Biology subjects

Camunas-Soler, J.

Publications and source records attributed to Camunas-Soler, J..

14 recordsLinked to original sources

bioRxiv2026

Spatial and functional mapping of the human pancreas reveals endocrine and exocrine cell states in health and metabolic disease

The human pancreas contains diverse endocrine and exocrine cell populations whose spatial organization is essential for tissue physiology. While single-cell and spatial transcriptomics revealed molecular heterogeneity across pancreatic cell types, linking these states to physiological activity in situ has remained challenging. Here, we combined single-nucleus RNA sequencing, spatial transcriptomics, and functional calcium imaging across pancreatic samples in health and metabolic disease. We identified heterogeneous endocrine and exocrine cell states associated with obesity and diabetes, including inflammatory remodeling of acinar and ductal populations. To directly couple tissue physiology with molecular state, we developed Slice-seq, which integrates calcium imaging with spatial transcriptomics in acute pancreatic slices. Slice-seq linked local endocrine composition and transcriptional programs with {beta} cell activity and identified extra-islet {beta} cells with reduced glucose responsiveness and mitochondrial oxidative metabolism. Together, our study provides a framework for linking pancreatic cell states to tissue organization and physiological activity in health and disease.

genomics↗

bioRxiv2025

Cell-free RNA reveals host and microbial correlates of broadly neutralizing antibody development against HIV

A small number of people living with HIV (PLWH) develop broadly neutralizing antibodies (bNAbs) targeting multiple HIV strains. Although several viral and immune factors contribute to bNAb development, the genetic and environmental factors driving this response remain largely unknown. We performed combined cell-free DNA (cfDNA) and cell-free RNA (cfRNA) sequencing in 42 plasma samples from a longitudinal cohort of 14 PLWH (7 who develop bNAbs and 7 matched controls). This approach enabled us to non-invasively monitor the host transcriptome, viral genetic variation, and microbiome composition during HIV infection, and to identify molecular correlates of bNAb development. We find that development of bNAbs is associated with a transcriptomic signature of early immune activation characterized by elevated levels of MHC class I antigen presentation genes. This signature is independent of viral load or CD4 count and declines over time. In addition to host features, we recovered sufficient viral reads to reconstruct HIV consensus sequences, supporting the utility of cfRNA for viral genotyping. Finally, we also identified an enrichment of several microbial taxa in bNAb producers and increased levels of GB virus C (GBV-C), a non-pathogenic lymphotropic virus. Our findings suggest a distinct early immune activation profile in PLWH who develop bNAbs. More broadly, we show that combined cfDNA/cfRNA sequencing can reveal relationships between a protective immunogenic response to HIV infection, the host immune system, and microbiome, highlighting its potential for biomarker discovery in future vaccine and therapeutic studies. Author SummaryA subset of people living with HIV develop broadly neutralizing antibodies (bNAbs), a phenomenon that remains poorly understood but relevant to vaccine development. We applied combined cell-free RNA and DNA sequencing to 42 longitudinal plasma samples (7 bNAb producers, 7 controls) to monitor the host transcriptome, viral variation, and microbiome composition during bNAb development. Early in infection, bNAb producers showed an MHC class I-linked immune activation signature that declined over time, alongside changes in commensal microbial sequences and increased levels of GB virus C in cfRNA. These findings support the use of cfDNA/cfRNA sequencing for biomarker discovery in HIV research.

genomics↗

bioRxiv2025

The maternal inflammatory proteome during pregnancy and its role in predicting the risk of spontaneous preterm birth

