Biology subjects

Serrano, G.

Publications and source records attributed to Serrano, G..

At least 19 recordsLinked to original sources

bioRxiv2026

Environmental gradients and habitat specificity structure benthic microbial assemblages in a temperate seagrass ecosystem

Seagrass meadows are globally distributed coastal ecosystems that provide habitats for diverse species and facilitate ecosystem services, such as carbon storage and nutrient cycling. However, factors linked to human activities and climate change are causing seagrass decline worldwide, thus impacting benthic community structure and ecosystem functioning. Although macrofaunal communities in seagrass habitats are well studied, the structure and function of bacteria/archaea and microeukaryote assemblages remains underexplored. In this study, we used environmental DNA (eDNA) metabarcoding (16S and 18S rRNA genes) to analyze bacteria/archaea (16S), microeukaryotes (18S raw sediment), and meiofauna (18S Ludox) communities in seagrass and bare sediment habitats across three sites along an estuarine gradient in Bodega Harbor, California. We found that microbial and microeukaryote communities were primarily structured by site as a response to the environmental gradient (e.g., sediment properties), whereas meiofauna responded more strongly to the presence of seagrass. Beta diversity showed strong differentiation among estuarine sites, while alpha diversity varied within sites, with bare sediments often displaying higher diversity. Network analysis revealed significant co-occurrences between bacteria and nematodes, including chemosynthetic symbiont-bearing lineages in mudflats and stress-tolerant bioindicators. Our findings underscore the importance of environmental gradients and microhabitat features in shaping benthic biodiversity in temperate seagrass ecosystems. Furthermore, it highlights potential microbial-nematode associations, likely a response to environmental variation. By integrating multiple benthic components, our study advances understanding of biodiversity drivers in temperate estuarine seagrass habitats and provides new insights on microbial community structure in these ecosystems. ImportanceSeagrass meadows, which sustain a wide variety of plant and animal life, are vital coastal habitats. These submerged ecosystems support biodiversity, protection of coasts, nitrogen cycling, and carbon storage. However, they are declining due to pressures from climate change and human activity. This study characterizes the microbial and microeukaryote communities, including meiofauna, that inhabit and surround temperate seagrass meadows. By analyzing these communities across different areas of Bodega Harbor, California, we demonstrate how seagrass and environmental factors affect the resilience and overall health of the ecosystem. Our findings highlight the importance of seagrass in maintaining biodiversity and suggest that microscale interactions and habitat variation are important factors shaping these temperate coastal ecosystems. A comprehensive understanding of the variation within benthic communities associated with seagrass habitats can significantly enhance conservation and restoration efforts for seagrass meadows..

ecology↗

bioRxiv2025

A haplotype-resolved, chromosome-scale genome assembly and annotation for Carya glabra (pignut hickory; Juglandaceae)

Carya glabra (2n = 4x = 64), also known as pignut hickory, is a widely distributed species in the walnut family (Juglandaceae). Native to the central and eastern United States and southeastern Canada, C. glabra plays an important ecological role as a common upland forest species; it is closely related to several economically valuable nut trees, including C. illinoinensis (pecan). A deeper understanding of the genetics of C. glabra is essential for studying its evolutionary history and biology, with potential implications for agricultural improvement of pecan. Here, we present the first nuclear genome assembly and annotation of C. glabra. The assembly is chromosome-level and phased, representing the first assembled polyploid genome in the genus Carya. A total of 64 pseudochromosomes were assembled and phased into four haplotypes. The haplotype A assembly spans 600.4 Mb, comprises 55.0% repetitive sequences, and contains 30,947 protein-coding genes, with a BUSCO completeness score of 97.7%. Functional annotation assigned 94.3% of haplotype A genes to gene families, and 79.7% and 86.3% of genes were annotated with Gene Ontology terms and protein domains, respectively; 635 putative plant disease resistance genes were found in haplotype A. The other three haplotypes exhibited similarly high-quality annotation metrics. Our genomic analyses also suggest that C. glabra is an autotetraploid. Comparative genomic analyses revealed high collinearity among the four haplotypes of C. glabra and the published genomes of three other Carya species, although structural variation among the genomes of these species was identified. In addition, we provide an improved chloroplast genome assembly and the first mitochondrial genome for C. glabra. Importantly, most members of the research team are undergraduate students; the sequenced individual is located in McCarty Woods, a Conservation Area on the University of Florida campus. This work highlights the value of genome assembly efforts as powerful tools for teaching genomics and supporting conservation initiatives. This first high-quality reference genome for C. glabra provides a valuable resource for studying Carya, a genus of significant ecological and economic importance. Article summaryCarya glabra (pignut hickory) is a common upland forest species in North America. This species is a member of the walnut family (Juglandaceae), which includes many economically important nut trees. Here, we present the first nuclear genome assembly and annotation of C. glabra. The assembly is chromosome-level and phased. The haplotype A assembly contains 30,947 protein-coding genes, with a BUSCO completeness score of 97.7%. Our genomic analyses suggest that C. glabra is an autopolyploid. We also provide chloroplast and mitochondrial genome assemblies. This nuclear genome provides a valuable resource for studying Carya, a genus of significant ecological and economic importance.

