Biology subjects

Jacobs, G.

Publications and source records attributed to Jacobs, G..

7 recordsLinked to original sources

bioRxiv2026

Semi-automated identification of southern right whales from drone imagery by classical image matching methods

Individual southern right whales (Eubalaena australis) can be identified from the callosity pattern on the head, a stable pattern of roughened keratinized patches. Manual comparison of drone images with large catalogs, however, is time-consuming. For southern right whales, automated photo-identification approaches typically require substantial training data or retraining when new individuals are added. Here we evaluate two classical image-similarity methods for individual identification from standardized dorsal head images: histograms of oriented gradients (HOG), and symmetric log-chamfer distance. We tested 375 query images from 198 known whales with recurrent sightings against 411 reference images, one for each individual whale. HOG ranked the correct whale first in 361 of 375 cases (96.3%), whereas log-chamfer ranked the correct whale first in 355 cases (94.7%). All incorrect rank-1 matches could be identified by a high risk score computed from query-reference distance distributions. A combined rule selecting the first-ranked candidate from the method with the lower risk score increased rank-1 accuracy to 368 cases (98.1%). These results show that classical registered image matching provides a practical tool for southern right whale photo-identification.

ecology↗

bioRxiv2026

Calibrating for absolute microbiome abundances without spike-ins

Metagenomics is a widely used approach in microbiome research. However, a major limitation of metagenomic datasets is their compositional nature, which prevents direct quantification of absolute abundances and complicates cross-sample comparisons. Existing strategies for absolute quantification typically require additional experiments or spike-in controls. Here, we introduce the MetaGenome Calibrator (MGCalibrator), a new tool that enables spike-in free, absolute abundance estimation based on routine DNA concentration measurements. We validated the accuracy of absolute abundances obtained with MGCalibrator against qPCR for 5 targets. Our results show a strong correlation with qPCR data, indicating that MGCalibrator enables qPCR-like trend analyses. For Bacteroides dorei, the estimated abundances were highly similar between the two methods (r2 = 0.98, y = 1.00x). For other targets like crAssphage or the bacterial 16S rRNA gene, qPCR values were underrepresented by a factor of 7 or overrepresented by a factor of 4. Benchmarking with synthetic microbiome data demonstrated that our method accurately determines copy numbers in sequencing datasets, and application to whole-cell mock community samples produced expected values based on known extraction biases. In an extraction-bias-free experiment, MGCalibrator accurately quantified genome copy numbers within a twofold range in 98% of cases and determined 16S rRNA gene copies within 1.6-fold or less. Finally, we applied MGCalibrator to track temporal trends in antibiotic resistance genes (ARGs) in wastewater treatment plants in two Dutch provincial capitals. We observed an overall increase in ARGs--such as sul2 in Utrecht and qnrS5 in Houtrust--likely driven by rising bacterial loads. Our findings demonstrate that MGCalibrator provides robust calibration of metagenomic data, paving the way for metagenomics to play a central role in future surveillance by enabling trend analysis across thousands of genetic targets, similar to the capabilities of qPCR for individual genes. The source code and documentation for MGCalibrator are available at github.com/NimroddeWit/MGCalibrator.

microbiology↗

bioRxiv2025

Representational dynamics during extinction of fear memories in the human brain

Extinction learning - the suppression of a previously acquired fear response - is critical for adaptive behavior and core for understanding the etiology and treatment of anxiety disorders. Electrophysiological studies in rodents have revealed critical roles of theta (4-12Hz) oscillations in amygdala and hippocampus during both fear learning and extinction, and engram research has shown that extinction relies on the formation of novel, highly context-dependent memory traces that suppress the initial fear memories. Whether similar processes occur in humans and how they relate to previously described neural mechanisms of episodic memory formation and retrieval remains unknown. Intracranial EEG (iEEG) recordings in epilepsy patients provide direct access to the deep brain structures of the fear and extinction network, while representational similarity analysis (RSA) allows characterizing the memory traces of specific cues and contexts. Here we combined these methods to show that amygdala theta oscillations during extinction learning signal safety rather than threat and that extinction memory traces are characterized by stable and context-specific neural representations that are coordinated across the extinction network. We further demonstrate that context specificity during extinction learning predicts the reoccurrence of fear memory traces during a subsequent test period, while reoccurrence of extinction memory traces predicts safety responses. Our results reveal the neurophysiological mechanisms and representational characteristics of context-dependent extinction learning in the human brain. In addition, they show that the mutual competition of fear and extinction memory traces provides a mechanistic basis for clinically important phenomena such as fear renewal and extinction retrieval.

neuroscience↗

bioRxiv2025

From sporulation to village differentiation: the shaping of the social microbiome over rural-to-urban lifestyle transition in Indonesia

