Biology subjects

Schiller, J.

Publications and source records attributed to Schiller, J..

At least 19 recordsLinked to original sources

bioRxiv2026

A global genomic survey of prokaryotic carbon fixation reveals an oxygen-tolerant rTCA cycle in the surface ocean

Autotrophic carbon fixation, the conversion of inorganic carbon into biomass, underpins life on Earth. Prokaryotes can carry out this process via at least seven biochemically distinct pathways, yet the phylogenetic and environmental distribution of most remains poorly resolved. Screening approximately 40 billion genes from reference genomes, metagenome-assembled genomes (MAGs) and unbinned metagenomic contigs, we provide a global assessment of the phylogeny and ecophysiology of prokaryotic autotrophs. Most pathway marker genes occurred in unbinned contigs and low-quality MAGs, representing phylogenetically distinct lineages absent from isolate genomes and quality filtered MAGs. Established autotrophs accounted for the large majority of pathway detections in quality filtered MAGs, largely recapitulating known biology from cultivated model organisms. Against this backdrop, the reductive TriCarboxylic Acid (rTCA) cycle, long considered restricted to anoxic environments, was detected in three phylogenetically distinct Campylobacterota lineages from oxygenated surface seawater, suggesting a previously unrecognized and unexpected niche for this pathway. We show that all three MAGs share an enzyme variant, previously described in other oxygen-tolerant lineages, that likely underlies their presence in the oxygenated surface ocean. Read mapping across global ocean metagenomes indicates that the organisms carrying it could be far more widespread than the scarcity of recovered MAGs alone would suggest. Together, these findings illustrate that the current view of global autotrophic carbon fixation is largely shaped by what genome-resolved methods can readily recover, while the true phylogenetic and ecological distribution of autotrophic carbon fixation appears to be much broader.

microbiology↗

bioRxiv2026

Planetary structure and drivers of diazotroph communities reveal key reservoirs of nitrogen-fixation potential

Biological nitrogen fixation sustains productivity across Earths ecosystems, yet the diversity, distribution and ecological drivers of nitrogen-fixing prokaryotes (diazotrophs) remain incompletely resolved. Here we screened approximately 40 billion genes to generate a catalogue of 21,157 diazotroph genomes. Using this catalogue, we quantified diazotroph diversity and abundance across 9,163 metagenomes spanning diverse environments. Diazotrophy was distributed across the prokaryotic tree of life, but both gene diversity and metagenomic abundance were dominated by heterotrophic lineages. Freshwater and sedimentary ecosystems emerged as major reservoirs of nitrogen-fixation potential beyond the environments that have historically anchored the field. Diazotroph-rich assemblages were associated with nitrogen and phosphorus limitation together with carbohydrate-rich metabolic regimes, revealing distinct nutrient and energy niches for cyanobacterial and heterotrophic diazotrophs. Together, this framework unifies disparate views of diazotroph diversity, abundance and ecology, providing a foundation for improved prediction of biological nitrogen fixation across Earths ecosystems.

microbiology↗

bioRxiv2026

Genotype and farm effects on yield and morphology reveal potential for breeding and site selection for sugar kelp

Seaweed cultivation has recently gained increased attention in North-West Europe as a sustainable source of biomass for biobased products. However, yields need to increase to make the seaweed sector economically viable. To achieve this, higher yielding varieties can be bred but this requires variation for yield and yield-related traits among genotypes. To reliably select high-yielding genotypes, an understanding is required of how both within-farm and between-farm environmental differences affect phenotypes and how to identify simple and reliable proxies for yield. In this study we evaluated growth of nine Saccharina latissima genotypes on two farms, 12 km apart, within the same season. We observed a threefold difference in yield among genotypes, demonstrating the potential for improvement through selection and breeding. Blade thickness and blade size-related traits were strongly correlated with yield, highlighting their potential to serve as rapid and non-destructive proxies for yield, thereby accelerating selection. Furthermore, we demonstrated the importance of adequate replication in farm trials to improve genotype performance estimation by correcting for within-farm spatial variation. Moreover, phenotypic variation was most explained by the genotype and environment, highlighting the importance of both genotype and site selection. Although genotype by environment interactions (GxE) were significant, its contributions were small, indicating stable genotype ranking across farms. Overall, these results are promising for breeding improved S. latissima as it indicates that genotype performance is consistent across close by locations and that local S. latissima populations harbour substantial phenotypic variation that can be used to breed for increased yield. Highlights- Local genetic resources harbour substantial variation in yield and morphology for breeding. - Minor GxE allows for breeding across farms. - Blade thickness and blade size related traits are good predictors of yield. - Correction for on-farm spatial variation improves genotype performance estimation.

