Biology subjects

Scherer, C.

Publications and source records attributed to Scherer, C..

9 recordsLinked to original sources

bioRxiv2025

Subthreshold violations of trajectory predictions are sensitive to TMS of Cerebellum CRUS I/II

Temporal prediction can help to follow a trajectory. In case of an error, the prediction can be adjusted. However, processing the error and adjusting the prediction can take time. What happens immediately after a prediction error, and can the processing of the prediction be modulated? We use a newly found illusion based on moving squares and requiring trajectory regularity to be elicited. We examined the conscious consequences of a sub-threshold manipulation of the square trajectories, and transcranial magnetic stimulation (TMS) on the cerebellum (right CRUS I/II) to study the modulation of the processing of the trajectory manipulations. The TMS was a typical intermittent theta-burst stimulation, but only one sequence of around 3 minutes, compared with a placebo stimulation. The trajectory manipulation had a reliable effect on the illusion, even though the illusion emerged within less than 100 ms after the trajectory manipulation. The results suggest that the prediction is temporarily stopped after the trajectory change. The illusion was accompanied by EEG signals whose amplitude was modulated by TMS on the cerebellum, at least in those participants who received verum TMS after having performed the task three times. Those EEG signals resembled a late LPP (Late Positive Potential). As LPP spontaneously decreased over time, the results suggest the effect of TMS may represent a reinstation of the EEG consequences of the prediction error, i.e., a modulation of its significance.

neuroscience↗

bioRxiv2022

Resource asynchrony and landscape homogenization as drivers of virulence evolution

In the last years, the emergence of zoonotic diseases and the frequency of disease outbreaks have increased substantially, fuelled by habitat encroachment and asynchrony of biological cycles due to global change. The virulence of these diseases is a key aspect for their success. In order to understand the complex processes of pathogen virulence evolution in the global change context, we adapted an established individual-based model of host-pathogen dynamics. Our model simulates a population of social hosts affected by an evolving pathogen in a dynamic landscape. Pathogen virulence evolution is explored by the inclusion of multiple strains in the model that differ in their transmission capability and lethality. Simultaneously, the hosts resource landscape is subjected to spatial and temporal dynamics, emulating effects of global change. We found an increase in pathogenic virulence and a shift in strain dominance with increasing landscape homogenisation. Our model further shows a trend to lower virulence pathogens being dominant in fragmented landscapes, although pulses of highly virulent strains are expected under resource asynchrony. While all landscape scenarios favour coexistence of low and high virulent strains, when host density increases, the high virulence strains capitalize on the high possibility for transmission and are likely to become dominant. Author SummaryDisease outbreaks primarily caused by contact with animals are increasing in recent years, related to habitat destruction and altered biological cycles due to climate change. Pathogens associated with such outbreaks will be more successful the more effectively they can spread in a population. Thus, understanding the conditions over which those pathogens evolve will help us to limit the impact of disease outbreaks in the future. To this end, we used an individual based model that allowed us to study different scenarios. Our model had three main components: a host-pathogen system, a dynamic resource landscape with different degrees of fragmentation and temporal resource mismatches. We used dynamic landscapes with varying resource amounts over the years and consisting of multiple large or smaller habitat clusters. Our simulations showed that homogenous landscapes resulted in higher virulent pathogens and fragmented landscapes in lesser virulent pathogens. However, across all scenarios, high and low virulent pathogen strains were able to coexist.

ecology↗

bioRxiv2022

Effects of microplastics mixed with natural particles on Daphnia magna populations

The toxicity of microplastics on Daphnia magna as a key model for freshwater zooplankton is well described. While several studies predict population-level effects based on short-term, individual-level responses, only very few have validated these predictions experimentally. Thus, we exposed D. magna populations to irregular polystyrene microplastics and diatomite as natural particle (both [≤] 63 m) over 50 days. We used mixtures of both particle types at fixed particle concentrations (50,000 particles mL-1) and recorded the effects on overall population size and structure, the size of the individual animals, and resting egg production. Particle exposure adversely affected the population size and structure and induced resting egg production. The terminal population size was 28-42% lower in exposed compared to control populations. Interestingly, mixtures containing diatomite induced stronger effects than microplastics alone, highlighting that natural particles are not per se less toxic than microplastics. Our results demonstrate that an exposure to synthetic and natural particles has negative population-level effects on zooplankton. Understanding the mixture toxicity of microplastics and natural particles is important given that aquatic organisms will experience exposure to both. Just as for chemical pollutants, better knowledge of such joint effects is essential to fully understand the environmental impacts of complex particle mixtures. Environmental ImplicationsWhile microplastics are commonly considered hazardous based on individual-level effects, there is a dearth of information on how they affect populations. Since the latter is key for understanding the environmental impacts of microplastics, we investigated how particle exposures affect the population size and structure of Daphnia magna. In addition, we used mixtures of microplastics and natural particles because neither occurs alone in nature and joint effects can be expected in an environmentally realistic scenario. We show that such mixtures adversely affect daphnid populations and highlight that population-level and mixture-toxicity designs are one important step towards more environmental realism in microplastics research. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=118 SRC="FIGDIR/small/490562v3_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@11a9358org.highwire.dtl.DTLVardef@1bfa315org.highwire.dtl.DTLVardef@6bc0cdorg.highwire.dtl.DTLVardef@3ef1b8_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIDaphnia populations exposed to mixtures of microplastics and diatomite C_LIO_LIEffects on population size, structure, and resting egg production C_LIO_LIDiatomite as natural particle more toxic than microplastics C_LIO_LIParticle mixtures induce negative population-level effects C_LIO_LIParticle mixtures represent more realistic exposure scenario C_LI