BackgroundSpontaneous preterm birth (sPTB) is a significant adverse outcome of pregnancy. Being able to identify and improve the management of those who may be at risk requires robust screening methods. The use of circulating molecular markers provides a promising and non-invasive solution to this problem to allow necessary and successful intervention. The role of inflammation has been continuously demonstrated to play a key role in the onset of sPTB with intrauterine inflammation being a key driver. Here we sought out to explore the inflammatory proteome using a nested case-control approach using samples from pregnant participants in the INSIGHT cohort. ObjectivesTo explore the maternal blood proteome in the second trimester using the Olink Explore panel to identify inflammatory proteins associated with sPTB and assess their predictive value, both independently and in combination with cell-free RNA (cfRNA). Study DesignWe conducted a nested case-control study to investigate inflammatory protein profiles during the second trimester of pregnancy. A total of 138 maternal blood plasma samples were analysed using a targeted proteomic assay quantifying 384 inflammation-related proteins. Differential expression analysis and a LASSO-logistic regression model with Leave-One-Out Cross-Validation (LOOCV) were applied to evaluate the association between inflammatory biomarkers and spontaneous preterm birth (sPTB) outcomes. ResultsUsing predictive modelling of the maternal blood proteome, 16 inflammation-related proteins were identified as key discriminators of sPTB risk, with proteins such as PGF, COL9A1, CST7, CXCL6 and GALNT3 emerging as major contributors for predicting sPTB risk. Using inflammation-related maternal proteins alone to predict sPTB (<35 weeks) achieved an area under the receiver operating characteristic curve (AUC-ROC) of 0.76 (95% CI: 0.66-0.84). The incorporation of both cfRNA and proteomic data into an integrated model, improved the area under the curve to 0.85 (95% CI: 0.78-0.92). The integrated model highlighted inflammatory biomarkers that are not only implicated in preterm birth but also in essential physiological mechanisms such as placental function, tissue remodelling, and extracellular matrix composition, which are critical to maintaining pregnancy and preventing premature labour. ConclusionsThese findings demonstrate that an integrated approach using both cfRNA and proteomic signatures of the second trimester maternal blood plasma yields a more comprehensive biomarker profile for predicting preterm birth risk. This multimodal strategy not only enhances the predictive accuracy but also captures a broader array of biological signals across multiple organ systems. Compared to relying solely on inflammatory proteome markers, this multiomic method offers a deeper molecular characterisation of preterm birth risk in the maternal blood plasma.

systems biology↗

bioRxiv2025

Linking molecular pathways and islet cell dysfunction in human type 1 diabetes

Type 1 diabetes (T1D) is characterized by the autoimmune destruction of most insulin-producing {beta}-cells, along with dysregulated glucagon secretion from pancreatic -cells. We conducted an integrated analysis that combines electrophysiological and transcriptomic profiling, along with machine learning, of islet cells from T1D donors to investigate the mechanisms underlying their dysfunction. Surviving {beta}-cells exhibit altered electrophysiological properties and transcriptomic signatures indicative of increased antigen presentation, metabolic reprogramming, and impaired protein translation. In -cells, we observed hyper-responsiveness and increased exocytosis, which are associated with upregulated immune signaling, disrupted transcription factor localization and lysosome homeostasis, as well as dysregulation of mTORC1 complex signaling. Notably, key genetic risk signals for T1D were enriched in transcripts related to -cell dysfunction, including MHC class I which were closely linked with -cell dysfunction. Our data provide novel insights into the molecular underpinnings of islet cell dysfunction in T1D, highlighting pathways that may be leveraged to preserve residual {beta}-cell function and modulate -cell activity. These findings underscore the complex interplay between immune signaling, metabolic stress, and cellular identity in shaping islet cell phenotypes in T1D. HighlightsO_LISurviving {beta}-cells in T1D show disrupted electrical function linked to metabolic reprogramming and immune stress. C_LIO_LITranscripts associated with -cell dysfunction are enriched in genetic risk alleles for T1D. C_LIO_LIUpregulated MHC class I and impaired nuclear localization of key transcription factors associate with -cell dysfunction in T1D. C_LIO_LIT1D -cells exhibit increased hyper-activity, lysosomal imbalance and impaired mTORC1 signaling, which promotes dysregulated glucagon secretion. C_LI

cell biology↗

bioRxiv2023

Integration of single-cell multiomic measurements across disease states with genetics identifies mechanisms of beta cell dysfunction in type 2 diabetes