Despite established roles in human health and profound global diversity, existing gut microbiome datasets are biased toward Western urban cohorts, with especial under-representation of Southeast Asia. Here, we present a novel gut microbiome dataset from 116 Indonesians representing a cline from transitional hunter-gatherers to rural agricultural to urban lifestyles. We identify 1,304 species and 3,258 subspecies by assembling 11,070 metagenome-assembled genomes, revealing substantial species (15%) and subspecies level (50%) novelty. Novel taxa are rare, often village-specific, and depleted for sporulation genes, revealing a direct link between bacterial physiology, transmission, prevalence and discovery. We identify a rural-to-urban cline across multiple levels of biological organisation, from species abundance to microbiome composition and diversity. Furthermore, between-community, but not within-community, variation in diet is strongly predictive of microbiome composition, offering compelling evidence that microbiome divergence is driven by community-level differences. Our work highlights the interplay of host lifestyle, population structure and bacterial physiology in shaping microbiome diversity and biogeography, at the key scale of human communities.

microbiology↗

bioRxiv2020

Genetic architecture of gene regulation in Indonesian populations identifies QTLs associated with local ancestry and archaic introgression

Lack of diversity in human genomics limits our understanding of the genetic underpinnings of complex traits, hinders precision medicine, and contributes to health disparities. To map genetic effects on gene regulation in the underrepresented Indonesian population, we have integrated genotype, gene expression, and CpG methylation data from 115 participants across three island populations that capture the major sources of genomic diversity on the region. In a comparison with a European dataset, we identify 166 uniquely Indonesia-specific eQTLs, highlighting the benefits of performing association studies on non-European populations. By combining local ancestry and archaic introgression inference eQTLs and methylQTLs, we identify regulatory loci driven by modern Papuan ancestry as well as introgressed Denisovan and Neanderthal variation. GWAS colocalization connects QTLs detected here to hematological traits. Our findings illustrate how local ancestry and archaic introgression drive variation in gene regulation across genetically distinct and in admixed populations.

genomics↗

bioRxiv2020

Moving Beyond the Mean: Subgroups and dimensions of brain activity and cognitive performance across domains

Human neuroimaging during cognitive tasks has provided unique and important insights into the neurobiology of cognition. However, the vast majority of research relies upon group aggregate or average statistical maps of activity, which do not fully capture the rich variability which exists across individuals. To better characterize individual variability, hierarchical clustering was performed separately on six fMRI tasks in 822 participants from the Human Connectome Project. Across all tasks, clusters ranged from a predominantly deactivating pattern towards a more activating pattern of brain activity, with differences in out-of-scanner cognitive test scores between clusters. Cluster stability was assessed via bootstrapping approach. Cluster probability did not indicate distinct/clear clustering. However, when participants were plotted in a dimensionally reduced similarity space derived from bootstrapping, variability in brain activity among participants was best represented multidimensionally. A positive to negative axis of activity was the strongest driver of individual differences.

neuroscience↗

bioRxiv2019

Human and mouse iPSC-derived astrocyte subtypes reveal vulnerability in Vanishing White Matter

Astrocytes gained attention as important players in neurological disease, including a number of leukodystrophies. Several studies explored the generation of induced pluripotent stem cell-derived astrocytes for drug screening and regenerative studies. Developing robust models of patient induced pluripotent stem cells is challenged by high variability due to diverse genetic backgrounds and long-term culture procedures. While human models are of special interest, mouse-based models have the advantage that for them these issues are less pronounced. Here we present astrocyte differentiation protocols for both human and mouse induced pluripotent stem cells to specifically induce grey and white matter astrocytes. Both subtypes expressed astrocyte-associated markers, had typical astrocyte morphologies, and gave a reactive response to stress. Importantly, the grey and white matter-like astrocytes differed in size, complexity of processes, and expression profile, conform primary grey and white matter astrocytes. The newly presented mouse and human stem cell-based models for the leukodystrophy Vanishing White Matter replicated earlier findings, such as increased proliferation, decreased OPC maturation and modulation by hyaluronidase. We studied intrinsic astrocyte subtype vulnerability in Vanishing White Matter in both human and mouse cells. Oligodendrocyte maturation was specifically inhibited in cultures with Vanishing White Matter white matter-like astrocytes. By performing RNA sequencing, we found more differentially regulated genes in the white than in the grey matter-like astrocytes. Human and mouse astrocytes showed the same affected pathways, although human white matter-like astrocytes presented human-specific disease mechanisms involved in Vanishing White Matter. Using both human and mouse induced pluripotent stem cells, our study presents protocols to generate white and grey matter-like astrocytes, and shows astrocyte subtype-specific defects in Vanishing White Matter. While mouse induced pluripotent stem cell-based cultures may be less suitable to mimic human astrocyte subtype- or patient-specific changes, they might more robustly represent disease mutation-related cellular phenotypes as the cells are derived from inbred mice and the protocols are faster. The presented models give new tools to generate astrocyte subtypes for in vitro disease modeling and in vivo regenerative applications.

neuroscience↗