genetics↗

bioRxiv2026

Coenzyme A is bound to tafazzin - a paradigm change for transacylation

Cardiolipin (CL) is the signature phospholipid of mitochondria. In an obligatory remodeling process, the mitochondrial transacylase tafazzin exchanges its acyl chains to create the highly unsaturated, mature form of CL. Tafazzin dysfunction causes Barth syndrome, a severe multisystem disorder. We determined the structure of tafazzin at a resolution of 2.2 [A] using cryo-electron microscopy (cryo-EM). Until now, the tafazzin reaction has been thought to be independent of coenzyme A (CoA). However, our structure clearly shows an acyl-CoA molecule bound to tafazzin. To decipher how substrates bind to the active site, we combine cryo-EM with structure predictions and molecular dynamics simulations, giving us detailed insights into a transacylation mechanism mediated by CoA. By providing molecular explanations of tafazzin dysfunction caused by pathogenic mutations, we gain a molecular understanding of Barth syndrome.

biochemistry↗

bioRxiv2025

Clathrin adaptors drive phase separation in endocytosis and trafficking

Liquid-liquid phase separation (LLPS) underlies the formation of biomolecular condensates that organize cellular processes, including endocytosis and membrane trafficking. Although LLPS has been implicated in clathrin-mediated pathways, the specific contribution of adaptor proteins to condensate formation and function remains unclear. Here we show that two yeast adaptors, Ent5 and Sla2, undergo LLPS in vitro and that this property correlates with their distinct roles in membrane trafficking and condensate recruitment in vivo. Ent5 condensation is driven by a dynamic helix within its disordered region that acts as a molecular "sticker." Deletion of this helix disrupts membrane-associated condensation and leads to altered cargo trafficking dynamics in vivo, with Ent5-dependent transport events becoming delayed. In contrast, Sla2 behaves both as a driver and as a client of LLPS, with its coiled-coil (CC) region mediating condensation. Together, these findings reveal that endocytic adaptors can promote condensate formation through distinct structural features, thereby coupling clathrin binding and membrane association through phase separation.

biophysics↗

bioRxiv2025

Variations in the latitudinal diversity gradients of the ocean microbiome

Latitudinal diversity gradients (LDGs), typically declining from equator to poles, are a pervasive macroecological pattern, yet their generality and drivers in the ocean microbiome remain widely unresolved. We integrated global-scale metagenomic data with habitat modeling to study marine microbial LDGs across seasons and depths. Surface mixed layer microbiomes exhibited diversity peaks at (sub)tropical latitudes and a poleward decline, whereas mesopelagic communities (200-1,000 m) showed no latitudinal diversity structuring. Taxonomic resolution revealed that the mixed layer LDG was underpinned by Alphaproteobacteria and Cyanobacteriia, while other taxa exhibited distinct or contrasting LDGs. Diversity structuring also varied by seasons and regions, governed by temperature and nutrient availability. Together, these findings highlight that within the ocean microbiome, LDGs are not universal, but lineage-specific ecological strategies and responses to environmental gradients. Our study provides fundamental insights into the structuring of ocean microbiome diversity and lays the foundation for predicting responses to environmental change.

microbiology↗

bioRxiv2025

Explainable AI shows climate impacts on wheat yields: insights from 30 years of field data.

Wheat (Triticum aestivum L.) is amongst the worlds most important staple crops and primary food source for an estimated 35% of the global population. Climate impacts have caused global yield stagnation and quantifying the climatic variables influencing wheat yield is critical to anticipate yield losses and design climate-resilient agricultural strategies. Here, we use a unique 30-year dataset on winter wheat variety trials in six sites across Switzerland, explainable artificial intelligence (XAI) and interpretable machine learning (IML) methods (i.e., decision trees and gradient boosting models combined with post hoc tests) to elucidate climate drivers on wheat yields. We showed based on 405 varieties and over 10,000 observations, that climatic variables such as cumulative solar radiation, precipitation from sowing to harvest and genotype makeup are significant yield drivers. Partial dependence plots and variable interaction analyses revealed, for example, a yield plateau above cumulative solar radiation levels of [~]3000 MJ m-{superscript 2}, suggesting complex genotype-by-environment interactions. These findings suggest that XAI adds important biological interpretability to predictive performance, and reveals the mechanisms how climate affects wheat yields. Our methodological framework and results can inform breeding activities, agronomic management, and adaptation strategies under climate change across environmental conditions in Switzerland and with global ramifications.

