Biology subjects

Welter, D.

Publications and source records attributed to Welter, D..

6 recordsLinked to original sources

bioRxiv2025

Regulation of input excitability in human and mouse parvalbumin interneurons by Kir potassium channels

Compared to rodents, inhibitory interneurons in the human neocortex exhibit high input excitability because of reduced passive ion leakage across their extracellular membrane. However, the regulation of intrinsic excitability by voltage-gated ion channels activated over a wide range of membrane potentials in human interneurons remains poorly understood. We performed whole-cell patch-clamp microelectrode recordings in mouse and human neocortical slices obtained from surgically resected non-pathological brain tissue finding that Kir channels control the electrical resistance of parvalbumin (Pvalb) neurons in an identical manner in the human and mouse. Molecular analyses revealed predominantly Kir3.1 and Kir3.2 channels in Pvalb neurons in both species. Using whole-cell recordings from synaptically connected neuron pairs and a computational model, we demonstrated that physiological Kir activation inhibits human Pvalb interneurons during postsynaptic potentials evoked by presynaptic neurogliaform cells. The similarity of Kir-mediated inhibition across species suggests that it is an archetypal property of Pvalb neurons.

neuroscience↗

bioRxiv2025

FAIRification of computational models in biology

Computational models are essential for studying complex systems which, particularly in clinical settings, need to be quality-approved and transparent. To enhance the communication of a models features and capabilities, we propose an adaptation of the Findability, Accessibility, Interoperability and Reusability (FAIR) indicators published by the Research Data Alliance to assess models encoded in domain-specific standards, such as those established by COMBINE. The assessments guide FAIRification and add value to models.

systems biology↗

bioRxiv2025

Obligate cross-feeding of metabolites is common in soil microbial communities

Many microorganisms are refractory to laboratory cultivation. One possible explanation, known as the great plate count anomaly, is metabolic dependencies among community members. However, systematic studies of these interactions in communities like soil are missing, hindering advances in understanding these ecologically important ecosystems. Here, we address this issue by systematically analysing 6,931 bacterial isolates of 27 soil microbial communities. We find that the growth of up to 50% of all community members depended essentially on supplementation with amino acids, vitamins, or nucleotides. In 73% of cases, supplementation with multiple amino acids was necessary. Genomic analysis of 62 strains revealed that accumulation of insertion sequences and specific gene loss was associated with the observed auxotrophies. Finally, genome-scale metabolic models, computational analyses, and cocultivation experiments demonstrated that other co-occurring genotypes complemented the metabolic needs of auxotrophs, thus facilitating their growth. Our results demonstrate that soil bacteria exist within integrated metabolic networks, which hampers their cultivation.

microbiology↗

bioRxiv2024

Mechanisms and purpose of lowered action potential firing threshold in fast-spiking interneurons in the human neocortex

The mammalian brain exhibits notable interspecies variation. Microanatomical and molecular differences in homologous neurons, those with similar locations and developmental origins across species, are best characterized in the neocortical mantle, the center of complex brain functions; however, the purpose of these differences remains unclear. We performed whole-cell microelectrode recordings along with microanatomical and molecular analyses of human fast-spiking parvalbumin (pvalb)-expressing interneurons in neocortical tissue resected during brain surgery, comparing them with similar data obtained from the mouse neocortex. The action potential (AP) firing threshold was lower in human neurons than in mouse neurons. This was due to a deficiency in low-voltage-activated inhibitory Kv1.1 and Kv1.2 potassium channels in the axon initial segment (AIS), a specialized axonal region that determines AP threshold and initiation, in human cells. In contrast, Kv1 ion channels were prominent in mouse neurons. The AIS was also elongated in humans. Computational simulations of fast-spiking interneurons revealed that the human-type AIS lowers the AP threshold and shortens the time lag for AP initiation. We found that the low membrane AP firing threshold in pvalb neurons is closely linked to slow membrane potential kinetics in the soma. Thus, the human AIS supports fast in-fast out circuit function in human pvalb neurons, compensating for electrically slow somatic membrane responses. When formulating therapeutic strategies that involve fast- spiking neurons, it is crucial to take into account the molecular and functional species differences. Short blurb: Fast-spiking neurons in the human neocortex feature structural and molecular specializations in the axon initial segment that lower firing thresholds and minimize input- output delay.

neuroscience↗

bioRxiv2024

FAIR assessment of MINERVA as an opportunity to foster open science and scientific crowdsourcing in systems biomedicine

1The Disease Maps Project (https://disease-maps.org) focuses on the development of diseasespecific comprehensive structured knowledge repositories supporting translational medicine research. These disease maps require continuous interdisciplinary collaboration and should be reusable and interoperable. Adhering to the Findable, Accessible, Interoperable and Reusable (FAIR) principles enhances the utility of such digital assets. We used the RDA FAIR Data Maturity Model and assessed the FAIRness of the Molecular Interaction NEtwoRk VisuAlization (MINERVA) Platform. MINERVA is a standalone webserver that allows users to manage, explore and analyse disease maps and their related data manually or programmatically. We exemplify the FAIR assessment on the Parkinsons Disease Map (PD map) and the COVID-19 Disease Map, which are large-scale projects under the umbrella of the Disease Maps Project, aiming to investigate molecular mechanisms of the Parkinsons disease and SARS-CoV-2 infection, respectively. We discuss the FAIR features supported by the MINERVA Platform and we outline steps to further improve the MINERVA FAIRness and to better connect this resource to other ongoing scientific initiatives supporting FAIR in computational systems biomedicine.

systems biology↗

bioRxiv2017

A Standardized Framework For Representation Of Ancestry Data In Genomics Studies

BackgroundThe accurate description of ancestry is essential to interpret and integrate human genomics data, and to ensure that advances in the field of genomics benefit individuals from all ancestral backgrounds. However, there are no established guidelines for the consistent, unambiguous and standardized description of ancestry. To fill this gap, we provide a framework, designed for the representation of ancestry in GWAS data, but with wider application to studies and resources involving human subjects.\n\nResultHere we describe our framework and its application to the representation of ancestry data in a widely-used publically available genomics resource, the NHGRI-EBI GWAS Catalog. We present the first analyses of GWAS data using our ancestry categories, demonstrating the validity of the framework to facilitate the tracking of ancestry in big data sets. We exhibit the broader relevance and integration potential of our method by its usage to describe the well-established HapMap and 1000 Genomes reference populations. Finally, to encourage adoption, we outline recommendations for authors to implement when describing samples.\n\nConclusionsWhile the known bias towards inclusion of European ancestry individuals in GWA studies persists, African and Hispanic or Latin American ancestry populations contribute a disproportionately high number of associations, suggesting that analyses including these groups may be more effective at identifying new associations. We believe the widespread adoption of our framework will increase standardization of ancestry data, thus enabling improved analysis, interpretation and integration of human genomics data and furthering our understanding of disease.

genetics↗