genomics↗

bioRxiv2025

Effects of Willow and Pine tree growth in bacterial abundance, interactions and metabolic profile in a copper mine tailing

The Cauquenes tailings is one of the largest mine tailings in Chile and represents a significant environmental hazard due to its high copper levels and acidic pH. However, there is evidence of willow and pine tree growth in these terrains, which is unexpected given the extreme conditions of this environment. Considering the importance of plants in restoration strategies, the objective of this study was to analyze the effect that willow and pine growth have on the heavy metal contents of their surrounding soil, and the abundance, interaction, metabolic profile and assembly of the bacterial community. In the Cauquenes tailing, we collected samples from willow and pine vegetated soils as well as the surrounding non-vegetated soils. We analyzed characteristics such as heavy metal concentrations and pH levels in all sampled soils, and in tree leaves and roots. Vegetated sites exhibited lower copper levels and a neutral pH, while both tree species accumulated heavy metals in their tissues. We also determined bacterial abundance in all soil samples, and co-occurrence networks were constructed to assess bacterial interactions. Both trees promoted a higher abundance of Proteobacteria and had networks with higher modularity compared to non-vegetated soils. Finally, we estimated the metabolic profile of the bacterial community using PICRUSt 2 analysis and determined carbon source utilization with BioLog Ecoplates. PICRUSt 2 predicted higher metabolic activity in vegetated soils, and BioLog Ecoplate analysis revealed the utilization of a greater number of carbon sources. The microbial communities from vegetated soils were assembled in a deterministic manner, while the community from non-vegetated soils were stochastically assembled. In conclusion, tree growth mitigated the extreme conditions of the tailing and promoted a more active and healthier bacterial community. HighlightsO_LIWillow and pine tree can grow and mitigate toxic metal conditions in the tailings C_LIO_LIBoth trees provoked a shift in bacterial abundance and interaction network C_LIO_LIThe provoked shift was tree-dependent C_LIO_LIMicrobial activity was higher in vegetated soils C_LI

microbiology↗

bioRxiv2025

Single-Cell Multiomics Reveals Regulatory Mechanisms of CAR T Cell Persistence and Dysfunction in Multiple Myeloma

Understanding the mechanisms that drive chimeric antigen receptor (CAR) T cell function and persistence in multiple myeloma (MM) remains a critical challenge for improving therapeutic outcomes. In this study, we applied single-cell multiomics and gene regulatory network (GRN) analysis to characterize the transcriptional dynamics and clonal evolution of BCMA-targeted CAR T cells in longitudinally collected bone marrow (BM) and peripheral blood (PB) samples from MM patients. Our results revealed that CAR T cells infiltrating BM exhibited a more activated and exhausted phenotype compared to their PB counterparts, with key transcriptional regulators driving these changes. Dysregulation in the effector-to-memory transition led to an increased presence of terminally differentiated CAR T cells, correlating with poor persistence. Additionally, we identified a hyperexpanded CAR T clone in the BM of a patient with partial response, marked by elevated IL10 expression. Functional analyses demonstrated that stimulation of endogenous TCR enhanced IL10 production, potentially contributing to impaired CAR T cell proliferation and persistence. These findings uncover critical regulatory mechanisms influencing CAR T cell dynamics, offering new insights into improving CAR T cell persistence and therapeutic efficacy in MM and highlights potential molecular targets for optimizing CAR T cell therapy in patients with MM.

