Biology subjects

Hernandez-Lemus, E.

Publications and source records attributed to Hernandez-Lemus, E..

11 recordsLinked to original sources

bioRxiv2026

Metabolic cost sets the shear stress profile of optimal vascular trees

Vascular remodeling responds to local wall shear stress, but transport efficiency belongs to the network as a whole. We connect these scales by minimizing dissipation under a fixed maintenance budget, with vessel cost proportional to mass raised to an exponent b. At an optimum, dissipated power is proportional to vessel cost. This yields the shear set point |{tau} | {propto} r^(b-1){ell}^(b-1)/2 for radius r and length {ell}, with uniform shear recovered at b = 1. The associated local adaptation rule decreases the global functional, although the topology it reaches retains a memory of development. Simulations with 400 and 700 sinks show that staged growth improves transport mainly by allowing pruned connections to regrow. Fluctuating demand sustains loops without increasing the maintenance budget. The local condition fixes allocation on a given support, whereas growth and variable demand shape the topology that survives.

biophysics↗

bioRxiv2025

The Crunchometer: A Low-Cost, Open-Source Acoustic Analysis of Feeding Microstructure

Elucidating the neuronal circuits that govern appetite requires precise, high-resolution monitoring of the microstructure of solid food consumption, a need unmet by existing tools, which are either costly or lack the temporal resolution to align feeding events with neuronal activity. To overcome this, we developed the Crunchometer, a low-cost, open-source acoustic system that uses computational algorithms to generate high-resolution feeding ethograms from the sounds produced during solid food consumption. Validation across energy states (hunger/satiety) confirmed its sensitivity to changes in feeding microstructure, and the system reliably detected semaglutide-induced suppression of intake and reduced preference for a high-fat diet. Leveraging its seamless integration with in vivo recordings in freely behaving mice, we paired the Crunchometer with lateral hypothalamus (LH) electrophysiology to identify "meal-related" neurons that track entire meals rather than individual bouts. Calcium imaging further revealed that distinct subsets of LH GABAergic and glutamatergic neurons were tuned to feeding only, to licking only, or to both behaviors. Thus, LH neuronal ensembles differentially encode the consumption of solid food versus liquid sucrose. These findings demonstrate that the Crunchometer is a robust, accessible platform for dissecting the neural correlates of feeding behavior at the resolution of a single bite. Significance statementThe Crunchometer is a low-cost, open-source technology that democratizes feeding analysis, enabling the precise dissection of neuronal circuits involved in appetite to advance therapies for obesity and eating disorders.

neuroscience↗

bioRxiv2024

Patient-specific gene networks reveal novel subtypes and predictive biomarkers in lung cancer

Lung adenocarcinoma (LUAD) is a highly heterogenous and aggressive form of non-small cell lung cancer (NSCLC). The use of genome-wide gene co-expression networks (GCNs) has been paramount to describe changes in the transcriptional regulatory programs found between diseased and healthy states of LUAD. Recently, studies have shown that multiple cancerous phenotypes share a distinct GCN architecture, suggesting that network topology holds promise for understanding disease pathology. However, conventional GCN inference methods struggle to capture the inherent context-specificity within a patient population, thus flattening its heterogeneity. To address this issue, the use of single-sample network (SSN) modelling has emerged as a promising solution into studying heterogeneous traits of cancer through network-based approaches. Here, we reconstructed patient-specific GCNs (n=334) using the LIONESS equation and mutual information as the network inference method. Unsupervised analysis revealed six novel LUAD subtypes based on inter-patient network similarity, each with distinct network motifs reflecting unique biological programs. Supervised analysis, employing regularized Cox regression, identified 12 genes (CHRDL2, SPP2, VAC14, IRF5, GUCY1B1, NCS1, RRM2B, EIF5A2, CCDC62, CTCFL, XG, andTP53INP2) whose weighted degree in SSNs is predictive of patient survival in LUAD. These findings suggest that topological features of SSNs offer valuable insights into the context-specific nature of LUAD malignancy, highlighting the potential of SSN-based approaches for further research.

systems biology↗

bioRxiv2024

The flow of reward information through neuronal ensembles in the accumbens

Reward information flows through neuronal ensembles in the nucleus accumbens shell (NAcSh), influencing decision-making. We investigated this phenomenon by training rats in a self-guided probabilistic choice task while recording single-unit activity in the NAcSh. We found that rats dynamically adapted their choices based on an internal representation of reward likelihood. Neuronal ensembles in the NAcSh act as dynamic modules to process different aspects of reward-guided behavior. Ensembles dynamically change composition and functional connections throughout reinforcement learning. The NAcSh forms a highly connected network with a heavy-tailed distribution and neuronal hubs, facilitating efficient reward information flow. Reward delivery evokes higher mutual information between ensembles and unifies network activity, while omission leads to less synchronization. Our recordings shed light on how reward information propagates through dynamically changing ensembles of neurons in the NAcSh. These functional ensembles exhibit flexible membership, dropping in and out and even shrinking in number as the rat learns to obtain (energy) rewards in an ever-changing environment. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=189 HEIGHT=200 SRC="FIGDIR/small/580379v2_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@1e870org.highwire.dtl.DTLVardef@1434c90org.highwire.dtl.DTLVardef@157971aorg.highwire.dtl.DTLVardef@1812ca6_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2023

