Biology subjects

Keller, P.

Publications and source records attributed to Keller, P..

7 recordsLinked to original sources

bioRxiv2026

DCAFA: Differential Community Abundance and Feature Analysis for Histological Images

Histological images are composed of diverse local structures such as cells, glands, or tissue patches, whose organisation and relative abundance reflect underlying biological processes. While most computational approaches focus on analysing individual features, many clinically relevant signals arise from changes in the composition of these structures rather than isolated measurements. This motivates the need for explicitly modelling how groups of similar instances vary across samples and relate to outcomes. We present DCAFA (Differential Community Abundance and Feature Attribution Analysis), a regression-based framework for analysing hierarchical biomedical data through both compositional and feature-level perspectives. DCAFA groups instances into latent communities representing recurring morphological or phenotypic patterns, and then performs two complementary analyses: (i) community composition analysis, which identifies groups that are enriched or depleted across outcomes, and (ii) feature attribution analysis, which quantifies how instance-level features relate to outcomes directly or within specific communities. Both use generalised linear and mixed-effects models, enabling covariate adjustment and inference through effect sizes, confidence intervals, and false discovery rate control. We demonstrate the utility of DCAFA across multiple biomedical settings, including endometrial histopathology, spatial transcriptomics, multiplex immunofluorescence imaging, and predefined cell-type analyses in colorectal cancer. These examples identify interpretable compositional shifts and context-specific feature associations that are not captured by conventional feature-based approaches. By unifying differential abundance testing and feature attribution within a single statistical framework, DCAFA serves as an openly available toolbox that provides a practical and interpretable means of linking tissue composition with clinical or molecular outcomes in biomedical imaging data. Code available at: https://github.com/wgrgwrght/DCAFA

bioinformatics↗

bioRxiv2025

The Gfr uptake system provides a context-dependent fitness advantage to Salmonella Typhimurium SL1344 during the initial gut colonization phase

Salmonella enterica serovar Typhimurium (S. Tm) is a major cause of foodborne diarrhea. However, in healthy individuals, the microbiota typically restricts the growth of incoming pathogens, a protective mechanism termed colonization resistance (CR). To circumvent CR, Salmonella strains can utilize private nutrients that remain untapped by the resident microbiota. However, the metabolic pathways and environmental niches promoting pathogen growth are still not completely understood. Here, we investigate the significance of the gfr operon in gut colonization of S. Tm, which is essential for the utilization of fructoselysine (FL) and glucoselysine (GL). These Amadori compounds are present in heated foods with high protein and carbohydrate contents, particularly in Western-type diets. We detected FL in both mouse chow and the intestinal tract of mice and showed that gfr mutants are attenuated during the initial phase of colonization in the murine model. Experiments in gnotobiotic mice and competition experiments with Escherichia coli suggest that gfr-dependent fitness advantage is context-dependent. We conclude that dietary Amadori products like FL can support S. Tm gut colonization, depending on the metabolic capacities of the microbiota.

microbiology↗

bioRxiv2024

FREQuency-resolved brain Network Estimation via Source Separation (FREQ-NESS)

The brain is a dynamic system whose network organization is often studied by focusing on specific frequency bands or anatomical regions, leading to fragmented insights, or by employing complex and elaborate methods that hinder straightforward interpretations. To address this issue, a new analytical pipeline named FREQuency-resolved Network Estimation via Source Separation (FREQ-NESS) is introduced. This is designed to estimate the activation and spatial configuration of simultaneous brain networks across frequencies by analyzing the frequency-resolved multivariate covariance between whole-brain voxel time series. FREQ-NESS is applied to source-reconstructed magnetoencephalography (MEG) data during resting state and isochronous auditory stimulation. Results reveal simultaneous, frequency-specific brain networks during resting state, such as the default mode, alpha-band, and motor-beta networks. During auditory stimulation, FREQ-NESS detects: (1) emergence of networks attuned to the stimulation frequency, (2) spatial reorganization of existing networks, such as alpha-band networks shifting from occipital to sensorimotor areas, (3) stability of networks unaffected by auditory stimuli. Furthermore, auditory stimulation significantly enhances cross-frequency coupling, with the phase of attuned auditory networks modulating the gamma band amplitude of medial temporal lobe networks. In conclusion, FREQ-NESS effectively maps the brains spatiotemporal dynamics, providing a comprehensive view of brain function by revealing simultaneous, frequency-resolved networks and their interaction.

neuroscience↗

bioRxiv2019

Distinguishing \"self\" from \"other\" in a dynamic synchronization task with an adaptive virtual partner.

