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Martin Meier-Schellersheim

Publications and source records attributed to Martin Meier-Schellersheim.

9 recordsLinked to original sources
PubMed2026

Moderated designs can balance between batch-effect mitigation and cell loss due to hashtag-assisted pooling in single-cell experiments.

Minimizing experimental noise is integral to robust data generation in single-cell omics. The current standard for avoiding batch effects during sample processing is barcode- or hashtag-assisted combining of different experimental treatments into one pool, allowing all samples to be subject to the technical protocols uniformly. The final data points for each treatment group are then computationally separated based on the original hashtag labels. Clearly, whereas hashtagging all groups and pooling them in a single well is expected to minimize batch effects, the procedure can also lead to a loss of cells that cannot be confidently decoded during the computational demultiplexing step. Here, we examine four alternate experimental designs, namely, compound, reference, chain, and confounded, that could be used instead of a single-pool approach and quantify the batch effects as well as cell loss in each case. We find a linear relationship-the percentage of cells lost is double the number of hashtags used in the experiment. We use these analyses to identify experimental designs that can successfully mitigate batch effects while minimizing multiplexing, hence the cell loss, in each well. Although a reference design offers the best overall performance, this study can help individual investigators choose particular approaches that are best suited for their biological questions.

Journal Article↗
PubMed2025

CountASAP: a lightweight, easy to use python package for processing ASAPseq data.

BACKGROUND: Declining sequencing costs coupled with the increasing availability of easy-to-use kits for the isolation of DNA and RNA transcripts from single cells have driven a rapid proliferation of studies centered around genomic and transcriptomic data. Simultaneously, a wealth of new techniques have been developed that utilize single cell technologies to interrogate a broad range of cell-biological processes. One recently developed technique, transposase-accessible chromatin with sequencing (ATAC) with select antigen profiling by sequencing (ASAPseq), provides a combination of chromatin accessibility assessments with measurements of cell-surface marker expression levels. While software exists for the characterization of these datasets, there currently exists no tool explicitly designed to reformat ASAP surface marker FASTQ data into a count matrix which can then be used for these downstream analyses. RESULTS: To address this lack of a dedicated tool for ASAPseq data processing, we created CountASAP, an easy-to-use Python package purposefully designed to transform FASTQ files from ASAP experiments into count matrices compatible with commonly-used downstream bioinformatic analysis packages. CountASAP takes advantage of the independence of the relevant data structures to perform fully parallelized matches of each sequenced read to user-supplied input ASAP oligos and unique cell-identifier sequences. We directly compare the performance and user-friendliness of CountASAP to existing tools using similarly-structured data from a more common sequencing experiment: cellular indexing of transcriptomes and epitopes by sequencing (CITEseq). Further benchmarking against existing tools helps to identify proper defaults for CountASAP and assess the agreement of outputs from all tested software. A final test using a novel ASAPseq dataset provides evidence that CountASAP can generate biologically meaningful results that correlate well with paired chromatin accessibility data. CONCLUSIONS: CountASAP shows good agreement with existing, well-tested data processing tools in the analysis of similarly-structured benchmarking data. CountASAP runs efficiently on a standard laptop, has user-friendly documentation, a one-step installation, and represents the first and only tool designed specifically for the processing of ASAPseq data.

Software↗
PubMed2006

Key role of local regulation in chemosensing revealed by a new molecular interaction-based modeling method.

The signaling network underlying eukaryotic chemosensing is a complex combination of receptor-mediated transmembrane signals, lipid modifications, protein translocations, and differential activation/deactivation of membrane-bound and cytosolic components. As such, it provides particularly interesting challenges for a combined computational and experimental analysis. We developed a novel detailed molecular signaling model that, when used to simulate the response to the attractant cyclic adenosine monophosphate (cAMP), made nontrivial predictions about Dictyostelium chemosensing. These predictions, including the unexpected existence of spatially asymmetrical, multiphasic, cyclic adenosine monophosphate-induced PTEN translocation and phosphatidylinositol-(3,4,5)P3 generation, were experimentally verified by quantitative single-cell microscopy leading us to propose significant modifications to the current standard model for chemoattractant-induced biochemical polarization in this organism. Key to this successful modeling effort was the use of "Simmune," a new software package that supports the facile development and testing of detailed computational representations of cellular behavior. An intuitive interface allows user definition of complex signaling networks based on the definition of specific molecular binding site interactions and the subcellular localization of molecules. It automatically translates such inputs into spatially resolved simulations and dynamic graphical representations of the resulting signaling network that can be explored in a manner that closely parallels wet lab experimental procedures. These features of Simmune were critical to the model development and analysis presented here and are likely to be useful in the computational investigation of many aspects of cell biology.

Animals↗
PubMed2006

Pathogenesis of HIV infection: what the virus spares is as important as what it destroys.