genomics↗

bioRxiv2025

Patient-derived liver biopsy organoids enable precision alcohol-associated liver disease modeling

Background & AimsAlcohol-associated liver disease (ALD) is a major cause of liver disease worldwide with scarce therapeutic options. Animal models poorly recapitulate advanced ALD precluding the development of new treatments. Organoids have emerged as a powerful human-based preclinical tool. However, current patient-derived liver organoids fail to recapitulate the epithelial heterogeneity and its generation requires liver surgical resections, thus limiting personalized disease modeling. Here, we report the development of organoids from liver needle biopsies (b-Orgs) from patients with ALD. Methodsb-Orgs were generated from tru-cut biopsies from patients at early (n=28) and advanced (n=34) stages of ALD. b-Orgs were characterized by immunofluorescence, bulk and single cell RNA-sequencing and compared to parental tissues. b-Orgs were used to model ALD progression, identify pathogenic drivers, induce alcohol-associated hepatitis (AH) and evaluate response to prednisolone. ResultsPhenotypic and functional analysis of b-Orgs showed hepatocyte- enriched features. Single-cell RNA-sequencing revealed a heterogeneous cell composition comprising hepatocyte, biliary and progenitor populations, mirroring the epithelial landscape found in patients with advanced ALD. Moreover, b-Orgs preserved disease-stage features and allowed to identify the association of ELF3 with cell plasticity and disease progression. Finally, stimulation of b-Orgs with drivers of ALD induced pathophysiological features of alcohol-associated hepatitis, including ROS production, lipid accumulation, inflammation and decreased cell proliferation, which were mitigated in response to prednisolone. Conclusions Overall, we provide a human-based model that recapitulates epithelial complexity and patient specific features, allowing to identify drivers of cell plasticity and expanding organoid-based liver disease modeling for personalized medicine. Impact and implications Here, we describe the generation of biopsy-derived organoids (b-Orgs) from patients with liver disease. b-Orgs reproduce the liver epithelial cell composition found in patients liver tissue and are efficiently generated from different stages of the disease, providing a platform for patient- tailored disease modeling and drug testing.

cell biology↗

bioRxiv2025

JIND-Multi: Leveraging Multiple Labeled Datasets for Automated Annotation of Single-Cell RNA and ATAC Data

BackgroundThe creation of single-cell atlases is essential for understanding cellular diversity and heterogeneity. However, assembling these atlases is challenging due to batch effects and the need for accurate cell annotation. Current methods for single-cell RNA and ATAC sequencing, while effective for integration, are not optimized for cell annotation. Additionally, many annotation tools rely on external databases or reference scRNA-Seq datasets, which may limit their adaptability to specific study needs, especially for rare cell-types or scATAC-Seq data. ResultsWe introduce JIND-Multi, an extended version of the JIND framework, designed to transfer cell-type labels across multiple annotated datasets. JIND-Multi significantly reduces the proportion of unclassified cells in single-cell RNA sequencing (scRNA-Seq) data while maintaining the accuracy and performance of the original JIND model. Furthermore, JIND-Multi demonstrates robust and precise annotation results in its inaugural application to scATAC-Seq data, proving its versatility and effectiveness across different single-cell sequencing technologies. ConclusionsJIND-Multi represents an improvement in cell annotation, reducing unassigned cells and offering a reliable solution for both scRNA-Seq and scATAC-Seq data. Its ability to handle multiple labeled datasets enhances the precision of annotations, making it a valuable tool for the single-cell research community. JIND-Multi is publicly available at:https://github.com/ML4BM-Lab/JIND-Multi.git.

