Biology subjects

Guevara-Coto, J.

Publications and source records attributed to Guevara-Coto, J..

5 recordsLinked to original sources

bioRxiv2025

A bistable circuit regulates miRNA-155 levels in human macrophage inflammatory transitions

Macrophages are crucial immune regulators as they can either trigger or resolve inflammation. These properties rely on defined inflammatory states and make macrophages valuable therapeutic targets. Identification of stable steady states and bistability in inflammatory transitions provides deeper insights into immune regulation and facilitates the development of novel therapeutic strategies. We present a multiomic and systems biology approach for the top-down identification of bistable circuits in human macrophages polarized towards pro- and anti-inflammatory phenotypes. Using differential gene expression profiles, we identified three criteria to suspect bistability: two potential attractors, a hysteresis behavior between their transitions, and the presence of potential modules of coregulated genes. This was further confirmed by proteomics data pointing to mutually exclusive and time-dependent profiles of gene expression. By network simplification and creation of a novel pipeline for parameter estimation in bistable models, we obtained a minimal model of inflammatory transitions in which we identified ultrasensitivity and hysteresis. Our minimal model genes establish a regulatory circuit switching miR-155 expression, which in turn regulates the expression of inflammatory marker genes during inflammatory transitions.

systems biology↗

bioRxiv2021

Persistence of SARS CoV-2 S1 Protein in CD16+ Monocytes in Post-Acute Sequelae of COVID-19 (PASC) Up to 15 Months Post-Infection

The recent COVID-19 pandemic is a treatment challenge in the acute infection stage but the recognition of chronic COVID-19 symptoms termed post-acute sequelae SARS-CoV-2 infection (PASC) may affect up to 30% of all infected individuals. The underlying mechanism and source of this distinct immunologic condition three months or more after initial infection remains elusive. Here, we investigated the presence of SARS-CoV-2 S1 protein in 46 individuals. We analyzed T-cell, B-cell, and monocytic subsets in both severe COVID-19 patients and in patients with post-acute sequelae of COVID-19 (PASC). The levels of both intermediate (CD14+, CD16+) and non-classical monocyte (CD14Lo, CD16+) were significantly elevated in PASC patients up to 15 months post-acute infection compared to healthy controls (P=0.002 and P=0.01, respectively). A statistically significant number of non-classical monocytes contained SARS-CoV-2 S1 protein in both severe (P=0.004) and PASC patients (P=0.02) out to 15 months post-infection. Non-classical monocytes were sorted from PASC patients using flow cytometric sorting and the SARS-CoV-2 S1 protein was confirmed by mass spectrometry. Cells from 4 out of 11 severe COVID-19 patients and 1 out of 26 PASC patients contained ddPCR+ peripheral blood mononuclear cells, however, only fragmented SARS-CoV-2 RNA was found in PASC patients. No full length sequences were identified, and no sequences that could account for the observed S1 protein were identified in any patient. Non-classical monocytes are capable of causing inflammation throughout the body in response to fractalkine/CX3CL1 and RANTES/CCR5.

immunology↗

bioRxiv2021

MYC dosage compensation is mediated by miRNA-transcription factor interactions in aneuploid cancer

We hypothesize that dosage compensation of critical genes arises from systems-level properties for cancer cells to withstand the negative effects of aneuploidy. We identified several candidate genes in cancer multi-omics data and developed a biocomputational platform to construct a mathematical model of their interaction network with miRNAs and transcription factors, where the property of dosage compensation emerged for MYC and was dependent on the kinetic parameters of its feedback interactions with three micro-RNAs. These circuits were experimentally validated with a novel genetic tug-of-war technique by overexpressing an exogenous MYC leading to over-expression of the three microRNAs involved and down-regulation of endogenous MYC. In addition, MYC overexpression or inhibition of its compensating miRNAs led to dosage-dependent cytotoxicity in MYC-amplified colon cancer cells. Finally, we identified negative correlation of MYC dosage compensation with patient survival in TCGA breast cancer patients, highlighting the potential of this mechanism to prevent aneuploid cancer progression. HighlightsThe systems-level property of gene dosage-compensation emerges in silico in miRNA-transcription factor networks depending on the kinetic parameters of its interactions. We established a criterion to identify compensated candidate genes with low variation in expression despite high copy number variation. BioNetUCR is a novel biocomputational platform to model miRNA-transcription factor interactions We present a novel genetic tug-of-war technique to experimentally validate gene dosage compensation at the transcriptional level. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=131 SRC="FIGDIR/small/440572v2_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@104a93forg.highwire.dtl.DTLVardef@1039ae9org.highwire.dtl.DTLVardef@1af41c6org.highwire.dtl.DTLVardef@1073e6a_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2020

Immune-Based Prediction of COVID-19 Severity and Chronicity Decoded Using Machine Learning

Individuals with systemic symptoms long after COVID-19 has cleared represent approximately ~10% of all COVID-19 infected individuals. Here we present a bioinformatics approach to predict and model the phases of COVID so that effective treatment strategies can be devised and monitored. We investigated 144 individuals including normal individuals and patients spanning the COVID-19 disease continuum. We collected plasma and isolated PBMCs from 29 normal individuals, 26 individuals with mild-moderate COVID-19, 25 individuals with severe COVID-19, and 64 individuals with Chronic COVID-19 symptoms. Immune subset profiling and a 14-plex cytokine panel were run on all patients. Data was analyzed using machine learning methods to predict and distinguish the groups from each other.Using a multi-class deep neural network classifier to better fit our prediction model, we recapitulated a 100% precision, 100% recall and F1 score of 1 on the test set. Moreover, a first score specific for the chronic COVID-19 patients was defined as S1 = (IFN-{gamma} + IL-2)/ CCL4-MIP-1{beta}. Second, a score specific for the severe COVID-19 patients was defined as S2 = (10*IL-10 + IL-6) - (IL-2 + IL-8). Severe cases are characterized by excessive inflammation and dysregulated T cell activation, recruitment, and counteracting activities. While chronic patients are characterized by a profile able to induce the activation of effector T cells with pro-inflammatory properties and the capacity of generating an effective immune response to eliminate the virus but without the proper recruitment signals to attract activated T cells. SummaryImmunologic Modeling of Severity and Chronicity of COVID-19

immunology↗

bioRxiv2020

Complex networks of miRNA-transcription factors mediate gene dosage compensation in aneuploid cancer

Cancer complexity is consequence of enormous genomic instability leading to aneuploidy, a hallmark of most cancers. We hypothesize that dosage compensation of critical genes could arise from systems-level properties of complex networks of microRNAs (miRNA) and transcription factors (TF) as a way for cancer cells to withstand the negative effects of aneuploidy. We studied gene dosage compensation at the transcriptional level on data of the NCI-60 cancer cell line panel with the aid of computational models to identify candidate genes with low tolerance to variation in gene expression despite high variation in copy numbers. We identified a network of TF and miRNAs validated interactions with those genes to construct a mathematical model where the property of dosage compensation emerged for MYC and STAT3. Compensation was mediated by feedback and feed-forward motifs with 4 miRNAs and was dependent on the kinetic parameters of these TF-miRNA interactions, indicating that network analysis was not enough to identify this emergent property. The inhibition of miRNAs compensating MYC suggest a therapeutic potential of targeting gene dosage compensation against aneuploid cancer.

systems biology↗