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Lerner, J.

Publications and source records attributed to Lerner, J..

6 recordsLinked to original sources

Community reorganization without collapse in a warming world: Habitat-contingent, trait-mediated biodiversity change within a conserved multi-scale structure

Biodiversity change under sustained environmental pressure is increasingly understood as a process of long-term reorganization across spatial scales rather than uniform loss or gain. Estuarine ecosystems, which experience strong environmental gradients and frequent short-term extreme disturbances, provide an ideal context for evaluating how local (), spatial ({beta}), and regional ({gamma}) diversity reorganize across habitat domains and functional guilds through time. Here, we examined four decades of fish and invertebrate community data from a coastwide, ecological monitoring program, spanning multiple estuarine systems along the Texas coast. We asked three main questions: whether habitat context modifies the direction of trait-mediated biodiversity responses across the full -{beta}-{gamma} structure; whether spatial homogenization is detectable through dominance-weighted {beta}-diversity metrics and how they relate to richness-based metrics; and whether the pace of reorganization has intensified over time. Functional traits related to dispersal capacity and thermal affinity structured the magnitude of biodiversity change within habitat domains, but habitat context determined its direction, the same guilds exhibited opposite diversity trajectories across gear-defined habitat domains despite broadly similar functional composition, demonstrating that trait-based forecasting frameworks will mispredict reorganization direction when habitat context is ignored. Spatial homogenization proceeded undetected by richness-based {beta}-diversity metrics but was revealed through dominance-weighted measures, indicating that dominance-weighted homogenization operates through two distinct habitat-dependent mechanisms: convergence on shared warm-adapted dominant taxa in shallow assemblages, and convergence toward impoverished assemblages as dominant taxa declined in deeper habitats, both processes invisible to richness-based metrics. Despite a measurable intensification in the pace of local and regional diversity change after approximately 2000, spatial turnover among bays remained stable and -{beta}-{gamma} scaling relationships were preserved across all diversity orders, demonstrating that rapid reorganization can proceed without destabilizing fundamental metacommunity structure. Across all findings, biodiversity change was persistent, directional, and strongly habitat dependent, following a chronic rather than episodic trajectory consistent with sustained environmental processes as the primary driver.

ecology↗

Foundation cell segmentation models performance on live microscopy and spatial-omics data

Accurate cell segmentation is an essential step for quantitative analysis of biological imaging data. Recent advances in deep learning have led to the development of generalist segmentation models that perform robustly across multiple imaging modalities, including label-free phase contrast, fluorescence cell culture, and multiplexed fluorescence tissue imaging. However, systematic comparisons of these models at the level of downstream biological analysis remain limited. To address this gap, we evaluated several recent segmentation models, including Cellpose cyto3, Cellpose-SAM, {micro}SAM, and CellSAM, on phase contrast and fluorescence cell culture images. In addition, Mesmer and InstanSeg were included for benchmarking on multiplexed fluorescence tissue images generated using CO-Detection by IndEXing (CODEX). We found that Cellpose-SAM achieved strong performance on phase contrast images, while SAM-based models consistently performed well on fluorescence cell culture data. In contrast, no single model consistently outperformed others on CODEX datasets. Instead, each model exhibited distinct strengths and limitations, which led to differences in downstream analyses, including clustering and cell type identification. Together, our study emphasizes the importance of selecting segmentation models based on dataset characteristics and analytical goals, rather than relying on a single universal approach.

bioinformatics↗

Parallelized Brightfield and Fluorescence Imaging of Organoids Using a Scalable Multi-Camera Platform

Organoid viability, maturation, and growth is commonly assayed through brightfield and fluorescence microscopy using a single objective lens. However, standard microscopic imaging systems pose significant limitations for high-throughput applications, particularly in large-scale experiments where simultaneous imaging of multiple organoids requires increased throughput. There is a strong need for systems that can capture organoid growth rapidly and consistently while minimizing disturbances to culture conditions. Here, we present a novel multi-camera array scanner (MCAS) that parallelizes imaging through the simultaneous use of 48 objective lenses and sensors, resulting in a 95% reduction in acquisition times compared to commercial high-content imagers. We demonstrate and validate this system in multiple well plate formats, in both 2D and 3D neural cell cultures, and in brightfield and fluorescence. The MCAS improves efficiency for measuring organoid growth rates, assessing responses to morphogens and drugs, and measuring viral transduction efficiency. Together, these findings establish the MCAS as a scalable and versatile imaging platform for rapid phenotyping in organoid research.