bioinformatics↗

bioRxiv2024

Profiling extremophile bacterial communities recovered from a mining tailing against soil ecosystems through comparative genome-resolved metagenomics and evolutionary analysis

Microbial communities inhabiting mining environments harbor a diverse array of bacteria with specialized metabolic capacities adapted to extreme conditions. Here, we utilized comparative genome-resolved metagenomics of a high-quality Illumina-sequenced sample from the Cauquenes copper tailing in central Chile. We investigate the metabolic roles and evolutionary behaviors of the resident microorganisms, focusing on capacities related to copper, iron, and sulfur metabolism. We recovered 44 medium and high-quality metagenome-assembled genomes (MAGs), primarily classified belonging to phylum Actinobacteriota (21), Proteobacteria (10), and Acidobacteriota (6). These MAGs were compared to the Global Soil MAGs project (SMAG catalog), which includes bacteria from conventional or natural ecosystems, to uncover specialized properties of mining bacteria. Notably, we discovered a new phylum, Nitrospirota_A, and provided insights into the unexplored taxonomic classifications at the lowest ranks such as genus and species. Functional potential analysis revealed that the mining community has enhanced molecular capabilities associated with sulfur and copper metabolism. Evolutionary analysis revealed that mining genes involved in targeted metabolism are under strong negative selection, indicating conservative evolutionary pressure within the mining environment. In particular, it was possible to identify a MAG from the genus Acidithrix with a global dN/dS ratio greater than 1, suggesting positive selection. Additionally, core proteins essential for bacterial survival, such as flagellar motors, cell cycle regulators, and biogenesis proteins, were also under positive selection. The latter points to the need for enhanced mobility in these microorganisms to locate resources efficiently. We demonstrate that copper mining communities are diverse and possess a significant metabolic repertoire under extreme conditions in sulfur and copper proteins. Those specialized genes appear to be in a conservative state rather than undergoing adaptive evolution. This study enhances our understanding of extremophile mining microbiomes, highlighting their high variability in classification, metabolic functions, evolution, and adaptation, which can be leveraged for further biotechnological applications.

genomics↗

bioRxiv2024

Upregulation of the Proto-Oncogene Src Kinase in Alzheimer's Disease: From Molecular Interactions to Therapeutic Potential

Alzheimers disease (AD) is a progressive neurodegenerative disease, resulting in an irreversible deterioration of multiple brain regions associated with cognitive dysfunction. Phosphorylation of the microtubule-associated protein, Tau, is known to occur decades before symptomatic AD. The Src family of tyrosine kinases are known to phosphorylate select tyrosine sites on Tau and promote microtubule disassembly and subsequent neurofibrillary tangle (NFT) formation. Our data show that the proto-oncogene, non-receptor tyrosine kinase Src colocalizes with a range of late (PHF1) to early (MC1) AD-associated phosphorylated Tau epitopes. The strongest co-occurrence is seen with MC1 (probability of MC1 given Src =100%), an early AD-specific conformational dependent epitope. Single-cell RNA sequencing data of 101 subjects show that Src is upregulated in both AD inhibitory and excitatory neurons. The most significantly affected, by orders of magnitude, were excitatory neurons which are the most prone to pathological Tau accumulation. We measured Src phosphorylation by mass spectrometry across a cohort of 48 patient neocortical tissues and found that Src has increased phosphorylation on Ser75, Tyr187, and Tyr440 in AD, showing that Src kinase undergoes distinct phosphorylation alterations in AD. Through Brownian dynamics simulations of Src and Tau, we show that as Tau undergoes the transition into disease-associated paired helical filaments, there is a notable seven-fold increase in Src contact with Tau. These results collectively emphasize Src kinases central role in Tau phosphorylation and its close association with Tau epitopes, presenting a promising target for potential therapeutic intervention.

neuroscience↗

bioRxiv2023

A public resource of single cell transcriptomes and multiscale networks from persons with and without Alzheimer's disease

