Biology subjects

Hirsch, P.

Publications and source records attributed to Hirsch, P..

6 recordsLinked to original sources

bioRxiv2026

Neuron types and distribution of a Drosophila driver line collection

Cell type designations label uniquely-identifiable groups of related cells that typically function in similar ways. Cell types divide the Drosophila melanogaster central nervous system into functional units, but remain challenging to target and identify. Previously we generated a driver line and image resource for targeting many neuron types (Meissner et al., 2025). Here we improve on identifying the targeted neurons by automated searching against electron microscopy datasets and manual scoring of search results to add 6,368 annotations across 1,772 driver lines in the collection. These annotations provide a potential training resource for future search algorithms. We then estimate the number of cell types and thus the fraction of the central nervous system labeled by the collection as a whole.

neuroscience↗

bioRxiv2026

Unveiling the taxonomic diversity and unprecedented biosynthetic treasure of the phylum Myxococcota

Natural products remain vital sources of therapeutics, particularly anti-infectives, and members of the phylum Myxococcota constitute an especially rich reservoir for their discovery. Based on decades of microbiological efforts, we present 154 new Myxococcota genomes and propose a revised taxonomy expanding the number of described families from 11 to 28 and genera from 32 to 90. Comparison with an equivalent set from the prime source Actinomycetota shows that Myxococcota possess a comparable biosynthetic diversity, underscoring their promise for large-scale isolation and sequencing efforts. The vast untapped potential reflected in 2,387 uncharacterized gene cluster families is highlighted by genome mining efforts, yielding four validated compounds exhibiting novel chemistry, including myxolutamids and myxopentacins. We show that many Myxococcota-derived natural products, such as myxolutamid A and two new sorangicin derivatives, are conserved within taxonomic lineages. New described families thus bear high biosynthetic potential underpinning the importance of precise taxonomic classification guiding targeted drug discovery.

microbiology↗

bioRxiv2025

ROSMAP-Compass: A data-harmonised, AI-ready atlas of 22 million single nuclei from the ROSMAP cohort

The Religious Orders Study and Memory and Aging Project (ROSMAP) cohort has generated the worlds most comprehensive single-cell transcriptomic resource for Alzheimers disease research. Naturally, in a project spanning multiple years with dozens of research groups involved, the resulting data landscape shows fragmentation across sequencing chemistries, protocols, and pipelines. This presents both a challenge and a unique opportunity for harmonized, collaborative analysis. Following an early data integration strategy and complete realignment of all single nucleus RNA sequencing data, we generated a fully harmonized resource: ROSMAP-Compass, comprising more than 22 million high-quality nuclei from 2,058 donors in multiple brain regions from the ROSMAP and Neuro Psychiatric Symptoms (NPS-AD) cohorts. Through systematic curation and unified reprocessing, we addressed substantial technical challenges including chemistry-specific biases, cross-study batch effects, and sample redundancies across multiple studies spanning different time periods and research groups. ROSMAP-Compass demonstrates the critical importance of systematic data harmonization when integrating large-scale single-cell datasets from multiple sources. By combining open science principles with cutting-edge AI integration, we provide both a critical resource for understanding Alzheimers disease heterogeneity and a blueprint for making complex biomedical data accessible to the global research community. The full resource, interactive web portal, and LLM compatible API are freely available, empowering researchers worldwide to accelerate discovery in neurodegenerative diseases.

neuroscience↗

bioRxiv2023

ABC-HuMi: the Atlas of Biosynthetic Gene Clusters in the Human Microbiome

The human microbiome has emerged as a rich source of diverse and bioactive natural products, harboring immense potential for therapeutic applications. To facilitate systematic exploration and analysis of its biosynthetic landscape, we present ABC-HuMi: the Atlas of Biosynthetic Gene Clusters (BGCs) in the Human Microbiome. ABC-HuMi integrates data from major human microbiome sequence databases and provides an expansive repository of BGCs compared to the limited coverage offered by existing resources. Employing state-of-the-art BGC prediction and analysis tools, our database ensures accurate annotation and enhanced prediction capabilities. ABC-HuMi empowers researchers with advanced browsing, filtering, and search functionality, enabling efficient exploration of the resource. At present, ABC-HuMi boasts a catalog of 19,218 representative BGCs derived from the human gut, oral, skin, respiratory and urogenital systems. By capturing the intricate biosynthetic potential across diverse human body sites, our database fosters profound insights into the molecular repertoire encoded within the human microbiome and offers a comprehensive resource for the discovery and characterization of novel bioactive compounds. The database is freely accessible at https://www.ccb.uni-saarland.de/abc_humi/. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=149 SRC="FIGDIR/small/558305v2_ufig1.gif" ALT="Figure 1"> View larger version (52K): org.highwire.dtl.DTLVardef@15af4f6org.highwire.dtl.DTLVardef@886a27org.highwire.dtl.DTLVardef@1f12de5org.highwire.dtl.DTLVardef@fc24be_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2021

Automated Reconstruction of Whole-Embryo Cell Lineages by Learning from Sparse Annotations

We present a method for automated nucleus identification and tracking in time-lapse microscopy recordings of entire developing embryos. Our method combines deep learning and global optimization to enable complete lineage reconstruction from sparse point annotations, and uses parallelization to process multi-terabyte light-sheet recordings, which we demonstrate on three common model organisms: mouse, zebrafish, Drosophila. On the most difficult dataset (mouse), our method correctly reconstructs 75.8% of cell lineages spanning 1 hour, compared to 31.8% for the previous state of the art, thus enabling biologists to determine where and when cell fate decisions are made in developing embryos, tissues, and organs.

bioinformatics↗

bioRxiv2021

PatchPerPixMatch for Automated 3d Search of Neuronal Morphologies in Light Microscopy

Studies of individual neurons in the Drosophila nervous system are facilitated by transgenic lines that sparsely and repeatably label respective neurons of interest. Sparsity can be enhanced by means of intersectional approaches like the split-GAL4 system, which labels the positive intersection of the expression patterns of two (denser) GAL4 lines. To this end, two GAL4 lines have to be identified as labelling a neuron of interest. Current approaches to tackling this task include visual inspection, as well as automated search in 2d projection images, of single cell multi-color flip-out (MCFO) acquisitions of GAL4 expression patterns. There is to date no automated method available that performs full 3d search in MCFO imagery of GAL4 lines, nor one that leverages automated reconstructions of the labelled neuron morphologies. To close this gap, we propose PatchPerPixMatch, a fully automated approach for finding a given neuron morphology in MCFO acquisitions of Gen1 GAL4 lines. PatchPerPixMatch performs automated instance segmentation of MCFO acquisitions, and subsequently searches for a target neuron morphology by minimizing an objective that aims at covering the target with a set of well-fitting segmentation fragments. Patch-PerPixMatch is computationally efficient albeit being full 3d, while also highly robust to inaccuracies in the automated neuron instance segmentation. We are releasing PatchPerPixMatch search results for ~30,000 neuron morphologies from the Drosophila hemibrain in ~20,000 MCFO acquisitions of ~3,500 Gen1 GAL4 lines. Codehttps://github.com/Kainmueller-Lab/PatchPerPixMatch Resultshttps://pppm.janelia.org

bioinformatics↗