Altered function and gene regulation of pancreatic islet beta cells is a hallmark of type 2 diabetes (T2D), but a comprehensive understanding of mechanisms driving T2D is still missing. Here we integrate information from measurements of chromatin activity, gene expression and function in single beta cells with genetic association data to identify disease-causal gene regulatory changes in T2D. Using machine learning on chromatin accessibility data from 34 non-diabetic, pre-T2D and T2D donors, we robustly identify two transcriptionally and functionally distinct beta cell subtypes that undergo an abundance shift in T2D. Subtype-defining active chromatin is enriched for T2D risk variants, suggesting a causal contribution of subtype identity to T2D. Both subtypes exhibit activation of a stress-response transcriptional program and functional impairment in T2D, which is likely induced by the T2D-associated metabolic environment. Our findings demonstrate the power of multimodal single-cell measurements combined with machine learning for identifying mechanisms of complex diseases.

systems biology↗

bioRxiv2021

Heterogenous impairment of α-cell function in type 2 diabetes is linked to cell maturation state

In diabetes, glucagon secretion from pancreatic -cells is dysregulated. We examined -cells from human donors and mice using combined electrophysiological, transcriptomic, and computational approaches. Rising glucose suppresses -cell exocytosis by reducing P/Q-type Ca2+ channel activity, and this is disrupted in type 2 diabetes (T2D). Upon high-fat-feeding of mice, -cells shift towards a {beta}-cell-like electrophysiologic profile in concert with an up-regulation of the {beta}-cell Na+ channel isoform Scn9a and indications of impaired -cell identity. In human -cells we identify links between cell membrane properties and cell surface signalling receptors, mitochondrial respiratory complex assembly, and cell maturation. Cell type classification using machine learning of electrophysiology data demonstrates a heterogenous loss of electrophysiologic identity in -cells from donors with T2D. Indeed, a sub-set of -cells with impaired exocytosis is defined by an enrichment in progenitor markers suggesting important links between -cell maturation state and dysfunction in T2D. Key findingsO_LI-cell exocytosis is suppressed by glucose-dependent inhibition of P/Q-type Ca2+ currents C_LIO_LIDysfunction of -cells in type 2 diabetes is associated with a {beta}-cell-like electrophysiologic signature C_LIO_LIPatch-seq links maturation state, the mitochondrial respiratory chain, and cell surface receptor expression to -cell function C_LIO_LI-cell dysfunction occurs preferentially in cells enriched in endocrine lineage markers C_LI

cell biology↗

bioRxiv2021

Combinatorial transcription factor profiles predict mature and functional human islet α and β cells

Islet-enriched transcription factors (TFs) exert broad control over cellular processes in pancreatic and {beta} cells and changes in their expression are associated with developmental state and diabetes. However, the implications of heterogeneity in TF expression across islet cell populations are not well understood. To define this TF heterogeneity and its consequences for cellular function, we profiled >40,000 cells from normal human islets by scRNA-seq and stratified and {beta} cells based on combinatorial TF expression. Subpopulations of islet cells co-expressing ARX/MAFB ( cells) and MAFA/MAFB ({beta} cells) exhibited greater expression of key genes related to glucose sensing and hormone secretion relative to subpopulations expressing only one or neither TF. Moreover, all subpopulations were identified in native pancreatic tissue from multiple donors. By Patch-seq, MAFA/MAFB co-expressing {beta} cells showed enhanced electrophysiological activity. Thus, these results indicate combinatorial TF expression in islet and {beta} cells predicts highly functional, mature subpopulations.

genomics↗

bioRxiv2020

The type 1 diabetes at-risk allele at rs3842753 increases beta cell INS mRNA expression and variance in a meta-analysis of single cell RNA sequencing data

Type 1 diabetes is characterized by the autoimmune destruction of insulin secreting {beta} cells. Genetic variations upstream at the insulin (INS) locus contribute to ~10% of type 1 diabetes heritable risk. Multiple studies showed an association between rs3842753 C/C genotype and type 1 diabetes susceptibility, but the molecular mechanisms remain unclear. To date, no large-scale studies have looked at the effect of genetic variation at rs3842753 on INS mRNA at the single cell level. We aligned all human islet single cell RNA sequencing datasets available to us in 2020 to the reference genome GRCh38.98 and genotyped rs3842753, integrating 2315 {beta} cells and 1223 {beta}-like cells from 13 A/A protected donors, 23 A/C heterozygous donors, and 35 C/C at-risk donors, including adults without diabetes and with type 2 diabetes. INS expression mean and variance were significantly higher in single {beta} cells from females compared with males. Comparing across {beta} cells and {beta}-like cells, we found that rs3842753 C containing cells (either homozygous or heterozygous) had the highest INS expression. We also found that {beta} cells with the rs3842753 C allele had significantly higher ER stress marker gene expression compared to the A/A homozygous genotype. These findings support the emerging concept that inherited risk of type 1 diabetes may be associated with inborn, persistent elevated insulin production which may lead to {beta} cell ER stress and fragility.