The emergence of technologies that can support high-throughput profiling of single cell transcriptomes offers to revolutionize the study of brain tissue from persons with and without Alzheimers disease (AD). Integration of these data with additional complementary multiomics data such as genetics, proteomics and clinical data provides powerful opportunities to link observed cell subpopulations and molecular network features within a broader disease-relevant context. We report here single nucleus RNA sequencing (snRNA-seq) profiles generated from superior frontal gyrus cortical tissue samples from 101 exceptionally well characterized, aged subjects from the Banner Brain and Body Donation Program in combination with whole genome sequences. We report findings that link common AD risk variants with CR1 expression in oligodendrocytes as well as alterations in peripheral hematological lab parameters, with these observations replicated in an independent, prospective cohort study of ageing and dementia. We also observed an AD-associated CD83(+) microglial subtype with unique molecular networks that encompass many known regulators of AD-relevant microglial biology, and which are associated with immunoglobulin IgG4 production in the transverse colon. These findings illustrate the power of multi-tissue molecular profiling to contextualize snRNA-seq brain transcriptomics and reveal novel disease biology. The transcriptomic, genetic, phenotypic, and network data resources described within this study are available for access and utilization by the scientific community.

genomics↗

bioRxiv2023

Single cell profiling of del(5q) MDS unveils its transcriptional landscape and the impact of lenalidomide

While del(5q) MDS patients comprise a well-defined hematological subgroup, the molecular basis underlying its origin, and the reason behind the relapse after lenalidomide remains unknown. Using scRNA-seq on CD34+ progenitor cells from patients with del(5q) MDS we were able to identify cells harboring the deletion, enabling us to deeply characterize the transcriptional impact of this genetic insult on disease pathogenesis and treatment response. We found, across all patients, an enrichment of del(5q) cells in GMP and megakaryocyte-erythroid progenitors not described to date. Interestingly, both del(5q) and non-del(5q) cells presented similar transcriptional lesions when compared to progenitors from healthy individuals, indicating that all cells, and not only those harboring the deletion, are altered in these patients and may contribute to aberrant hematopoietic differentiation. However, GRN analysis revealed a group of regulons with aberrant activity in del(5q) cells that could be responsible for triggering altered hematopoiesis, pointing to a more prominent role of these cells in the phenotype of these patients. An analysis of del(5q) MDS patients achieving hematological response upon lenalidomide treatment showed that the drug reverted several transcriptional alterations in both del(5q) and non-del(5q) cells, but other lesions remained, which may be responsible for potential future relapses. Moreover, lack of hematological response was associated with the inability of lenalidomide to reverse transcriptional alterations. Collectively, this study provides a deep characterization of del(5q) and non-del(5q) cells at single-cell resolution, revealing previously unknown transcriptional alterations that could contribute to disease pathogenesis, or lack of responsiveness to lenalidomide. KEY POINTS- Del(5q) and non-del(5q) CD34+ cells share similar transcriptional alterations, with del(5q) cells presenting additional lesions. - Hematological response to lenalidomide is associated with the reversal of some transcriptional lesions in del(5q) and non-del(5q) cells

cancer biology↗

bioRxiv2023

GeNNius: An ultrafast drug-target interaction inference method based on graph neural networks

Drug-target interaction (DTI) prediction is a relevant but challenging task in the drug repurposing field. In-silico approaches have drawn particular attention as they can reduce associated costs and time commitment of traditional methodologies. Yet, current state-of-the-art methods present several limitations: existing DTI prediction approaches are computationally expensive, thereby hindering the ability to use large networks and exploit available datasets and, the generalization to unseen datasets of DTI prediction methods remains unexplored, which could potentially improve the development processes of DTI inferring approaches in terms of accuracy and robustness. In this work, we introduce GO_SCPLOWEC_SCPLOWnnO_SCPLOWIUSC_SCPLOW (Graph Embedding Neural Network Interaction Uncovering System), a Graph Neural Network (GNN)-based method that outperforms state-of-the-art models in terms of both accuracy and time efficiency across a variety of datasets. We also demonstrated its prediction power to uncover new interactions by evaluating not previously known DTIs for each dataset. We further assessed the generalization capability of GO_SCPLOWEC_SCPLOWnnO_SCPLOWIUSC_SCPLOW by training and testing it on different datasets, showing that this framework can potentially improve the DTI prediction task by training on large datasets and testing on smaller ones. Finally, we investigated qualitatively the embeddings generated by GO_SCPLOWEC_SCPLOWnnO_SCPLOWIUSC_SCPLOW, revealing that the GNN encoder maintains biological information after the graph convolutions while diffusing this information through nodes, eventually distinguishing protein families in the node embedding space. Code Availabilityhttps://github.com/ubioinformat/GeNNius

