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Maestas, M. M.

Publications and source records attributed to Maestas, M. M..

5 recordsLinked to original sources

A digital twin of pancreatic islet differentiation predicts cell fate

The controlled generation of mature stem cell-derived islets (SC-islets) remains a barrier to scalable cell therapy for diabetes. Here, we develop a predictive digital model defining the cell-state-specific regulatory logic governing fate specification during human SC-islet differentiation. We integrate 400,603 cells from 9 original single-cell multiomic datasets and 52 public single-cell RNA-seq and ATAC-seq datasets across 4 cell lines and 7 differentiation protocols. This model resolves transcriptional and chromatin accessibility dynamics while enabling time-resolved inference and in silico perturbation of cell-state-specific gene regulatory networks. We identify regulators across trajectories from endoderm progenitors to pancreatic exocrine and endocrine lineages, nominating new candidate regulators. Among these candidates, we validate previously unreported roles for STAT1 as an exocrine driver and ZEB1 as a dynamic regulator of early endocrine specification and later off-target serotonergic islet cell fate. This work provides an experimentally supported predictive framework and an interactive resource comprising 1,116 simulations to prioritize transcription factors and intervention windows for refining SC-islet differentiation.

cell biology↗

Optimizing Post-Transplantation Detection of Subcutaneously Transplanted Islets Using Dithizone Staining

IntroductionPancreatic islet transplantation is a promising therapeutic strategy to restore insulin independence in patients with type 1 diabetes mellitus. In addition to primary human islets, human pluripotent stem cell-derived islets have shown clinical promise. However, optimizing transplantation sites and improving methods for standardized islet dosing and post-transplant graft localization are key limitations. The subcutaneous space offers an alternative site for transplantation due to its accessibility and minimally invasive nature; nevertheless, poor vascularization and difficulty locating engrafted islets limit its experimental utility. The use of dithizone, a zinc-chelating dye that selectively binds the high intracellular zinc concentrations of insulin-producing {beta}-cells, may enable rapid graft localization through selective staining. Here, we investigate whether dithizone staining can reliably localize transplanted islet grafts within the subcutaneous space of murine models. MethodsSC-islets were generated from HUES8 stem cells and functionally validated using glucose-stimulated insulin secretion. Islet volume was standardized prior to transplantation using automated islet equivalent quantification with the BioRep Islet Cell Counter. Approximately 4,000 islet equivalents of either SC-islets or primary human islets were transplanted into the subcutaneous space of immunodeficient mice. Graft function was assessed longitudinally via blood glucose monitoring, glucose tolerance testing, and human C-peptide measurements. Four weeks post-transplantation, dithizone staining was applied to harvested skin tissue to localize islet grafts, and immunohistochemical validation was performed. ResultsAutomated quantification of islet equivalents enabled consistent dosing across transplantation groups. Transplanted islets maintained function in vivo, as demonstrated by reduced blood glucose levels, preserved glucose tolerance, and detectable human C-peptide. Dithizone staining produced clear and selective red labeling of insulin-producing {beta}-cell grafts within the subcutaneous tissue, enabling reliable localization and recovery of engrafted islets. Immunohistochemical analyses confirmed the presence of insulin-expressing cells at isolated islet grafts. DiscussionDithizone staining is a rapid, cost-effective approach to identify subcutaneous islet grafts and enables downstream analyses, addressing a significant limitation in islet transplantation research. When combined with standardized pre-transplant islet quantification, this approach provides a cohesive and reproducible framework for evaluating subcutaneous islet transplantation. Future studies could complement these results by assessing the potential effects of dithizone exposure and exploring its applicability across other transplantation sites and imaging modalities.

cell biology↗

Divergent Cell-Type Specific Hypoxia Responses in Human Stem Cell-Derived and Primary Islets