cell biology↗

bioRxiv2019

NFIA regulates granule recruitment and exocytosis in the adult pancreas

After food ingestion, pancreatic cells secrete zymogen and hormone-containing granules to precisely control digestion and blood glucose levels. Identifying regulators of this process is paramount to combatting multiple pancreatic diseases. Here we show that pancreatic deletion of the transcription factor nuclear factor IA (NFIA) leads to hyperglycemia, hypoinsulinemia, and hypolipidemia. Surprisingly, insulin and digestive enzymes are produced in the absence of NFIA, however, they are not secreted properly and instead accumulate inside pancreatic cells. In NFIA-deficient mice we saw a reduction of insulin granules in the ready releasable pool and the first-phase insulin response was impaired. We found that NFIA binds to and activates Rab39b, a Rab GTPase critical for exocytosis. Re-expression of Rab39b in NFIA knockout islets restored glucose-stimulated insulin secretion. In sum, the NFIA-Rab39b axis regulates pancreatic physiology through granule recruitment and docking, linking NFIA to a new process with potential effects in diabetes, pancreatitis, and lipid disorders.

cell biology↗

bioRxiv2019

Molecular and genetic regulation of pig pancreatic islet cell development

Reliance on rodents for understanding pancreatic genetics, development and islet function could limit progress in developing interventions for human diseases like diabetes mellitus. Similarities of pancreas morphology and function suggest that porcine and human pancreas developmental biology may have useful homologies. However, little is known about pig pancreas development. To fill this knowledge gap, we investigated fetal and neonatal pig pancreas at multiple, crucial developmental stages using modern experimental approaches. Purification of islet {beta}-, - and {delta}-cells followed by transcriptome analysis (RNA-Seq) and immunohistology identified cell- and stage-specific regulation, and revealed that pig and human islet cells share characteristic features not observed in mice. Morphometric analysis also revealed endocrine cell allocation and architectural similarities between pig and human islets. Our analysis unveiled scores of signaling pathways linked to native islet {beta}-cell functional maturation, including evidence of fetal -cell GLP-1 production and signaling to {beta}-cells. Thus, the findings and resources detailed here show how pig pancreatic islet studies complement other systems for understanding the developmental programs that generate functional islet cells, and that are relevant to human pancreatic diseases. Summary StatementThis study reveals transcriptional, signaling and cellular programs governing pig pancreatic islet development, including striking similarities to human islet ontogeny, providing a novel resource for advancing human islet replacement strategies.

developmental biology↗

bioRxiv2019

Pancreas patch-seq links physiologic dysfunction in diabetes to single-cell transcriptomic phenotypes

Pancreatic islet cells regulate glucose homeostasis through insulin and glucagon secretion; dysfunction of these cells leads to severe diseases like diabetes. Prior single-cell transcriptome studies have shown heterogeneous gene expression in major islet cell-types; however it remains challenging to reconcile this transcriptomic heterogeneity with observed islet cell functional variation. Here we achieved electrophysiological profiling and single-cell RNA sequencing in the same islet cell (pancreas patch-seq) thereby linking transcriptomic phenotypes to physiologic properties. We collected 1,369 cells from the pancreas of donors with or without diabetes and assessed function-gene expression networks. We identified a set of genes and pathways that drive functional heterogeneity in {beta}-cells and used these to predict {beta}-cell electrophysiology. We also report specific transcriptional programs that correlate with dysfunction in type 2 diabetes (T2D) and extend this approach to cryopreserved cells from donors with type 1 diabetes (T1D), generating a valuable resource for understanding islet cell heterogeneity in health and disease. Key findingsO_LIPancreas patch-seq provides a single-cell survey of function-transcriptome pairing in 1,369 islet cells from donors with and without diabetes C_LIO_LIExpression of a specific subset of genes predicts {beta}-cell electrophysiology in transcriptome-function networks. C_LIO_LICompromised {beta}-cell function in T2D correlates with altered ETV1 expression and inflammatory pathways C_LIO_LIFunctional heterogeneity in -cells maps to ER stress and islet lineage markers C_LIO_LIApplication of patch-seq to cells from rare cryopreserved islets from donors with T1D C_LI