bioinformatics↗

bioRxiv2022

Aging impairs the clustering and reduces the activity of L-type calcium channels in cardiac pacemaker cells

Every heartbeat is initiated by a spontaneous electrical signal generated inside the cardiac pacemaker. The generation of this electrical signal depends on the coordinated opening and closing of different ion channels, where voltage-gated L-type calcium channels play a central role. Despite the reliability of the pacemaker, all mammals experience a linear slowdown of the pacemaker rate with age. In humans, this slowing can become pathological and constitutes the main cause for the requirement of the implantation of artificial pacemakers. However, the mechanisms behind the age-associated slowdown of the pacemaker are not well understood. Here, we show that age alters L-type calcium channels in pacemaker cells from mice. The age-associated alterations include: i) a reduction in the density of the channels at the plasma membrane, ii) a reduction in the clustering of the channels, and iii) a decrease in channel open probability. Altogether, these age-associated alterations result in a global reduction of the L-type calcium current density and in a slowdown of the pacemaker diastolic depolarization. Remarkably, increasing the open probability of L-type calcium channels pharmacologically was enough to restore pacemaker rate in old cells to the same levels observed in the young. Overall, our findings provide evidence that proper organization and function of L-type calcium channels is impaired by aging and that this dysfunction contributes to the slowdown of pacemaker cells in old animals.

biophysics↗

bioRxiv2022

Evolution of decreased aggression in honey bees targeted brain cell gene regulatory networks

Understanding how genotypic variation results in phenotypic variation, a major challenge in biology, is especially difficult for collective behaviour because collective group phenotypes arise from complex interactions between group members1. Honeybees aggressively defend their colony from attacks with highly integrated collective behaviour in which different groups of bees play specific roles, giving rise to distinct colony-level differences in aggression. A previous genome-wide association study of a population of Africanized honeybees (Apis mellifera scutellata) from Puerto Rico that recently evolved decreased aggression identified hundreds of genes with single nucleotide polymorphisms (SNPs) that associated with colony-level variation in aggression2. Many of these SNPs also showed strong signals of selection for decreased aggression2,3, but their influence on brain function was unknown. Using brain single-cell (sc) transcriptomics and sc gene regulatory network analysis, we show here that variants of these genes give rise to genetic differences in transcription factor-target gene relationships. These differences involved the activity of several TFs, some that have been previously associated with aggression, like single stranded-binding protein c31A, and some that have been associated with tissue morphogenesis but not behaviour, like apontic. The activity of these and other TFs was located in specific brain cell populations related to olfaction and vision, the two sensory modalities that bees use in colony defence. They also implicate metabolism of serotonin, a neurochemical already known to influence honeybee aggression, but not from a genetic perspective. Surprisingly, genetic differences were more pronounced in the brains of forager bees than in similarly aged but more aggressive soldier bees, pointing to an evolutionary change in division of labour for colony defence. Our results demonstrate how group genetics can shape a collective phenotype by modulating individual brain gene regulatory network architecture.

genomics↗

bioRxiv2021

Transcriptional regulation of HSCs in Aging and MDS reveals DDIT3 as a Potential Driver of Transformation