ecology↗

bioRxiv2021

Antiviral RNAi response against the insect-specific Agua Salud alphavirus

Arboviruses transmitted by mosquitoes are responsible for the death of millions of people each year. In addition to arboviruses, many insect-specific viruses (ISVs) have been discovered in mosquitoes in the last decade. ISVs, in contrast to arboviruses transmitted by mosquitoes to vertebrates, cannot replicate in vertebrate cells even when they are evolutionarily closely related to arboviruses. The alphavirus genus includes many arboviruses, although only a few ISVs have been discovered from this genus so far. Here, we investigate the interactions of a recently isolated insect-specific alphavirus, Agua-Salud alphavirus (ASALV), with its mosquito host. RNAi is one of the essential antiviral responses against arboviruses, although there is little knowledge on the interactions of RNAi with ISVs. Through knock-down of transcripts of the different key RNAi pathway (siRNA, miRNA and piRNA) proteins, we show the antiviral role of Ago2 (siRNA), Ago1 (miRNA), and Piwi4 proteins against ASALV in Aedes aegypti derived cells. ASALV replication increased in Dicer2 and Ago2 knock-out cells, confirming the antiviral role of the siRNA pathway. In infected cells, mainly ASALV-specific siRNAs are produced while piRNAs, with the characteristic nucleotide bias resulting from ping-pong amplification, are only produced in Dicer2 knock-out cells. Taken together, ASALV interactions with the mosquito RNAi response differs from arthropod-borne alphaviruses in some aspects, although they also share some commonalities. Further research is needed to understand whether the identified differences can be generalised to other insect-specific alphaviruses.

microbiology↗

bioRxiv2021

Impaired function and delayed regeneration of dendritic cells in COVID-19

Disease manifestations in COVID-19 range from mild to severe illness associated with a dysregulated innate immune response. Alterations in function and regeneration of dendritic cells (DC) and monocytes may contribute to immunopathology and influence adaptive immune responses in COVID-19 patients. We analyzed circulating DC and monocyte subsets in 65 hospitalized COVID-19 patients with mild/moderate or severe disease from acute disease to recovery and in healthy controls. Persisting reduction of all DC subpopulations was accompanied by an expansion of proliferating Lineage- HLADR+ cells lacking DC markers. Increased frequency of the recently discovered CD163+ CD14+ DC3 subpopulation in patients with more severe disease was associated with systemic inflammation, activated T follicular helper cells, and antibody-secreting cells. Persistent downregulation of CD86 and upregulation of PD-L1 in conventional DC (cDC2 and DC3) and classical monocytes associated with a reduced capacity to stimulate naive CD4+ T cells correlated with disease severity. Long-lasting depletion and functional impairment of DCs and monocytes may have consequences for susceptibility to secondary infections and therapy of COVID-19 patients.

immunology↗

bioRxiv2021

Halfway to self-sustainability: Reintroduced migratory European Northern Bald Ibises (Geronticus eremita) still need management interventions for population viability

Northern Bald Ibis (NBI) have disappeared from Europe already in Middle Age. Since 2003 a migratory population is reintroduced in Central Europe. We conducted demographic analyses of survival and reproduction of 384 NBI over a period of 12 years (2008-2019). These data also formed the basis for a population viability analysis (PVA) simulating the possible future development of the NBI population in different scenarios. We tested life-stage specific survival rates for differences between these stages, raising types and colonies as well as the influence of stochastic events and NBI supplements on the population growth. Stage specific survival rates ranged from 0.64 to 0.78. 61% of the mature females reproduce with a mean fecundity of 2.15 fledglings per nest. The complementary PVA indicated that the release population is close to self-sustainability with a given lambda 0.95 and 24% extinction probability within 50 years. Of the 326 future scenarios tested, 94 % reached the criteria of <5% extinction probability and population growth rates >1. In case of positive population growth, stochastic events had a limited effect. Of 820 sub-scenarios with different stochastic event frequencies and severities 87 % show population growth despite the occurrence of stochastic events. Predictions can be made based on the results of the individual-based model as to whether and under what circumstances the reintroduced NBI population can survive. This study shows that a PVA can support reintroduction success that should work closely together with the project in the field for mutual benefit, to optimize future management decisions.

