Sushma Nagaraj

Single-cell and spatial transcriptomic datasets provide tremendous potential to identify the cellular states and communication networks associated with senescence. Annotating senescent cells in these datasets is hindered by the lack of universal markers for senescent cells and their context-dependent variability. To overcome this, several groups have developed gene signatures to annotate cells with distinct senotypes. However, comparing these signatures and their biological contexts to determine the specificity of senescence signatures remains complicated by the separate data platforms for signatures and datasets. We present SENgEAR, a no-code web platform for senescent cell annotation, visualization of cell-cell communication networks, and comparison of senescence signatures across studies, tissues, species, and data modalities. SENgEAR provides a unified framework to explore contextual signature specificity, cellular communication pathways, and senotype heterogeneity. We demonstrate the use of SENgEAR for applications spanning aging, fibrosis, and wound healing and its ability to interrelate these states.

Uterine fibroids (leiomyomas) are highly prevalent benign tumors defined by excessive extracellular matrix (ECM) deposition, altered vascular structure, and progressive tissue stiffening, yet the cellular programs that coordinate these features remain poorly understood. Cellular senescence has been implicated in fibroid biology, but whether senescence represents a uniform state or distinct, functionally specialized cell identities within fibroids is unknown. Here, we identify the distinct heterogeneous populations of senescent cells (“senotypes”) present in human fibroids and characterize their role in shaping the fibroid microenvironment. Using single-cell RNA sequencing (scRNA-seq) integrated with a senescence gene signature and protein-level validation, we identify senescent cells (SnC) distributed across fibroblast, mural, and endothelial compartments, each exhibiting distinct transcriptional programs. SnC endothelial cells (ECs) are enriched in fibroids relative to matched myometrium and activate TEAD4 -associated mechanosensing, angiogenic, and immune signaling pathways, despite being associated with impaired vessel maturation in situ . In parallel, SnC fibroblast and mural populations in fibroids upregulated SRF-associated cytoskeletal and ECM programs, accompanied by increased COL6A3 expression and collagen VI deposition, consistent with tissue stiffening. Ligand–receptor and spatial analyses reveal that these SnC populations function as interconnected signaling hubs, coordinating immune cell recruitment and stromal remodeling. Importantly, analysis of human fibroids treated with collagenase demonstrated a reduction in both ECM density and SnC burden, supporting a reinforcing relationship between matrix mechanics and senescence. Together, these findings establish senescence in fibroids as a heterogeneous, mechanically reinforced, and network-driven process that links vascular dysfunction, immune signaling, and fibrosis, highlighting distinct SnC states as potential translational targets for non-surgical therapies.

Fibrotic conditions contribute to significant global morbidity and mortality. Yet the underlying processes that orchestrate fibrosis remain poorly understood due to the cellular and spatial complexity of the stromal, immune, and vascular compartments that regulate fibrotic disease progression. Senescent cells (SnCs) have been implicated in fibrosis, but their roles are unclear, as evidence indicates that they serve both pathogenic and reparative functions. Here, we show that fibrosis-associated SnCs contain functionally divergent senotypes that are organized into distinct spatial niches. Using integrated single-cell and spatial transcriptomics analyses and hierarchical factorization in a murine fibrosis model, we identify fibroblast and perivascular SnC subpopulations that upregulate diverse programs related to extracellular matrix (ECM) production, immune signaling, and vascular remodeling. Fibroblast senotypes localize to discrete microenvironments with distinct tissue architectures, including niches associated with fibrotic signaling, immune activity, and cartilage development. Perivascular SnCs occupy interfaces between fibrotic signaling and immune-active niches and upregulate vascular and fibrotic remodeling pathways. Depletion of pericyte-lineage SnCs increases vascular maturation and fibrotic ECM deposition, providing mechanistic validation of the beneficial role these SnCs play in vascular remodeling and fibrosis modulation. In addition, using a new web-based infrastructure to query our senotype gene signatures in public datasets, we demonstrate that these senotypes are conserved across different murine and human fibrotic conditions. These findings establish senescence as a spatially organized regulator of fibrosis and identify perivascular senescence as a link between vascular remodeling and fibrotic outcomes.