A single-cell transposable element atlas of human cell identity

Single cell RNA sequencing (scRNA-seq) is revolutionizing the study of complex biological systems. However, most sequencing studies overlook the contribution of transposable element (TE) expression to the transcriptome. In both scRNA-seq and bulk tissue RNA sequencing (RNA-seq), quantification of TE expression is challenging due to repetitive sequence content and poorly characterized TE gene models. Here, we developed a tool and analysis pipeline for Single cell Transposable Element Locus Level Analysis of scRNA Sequencing (Stellarscope) that reassigns multi-mapped reads to specific genomic loci using an expectation-maximization algorithm. Using Stellarscope, we built an atlas of TE expression in human PBMCs. We found that locus-specific TEs delineate cell types and define new cell subsets not identified by standard mRNA expression profiles. Altogether, this study provides comprehensive insights into the influence of transposable elements in human biology.

genomics↗

bioRxiv2023

Differential effects of follicle-stimulating hormone glycoforms on the transcriptome profile of cultured rat granulosa cells as disclosed by RNA-seq

It has been documented that variations in glycosylation on glycoprotein hormones, confer distinctly different biological features to the corresponding glycoforms when multiple in vitro biochemical readings are analyzed. We here applied next generation RNA sequencing to explore changes in the transcriptome of rat granulosa cells exposed for 0, 6, and 12 h to 100 ng/ml of four highly purified follicle-stimulating hormone (FSH) glycoforms, each exhibiting different glycosylation patterns: human pituitary FSH18/21 and equine FSH (eqFSH) (hypo-glycosylated), and human FSH24 and chinese-hamster ovary cell-derived human recombinant FSH (recFSH) (fully-glycosylated). Total RNA from triplicate incubations was prepared from FSH glycoform-exposed cultured granulosa cells obtained from DES-pretreated immature female rats, and RNA libraries were sequenced in a HighSeq 2500 sequencer (2 x 125 bp paired-end format, 10-15 x 106 reads/sample). The computational workflow focused on investigating differences among the four FSH glycoforms at three levels: gene expression, enriched biological processes, and perturbed pathways. Among the top 200 differentially expressed genes, only 4 (0.6%) were shared by all 4 glycoforms at 6 h, whereas 118 genes (40%) were shared at 12 h. Follicle-stimulating hormone glycocoforms stimulated different patterns of exclusive and associated up regulated biological processes in a glycoform and time-dependent fashion with more shared biological processes after 12 h of exposure and fewer treatment-specific ones, except for recFSH, which exhibited stronger responses with more specifically associated processes at this time. Similar results were found for down-regulated processes, with a greater number of processes at 6 h or 12 h, depending on the particular glycoform. In general, there were fewer downregulated than upregulated processes at both 6 h and 12 h, with FSH18/21 exhibiting the largest number of down-regulated associated processes at 6 h while eqFSH exhibited the greatest number at 12 h. Signaling cascades, largely linked to cAMP-PKA, MAPK, and PI3/AKT pathways were detected as differentially activated by the glycoforms, with each glycoform exhibiting its own molecular signature. These data extend previous observations demonstrating glycosylation-dependent differential regulation of gene expression and intracellular signaling pathways triggered by FSH in granulosa cells. The results also suggest the importance of individual FSH glycoform glycosylation for the conformation of the ligand-receptor complex and induced signalling pathways.

genomics↗

bioRxiv2022

Loss of long-range co-expression is a common trait in cancer

Cancer cells display common features and enabling characteristics collectively known as the Hallmarks of Cancer, which occur alongside alterations in the regulatory mechanisms controlling gene transcription. Gene co-expression networks (GCNs) provide a framework to identify correlated gene sets that may share these regulatory mechanisms. Previously, we reported the loss of long-range co-expression in breast, lung, kidney, and hematopoietic cancer GCNs. Here, we expand the analysis to fifteen tissues, comprising 8,772 samples from two independent datasets. Unlike healthy phenotypes, cancer GCNs show that the strongest gene-pair interactions are intra-chromosomal, with their strength decaying as base-pair distance increases. Tumor GCN communities are strongly associated with cancerrelated processes and are enriched in gene families located on the same chromosome. In contrast, normal GCN communities are linked to metabolic and cell maintenance processes. Riboproteins remain highly co-expressed in both cancer and normal GCNs, highlighting their importance for cell viability. Notably, in other chronic diseases, such as Type-2 Diabetes and Alzheimers disease, the loss of long-range co-expression is absent, suggesting it is a distinctive feature of cancer.

cancer biology↗

bioRxiv2019

Highly-connected, non-redundant microRNAs functional control in breast cancer molecular subtypes

