation (indicated by levels of marker transcripts), oxidative stress (indicated by levels of GCLC transcript and oxidative derivatives of cholesterol), and levels of transcripts encoding enzymes involved in estrogen biotransformation was identified by multiple linear regression models. Metabolic fluxes to adducts of estrogens with DNA (E-DNA) were assessed by a metabolic network model (MNM) which was validated by comparison of calculated fluxes with data on methoxylated and glucuronidated estrogens determined by GC- and UHPLC-MS/MS. Intratissue estrogen levels significantly influenced ESR activation and fluxes to E-DNA within the MNM. Likewise, all BCRF directly and/or indirectly influenced ESR activation, proliferation, and key flux constraints influencing E-DNA (i.e., levels of estrogens, CYP1B1, SULT1A1, SULT1A2, and GSTP1). However, no unambiguous total effect of BCRF on proliferation became apparent. Furthermore, BMI was the only BCRF to indeed influence fluxes to E-DNA (via congruent adverse influence on levels of estrogens, CYP1B1 and SULT1A2).
Candida auris is a globally emerging fungal pathogen responsible for causing nosocomial outbreaks in healthcare associated settings. It is known to cause infection in all age groups and exhibits multi-drug resistance with high potential for horizontal transmission. Because of this reason combined with limited therapeutic choices available, C. auris infection has been acknowledged as a potential risk for causing a future pandemic, and thus seeking a promising strategy for its treatment is imperative. Here, we combined evolutionary information with reverse vaccinology approach to identify novel epitopes for vaccine design that could elicit CD4+ T-cell responses against C. auris. To this end, we extensively scanned the family of proteins encoded by C. auris genome. In addition, a pathogen may acquire substitutions in epitopes over a period of time which could cause its escape from the immune response thus rendering the vaccine ineffective. To lower this possibility in our design, we eliminated all rapidly evolving genes of C. auris with positive selection. We further employed highly conserved regions of multiple C. auris strains and identified two immunogenic and antigenic T-cell epitopes that could generate the most effective immune response against C. auris. The antigenicity scores of our predicted vaccine candidates were calculated as 0.85 and 1.88 where 0.5 is the threshold for prediction of fungal antigenic sequences. Based on our results, we conclude that our vaccine candidates have the potential to be successfully employed for the treatment of C. auris infection. However, in vivo experiments are imperative to further demonstrate the efficacy of our design.
Interactive effects of climate and land use on pollinator diversity differ among taxa and scales
(2022)
Changes in climate and land use are major threats to pollinating insects, an essential functional group. Here, we unravel the largely unknown interactive effects of both threats on seven pollinator taxa using a multiscale space-for-time approach across large climate and land-use gradients in a temperate region. Pollinator community composition, regional gamma diversity, and community dissimilarity (beta diversity) of pollinator taxa were shaped by climate-land-use interactions, while local alpha diversity was solely explained by their additive effects. Pollinator diversity increased with reduced land-use intensity (forest < grassland < arable land < urban) and high flowering-plant diversity at different spatial scales, and higher temperatures homogenized pollinator communities across regions. Our study reveals declines in pollinator diversity with land-use intensity at multiple spatial scales and regional community homogenization in warmer and drier climates. Management options at several scales are highlighted to mitigate impacts of climate change on pollinators and their ecosystem services.
For SARS-CoV-2, R0 calculations in the range of 2–3 dominate the literature, but much higher estimates have also been published. Because capacity for RT-PCR testing increased greatly in the early phase of the Covid-19 pandemic, R0 determinations based on these incidence values are subject to strong bias. We propose to use Covid-19-induced excess mortality to determine R0 regardless of RT-PCR testing capacity. We used data from the Robert Koch Institute (RKI) on the incidence of Covid cases, Covid-related deaths, number of RT-PCR tests performed, and excess mortality calculated from data from the Federal Statistical Office in Germany. We determined R0 using exponential growth estimates with a serial interval of 4.7 days. We used only datasets that were not yet under the influence of policy measures (e.g., lockdowns or school closures). The uncorrected R0 value for the spread of SARS-CoV-2 based on RT-PCR incidence data was 2.56 (95% CI 2.52–2.60) for Covid-19 cases and 2.03 (95% CI 1.96–2.10) for Covid-19-related deaths. However, because the number of RT-PCR tests increased by a growth factor of 1.381 during the same period, these R0 values must be corrected accordingly (R0corrected = R0uncorrected/1.381), yielding 1.86 for Covid-19 cases and 1.47 for Covid-19 deaths. The R0 value based on excess deaths was calculated to be 1.34 (95% CI 1.32–1.37). A sine-function-based adjustment for seasonal effects of 40% corresponds to a maximum value of R0January = 1.68 and a minimum value of R0July = 1.01. Our calculations show an R0 that is much lower than previously thought. This relatively low range of R0 fits very well with the observed seasonal pattern of infection across Europe in 2020 and 2021, including the emergence of more contagious escape variants such as delta or omicron. In general, our study shows that excess mortality can be used as a reliable surrogate to determine the R0 in pandemic situations.