BackgroundThe success of stem cell-derived islet (SC-islet) therapy for type 1 diabetes is limited by poor graft survival in the hypoxic post-transplantation microenvironment. While the response of SC-islets to chronic hypoxia has been studied, a direct comparison to primary human islets during the acute hypoxic phase has not been performed. Here, we conduct a comparative single-cell transcriptomic and functional analysis of human SC-islets and primary islets exposed to acute hypoxia (1% O2) over 48 hours. ResultsOur analysis reveals two divergent response patterns. Primary islets exhibit an energy-conserving response, characterized by a {beta}-cell-specific suppression of identity genes (PDX1, MAFA) and pro-apoptotic factors like DDIT3, alongside a shift toward metabolic quiescence. In contrast, the SC-islet response is characterized by lineage instability, a significant metabolic shift toward glycolysis, and the activation of pro-apoptotic pathways. Functionally, these transcriptomic differences result in a loss of glucose-stimulated insulin secretion in both islet types, but through different mechanisms: a suppression of secretion in primary islets versus dysregulated, glucose-unresponsive insulin release in SC-islets. ConclusionThese findings demonstrate that SC-islets are particularly vulnerable under hypoxic stress, exhibiting an unstable, plastic phenotype. This comparative dataset provides a resource for developing source-specific therapeutic interventions to overcome the hypoxic barrier and improve the efficacy of cell replacement therapies.

cell biology↗

Controlling human stem cell-derived islet composition using magnetic sorting

Stem cell-derived islets (SC-islets) consists of multiple hormone-producing cell types and offer a promising therapeutic avenue for treating type 1 diabetes (T1D). Currently, the composition of cell types generated within these SC-islets currently cannot be controlled via soluble factors during this differentiation process and consist of off-target cell types. In this study, we devised a magnetic-activated cell sorting (MACS) protocol to enrich SC-islets for CD49a, a marker associated with functional insulin-producing {beta} cells. SC-islets were generated from human pluripotent stem cells (hPSCs) using an adherent differentiation protocol and then sorted and aggregated into islet-like clusters to produce CD49a-enriched, CD49a-depleted, and unsorted SC-islets. Single-cell RNA sequencing (scRNA-seq) and immunostaining revealed that CD49a-enriched SC-islets had higher proportions of {beta} cells and improved transcriptional identity compared to other cell types. Functional assays demonstrated that CD49a-enriched SC-islets exhibited enhanced glucose-stimulated insulin secretion both in vitro and in vivo following transplantation into diabetic mice. These findings suggest that CD49a-based sorting significantly improves {beta} cell identity and the overall function of SC-islets, improving their effectiveness for T1D cell replacement therapies.

bioengineering↗

Multiomic profiling defines cell fate plasticity of in vitro-derived islets

Transplantation of insulin-secreting {beta}-cells differentiated from human pluripotent stem cells holds great potential as a cell therapy for treating insulin-dependent diabetes. While these stem cell-derived islets (SC-islets) are able to reverse diabetes in animal models, they are not fully equivalent to their in vivo counterparts. To better define the state of the cell types generated within these SC-islets and provide a resource for identifying deficiencies in lineage specification, we used single-cell multiomic sequencing to simultaneously measure the chromatin accessibility and transcriptional profiles of SC-islets at multiple time points as well as primary human islets. The integrated analysis of both the transcriptional and chromatin landscape for each cell provided greater resolution for defining cell identity, allowing us to derive novel gene lists for identifying each islet cell type. Furthermore, this multiomic analysis revealed that the difference between SC-{beta} cells and enterochromaffin-like cells, which are a major off-target from in vitro differentiation, is a gradient of progressive cell states rather than a stark difference in identity. The chromatin landscape of primary human islets was much more restricted, suggesting that stem cell-derived cells are not fully locked into their cell fate. While long term culture of SC-islets both in vitro and in vivo does close overall chromatin state, only in vivo transplantation directs cells toward their correct identities. Collectively, our multiomic analysis demonstrates that both the chromatin and transcriptional landscapes play significant roles in islet cell identity, and these data can be used as a resource to identify specific deficiencies in the chromatin and transcriptional state of SC-islet cell types.

cell biology↗