Biology subjects

Becker, M.

Publications and source records attributed to Becker, M..

67 records · Page 4Linked to original sources

bioRxiv2020

Using relative brain size to better understand trophic interactions and phenotypic plasticity of invasive lionfish (Pterois volitans)

Predator-prey dynamics provide critical insight into overall coral reef health. It has been shown that predator-prey relationships link the relative brain size of predators to their prey. Predation pressure forces prey to use decision-making skills that require higher cognition by inspecting and identifying predators and then adjusting their behavior to achieve the highest chance for survival. However, the predation pressure that prey face outweighs the pressure predators face to find prey, resulting in prey having larger relative brain sizes than their predators. There is little data on the relative brain size of fishes with few natural predators such as Pterois volitans. This study compared the brain mass to body mass ratio of Pterois volitans, which have very few natural predators and thus very little predation pressure, to the brain mass to body mass ratio of their prey, possible predators, competitors, and taxonomically similar fish. Lionfish had a significantly smaller relative brain size than their predators, prey, and competitors, but was not significantly smaller than taxonomically similar fish. These results demonstrate that the morphological anti-predator adaptation of venomous spines causes little predation pressure. Thus, lionfish do not use the same cognitive skills as other prey or predators and, in turn, have smaller relative brain sizes.

evolutionary biology↗

bioRxiv2019

Presynaptic dysfunction in CASK-related neurodevelopmental disorders

CASK-related disorders are a genetically defined group of neurodevelopmental syndromes. There is limited information about the effects of CASK mutations in human neurons. Therefore, we sought to delineate CASK mutation consequences and neuronal level effects using induced pluripotent stem cell-derived neurons from two mutation carriers; one male diagnosed with ASD and a female with MICPCH. We show a reduction of the CASK protein in maturing neurons from the mutation carriers, which leads to significant downregulation of gene sets involved in presynaptic development and CASK protein interactors. Furthermore, CASK-deficient neurons showed decreased inhibitory presynapse size as indicated by VGAT staining, which may alter the excitatory-inhibitory (E/I) balance in developing neural circuitries. Using in vivo magnetic resonance spectroscopy quantification of GABA in the male mutation carrier, we further highlight the possibility to validate in vitro cellular data in brain. Our data shows that future pharmacological and clinical studies on targeting presynapses and E/I imbalance could lead to specific treatments for CASK-related disorders. HighlightsModelling of CASK-related disorders using iPSC-derived human neuronal cells CASK mutations cause dysregulation of its protein interactor partners Reduced CASK levels primarily affect inhibitory presynapse development In vitro GABAergic phenotype predicts in vivo neurotransmitter levels

genetics↗

bioRxiv2019

Investigation of the quorum-sensing regulon of the biocontrol bacterium Pseudomonas chlororaphis strain PA23

Pseudomonas chlororaphis strain PA23 is a biocontrol agent capable of protecting canola from stem rot disease caused by the fungal pathogen Sclerotinia sclerotiorum. PA23 produces several of inhibitory compounds that are under control of a complex regulatory network. Included in this cascade is the PhzRI quorum sensing (QS) system, which plays an essential role in PA23 biocontrol. The focus of the current study was to employ RNA sequencing to explore the spectrum of PA23 genes under QS control. Transcriptomic profiling revealed 545 differentially expressed genes (365 downregulated; 180 upregulated) in the phzR mutant and 534 genes (382 downregulated; 152 upregulated) in the AHL-deficient PA23-6863. In both strains, decreased expression of phenazine, pyrrolnitrin, and exoprotease biosynthetic genes was observed. We have previously reported that QS activates expression of these genes and their encoded products. In addition, elevated siderophore and decreased chitinase gene expression was observed in the QS-deficient stains, which was confirmed by phenotypic analysis. Inspection of the promoter regions revealed the presence of "phz-box" sequences in only 58 of the 807 differentially expressed genes, suggesting that much of the QS regulon is indirectly regulated. Consistent with this notion, 41 transcriptional regulators displayed altered expression in one or both of the QS-deficient strains. Collectively, our findings indicate that QS governs expression of approximately 13% of the PA23 genome affecting diverse functions ranging from secondary metabolite production to general metabolism. To the best of our knowledge, this represents the first global transcriptomic analysis of the QS regulon of a biocontrol pseudomonad.

microbiology↗

bioRxiv2019

Evaluation of rice wild relatives as a source of traits for adaptation to iron toxicity and enhanced grain quality

