Biology subjects

Maier, R.

Publications and source records attributed to Maier, R..

11 recordsLinked to original sources

bioRxiv2026

Circulating extracellular vesicles display immunotherapeutic targets and complement circulating tumor DNA in high-risk neuroblastoma

Extracellular vesicles (EVs) offer a minimally invasive window into tumor biology through surface molecules reflecting their cellular origin. Here, we investigated whether neuroblastoma-derived EVs retain tumor-associated surface markers and provide complementary information to established biomarkers in children with neuroblastoma. EVs from neuroblastoma cell lines were characterized using orthogonal biochemical, morphological and biophysical approaches, followed by analysis of GD2, L1CAM and NCAM1 surface expression. EV-associated markers were subsequently evaluated in blood plasma-derived EVs from children with neuroblastoma and pediatric controls and compared with clinical and circulating cell-free DNA (cfDNA) parameters. Neuroblastoma EVs displayed GD2, L1CAM and NCAM1 in patterns reflecting donor-cell surface expression, supported by a positive correlation between cellular and EV marker abundance (Spearman {rho}=0.74, P<0.0001). Genetic disruption of GD2 biosynthesis resulted in corresponding loss of EV-associated GD2, further supporting its cellular origin. In plasma, GD2-, L1CAM- and NCAM1-positive EVs were enriched in patients with high-risk neuroblastoma and correlated with LDH level, soft tissue disease burden (GD2, L1CAM) and cfDNA concentration (GD2, NCAM1). Longitudinal analyses demonstrated dynamic and partially discordant changes in EV- and cfDNA-markers. These findings identify tumor-associated EV surface phenotypes as complementary circulating biomarkers and support their further evaluation for minimally invasive monitoring of neuroblastoma evolution.

cancer biology↗

bioRxiv2025

The yeast peroxisomal proteome at absolute quantitative scale

Peroxisomes are dynamic organelles vital for lipid metabolism and redox homeostasis. In Saccharomyces cerevisiae, the expression of peroxisomal proteins is tightly regulated in response to metabolic conditions. Here, we provide the first absolute quantification of the yeast peroxisomal proteome under peroxisome-inducing (oleate) and fermentative (glucose) conditions using a label-free mass spectrometry approach. We determined protein copy numbers for [~]4,500 proteins, including 99 peroxisomal and peroxisome-associated proteins. Our data reveal that the peroxisomal proteome is [~]3-fold higher abundant in oleate-grown cells, constituting 2.8% of the total proteome (corresponding to 2.01 x 106 protein copies) compared to 0.8% (6.67 x 105 protein copies) in glucose, reflecting the necessity for peroxisomal functions such as fatty acid beta-oxidation. Enzymes of the beta-oxidation and glyoxylate cycle showed up to >500-fold higher abundance in oleate. In contrast, core components of the peroxisomal protein import machinery (e.g., Pex5, Pex14) exhibited only moderate changes ([~]2- to 8-fold). In addition to metabolic enzymes and components of the peroxisomal protein import pathways, we provide copy number data for proteins involved in cellular stress response, peroxisome proliferation, division and organization, peroxisome-associated membrane contact sites, and metabolite transporter. Taken together, our dataset offers a quantitative framework of peroxisomal remodeling under different metabolic conditions and highlights the organelles adaptive flexibility, providing a valuable resource for future studies on peroxisome biology.

cell biology↗

bioRxiv2023

Testing Times: Challenges in Disentangling Admixture Histories in Recent and Complex Demographies

Paleogenomics has expanded our knowledge of human evolutionary history. Since the 2020s, the study of ancient DNA has increased its focus on reconstructing the recent past. However, the accuracy of paleogenomic methods in answering questions of historical and archaeological importance amidst the increased demographic complexity and decreased genetic differentiation within the historical period remains an open question. We used two simulation approaches to evaluate the limitations and behavior of commonly used methods, qpAdm and the f3-statistic, on admixture inference. The first is based on branch-length data simulated from four simple demographic models of varying complexities and configurations. The second, an analysis of Eurasian history composed of 59 populations using whole-genome data modified with ancient DNA conditions such as SNP ascertainment, data missingness, and pseudo-haploidization. We show that under conditions resembling historical populations, qpAdm can identify a small candidate set of true sources and populations closely related to them. However, in typical ancient DNA conditions, qpAdm is unable to further distinguish between them, limiting its utility for resolving fine-scaled hypotheses. Notably, we find that complex gene-flow histories generally lead to improvements in the performance of qpAdm and observe no bias in the estimation of admixture weights. We offer a heuristic for admixture inference that incorporates admixture weight estimate and P-values of qpAdm models, and f3-statistics to enhance the power to distinguish between multiple plausible candidates. Finally, we highlight the future potential of qpAdm through whole-genome branch-length f2-statistics, demonstrating the improved demographic inference that could be achieved with advancements in f-statistic estimations.