Transcriptional patterns are altered in breast cancer. These alterations capture the heterogeneity of breast cancer, leading to the emergence of molecular subtypes. Network biology approaches to study gene co-expression are able to capture the differences between breast cancer subtypes.\n\nNetwork biology approaches may be extended to include other co-expression patterns, like those found between genes and non-coding RNA: such as mi-croRNAs (miRs). Commodore miRs are microRNAs that, based on their connectivity and redundancy in co-expression networks, have been proposed as potential control elements of biological functions.\n\nIn this work, we reconstructed miR-gene co-expression networks for each breast cancer molecular subtype. We identified Commodore miRs in three out of four molecular subtypes. We found that in each subtype, each cdre-miR had a different set of associated genes, as well as a different set of associated biological functions. We used a systematic literature validation strategy, and identified that the associated biological functions to these cdre-miRs are hallmarks of cancer.

genomics↗

bioRxiv2018

Master regulators of signaling pathways coordinate key processes of embryonic development in breast cancer

Signal transduction pathways allow cells to respond to environmental cues and can induce intracellular changes. In some contexts, like embryonic development, signal transduction plays crucial roles in cell fate determination and differentiation, while in developed organisms some of this processes contribute in the maintenance of the structural integrity of tissues.\n\nTumor cells are recognized as having deregulated signaling which leads to a series of abnormal behaviors known as the hallmarks of cancer. Although gene regulation is often viewed as the last step in signal transduction, transcriptional regulation of the components of a pathway may impact in the long term deregulation observed in tumors. The study of gene regulatory networks centered around genes of the signal transduction pathways allows the identification of transcriptional regulators with the greatest influence over the signal transduction gene signature, also denominated Master Regulators.\n\nIn this work we identify, the master regulators that regulate the expression of genes of 25 relevant pathways grouped in KEGG within the category of signal transduction in a breast cancer dataset. For this purpose we implemented a modified MARINa algorithm that identifies, from a network of regulons, those that possess more differentially expressed genes related to the process to be studied. We identified CLOCK, TSHZ2, HOXA2, MEIS2, HOXA3, HAND2, HOXA5, TBX18, PEG3 and GLI2 as the top 10 master regulators of signaling pathways in breast cancer. Nine of them are recognized for taking part in embryonic development associated processes.\n\nIndividual enrichment GO biological function for each TMR regulons showed to be significantly enriched in embryonic development related processes. Hedgehog signaling pathway was shown as enriched and also highly deregulated. The genes of the HOXA family are shared among most of the TMRs. Overall, this suggests the importance of the aberrant reprogramming of mechanisms present during embryonic development, being coopted in favor of tumor development.

systems biology↗

bioRxiv2018

Loss of Trans Regulation in Breast Cancer Molecular Subtypes

Breast carcinomas are characterized by anomalous gene regulatory programs. As is well known, gene expression programs are able to shape phenotypes. Hence, the understanding of gene co-expression may shed light on the underlying mechanisms behind the transcriptional regulatory programs affecting tumor development and evolution. For instance, in breast cancer, there is a clear loss of inter-chromosomal (trans-) co-expression, compared with healthy tissue. At the same time cis- (intra-chromosomal) interactions are favored in breast tumors. In order to have a deeper understanding of regulatory phenomena in cancer, here, we constructed Gene Co-expression Networks by using 848 RNA-seq whole-genome samples corresponding to the four breast cancer molecular subtypes, as well as healthy tissue. We quantify the cis-/trans- co-expression imbalance in all phenotypes. Additionally, we measured the association between co-expression and physical distance between genes, and characterized the proportion of intra/inter-cytoband interactions per phenotype. We confirmed loss of trans- co-expression in all molecular subtypes. We also observed that gene cisco-expression decays abruptly with distance in all tumors in contrast with healthy tissue. We observed co-expressed gene hotspots, that tend to be connected at cytoband regions, and coincide accurately with already known copy number altered regions, such as Chr17q12, or Chr8q24.3 for all subtypes. Our methodology recovered different alterations already reported for specific breast cancer subtypes, showing how co-expression network approaches might help to capture distinct events that modify the cell regulatory program.

systems biology↗

bioRxiv2018

Identification of Casiopeina II-gly secondary targets through a systems pharmacology approach

Casiopeinas are a group of copper-based compounds designed to be used as less toxic, more efficient chemotherapeutic agents. In this study, we analyzed the in vitro effects of Casiopeina Il-gly on the expression of canonical biological pathways. Using microarray data from HeLa cell lines treated with Casiopeina II-gly, we identified biological pathways that are perturbed after treatment. We present a novel approach integrating pathway analysis and network theory: The Pathway Crosstalk Network. We constructed a network with deregulated pathways, featuring links between those pathways that crosstalk with each other. We identified modules grouping deregulated pathways that are functionally related. Through this approach, we were able to identify three features of Casiopeina treatment: a) Perturbation of signaling pathways, related to induction of apoptosis; b) perturbation of metabolic pathways, and c) activation of immune responses. These findings can be useful to drive new experimental exploration on their role in adverse effects and efficacy of Casiopeinas.

systems biology↗