For precise interpersonal coordination, some degree of merging a sense of self with other is required. In group music making, one may want to be in \"sync\" with ones ensemble and, if playing a similar instrument, one can assume a degree of temporal and acoustic overlap. However, to what extent is self-other merging optimal? An incorrect balance of segregation and integration of self and other information would result in a lack of interpersonal cohesion or a disruption of self-agency. Using an interactive finger-tapping task with a virtual partner and functional MRI, we explored neural differences between self-other merging and distinction. Varying both the level of adaptivity of a virtual partner and the quality of self-related auditory feedback, we show that the predictability of the other and availability of distinguishable, self-related information improve performance and demonstrate how dynamic interactions vary ones sense of agency. From neuroimaging data, we identify regions that are more active when self and other are distinct, including the TPJ. Conversely, we observe activity in the cerebellum, EBA and SMA when self and other blur. These findings suggest that a certain degree of self-other distinction at sensorimotor, experiential, and neurophysiological levels is required to maintain successful interpersonal coordination.

neuroscience↗

bioRxiv2019

Quantitative measurements of chromatin modification dynamics during zygotic genome activation

Histone posttranslational modifications (PTMs) are key gene expression regulators, but their rapid dynamics during development remain difficult to capture. We describe an approach that images fluorescent antibody fragments to quantify PTM enrichment and active transcription at defined loci during zygotic genome activation in living zebrafish embryos. The technique reveals a drastic increase in histone H3 Lys27 acetylation (H3K27ac) before genome activation both at a specific locus and globally.

cell biology↗

bioRxiv2019

Interkinetic nuclear migration in the zebrafish retina as a diffusive process

A major hallmark of neural development is the oscillatory movement of nuclei between the apical and basal surfaces of the neuroepithelium during the process of interkinetic nuclear migration (IKNM). Here, we employ long-term, rapid lightsheet and two-photon imaging of Zebrafish retinas in vivo during early development to uncover the physical processes that govern the behavior of nuclei during IKNM. These images allow the capture of reliable tracks of nuclear movements and division during early retinogenesis for many tightly packed nuclei. These tracks are then used to create and test a theory of retinal IKNM as a diffusive process across a nuclear concentration gradient generated by the addition of new nuclei at the apical surface. The analysis reveals the role of nuclear packing at the apical surface on the migration dynamics of nuclei, provides a robust quantitative explanation for the distribution of nuclei across the retina, and may have implications for stochastic fate choice in this system.

developmental biology↗

bioRxiv2018

The RNA-binding protein AATF coordinates rRNA maturation

AATF is a central regulator of the cellular outcome upon p53 activation, a finding that has primarily been attributed to its function as a transcription factor. Recent data showed that AATF is essential for ribosome biogenesis and plays a role in rRNA maturation. AATF has been implicated to fulfil this role through direct interaction with rRNA and was identified in several RNA-interactome capture experiments. Here, we provide a first comprehensive analysis of the RNA bound by AATF using CLIP-sequencing. Interestingly, this approach shows predominant binding of the 45S pre-ribosomal RNA precursor molecules. Furthermore, AATF binds to mRNAs encoding for ribosome biogenesis factors as well as snoRNAs. These findings are complemented by an in-depth analysis of the protein interactome of AATF containing a large set of proteins known to play a role in rRNA maturation with an emphasis on the protein-RNA-complexes known to be required for the generation of the small ribosomal subunit (SSU). In line with this finding, the binding sites of AATF within the 45S rRNA precursor localize in close proximity to the SSU cleavage sites. Consequently, our multilayer analysis of the protein-RNA interactome of AATF reveals this protein to be an important hub for protein and RNA interactions involved in ribosome biogenesis.

molecular biology↗