Upon transmission to a new host, HIV targets CCR5+ CD4+ effector memory T cells, resulting in acute, massive depletion of these cells from mucosal effector sites. This depletion does not initially compromise the regenerative capacity of the immune system because naive and most central memory T cells are spared. Here, we discuss evidence suggesting that frequent activation of these spared cells during the chronic phase of HIV infection supplies mucosal tissues with short-lived CCR5+ CD4+ effector cells that prevent life-threatening infections. This immune activation also facilitates continued viral replication, but infection and killing of target T cells by HIV are selective and the impact on effector-cell lifespan is limited. We propose, however, that persistent activation progressively disrupts the functional organization of the immune system, reducing its regenerative capacity and facilitating viral evolution that leads to loss of the exquisite target cell-sparing selectivity of viral replication, ultimately resulting in AIDS.

Acquired Immunodeficiency Syndrome↗
PubMed2004

Quantitative imaging of single live cells reveals spatiotemporal dynamics of multistep signaling events of chemoattractant gradient sensing in Dictyostelium.

Activation of G-protein-coupled chemoattractant receptors triggers dissociation of Galpha and Gbetagamma subunits. These subunits induce intracellular responses that can be highly polarized when a cell experiences a gradient of chemoattractant. Exactly how a cell achieves this amplified signal polarization is still not well understood. Here, we quantitatively measure temporal and spatial changes of receptor occupancy, G-protein activation by FRET imaging, and PIP3 levels by monitoring the dynamics of PH(Crac)-GFP translocation in single living cells in response to different chemoattractant fields. Our results provided the first direct evidence that G-proteins are activated to different extents on the cell surface in response to asymmetrical stimulations. A stronger, uniformly applied stimulation triggers not only a stronger G-protein activation but also a faster adaptation of downstream responses. When naive cells (which have not experienced chemoattractant) were abruptly exposed to stable cAMP gradients, G-proteins were persistently activated throughout the entire cell surface, whereas the response of PH(Crac)-GFP translocation surprisingly consisted of two phases, an initial transient and asymmetrical translocation around the cell membrane, followed by a second phase producing a highly polarized distribution of PH(Crac)-GFP. We propose a revised model of gradient sensing, suggesting an important role for locally controlled components that inhibit PI3Kinase activity.

Animals↗
PubMed2004

Spontaneous proliferation, a response of naive CD4 T cells determined by the diversity of the memory cell repertoire.

T cell numbers are maintained within narrow ranges in vivo. Introduction of naïve cells into lymphopenic environments results in proliferation and differentiation driven by the recognition of peptide/MHC complexes and by cytokine signaling. This process, often described as homeostatic proliferation, is here referred to as spontaneous proliferation. We show that, although the presence of memory CD4 T cells of broad repertoire efficiently inhibits proliferation/differentiation of naïve CD4 T cells, a memory population of similar size comprised of cells with a repertoire of limited diversity fails to do so, implying that cells of a given specificity prevent responses of cells of the same or related specificity. This finding suggests that the immune system has evolved mechanisms to attain a memory cell repertoire of great diversity independently of foreign antigens.

Animals↗
PubMed2002

CD4 T cell depletion is linked directly to immune activation in the pathogenesis of HIV-1 and HIV-2 but only indirectly to the viral load.

The causal relationships among CD4 cell depletion, HIV replication, and immune activation are not well understood. HIV-2 infection, "nature's experiment" with inherently attenuated HIV disease, provides additional insights into this issue. We report the finding that in HIV-2 and HIV-1 patients with a comparable degree of CD4 depletion the imbalance in the relative sizes of the naive and memory T cell populations and the up-regulation of CD4 and CD8 cell activation markers (HLA-DR, CD38, CD69, Fas molecules) are similar, even though the viral load in the plasma of HIV-2-infected patients is two orders of magnitude lower than in HIV-1 patients and HIV-2 patients are known to have slower rates of CD4 T cell decline and a better clinical prognosis. Moreover, we found a similar increase in the frequency of cycling CD4 T cells (Ki67+), which was in strong correlation with the expression of activation markers. Finally, the level of T cell anergy, as assessed by the proliferative responses to CD3 stimulation and to a panel of microbial Ags, proved to be comparable in HIV-1 and HIV-2 patients with a similar degree of CD4 depletion despite large differences in viral load. Our data are consistent with a direct causal relationship between immune activation and CD4 cell depletion in HIV disease and an only indirect relation of these parameters to the virus replication rate. Invoking the concept of proximal immune activation and virus transmission, which links efficient transmission of virus to local cell activation and proliferation in response to Ags and inflammation, we propose an integrative interpretation of the data and suggest that strongly elevated immune activation induces CD4 cell depletion and not vice versa, with potential implications for the choice of treatment strategies.

Biomarkers↗