plant biology↗

bioRxiv2025

Epigenetic inheritance of complex learning abilities in the mammalian brain

For several decades, the question of whether cognitive and learning capacities can be inherited through non-genetic mechanisms has been the subject of ongoing debate. Here, we provide the first evidence of transgenerational inheritance of enhanced ability to learn complex tasks in the mammalian rodent brain. These inherited learning enhancements are not limited to specific stimuli, sensory modalities, or learning paradigms. Using behavioral, cellular biophysical, methylomics, genetics and molecular methods, we find that the inherited epigenetic modifications reflect an enhanced neuronal learning state, driven by increased intrinsic neuronal excitability in most pyramidal neurons in the relevant neuronal networks. This enhancement is mediated by persistent downregulation of the muscarinic M-current and is associated with widespread changes in DNA methylation, notably within coding genes associated with the M-current, the Kv7 pathway, in the hippocampi of trained F0 rats, as well as in non-coding RNAs in their sperm samples. Remarkably, a significant portion of these DNA methylation changes were also observed in the hippocampi of their untrained F1 offspring. These findings suggest that complex learning abilities can be inherited in the mammalian brain, as the offspring of trained rodents are born with the biophysical modifications that enable them to become super-learners, the exact change that occurs in their parents brains only after the rule learning.

neuroscience↗

bioRxiv2025

Metalog: curated and harmonised contextual data for global metagenomics samples

Metagenomic sequencing enables the in-depth study of microbes and their functions in humans, animals and the environment. While sequencing data is deposited in public databases, the associated contextual data is often not complete and needs to be retrieved from primary publications. This lack of access to sample-level metadata like clinical data or in situ observations impedes cross-study comparisons and meta-analyses. We therefore created the Metalog database, a repository of manually curated metadata for metagenomics samples across the globe. It contains 73,082 samples from humans (including 58,506 of the gut microbiome), 10,703 animal samples, 5,146 ocean water samples, and 21,802 samples from other environmental habitats such as soil, sediment, or fresh water. Samples have been consistently annotated for a set of habitat-specific core features, such as demographics, disease status and medication for humans, host species and captivity status for animals, and filter sizes and salinity for marine samples. Additionally, all original metadata is provided in tabular form, simplifying focused studies e.g. into nutrient concentrations. Pre-computed taxonomic profiles facilitate rapid data exploration, while links to the SPIRE database enable genome-based analyses. The database is freely available for browsing and download at https://metalog.embl.de/.

microbiology↗

bioRxiv2025

BIOPHYSICAL MECHANISMS UNDERLYING THE GENERATION AND MAINTENANCE OF RULE-LEARNING ENGRAM

Training rodents in a particularly difficult olfactory-discrimination task results with acquisition of high skill to perform the task superbly, termed rule-learning. We show that rule-learning occurs abruptly, in a "light bulb moment". Using whole-cell patch-clamp recordings in the piriform cortex of Fos2A-iCreER/TRAP2 mice, we targeted activated neurons, expressing immediate early genes (IEG). From the onset of training, IEG-positive neurons from trained animals display enhanced intrinsic excitability. Subsequently, synaptic excitation and inhibition is enhanced in these neurons, in a coordinated, cell-wide process. In parallel, the density of IEG-expressing neurons sharply declines. Double labeling with TRAP and c-Fos reveals that nearly two-thirds of the rule-memory engram neurons were engaged from the beginning of training. Silencing TRAP-expressing neurons using DREADDs leads to a complete loss of rule memory. We propose that rule learning occurs at a discrete moment, and is developed through a gradual process that stabilizes the memory of the rule.

neuroscience↗

bioRxiv2025

Planetary microbiome structure and generalist-driven gene flow across disparate habitats