ecology↗

bioRxiv2021

Protective immune trajectories in early viral containment of non-pneumonic SARS-CoV-2 infection

The immune system of most SARS-CoV-2 infected individuals limits viral spread to the upper airways without pulmonary involvement. This prevents the development of pneumonic COVID-19. However, the protective immunological responses causative of successful viral containment in the upper airways remain unclear. Here, we combine longitudinal single-cell RNA sequencing, proteomic profiling, multidimensional flow cytometry, RNA-Seq of FACS-sorted leukocyte subsets and multiplex plasma interferon profiling to uncover temporally resolved protective immune signatures in non-pneumonic and ambulatory SARS-CoV-2 infected patients. We compare host responses in a high-risk patient population infected with SARS-CoV-2 but without pulmonary involvement to patients with COVID-19 pneumonia. Our data reveal a distinct immunological signature of successful viral containment, characterized by an early prominent interferon stimulated gene (ISG) upregulation across immune cell subsets. In addition, reduced cytotoxic potential of Natural Killer (NK) and T cells, as well as a monocyte phenotype with immune-modulatory potential are hallmarks of protective immunity. Temporal resolution across disease trajectories highlights ISG upregulation as particularly prominent early in the disease and confirms increased expression also in comparison to healthy controls. We validate this distinct temporal ISG signature by in-depth RNA-seq of FACS-sorted leukocyte subsets in a large prospective ambulatory SARS-CoV-2 infected cohort confirming early and robust ISG upregulation particularly in monocytes and T cells. In conclusion, our data demonstrate a protective ISG phenotype in patients with successful containment of SARS-CoV-2 infection without progression to COVID-19. This early protective interferon response might be exploited as a therapeutic approach and for disease course prediction.

immunology↗

bioRxiv2020

Analysis of 46,046 SARS-CoV-2 whole-genomes leveraging principal component analysis (PCA)

Since the beginning of the global SARS-CoV-2 pandemic, there have been a number of efforts to understand the mutations and clusters of genetic lines of the SARS-CoV-2 virus. Until now, phylogenetic analysis methods have been used for this purpose. Here we show that Principal Component Analysis (PCA), which is widely used in population genetics, can not only help us to understand existing findings about the mutation processes of the virus, but can also provide even deeper insights into these processes while being less sensitive to sequencing gaps. Here we describe a comprehensive analysis of a 46,046 SARS-CoV-2 genome sequence dataset downloaded from the GISAID database in June of this year. SummaryPCA provides deep insights into the analysis of large data sets of SARS-CoV-2 genomes, revealing virus lineages that have thus far been unnoticed.

bioinformatics↗

bioRxiv2018

NLMR and landscapetools: An integrated environment for simulating and modifying neutral landscape models in R

O_LINeutral landscape models (NLMs) simulate landscape patterns based on theoretical distributions and can be used to systematically study the effect of landscape structure on ecological processes. NLMs are commonly used in landscape ecology to enhance the findings of field studies as well as in simulation studies to provide an underlying landscape. However, their creation so far has been limited to software that is platform dependent, does not allow a reproducible workflow or is not embedded in R, the prevailing programming language used by ecologists.\nC_LIO_LIHere, we present two complementary R packages NLMR and land-scapetools, that allow users to generate, manipulate and analyse NLMs in a single environment. They grant the simulation of the widest collection of NLMs found in any single piece of software thus far while allowing for easy manipulation in a self-contained and reproducible workflow. The combination of both packages should stimulate a wider usage of NLMs in landscape ecology. NLMR is a comprehensive collection of algorithms with which to simulate NLMs. landscapetools provides a utility toolbox which facilitates an easy workflow with simulated neutral landscapes and other raster data.\nC_LIO_LIWe show two example applications that illustrate potential use cases for NLMR and landscapetools: First, an agent-based simulation study in which the effect of spatial structure on disease persistence was studied. Here, spatial heterogeneity resulted in more variable disease outcomes compared to the common well-mixed host assumption. The second example shows how increases in spatial scaling can introduce biases in calculated landscape metrics.\nC_LIO_LISimplifying the workflow around handling NLMs should encourage an uptake in the usage of NLMs. NLMR and landscapetools are both generic frameworks that can be used in a variety of applications and are a further step to having a unified simulation environment in R for answering spatial research questions.\nC_LI

ecology↗