Myelodysplastic syndromes (MDS) are hematopoietic stem cell (HSC) malignancies characterized by ineffective hematopoiesis, with increased incidence in elderly individuals. In this work, we analyzed the transcriptome of human HSCs purified from young and elderly healthy donors, as well as MDS patients, identifying transcriptional alterations following eight different patterns of expression. While aging-associated lesions seemed to predispose HSCs to myeloid transformation, disease-specific alterations may trigger MDS development. Among MDS-specific lesions, we detected the upregulation of the transcription factor DDIT3. Overexpression of DDIT3 in human healthy HSCs induced an MDS-like transcriptional state, and a delay in erythropoiesis. Such effect was associated with downregulation of transcription factors required for normal erythropoiesis, and with a failure in the activation of their transcriptional programs. Moreover, DDIT3 knockdown in CD34+ cells from MDS patients with anemia was able to restore erythropoiesis. These results identify DDIT3 as a driver of dyserythropoiesis, and a potential therapeutic target to restore the inefficient erythropoiesis characterizing MDS patients. STATEMENT OF SIGNIFICANCEThis study defines how human aging and MDS development are characterized by transcriptional alterations in HSCs that follow different patterns, some of which may contribute to myeloid transformation. Among them, we demonstrate how MDS-specific upregulation of DDIT3 in HSCs induces dyserythropoiesis, while its knockdown in HSPCs from MDS patients restores proper erythroid differentiation.

cancer biology↗

bioRxiv2021

Uncovering perturbations in human hematopoiesis associated with healthy aging and myeloid malignancies at single cell resolution

Early hematopoiesis is a continuous process in which hematopoietic stem and progenitor cells (HSPCs) gradually differentiate toward specific lineages. Aging and myeloid malignant transformation are characterized by changes in the composition and regulation of HSPCs. In this study, we used single cell RNA sequencing (scRNAseq) to characterize an enriched population of human hematopoietic stem and progenitor cells (HSPC) obtained from young and elderly healthy individuals. Based on their transcriptional profile, we identified changes in the proportions of progenitor compartments during aging, and differences in their functionality, as evidenced by gene set enrichment analysis. Trajectory inference revealed that altered gene expression dynamics accompanied cell differentiation, which could explain age-associated changes in hematopoiesis. Next, we focused on key regulators of transcription by constructing gene regulatory networks and detected regulons that were specifically active in elderly individuals. Using previous findings in healthy cells as a reference, we analyzed scRNA-seq data obtained from patients with myelodysplastic syndrome (MDS) and detected specific alterations of the expression dynamics of genes involved in erythroid differentiation in all patients with MDS such as TRIB2. In addition, the comparison between transcriptional programs and GRN regulating normal HSPCs and MDS HSPCs allowed identification of regulons that were specifically active in MDS cases such as SMAD1, HOXA6, POU2F2 and RUNX1 suggesting a role of these TF in the pathogenesis of the disease. In summary, we demonstrate that the combination of single cell technologies with computational analysis tools enable the study of a variety of cellular mechanisms involved in early hematopoiesis and can be used to dissect perturbed differentiation trajectories associated with aging and malignant transformation. Furthermore, the identification of abnormal regulatory mechanisms associated with myeloid malignancies could be exploited for personalized therapeutic approaches in individual patients.

genomics↗

bioRxiv2020

JIND: Joint Integration and Discrimination for Automated Single-Cell Annotation

Single-cell RNA-seq is a powerful tool in the study of the cellular composition of different tissues and organisms. A key step in the analysis pipeline is the annotation of cell-types based on the expression of specific marker genes. Since manual annotation is labor-intensive and does not scale to large datasets, several methods for automated cell-type annotation have been proposed based on supervised learning. However, these methods generally require feature extraction and batch alignment prior to classification, and their performance may become unreliable in the presence of cell-types with very similar transcriptomic profiles, such as differentiating cells. We propose JIND, a framework for automated cell-type identification based on neural networks that directly learns a low-dimensional representation (latent code) in which cell-types can be reliably determined. To account for batch effects, JIND performs a novel asymmetric alignment in which the transcriptomic profile of unseen cells is mapped onto the previously learned latent space, hence avoiding the need of retraining the model whenever a new dataset becomes available. JIND also learns cell-type-specific confidence thresholds to identify and reject cells that cannot be reliably classified. We show on datasets with and without batch effects that JIND classifies cells more accurately than previously proposed methods while rejecting only a small proportion of cells. Moreover, JIND batch alignment is parallelizable, being more than five or six times faster than Seurat integration. Availability: https://github.com/mohit1997/JIND.