Microbes are ubiquitous on Earth, forming microbiomes that sustain macroscopic life and biogeochemical cycles. Microbial dispersion, driven by natural processes and human activities, interconnects microbiomes across habitats, yet most comparative studies focused on specific ecosystems. To study planetary microbiome structure, function, and inter-habitat interactions, we systematically integrated 85,604 public metagenomes spanning diverse habitats worldwide. Using species-based unsupervised clustering and parameter modeling, we delineated 40 habitat clusters and quantified their ecological similarity. Our framework identified key drivers shaping microbiome structure, such as ocean temperature and host lifestyle. Regardless of biogeography, microbiomes were structured primarily by host-associated or environmental conditions, also reflected in genomic and functional traits inferred from 2,065,975 genomes. Generalists emerged as vehicles thriving and facilitating gene flow across ecologically disparate habitat types, illustrated by generalist-mediated horizontal transfer of an antibiotic resistance island across human gut and wastewater, further dispersing to other habitats, exemplifying human impact on the planetary microbiome.

microbiology↗

bioRxiv2025

Dendritic computation for rule-based flexible categorization

A hallmark of intelligent behavior is the ability to flexibly respond to external sensory inputs based on dynamically changing rules. A central question is how neurons in the brain implement computations underlying intelligent behaviors. The neocortical pyramidal neurons use their elaborated dendritic arbors to segregate a plethora of inputs and dynamically integrate them--a process known as dendritic computation--which may play important roles in rule-dependent sensory processing. However, evidence directly linking dendritic computation with intelligent cognitive behaviors has been absent. Here we combine two-photon imaging and a rule-switching flexible categorization task in mice to show that a projectome-defined extratelencephalic (ET) cortical layer 5 (L5) neurons in the auditory cortex integrate dendritic rule information and somatic sensory input to enable rule-dependent flexible categorization. The apical dendrite and soma within the same ET neurons exhibit distinct compartmental representations for sensory and rule information, with the soma predominantly encoding sensory information and the dendrites representing inferred task rule. Simultaneous optogenetic dendritic inhibition and two-photon imaging revealed that dendritic rule coding is essential for somatic output of flexible categorization. Our findings indicate that nonlinear dendritic integration of rule and sensory information constitutes a neuronal computational mechanism underlying rule-switching flexible decision-making.

neuroscience↗

bioRxiv2024

Deep lipidomic profiling reveals sex dimorphism of lipid metabolism in fibro-calcific aortic valve disease

Fibro-calcific aortic valve disease (FCAVD) is the most common valvular heart disease manifesting in pathological fibro-calcific remodeling of the aortic valve (AV) leaflets, ultimately leading to aortic stenosis. Although lipid dysmetabolism is a driver of FCAVD pathogenesis, the molecular details of the AV lipidome remodeling upon fibrosis and calcification remain largely unknown. Here, we employed advanced lipidomics technologies for deep quantitative profiling of metabolic trajectories in human tricuspid and bicuspid AVs at different pathological stages. Specific extrinsic and intrinsic lipid trends, accompanying the development of fibrosis and calcification, were identified. Importantly, significant differences in lipid signatures between male and female individuals were demonstrated and were attributable to altered sphingolipid metabolism. Taken together, deep lipidomics profiling allowed to identify major molecular events and revealed a high extent of sex-dimorphism in lipidomics signatures of human FCAVD.

pathology↗

bioRxiv2023

VTA projections to M1 are essential for reorganization of layer 2-3 network dynamics underlying motor learning

The primary motor cortex (M1) is crucial for motor skill learning. Previous studies demonstrated that skill acquisition requires dopaminergic VTA (ventral-tegmental area) signaling in M1, however little is known regarding the effect of these inputs at the neuronal and network levels. Using dexterity task, calcium imaging, chemogenetic silencing, and geometric data analysis, we demonstrate VTA-dependent reorganization of M1 layer 2-3 during motor learning. While average activity and average functional connectivity of layer 2-3 network remain stable during learning, the activity kinetics, the correlational configuration of functional connectivity, and average connectivity strength of layer 2-3 neurons gradually transform towards an expert configuration. In addition, task success-failure outcome signaling gradually emerges. Silencing VTA dopaminergic inputs to M1 during learning, prevents all these changes. Our findings demonstrate dopaminergic VTA-dependent formation of outcome signaling and new connectivity configuration of the layer 2-3 network, supporting reorganization of the M1 network for storing new motor skills.