Rice wild relatives (RWR) constitute an extended gene pool that can be tapped for the breeding of novel rice varieties adapted to abiotic stresses such as iron (Fe) toxicity. Therefore, we screened 75 Oryza genotypes including 16 domesticated O. sativas, one O. glaberrima, and 58 RWR representing 21 species, for tolerance to Fe toxicity. Plants were grown in a semi-artificial greenhouse setup, in which they were exposed either to control conditions, an Fe shock during the vegetative growth stage (acute treatment), or to a continuous moderately high Fe level (chronic treatment). In both stress treatments, foliar Fe concentrations were characteristic of Fe toxicity, and plants developed foliar stress symptoms, which were more pronounced in the chronic Fe stress especially toward the end of the growing season. Among the genotypes that produced seeds, only the chronic stress treatment significantly reduced yields due to increases in spikelet sterility. Moreover, a moderate but non-significant increase in grain Fe concentrations, and a significant increase in grain Zn concentrations were seen in chronic stress. Both domesticated rice and RWR exhibited substantial genotypic variation in their responses to Fe toxicity. Although no RWR strikingly outperformed domesticated rice in Fe toxic conditions, some genotypes scored highly in individual traits. Two O. meridionalis accessions were best in avoiding foliar symptom formation in acute Fe stress, while an O. rufipogon accession produced the highest grain yields in both chronic and acute Fe stress. In conclusion, this study provides the basis for using interspecific crosses for adapting rice to Fe toxicity.

plant biology↗

bioRxiv2019

A rule-based data-informed cellular consensus map of the human mononuclear phagocyte cell space

Single-cell genomic techniques are opening new avenues to understand the basic units of life. Large international efforts, such as those to derive a Human Cell Atlas, are driving progress in this area; here, cellular map generation is key. To expedite the inevitable iterations of these underlying maps, we have developed a rule-based data-informed approach to build next generation cellular consensus maps. Using the human dendritic-cell and monocyte compartment in peripheral blood as an example, we performed computational integration of previous, partially overlapping maps using an approach we termed backmapping, combined with multi-color flow-cytometry and index sorting-based single-cell RNA-sequencing. Our general strategy can be applied to any atlas generation for humans and other species.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC=\"FIGDIR/small/658179v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (18K):\norg.highwire.dtl.DTLVardef@c1b7b2org.highwire.dtl.DTLVardef@32b68org.highwire.dtl.DTLVardef@16e5fcorg.highwire.dtl.DTLVardef@1552028_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIDefining a consensus of the human myeloid cell compartment in peripheral blood\nC_LIO_LI3 monocytes subsets, pDC, cDC1, DC2, DC3 and precursor DC make up the compartment\nC_LIO_LIDistinguish myeloid cell compartment from other cell spaces, e.g. the NK cell space\nC_LIO_LIProviding a generalizable method for building consensus maps for the life sciences\nC_LI

immunology↗

bioRxiv2019

Memory-driven computing accelerates genomic data processing

Next generation sequencing (NGS) is the driving force behind precision medicine and is revolutionizing most, if not all, areas of the life sciences. Particularly when targeting the major common diseases, an exponential growth of NGS data is foreseen for the next decades. This enormous increase of NGS data and the need to process the data quickly for real-world applications requires to rethink our current compute infrastructures. Here we provide evidence that memory-driven computing (MDC), a novel memory-centric hardware architecture, is an attractive alternative to current processor-centric compute infrastructures. To illustrate how MDC can change NGS data handling, we used RNA-seq assembly and pseudoalignment followed by quantification as two first examples. Adapting transcriptome assembly pipelines for MDC reduced compute time by 5.9-fold for the first step (SAMtools). Even more impressive, pseudoalignment by near-optimal probabilistic RNA-seq quantification (kallisto) was accelerated by more than two orders of magnitude with identical accuracy and indicated 66% reduced energy consumption. One billion RNA-seq reads were processed in just 92 seconds. Clearly, MDC simultaneously reduces data processing time and energy consumption. Together with the MDC-inherent solutions for local data privacy, a new compute model can be projected pushing large scale NGS data processing and primary data analytics closer to the edge by directly combining high-end sequencers with local MDC, thereby also reducing movement of large raw data to central cloud storage. We further envision that other data-rich areas will similarly benefit from this new memory-centric compute architecture.