genomics↗

bioRxiv2023

Postglacial genomes from foragers across Northern Eurasia reveal prehistoric mobility associated with the spread of the Uralic and Yeniseian languages

The North Eurasian forest and forest-steppe zones have sustained millennia of sociocultural connections among northern peoples. We present genome-wide ancient DNA data for 181 individuals from this region spanning the Mesolithic, Neolithic and Bronze Age. We find that Early to Mid-Holocene hunter-gatherer populations from across the southern forest and forest-steppes of Northern Eurasia can be characterized by a continuous gradient of ancestry that remained stable for millennia, ranging from fully West Eurasian in the Baltic region to fully East Asian in the Transbaikal region. In contrast, cotemporaneous groups in far Northeast Siberia were genetically distinct, retaining high levels of continuity from a population that was the primary source of ancestry for Native Americans. By the mid-Holocene, admixture between this early Northeastern Siberian population and groups from Inland East Asia and the Amur River Basin produced two distinctive populations in eastern Siberia that played an important role in the genetic formation of later people. Ancestry from the first population, Cis-Baikal Late Neolithic-Bronze Age (Cisbaikal_LNBA), is found substantially only among Yeniseian-speaking groups and those known to have admixed with them. Ancestry from the second, Yakutian Late Neolithic-Bronze Age (Yakutia_LNBA), is strongly associated with present-day Uralic speakers. We show how Yakutia_LNBA ancestry spread from an east Siberian origin [~]4.5kya, along with subclades of Y-chromosome haplogroup N occurring at high frequencies among present-day Uralic speakers, into Western and Central Siberia in communities associated with Seima-Turbino metallurgy: a suite of advanced bronze casting techniques that spread explosively across an enormous region of Northern Eurasia [~]4.0kya. However, the ancestry of the 16 Seima-Turbino-period individuals--the first reported from sites with this metallurgy--was otherwise extraordinarily diverse, with partial descent from Indo-Iranian-speaking pastoralists and multiple hunter-gatherer populations from widely separated regions of Eurasia. Our results provide support for theories suggesting that early Uralic speakers at the beginning of their westward dispersal where involved in the expansion of Seima-Turbino metallurgical traditions, and suggests that both cultural transmission and migration were important in the spread of Seima-Turbino material culture.

genomics↗

bioRxiv2023

Modeling of African population history using f-statistics can be highly biased and is not addressed by previously suggested SNP ascertainment schemes

f-statistics have emerged as a first line of analysis for making inferences about demographic history from genome-wide data. These statistics can provide strong evidence for either admixture or cladality, which can be robust to substantial rates of errors or missing data. f-statistics are guaranteed to be unbiased under "SNP ascertainment" (analyzing non-randomly chosen subsets of single nucleotide polymorphisms) only if it relies on a population that is an outgroup for all groups analyzed. However, ascertainment on a true outgroup that is not co-analyzed with other populations is often impractical and uncommon in the literature. In this study focused on practical rather than theoretical aspects of SNP ascertainment, we show that many non-outgroup ascertainment schemes lead to false rejection of true demographic histories, as well as to failure to reject incorrect models. But the bias introduced by common ascertainments such as the 1240K panel is mostly limited to situations when more than one sub-Saharan African and/or archaic human groups (Neanderthals and Denisovans) or non-human outgroups are co-modelled, for example, f4-statistics involving one non-African group, two African groups, and one archaic group. Analyzing panels of SNPs polymorphic in archaic humans, which has been suggested as a solution for the ascertainment problem, cannot fix all these problems since for some classes of f-statistics it is not a clean outgroup ascertainment, and in other cases it demonstrates relatively low power to reject incorrect demographic models since it provides a relatively small number of variants common in anatomically modern humans. And due to the paucity of high-coverage archaic genomes, archaic individuals used for ascertainment often act as sole representatives of the respective groups in an analysis, and we show that this approach is highly problematic. By carrying out large numbers of simulations of diverse demographic histories, we find that bias in inferences based on f-statistics introduced by non-outgroup ascertainment can be minimized if the derived allele frequency spectrum in the population used for ascertainment approaches the spectrum that existed at the root of all groups being co-analyzed. Ascertaining on sites with variants common in a diverse group of African individuals provides a good approximation to such a set of SNPs, addressing the great majority of biases and also retaining high statistical power for studying population history. Such a "pan-African" ascertainment, although not completely problem-free, allows unbiased exploration of demographic models for the widest set of archaic and modern human populations, as compared to the other ascertainment schemes we explored.