neuroscience↗

bioRxiv2023

A novel polycistronic method tailored for engineering split GECIs

We assessed the feasibility of using stop-codons as means to obtain polycistronic expression in eukaryotic cells. We show robust bicistronic expression of different open reading frames (ORFs), when these are cloned in-sequence and simply separated by stop codons (in-or out-of-frame), in heterologous expression systems and primary neurons. We further find this method to support polycistronic expression of three stop-codon-separated ORFs in vivo, which guided us to develop a technicolor Genetically-Encoded Functional Rainbow Indicators (GEFRIs) for monitoring cellular morphology and neuronal firing, concomitantly. These findings guided us to develop a new technique we denote SPLIT--Stop-codon mediated Polycistronic Induction in HeTerologous expression systems-- for rapid and easy development of fragmented proteins by the sole use of stop codons. We validated the SPLIT method by generating several new split-GFP variants, then engineer a palette of functional split-GCaMP6s variants and, lastly, generate a split ca2+-probe localized at ER and mitochondria junctions, denoted split-MEGIC. With the use of the probe, we show presence and activity of mito-ER contact sites within individual dendritic spines. Split-MEGIC can thereby be imaged by two-photon excitation in vivo in mice brains and, by standard confocal microscope in transgenic zebrafish larvae. Together, we explore non-canonical translation mechanisms and show these to be highly pervasive in various cell types in vitro and in vivo. We harness translation re-initiation to express multiple ORFs, to engineer rainbow indicators and to swiftly produce functional split-proteins and probes.

neuroscience↗

bioRxiv2021

GraFT: Graph Filtered Temporal Dictionary Learning for Functional Neural Imaging

Optical imaging of calcium signals in the brain has enabled researchers to observe the activity of hundreds-to-thousands of individual neurons simultaneously. Current methods predominantly focus on matrix factorization and aim at detecting neurons in the imaged field-of-view, and then inferring the corresponding time-traces. The explicit locality constraints on the cell shapes additionally limits the applicability to optical imaging at different scales (i.e., dendritic or widefield data). Here we present a new method that frames the problem of isolating independent fluorescing components as a dictionary learning problem. Specifically, we focus on the time-traces, which are the main quantity used in scientific discovery, and learn the dictionary of time traces with the spatial maps acting as the presence coefficients encoding which pixels the time traces are active in. Furthermore, we present a novel graph filtering model which redefines connectivity between pixels in terms of their shared temporal activity, rather than spatial proximity. This model greatly eases the ability of our method to handle data with complex non-local spatial structure, such as dendritic imaging. We demonstrate important properties of our method, such as robustness to initialization, implicitly inferring number of neurons and simultaneously detecting different neuronal types, on both synthetic data and real data examples. Specifically, we demonstrate applications of our method to calcium imaging both at the dendritic, somatic, and widefield scales.

neuroscience↗

bioRxiv2021

Plasticity of olfactory bulb inputs mediated by dendritic NMDA-spikes in piriform cortex

The piriform cortex (PCx) is essential for learning of odor information. The current view postulates odor learning in the PCx is mainly due to plasticity in intracortical (IC) synapses, while odor information from the olfactory bulb carried via the lateral olfactory tract (LOT) is "hardwired". Here we revisit this notion by studying location and pathway dependent plasticity rules. We find that in contrast to the prevailing view, synaptic and optogenetically activated LOT synapses undergo strong and robust long-term potentiation (LTP) mediated by only few local NMDA-spikes delivered at theta frequency, while global spike timing dependent plasticity protocols (STDP) failed to induce LTP in these distal synapses. An inverse result was observed for more proximal apical IC synapses; they undergo plasticity with STDP but are refractive to local NMDA-spike protocols. These results are consistent with a self-potentiating mechanism of odor information via NMDA-spikes which can form branch-specific memory traces of odors.

neuroscience↗

bioRxiv2021

AdipoAtlas: A Reference Lipidome for Human White Adipose Tissue

Obesity, characterized by expansion and metabolic dysregulation of white adipose tissue (WAT), has reached pandemic proportions and acts as a primer for a wide range of metabolic disorders. Remodelling of WAT lipidome in obesity and associated comorbidities can explain disease etiology and provide valuable diagnostic and prognostic markers. To support understanding of WAT lipidome remodelling at the molecular level, we performed in-depth lipidomics profiling of human subcutaneous and visceral WAT of lean and obese individuals. Tissue-tailored preanalytical and analytical workflows allowed accurate identification and semi-absolute quantification of 1636 and 737 lipid molecular species, respectively, and summarized here in a form of human WAT reference lipidome. Deep lipidomic profiling allowed to identify main lipid (sub)classes undergoing depot/phenotype specific remodelling. Furthermore, previously unanticipated diversity of WAT ceramides was uncovered. AdipoAtlas reference lipidome will serve as a data-rich resource for the development of WAT-specific high-throughput methods and as a scaffold for systems medicine data integration.

biochemistry↗