bioinformatics↗

bioRxiv2018

Infectious Entry of Merkel Cell Polyomavirus

Merkel Cell Polyomavirus (MCPyV) is a small, non-enveloped tumor virus associated with an aggressive form of skin cancer, the Merkel cell carcinoma (MCC). MCPyV infections are highly prevalent in the human population with MCPyV virions being continuously shed from human skin. However, the precise host cell tropism(s) of MCPyV remains unclear: MCPyV is able to replicate within a subset of dermal fibroblasts, but MCPyV DNA has also been detected in a variety of other tissues. However, MCPyV appears different from other polyomaviruses as it requires sulfated polysaccharides such as heparan sulfates and/or chondroitin sulfates for initial attachment. Like other polyomaviruses, MCPyV engages sialic acid as a (co-receptor). To explore the infectious entry process of MCPyV, we analyzed the cell biological determinants of MCPyV entry into A549 cells, a highly transducible lung carcinoma cell line, in comparison to well-studied simian virus 40 and a number of other viruses. Our results indicate that MCPyV enters cells via caveolar/lipid raft-mediated endocytosis but not macropinocytosis, clathrin-mediated endocytosis or glycosphingolipid-enriched carriers. The viruses internalized in small endocytic pits that led the virus to endosomes and from there to the endoplasmic reticulum (ER). Similar to other polyomaviruses, trafficking required microtubular transport, acidification of endosomes, and a functional redox environment. To our surprise, the virus was found to acquire a membrane envelope within endosomes, a phenomenon not reported for other viruses. Only minor amounts of viruses reached the ER, while the majority was retained in endosomal compartments suggesting that endosome-to-ER trafficking is a bottleneck during infectious entry.\n\nImportanceMCPyV is the first polyomavirus directly implicated in the development of an aggressive human cancer, the Merkel Cell Carcinoma (MCC). Although MCPyV is constantly shed from healthy skin, MCC incidence increases among aging and immunocompromised individuals. To date, the events connecting initial MCPyV infection and subsequent transformation still remain elusive. MCPyV differs from other known polyomaviruses concerning its cell tropism, entry receptor requirements, and infection kinetics. In this study, we examined the cellular requirements for endocytic entry as well as the subcellular localization of incoming virus particles. A thorough understanding of the determinants of the infectious entry pathway and the specific biological niche will benefit prevention of virus-derived cancers such as MCC.

microbiology↗

bioRxiv2018

3-D navigation: A core driver of brain plasticity in video game interventions

Recent evidence has repeatedly shown that 3D platform video game training leads to substantial brain structural plasticity in hippocampus, prefrontal cortex and cerebellum. However, a great disadvantage of using complex video game interventions is the difficulty to attribute the observed effects to specific game mechanics.\n\nIn order to address this caveat, we conducted a longitudinal training study in which 40 participants were randomly assigned to train with a 3D platformer game or a 2D platformer game. The main difference between the two games lies within their affordance for spatial exploration. After a training phase of two months, we observed extended brain structural increases in the 3D in comparison to the 2D condition in bilateral prefrontal areas, hippocampus/ entorhinal cortex as well as precuneus and the temporal lobe. In the reverse contrast an increase in bilateral caudate nucleus was observed.\n\nThe results demonstrate a crucial role of 3D spatial navigation for widespread brain plasticity effects within a two-months training setup. Given the vast complexity of video games, spatial navigation seems to play an outstanding role in structural plasticity. Since prefrontal, temporal and hippocampal volume deficits are prominent risk factors for several psychiatric disorders, daily navigation habits (outdoor movement, using GPS devices etc.) have to be considered in future mental disorders prevention research.

neuroscience↗

bioRxiv2018

Influence of nutritional tyrosine on cognition and functional connectivity in healthy old humans

Tyrosine is precursor for monoamine neurotransmitters such as dopamine (DA), which is one of the key neurotransmitters in the frontostriatal network and of crucial relevance for mental disorders. Recent research reported that high dose tyrosine application resulted in increased brain DA synthesis, which is consistent with the observation of positive associations between daily tyrosine intake and cognitive test performance. In the present study, we investigated the associations between working memory (WM) dependent tasks and self-reported nutritional tyrosine intake within a large group of healthy elderly humans (286 subjects) by additionally including brain functional data. We observed a negative correlation between tyrosine intake and resting-state functional connectivity (rsFC) between the striatum (putamen) and the prefrontal cortex. That is to say, we found higher rsFC in individuals consuming less tyrosine per day. At the same time, this increased rsFC or hyperconnectivity was associated with lower WM performance. These findings suggest that lower or insufficient supply of tyrosine might result in dysfunctional connectivity between striatal and frontal regions leading to lower WM capacity in healthy elderly humans.

neuroscience↗

bioRxiv2018

Diagnostic value of blood gene expression-based classifiers as exemplified for acute myeloid leukemia