genetics↗

bioRxiv2022

On the limits of fitting complex models of population history to genetic data

Our understanding of human population history in deep time has been assisted by fitting "admixture graphs" to data: models that specify the ordering of population splits and mixtures which is the only information needed to capture the patterns of allele frequency correlation among populations. Not needing to specify population size changes, split times, or whether admixture events were sudden or drawn out simplifies the space of models that need to be searched. However, the space of possible admixture graphs relating populations is vast and cannot be sampled fully, and thus most published studies have identified fitting admixture graphs through a manual process driven by prior hypotheses, leaving the vast majority of alternative models unexplored. Here, we develop a method for systematically searching the space of all admixture graphs that can incorporate non-genetic information in the form of topology constraints. We implement this findGraphs tool within a software package, ADMIXTOOLS 2, which is a reimplementation of the ADMIXTOOLS software with new features and large performance gains. We apply this methodology to identify alternative models to admixture graphs that played key roles in eight published studies and find that graphs modeling more than six populations and two or three admixture events are often not unique, with many alternative models fitting nominally or significantly better than the published one. Our results suggest that strong claims about population history from admixture graphs should only be made when all well-fitting and temporally plausible models share common topological features. Our re-evaluation of published data also provides insight into the population histories of humans, dogs, and horses, identifying features that are stable across the models we explored, as well as scenarios of populations relationships that differ in important ways from models that have been highlighted in the literature, that fit the allele frequency correlation data, and that are not obviously wrong.

evolutionary biology↗

bioRxiv2022

Validation of the first PGT-whole genome sequencing approach including mitochondrial variants

Whole Genome Sequencing (WGS) is used in healthcare and in the clinic, with the notable exception of preimplantation genetic testing (PGT). In PGT, only a few cells are available for sequencing, requiring DNA amplification which reduces data quality, sequence fidelity and sharply limits subsequent clinical impact. Here we demonstrate the first clinical validation of WGS on embryo biopsies using our lab development protocol, opening the door to broad use of WGS in fertility. We find that amplified DNA with comparable sensitivity and specificity to genomic DNA when performing whole genome sequencing assays. DNA amplification on cell lines and donated human embryos had an amplification success rate of >99.9% and 98.2% respectively and accuracy on both was >99.9% on aneuploidy status. GIAB samples (Genome in the Bottle reference NA12878) showed that our amplified DNA was broadly comparable to genomic DNA (99.99% accuracy, 99.99% specificity, 98.0% sensitivity and 98.1% precision). Using our assay, we were able to call variants, detect mitochondrial heteroplasmy, perform high precision screening without access to parental genomes, detect compound heterozygous variants, and score microdups/dels and uniparental disomies (to reduce risk of diseases such as DiGeorge syndrome and Prader-Willi syndrome). Our clinical study suggests that the full spectrum of traditional clinical genome bioinformatics, so far reserved to large samples, can now be performed on embryos before implantation.

genomics↗

bioRxiv2021

Regulating peroxisome-ER contacts via the ACBD5-VAPB tether by FFAT motif phosphorylation and GSK3β

Peroxisomes and the endoplasmic reticulum (ER) cooperate in cellular lipid metabolism. They form membrane contacts through interaction of the peroxisomal membrane protein ACBD5 [acyl-coenzyme A-binding domain protein 5] and the ER-resident protein VAPB [vesicle-associated membrane protein-associated protein B]. ACBD5 binds to the major sperm protein domain of VAPB via its FFAT-like [two phenylalanines (FF) in an acidic tract] motif. However, molecular mechanisms, which regulate formation of these membrane contact sites, are unknown. Here, we reveal that peroxisome-ER associations via the ACBD5-VAPB tether are regulated by phosphorylation. We show that ACBD5-VAPB binding is phosphatase-sensitive and identify phosphorylation sites in the flanking regions and core of the FFAT-like motif, which alter interaction with VAPB and thus, peroxisome-ER contact sites differently. Moreover, we demonstrate that GSK3{beta} [glycogen synthase kinase-3 beta] regulates this interaction. Our findings reveal for the first time a molecular mechanism for the regulation of peroxisome-ER contacts in mammalian cells and expand the current model of FFAT motifs and VAP interaction. SUMMARYKors et al. reveal that peroxisome-ER associations via the ACBD5-VAPB tether are regulated by phosphorylation and GSK3{beta} in mammalian cells. Phosphorylation sites in the FFAT-like motif of ACBD5 affect the binding to VAPB and thus, peroxisome-ER contact sites, differently.

