Biology subjects

Hernandez, A. G.

Publications and source records attributed to Hernandez, A. G..

9 recordsLinked to original sources

bioRxiv2025

Modeling cellular influence delineates functionally relevant cellular neighborhoods in primary and metastatic pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer, with liver metastases significantly worsening outcomes. However, distinct features of the tumor microenvironment (TME) between primary and metastatic sites remain poorly defined. Cellular neighborhoods within the TME are recognized as functional units that influence tumor behavior. Conventional spatial methods, which assign equal weights to all cells in a region, fail to capture the nuances of cellular interactions. To address this, we developed Functional Cellular Neighborhood (FunCN) quantification, which integrates both the proportion and proximity of surrounding cells. Applying FunCN to PDAC imaging mass cytometry data, we identified neutrophil-enriched interactions in liver metastases compared to primary tumors, correlating with elevated VISTA expression by tumor cells. Additionally, FunCN clusters around CD8+ T cells in pancreas and liver were associated with higher TIGIT and LAG3, respectively. These findings demonstrate the importance of spatial immune landscapes in PDAC and identify potential therapeutic opportunities.

systems biology↗

bioRxiv2024

Neutrophils exposed to a cholesterol metabolite secrete extracellular vesicles that promote epithelial-mesenchymal transition and stemness in breast cancer cells.

Small extracellular vesicles (sEVs) are emerging as critical mediators of intercellular communication in the tumor microenvironment (TME). Here, we investigate the mechanisms by which sEVs derived from neutrophils treated with the cholesterol metabolite, 27-hydroxycholesterol (27HC), influence breast cancer progression. sEVs released from 27HC treated neutrophils enhance epithelial-mesenchymal transition (EMT) and stem-like properties in breast cancer cells, resulting in loss of adherence, increased migratory capacity and resistance to cytotoxic chemotherapy. Decreased microRNAs (miRs) within the sEVs resulted in activation of the WNT/{beta}-catenin signaling pathway in recipient cells and suggest that this may be a predominant pathway for stem-like phenotype and EMT. Our findings underscore a novel mechanism by which 27HC-modulated neutrophils contribute to breast cancer pathophysiology through EV-mediated intercellular communication, suggesting potential therapeutic targets in cancer treatment.

cancer biology↗

bioRxiv2021

Expanding the Molecular Alphabet of DNA-Based Data Storage Systems with Neural Network Nanopore Readout Processing

DNA is a promising next-generation data storage medium, but the recording latency and synthesis cost of oligos using the four natural nucleotides remain high. Here, we describe an improved DNA-based storage system that uses an extended 11-letter molecular alphabet combining natural and chemically modified nucleotides. Our extended-alphabet molecular storage paradigm offers a nearly two-fold increase in storage density and potentially the same order of reduction in the recording time. Experimental results involving a library of 77 custom-designed hybrid sequences reveal that one can readily detect and discriminate different combinations and orders of monomers via MspA nanopores. Furthermore, a neural network architecture designed to classify raw current signals generated by Oxford Nanopore Technologies sequencing ensures an average accuracy exceeding 60%, which is 39 times higher than that of random guessing. Molecular dynamics simulations reveal that the majority of modified nucleotides do not induce dramatic disruption of the DNA double helix, making the extended alphabet system potentially compatible with PCR-based random access data retrieval. The methodologies proposed provide a forward path for new implementations of molecular recorders.

synthetic biology↗

bioRxiv2021

Rewritable Two-Dimensional DNA-Based Data Storage with Machine Learning Reconstruction

DNA-based data storage platforms traditionally encode information only in the nucleotide sequence of the molecule. Here we report on a two-dimensional molecular data storage system that records information in both the sequence and the backbone structure of DNA and performs nontrivial joint data encoding, decoding and processing. Our 2DDNA method efficiently stores high-density images in synthetic DNA and embeds pertinent metadata as nicks in the DNA backbone. To avoid costly worst-case redundancy for correcting sequencing/rewriting errors and to mitigate issues associated with mismatched decoding parameters, we develop machine learning techniques for automatic discoloration detection and image inpainting. The 2DDNA platform is experimentally tested by reconstructing a library of images with undetectable or small visual degradation after readout processing, and by erasing and rewriting copyright metadata encoded in nicks. Our results demonstrate that DNA can serve both as a write-once and rewritable memory for heterogenous data and that data can be erased in a permanent, privacy-preserving manner. Moreover, the storage system can be made robust to degrading channel qualities while avoiding global error-correction redundancy.

synthetic biology↗

bioRxiv2020

Association of common genetic variants in the CPSF7 and SDHAF2 genes with Canine Idiopathic Pulmonary Fibrosis in the West Highland White Terrier

Canine Idiopathic Pulmonary Fibrosis (CIPF) is a chronic fibrotic lung disease that is observed at a higher frequency in the West Highland White Terrier dog breed (WHWT) and may have molecular pathological overlap with human lung fibrotic disease. We conducted a Genome-Wide Association Study (GWAS) in the WHWT using Whole Genome Sequencing (WGS) to discover genetic variants associated with CIPF. Saliva-derived DNA samples were sequenced using the Riptide DNA library prep kit. After quality controls, 28 affected, 44 unaffected and 1,843,695 informative Single Nucleotide Polymorphisms (SNPs) were included in the GWAS. Data were analyzed both at the single SNP and gene levels using the GEMMA and GATES methods, respectively. We detected significant signals at the gene level in both the CPSF7 and SDHAF2 genes (adjusted p = 0.016 and p = 0.025, respectively), two overlapping genes located on chromosome 18. The top SNP for both genes was rs22669389, however it did not reach genome-wide significance in the GWAS (adjusted p = 0.078). Our studies provide, for the first time, candidate loci for CIPF in the WHWT. CPSF7 was recently associated with lung adenocarcinoma further highlighting the potential relevance of our results since IPF and lung cancer share several pathological mechanisms.