neuroscience↗

Distinct Chromatin Scanning Modes Lead to Targeting of Compacted Chromatin by Pioneer Factors FOXA1 and SOX2

Pioneer transcription factors, by interacting with nucleosomes, can scan silent, compact chromatin to target gene regulatory sequences, enabling cooperative binding events that modulate local chromatin structure and gene activity. However, pioneer factors do not target all of their cognate motifs and it is unclear whether different pioneers scan compact chromatin the same way. Surprisingly, combined approaches of genomics and single-molecule tracking show that to target DNase-resistant, low-histone turnover sites, pioneer factors can use opposite dynamics of chromatin scanning. FOXA1 uses low nucleoplasmic diffusion and stable chromatin interactions, whereas SOX2 uses high nucleoplasmic diffusion and transient interactions, respectively. Despite such differences, FOXA1 and SOX2 scan low-mobility, silent chromatin to similar extents, as mediated by protein domains outside of the respective DNA binding domains. By contrast, the non-pioneer HNF4A predominantly targets DNase-sensitive, nucleosome-depleted regions. We conclude that the targeting of compact chromatin sites by pioneer factors can be through distinct dynamic processes.

molecular biology↗

Carm1 regulates the speed of C/EBPa-induced transdifferentiation by a cofactor stealing mechanism

Cell fate decisions are driven by lineage-restricted transcription factors but how they are regulated is incompletely understood. The C/EBP-induced B cell to macrophage transdifferentiation (BMT) is a powerful system to address this question. Here we describe that C/EBP with a single arginine mutation (C/EBPR35A) induces a dramatically accelerated BMT in mouse and human cells. Changes in the expression of lineage-restricted genes occur as early as within 1 hour compared to 18 hours with the wild type. Mechanistically C/EBPR35A exhibits an increased affinity for PU.1, a bi-lineage transcription factor required for C/EBP-induced BMT. The complex induces more rapid chromatin accessibility changes and an enhanced relocation (stealing) of PU.1 from B cell to myeloid gene regulatory elements. Arginine 35 is methylated by Carm1 and inhibition of the enzyme accelerates BMT, similar to the mutant. Our data suggest that the relative proportions of methylated and unmethylated C/EBP in a bipotent progenitor can determine the velocity of cell fate choice and lineage directionality.

cell biology↗

Chromosomal barcoding of E. coli populations reveals lineage diversity dynamics at high resolution

Evolutionary dynamics in large asexual populations is strongly influenced by multiple competing beneficial lineages, most of which segregate at very low frequencies. However, technical barriers to tracking a large number of these rare lineages have so far prevented a detailed elucidation of evolutionary dynamics in large bacterial populations. Here, we overcome this hurdle by developing a chromosomal barcoding technique that allows simultaneous tracking of [~]450,000 distinct lineages in E. coli. We used this technique to gather insights into the evolutionary dynamics of large (>107 cells) E. coli populations propagated for [~]420 generations in the presence of sub-inhibitory concentrations of common antibiotics. By deep sequencing the barcodes, we reconstructed trajectories of individual lineages at high frequency resolution (< 10-5). Using quantitative tools from ecology, we found that populations lost lineage diversity at distinct rates corresponding to their antibiotic regimen. Additionally, by quantifying the reproducibility of these dynamics across replicate populations, we found that some lineages had similar fates over independent experiments. Combined with an analysis of individual lineage trajectories, these results suggest how standing genetic variation and new mutations may contribute to adaptation to sub-inhibitory antibiotic levels. Altogether, our results demonstrate the power of high-resolution barcoding in studying the dynamics of bacterial evolution.

evolutionary biology↗