cell biology↗

bioRxiv2020

The genomic formation of First American ancestors in East and Northeast Asia

Upward Sun River 1, an individual from a unique burial of the Denali tradition in Alaska (11500 calBP), is considered a type representative of Ancient Beringians who split from other First Americans 22000-18000 calBP in Beringia. Using a new admixture graph model-comparison approach resistant to overfitting, we show that Ancient Beringians do not form the deepest American lineage, but instead harbor ancestry from a lineage more closely related to northern North Americans than to southern North Americans. Ancient Beringians also harbor substantial admixture from a lineage that did not contribute to other Native Americans: Amur River Basin populations represented by a newly reported site in northeastern China. Relying on these results, we propose a new model for the genomic formation of First American ancestors in Asia. One Sentence SummaryAncient Beringians do not form the deepest American lineage, but harbor admixture from Amur River Basin populations.

genetics↗

bioRxiv2020

Pex14p phosphorylation modulates import of citrate synthase 2 into peroxisomes in Saccharomyces cerevisiae

The peroxisomal biogenesis factor Pex14p is an essential component of the peroxisomal matrix protein import machinery. Together with Pex13p and Pex17p, it is part of the membrane-associated peroxisomal docking complex in yeast, facilitating the binding of cargo-loaded receptor proteins for translocation of cargo proteins into the peroxisome. Furthermore, Pex14p is part of peroxisomal import pores. The central role of Pex14p in peroxisomal matrix protein import processes renders it an obvious target for regulatory mechanisms such as protein phosphorylation. To explore this possibility, we examined the state of Pex14p phosphorylation in Saccharomyces cerevisiae. Phos-tag-SDS-PAGE of Pex14p affinity-purified from solubilized membranes revealed Pex14p as multi-phosphorylated protein. Using mass spectrometry, we identified 16 phosphorylation sites, with phosphorylation hot spots located in the N- and C-terminal regions of Pex14p. Analysis of phosphomimicking and nonphosphorylatable variants of Pex14p revealed a decreased import of GFP carrying a peroxisomal targeting signal type 1, indicating a functional relevance of Pex14p phosphorylation in peroxisomal matrix protein import. We show that this effect can be ascribed to the phosphomimicking mutation at serine 266 of Pex14p (Pex14p-S266D). We further screened the subcellular distribution of 23 native GFP-tagged peroxisomal matrix proteins by high-content fluorescence microscopy. Only Cit2p, the peroxisomal isoform of citrate synthase, was affected in the Pex14p-S266D mutant, showing increased cytosolic localization. Cit2p is part of the glyoxylate cycle, which is required for the production of essential carbohydrates when yeast is grown on non-fermentable carbon sources. Pex14p-S266 phosphosite mutants showed reversed growth phenotypes on oleic acid and ethanol with acetyl-CoA formed in peroxisomes and the cytosol, respectively. Our data point to the control of the peroxisomal import of Cit2p via the state of Pex14p phosphorylation at S266, which may help S. cerevisiae cells to rapidly adjust their carbohydrate metabolism according to the nutritional conditions.Competing Interest StatementThe authors have declared no competing interest.AbbreviationsPTSperoxisomal targeting signal;LC-MSliquid chromatography-mass spectrometry;TEVtobacco etch virus;TPATEV protease cleavage site-Protein AView Full Text

cell biology↗

bioRxiv2017

Causal associations between risk factors and common diseases inferred from GWAS summary data

Health risk factors such as body mass index (BMI), serum cholesterol and blood pressure are associated with many common diseases. It often remains unclear whether the risk factors are cause or consequence of disease, or whether the associations are the result of confounding. Genetic methods are useful to infer causality because genetic variants are present from birth and therefore unlikely to be confounded with environmental factors. We develop and apply a method (GSMR) that performs a multi-SNP Mendelian Randomization analysis using summary-level data from large genome-wide association studies (sample sizes of up to 405,072) to test the causal associations of BMI, waist-to-hip ratio, serum cholesterols, blood pressures, height and years of schooling (EduYears) with a range of common diseases. We identify a number of causal associations including a protective effect of LDL-cholesterol against type-2 diabetes (T2D) that might explain the side effects of statins on T2D, a protective effect of EduYears against Alzheimers disease, and bidirectional associations with opposite effects (e.g. higher BMI increases the risk of T2D but the effect T2D of BMI is negative). HDL-cholesterol has a significant risk effect on age-related macular degeneration, and the effect size remains significant accounting for the other risk factors. Our study develops powerful tools to integrate summary data from large studies to infer causality, and provides important candidates to be prioritized for further studies in medical research and for drug discovery.

genetics↗