ABSTRACTAcute Myeloid Leukemia (AML) is a severe, mostly fatal hematopoietic malignancy. Despite nearly two decades of promising results using gene expression profiling, international recommendations for diagnosis and differential diagnosis of AML remain based on classical approaches including assessment of morphology, immunophenotyping, cytochemistry, and cytogenetics. Concerns about the translation of whole transcriptome profiling include the robustness of derived predictors when taking into account factors such as study- and site-specific effects and whether achievable levels of accuracy are sufficient for practical use. In the present study, we sought to shed light on these issues via a large-scale analysis using machine learning methods applied to a total of 12,029 samples from 105 different studies. Taking advantage of the breadth of data and the now much improved understanding of high-dimensional modeling, we show that AML can be predicted with high accuracy. High-dimensional approaches - in which multivariate signatures are learned directly from genome-wide data with no prior biological knowledge - are highly effective and robust. We explore also the relationship between predictive signatures, differential expression and known AML-related genes. Taken together, our results support the notion that transcriptome assessment could be used as part of an integrated genomic approach in cancer diagnosis and treatment to be implemented early on for diagnosis and differential diagnosis of AML.\n\nOne Sentence SummaryBlood gene expression data and machine learning were used to develop robust and accurate classifiers for diagnosis and differential diagnosis of acute myeloid leukemia based on analysis of more than 12,000 samples derived from more than 100 individual studies

genomics↗

bioRxiv2018

Association Between Rare Copy Number Variation and Response to Social Skills Training in Autism Spectrum Disorder

Challenges in social communication and interaction are core symptoms in autism spectrum disorder (ASD) for which social skills group training (SSGT) is a commonly used intervention. SSGT has shown modest but heterogeneous effects in clinical trials, and therefore identification of effect moderators could enable more precise intervention decisions. One of the major genetic risk factors in ASD are rare copy number variation (CNV). However, limited information exists whether rare CNVs profiles can be used to aid in intervention decisions. Therefore, we conducted the first study to date analyzing rare CNVs as genetic moderators in the outcome of SSGT in ASD. For this, we analyzed rare genic CNV carrier status of 207 children of which 105 received SSGT and 102 standard care as part of a recent randomized clinical trial for 12-weeks SSGT. We used mixed linear models to assess the association of being a CNV carrier, grouped by the effect and size of the CNVs and the primary response to SSGT, the parent-report Social Responsiveness Scale (SRS) measured at post-intervention and 3-months follow-up. Additionally, we analyzed the secondary outcome assessments included parent-rated adaptive behaviors (ABAS-II) and trainer-rated clinical global impression (CGI). We show that being a carrier of any size rare genic CNV did not impact on the SSGT outcome. However, when stratifying the groups by size of the CNVs, we identified that carriers of large CNVs (>500 kb) showed inferior SRS outcomes at post-intervention ({beta} = 15.35, 95% CI 2.86-27.84, P=0.017) and follow-up ({beta} = 14.19, 95% CI 1.68-26.70, P=0.028). Similar results were shown for the parent-rated secondary outcome. In contrast, the carriers of small CNVs had better outcome at post-intervention ({beta} = -1.20, 95 % CI - 2.0 - -0.4 P = 0.003) but not at follow-up for the trainer-rated secondary outcome CGI. These results remained when we tested the specificity of the effect by including the standard care group and adjusting for IQ levels. While our study suggests that being a carrier of any size rare genic CNV did not impact the outcome, it provides preliminary evidence that carriers of high-risk CNVs might not benefit on SSGT as much as non-carriers. Our results indicate that genetic information eventually might help guide personalized intervention planning in ASD. We additionally highlight that more research is needed to understand the intervention needs of autistic individuals with specified molecular alterations.

genetics↗

bioRxiv2018

FASTGenomics: An analytical ecosystem for single-cell RNA sequencing data

Recent technological advances enable genomics of individual cells, the building blocks of all living organisms. Single cell data characteristics differ from those of bulk data, which led to a plethora of new analytical strategies. However, solutions are only useful for experts and currently, there are no widely accepted gold standards for single cell data analysis. To meet the requirements of analytical flexibility, ease of use and data security, we developed FASTGenomics (https://fastgenomics.org) as a powerful, efficient, versatile, robust, safe and intuitive analytical ecosystem for single-cell transcriptomics.

bioinformatics↗

bioRxiv2016

Resting-state fMRI correlations: from link-wiseunreliability to whole brain stability

The functional architecture of spontaneous BOLD fluctuations has been characterized in detail by numerous studies, demonstrating its potential relevance as a biomarker. However, the systematic investigation of its consistency is still in its infancy. Here, we analyze both the within- and between-subject variability as well as the test-retest reliability of resting-state functional connectivity (FC) estimates in a unique data set comprising multiple fMRI scans (42) from 5 subjects, and 50 single scans from 50 subjects. To this aim we adopted a statistical framework enabling us to disentangle the contribution of different sources of variability and their dependence on scan duration, and showed that the low reliability of single links can be largely improved using multiple scans per subject. Moreover, we show that practically all observed inter-region variability (at the link-level) is not significant and due to the statistical uncertainty of the estimator itself rather than to genuine variability among areas. Finally, we use the proposed statistical framework to demonstrate that, despite the poor consistency of single links, the information carried by the whole-brain spontaneous correlation structure is indeed robust, and can in fact be used as a functional fingerprint.

neuroscience↗