Biology subjects

Landsberg, J.

Publications and source records attributed to Landsberg, J..

3 recordsLinked to original sources

bioRxiv2026

SPARQ-MI leverages end-to-end spatial single-cell analysis of the tumor microenvironment

Detailed spatial analysis of the tumor micro-environment (TME) through multiplexed fluorescence imaging requires quantitative image-processing and data-analysis methods. While data-preprocessing down to segmentation of individual cells is captured by available methods, statistical analysis of single-cell features is compromised by the uneven noise distribution especially in complex tissues such as the TME, as well as by labor-intensive manual cell-type annotation and region segmentation. Here, we present SPARQ-MI (Spatial Phenotyping, Architecture Reconstruction and Quantification from Multiplexed Imaging) for streamlined spatial single-cell analysis, along with a tissue microarray PhenoCycler data-set with 37 fluorescent channels from melanoma patients under immunotherapy. We demonstrate that SPARQ-MI enables robust reconstruction of the cellular and spatial composition in this and other tissue types. Our analysis reveals associations of the cell-state and spatial location of CD8 T cells with response to immunotherapy. Overall, SPARQ-MI allows for quantitative analysis of complex fluorescence histology samples under minimal user input, and accounting for spatially uneven coverage of antibody signals, setting the stage for quantitative analysis of clinical samples.

bioinformatics↗

bioRxiv2021

Anisotropic interaction and motion states of locusts in a hopper band

Swarming locusts present a quintessential example of animal collective motion. Juvenile locusts march and hop across the ground in coordinated groups called hopper bands. Composed of up to millions of insects, hopper bands exhibit aligned motion and various collective structures. These groups are well-documented in the field, but the individual insects themselves are typically studied in much smaller groups in laboratory experiments. We present the first trajectory data that detail the movement of individual locusts within a hopper band in a natural setting. Using automated video tracking, we derive our data from footage of four distinct hopper bands of the Australian plague locust, Chortoicetes terminifera. We reconstruct nearly twenty-thousand individual trajectories composed of over 3.3 million locust positions. We classify these data into three motion states: stationary, walking, and hopping. Distributions of relative neighbor positions reveal anisotropies that depend on motion state. Stationary locusts have high-density areas distributed around them apparently at random. Walking locusts have a low-density area in front of them. Hopping locusts have low-density areas in front and behind them. Our results suggest novel insect interactions, namely that locusts change their motion to avoid colliding with neighbors in front of them.

animal behavior and cognition↗

bioRxiv2019

Experimental and stochastic models of melanoma T-cell therapy define impact of subclone fitness on selection of antigen loss variants

Antigen loss is a key mechanism how tumor cells escape from T-cell immunotherapy. Using a mouse model of melanoma we directly compared antigen downregulation by phenotypic adaptation with genetically hardwired antigen loss. Unexpectedly, genetic ablation of Pmel, the melanocyte differentiation antigen targeted by adoptively transferred CD8+ T-cells, impaired melanoma cell growth in untreated tumors due to competitive pressure exerted by the bulk wild-type population. This established an evolutionary scenario, where T-cell immunotherapy imposed a dynamic fitness switch on wild-type melanoma cells and antigen loss variants, which resulted in highly variable enrichment of the latter in recurrent tumors. Stochastic simulations by an individual-based continuous-time Markov process suggested variable fitness of subclones within the antigen loss variant population as the most likely cause, which was validated experimentally. In summary, we provide a framework to better understand how subclone heterogeneity in tumors influences immune selection of genetic antigen loss variants through stochastic events.

systems biology↗