Proper organization of the enteric nervous system (ENS) is critical for normal gastrointestinal (GI) physiology. Inflammatory bowel disease (IBD) disrupts key GI functions, including bowel motility. However, in many IBD patients, motility disorders persist even during remission, suggesting an irreversible ENS defect secondary to IBD. Here, we show that postinflammatory GI motility dysfunction arises from structural remodeling of the ENS, driven by a combination of neuronal loss and neurogenesis. During mucosal inflammation, enteric neurons upregulate CCL2 expression, facilitating the recruitment of monocytes into the myenteric plexus within the intestinal muscle. Monocyte-derived macrophages infiltrate the myenteric ganglia, contributing to excessive ENS remodeling and postinflammatory motility dysfunction. This neuroimmune axis is counterbalanced by a hypoxia-induced stress response in enteric neurons mediated by HIF1α. Enhancing the neuron-intrinsic hypoxia pathway limits ENS remodeling and preserves motility. In summary, this study presents a mechanistic model of postinflammatory GI motility dysfunction and proposes a therapeutic strategy to maintain ENS integrity and function during inflammation.

The enteric nervous system (ENS), a collection of neural cells contained in the wall of the gut, is of fundamental importance to gastrointestinal and systemic health. According to the prevailing paradigm, the ENS arises from progenitor cells migrating from the neural crest and remains largely unchanged thereafter. Here, we show that the lineage composition of maturing ENS changes with time, with a decline in the canonical lineage of neural-crest derived neurons and their replacement by a newly identified lineage of mesoderm-derived neurons. Single cell transcriptomics and immunochemical approaches establish a distinct expression profile of mesoderm-derived neurons. The dynamic balance between the proportions of neurons from these two different lineages in the post-natal gut is dependent on the availability of their respective trophic signals, GDNF-RET and HGF-MET. With increasing age, the mesoderm-derived neurons become the dominant form of neurons in the ENS, a change associated with significant functional effects on intestinal motility which can be reversed by GDNF supplementation. Transcriptomic analyses of human gut tissues show reduced GDNF-RET signaling in patients with intestinal dysmotility which is associated with reduction in neural crest-derived neuronal markers and concomitant increase in transcriptional patterns specific to mesoderm-derived neurons. Normal intestinal function in the adult gastrointestinal tract therefore appears to require an optimal balance between these two distinct lineages within the ENS.

As sequencing technologies have evolved, the tools to analyze these sequences have made similar advances. However, for multi-species samples, we observed important and adverse differences in alignment specificity and computation time for bwa- mem (Burrows–Wheeler aligner-maximum exact matches) relative to bwa-aln. Therefore, we sought to optimize bwa-mem for alignment of data from multi-species samples in order to reduce alignment time and increase the specificity of alignments. In the multi-species cases examined, there was one majority member (i.e. Plasmodium falciparum or Brugia malayi) and one minority member (i.e. human or the Wolbachia endosymbiont wBm) of the sequence data. Increasing bwa-mem seed length from the default value reduced the number of read pairs from the majority sequence member that incorrectly aligned to the reference genome of the minority sequence member. Combining both source genomes into a single reference genome increased the specificity of mapping, while also reducing the central processing unit (CPU) time. In Plasmodium, at a seed length of 18 nt, 24.1 % of reads mapped to the human genome using 1.7±0.1 CPU hours, while 83.6 % of reads mapped to the Plasmodium genome using 0.2±0.0 CPU hours (total: 107.7 % reads mapping; in 1.9±0.1 CPU hours). In contrast, 97.1 % of the reads mapped to a combined Plasmodium–human reference in only 0.7±0.0 CPU hours. Overall, the results suggest that combining all references into a single reference database and using a 23 nt seed length reduces the computational time, while maximizing specificity. Similar results were found for simulated sequence reads from a mock metagenomic data set. We found similar improvements to computation time in a publicly available human-only data set.