bioinformatics↗

bioRxiv2020

Transcriptional profiling of Multiple System Atrophy cerebellar tissue highlights differences between the parkinsonian and cerebellar sub-types of the disease

Multiple system atrophy (MSA) is a rare adult-onset neurodegenerative disease of unknown cause, with no effective therapeutic options, and no cure. Limited work to date has attempted to characterize the transcriptional changes associated with the disease, which presents as either predominating parkinsonian (MSA-P) or cerebellar (MSC-C) symptoms. We report here the results of RNA expression profiling of cerebellar white matter (CWM) tissue from two independent cohorts of MSA patients (n=66) and healthy controls (HC; n=66). RNA samples from bulk brain tissue and from oligodendrocytes obtained by laser capture microdissection (LCM) were sequenced. Differentially expressed genes (DEGs) were obtained and were examined before and after stratifying by MSA clinical sub-type. We detected the highest number of DEGs in the MSA-C group (n = 747) while only one gene was noted in MSA-P, highlighting the larger dysregulation of the transcriptome in the MSA-C CWM. Results from both bulk tissue and LCM analysis of MSA-C showed a downregulation of oligodendrocyte genes and an enrichment for myelination processes with a key role noted for the QKI gene. Additionally, we observed a significant upregulation of neuron-specific gene expression in MSA-C and an enrichment for synaptic processes. A third cluster of genes was associated with the upregulation of astrocyte and endothelial genes, two cell types with a key role in inflammation processes. Finally, network analysis in MSA-C showed enrichment for {beta}-amyloid related functional classes, including the known Alzheimers disease (AD) genes, APP and PSEN1. This is the largest RNA profiling study ever conducted on post-mortem brain tissue from MSA patients. We were able to define specific gene expression signatures for MSA-C highlighting the different stages of the complex neurodegenerative cascade of the disease that included alterations in several cell-specific transcriptional programs. Finally, several results suggest a common transcriptional dysregulation between MSA and AD-related genes despite the clinical and neuropathological distinctions between the two diseases.

genomics↗

bioRxiv2019

Alzheimer’s patient brain myeloid cells exhibit enhanced aging and unique transcriptional activation

Gene expression changes in brain microglia from mouse models of Alzheimers disease (AD) are highly characterized and reflect specific myeloid cell activation states that could modulate AD risk or progression. While some groups have produced valuable expression profiles for human brain cells1-4, the cellular clarity with which we now view transcriptional responses in mouse AD models has not yet been realized for human AD tissues due to limited availability of fresh tissue samples and technological hurdles of recovering transcriptomic data with cell-type resolution from frozen samples. We developed a novel method for isolating multiple cell types from frozen post-mortem specimens of superior frontal gyrus for RNA-Seq and identified 66 genes differentially expressed between AD and control subjects in the myeloid cell compartment. Myeloid cells sorted from fusiform gyrus of the same subjects showed similar changes, and whole tissue RNA analyses further corroborated our findings. The changes we observed did not resemble the \"damage-associated microglia\" (DAM) profile described in mouse AD models5, or other known activation states from other disease models. Instead, roughly half of the changes were consistent with an \"enhanced human aging\" phenotype, whereas the other half, including the AD risk gene APOE, were altered in AD myeloid cells but not differentially expressed with age. We refer to this novel profile in human Alzheimers microglia/myeloid cells as the HAM signature. These results, which can be browsed at research-pub.gene.com/BrainMyeloidLandscape/reviewVersion, highlight considerable differences between myeloid activation in mouse models and human disease, and provide a genome-wide picture of brain myeloid activation in human AD.

neuroscience↗