genomics↗

bioRxiv2017

A Noninvasive Molecular Clock for Fetal Development Predicts Gestational Age and Preterm Delivery

We performed a high time-resolution, longitudinal study of normal pregnancy development by measuring cell-free RNA (cfRNA) in blood from women during each week of pregnancy. Analysis of tissue-specific transcripts in these samples enabled us to follow fetal and placental development with high resolution and sensitivity, and also to detect gene-specific responses of the maternal immune system to pregnancy. We established a \"clock\" for normal pregnancy development and enabled a direct molecular approach to determine expected delivery dates with comparable accuracy to ultrasound, creating the basis for a portable, inexpensive fetal dating method. We also identified a related gene set that accurately discriminated women at risk for spontaneous preterm delivery up to two months in advance of labor, forming the basis of a potential screening test for risk of preterm delivery.

bioengineering↗

bioRxiv2017

Nonivasive prenatal diagnosis of single-gene disorders using droplet digital PCR

BackgroundPrenatal diagnosis in pregnancies at risk of single-gene disorders is currently performed using invasive methods such as chorionic villus sampling and amniocentesis. This is in contrast with screening for common aneuploidies, for which noninvasive methods with a single maternal blood sample have become standard clinical practice.\n\nMethodsWe developed a protocol for noninvasive prenatal diagnosis of inherited single gene disorders using droplet digital PCR (ddPCR) from circulating cell-free DNA (cfDNA) in maternal plasma. First, the amount of cfDNA and fetal fraction are determined using a panel of Taqman assays targeting high-variability SNPs. Second, the ratio of healthy and diseased alleles in maternal plasma are quantified using Taqman assays targeting the mutations carried by the parents. Two validation approaches of the mutation assay are presented.\n\nResultsWe collected blood samples from 9 pregnancies at risk for different single gene disorders including common conditions and rare metabolic disorders. We measured cases at risk of hemophilia, ornithine transcarbamylase deficiency, cystic fibrosis, {beta}-thalassemia, mevalonate kinase deficiency, acetylcholine receptor deficiency and DFNB1 nonsyndromic hearing loss. We correctly differentiated affected and unaffected pregnancies (2 affected, 7 unaffected), confirmed by neonatal testing. We successfully measured an affected pregnancy as early as week 11, and with a fetal fraction as low as 3.7{+/-}0.3%.\n\nConclusionOur method detects single nucleotide mutations of autosomal recessive diseases as early as the first trimester of pregnancy. This is of importance for metabolic disorders where early diagnosis can affect management of the disease and reduce complications and anxiety related to invasive testing.

genetics↗

bioRxiv2017

Humans are colonized by many uncharacterized and highly divergent microbes

Blood circulates throughout the entire body and contains molecules drawn from virtually every tissue, including the microbes and viruses which colonize the body. Through massive shotgun sequencing of circulating cell-free DNA from the blood, we identified hundreds of new bacteria and viruses which represent previously unidentified members of the human microbiome. Analysing cumulative sequence data from 1,351 blood samples collected from 188 patients enabled us to assemble 7,190 contiguous regions (contigs) larger than 1 kbp, of which 3,761 are novel with little or no sequence homology in any existing databases. The vast majority of these novel contigs possess coding sequences, and we have validated their existence both by finding their presence in independent experiments and by performing direct PCR amplification. When their nearest neighbors are located in the tree of life, many of the organisms represent entirely novel taxa, showing that microbial diversity within the human body is substantially broader than previously appreciated.

microbiology↗