genomics↗

bioRxiv2019

Image Processing in DNA

The main obstacles for the practical deployment of DNA-based data storage platforms are the prohibitively high cost of synthetic DNA and the large number of errors introduced during synthesis. In particular, synthetic DNA products contain both individual oligo (fragment) symbol errors as well as missing DNA oligo errors, with rates that exceed those of modern storage systems by orders of magnitude. These errors can be corrected either through the use of a large number of redundant oligos or through cycles of writing, reading, and rewriting of information that eliminate the errors. Both approaches add to the overall storage cost and are hence undesirable. Here we propose the first method for storing quantized images in DNA that uses signal processing and machine learning techniques to deal with error and cost issues without resorting to the use of redundant oligos or rewriting. Our methods rely on decoupling the RGB channels of images, performing specialized quantization and compression on the individual color channels, and using new discoloration detection and image inpainting techniques. We demonstrate the performance of our approach experimentally on a collection of movie posters stored in DNA.

bioinformatics↗

bioRxiv2019

DNA Punch Cards: Encoding Data on Native DNA Sequences via Topological Modifications

Synthetic DNA-based data storage systems have received significant attention due to the promise of ultrahigh storage density and long-term stability. However, all platforms proposed so far suffer from high cost, read-write latency and error-rates that render them noncompetitive with modern optical and magnetic storage devices. One means to avoid synthesizing DNA and to reduce the system error-rates is to use readily available native DNA. As the symbol/nucleotide content of native DNA is fixed, one may adopt an alternative recording strategy that modifies the DNA topology to encode desired information. Here, we report the first macromolecular storage paradigm in which data is written in the form of "nicks (punches)" at predetermined positions on the sugar-phosphate backbone of native dsDNA. The platform accommodates parallel nicking on multiple "orthogonal" genomic DNA fragments and paired nicking and disassociation for creating "toehold" regions that enable single-bit random access and strand displacement in-memory computations. As a proof of concept, we used the programmable restriction enzyme Pyrococcus furiosus Argonaute to punch two files into the PCR products of Escherichia coli genomic DNA. The encoded data is accurately reconstructed through high-throughput sequencing and read alignment.

synthetic biology↗

bioRxiv2018

Sex-dependent dominance maintains migration supergene in rainbow trout

Traits with different fitness optima in males and females cause sexual conflict when they have a shared genetic basis. Heteromorphic sex chromosomes can resolve this conflict and protect sexually antagonistic polymorphisms but accumulate deleterious mutations. However, many taxa lack differentiated sex chromosomes, and how sexual conflict is resolved in these species is largely unknown. Here we present a chromosome-anchored genome assembly for rainbow trout (Oncorhynchus mykiss) and characterize a 56 Mb double-inversion supergene that mediates sex-specific migration through sex-dependent dominance, a mechanism that reduces sexual conflict. The double-inversion contains key photosensory, circadian rhythm, adiposity, and sexual differentiation genes and displays frequency clines associated with latitude and temperature, revealing environmental dependence. Our results constitute the first example of sex-dependent dominance across a large autosomal supergene, a novel mechanism for sexual conflict resolution capable of protecting polygenic sexually antagonistic variation while avoiding the homozygous lethality and deleterious mutation load of heteromorphic sex chromosomes.

evolutionary biology↗

bioRxiv2017

Genome-wide Association Studies Reveal Similar Genetic Architecture with Shared and Unique QTL for Bacterial Cold Water Disease Resistance in Two Rainbow Trout Breeding Populations

Bacterial cold water disease (BCWD) causes significant mortality and economic losses in salmonid aquaculture. In previous studies, we identified moderate-large effect QTL for BCWD resistance in rainbow trout (Oncorhynchus mykiss). However, the recent availability of a 57K SNP array and a genome physical map have enabled us to conduct genome-wide association studies (GWAS) that overcome several experimental limitations from our previous work. In the current study, we conducted GWAS for BCWD resistance in two rainbow trout breeding populations using two genotyping platforms, the 57K Affymetrix SNP array and restriction-associated DNA (RAD) sequencing. Overall, we identified 14 moderate-large effect QTL that explained up to 60.8% of the genetic variance in one of the two populations and 27.7% in the other. Four of these QTL were found in both populations explaining a substantial proportion of the variance, although major differences were also detected between the two populations. Our results confirm that BCWD resistance is controlled by the oligogenic inheritance of few moderate-large effect loci and a large-unknown number of loci each having a small effect on BCWD resistance. We detected differences in QTL number and genome location between two GWAS models (weighted single-step GBLUP and Bayes B), which highlights the utility of using different models to uncover QTL. The RAD-SNPs detected a greater number of QTL than the 57K SNP array in one population, suggesting that the RAD-SNPs may uncover polymorphisms that are more unique and informative for the specific population in which they were discovered.

genetics↗