Biology subjects

Dias, N.

Publications and source records attributed to Dias, N..

4 recordsLinked to original sources

bioRxiv2025

Imputing missing minimum inhibitory concentration (MIC) values for Pseudomonas aeruginosa strains with a Denoising AutoEncoder

Pseudomonas aeruginosa is a problematic pathogen with complex antibiotic resistance patterns. In clinical practice, minimum inhibitory concentration (MIC) tests typically focus on a limited subset of antibiotics, hindering a comprehensive assessment of a strains resistance profile. Here, we introduce MICFiller, a Denoising AutoEncoder (DAE) model designed to impute missing MIC values for 14 antibiotics in Pseudomonas aeruginosa within a specific dilution range by leveraging known MIC measurements for other antibiotics in the same strain. We evaluated the performance of DAE against two other commonly used methods: Multiple Imputation by Chained Equations (MICE) and simple median imputation. The DAE achieved the highest balanced 1-tier accuracy for most antibiotics, with performance closely matching that of MICE. MICFiller is freely accessible through a user-friendly web interface at http://iorgalab.org:4567/micfiller, offering clinicians a more complete view of a strains antibiotic resistance profile.

microbiology↗

bioRxiv2024

A second wave of Notch signaling diversifies the intestinal secretory lineage

The small intestine is well known for the function of its nutrient-absorbing enterocytes; yet equally critical for the maintenance of homeostasis is a diverse set of secretory cells, all of which are presumed to differentiate from the same intestinal stem cell. Despite major roles in intestinal function and health, understanding how the full spectrum of secretory cell types arises remains a longstanding challenge, largely due to their comparative rarity. Here, we investigate the fate specification of a rare and distinct population of small intestinal epithelial cells found in rats and humans but not mice: CFTR High Expressers (CHEs). We use pseudotime trajectory analysis of single-cell RNA-seq data from rat intestinal jejunum to provide evidence that CHEs are specified along the secretory lineage and appear to employ a second wave of Notch-based signal transduction to distinguish these cells from other secretory cell types. We further validate the general order of transcription factors that direct these cells from unspecified progenitors within the crypt and experimentally demonstrate that Notch signaling is necessary to induce CHE fate both in vivo and in vitro. Our results suggest a model in which Notch is reactivated along the secretory lineage to specify the CHE population: a rare secretory cell type with putative functions in localized coordination of luminal pH and direct relevance to cystic fibrosis pathophysiology.

cell biology↗

bioRxiv2022

KDM6A/UTX promotes spermatogenic gene expression across generations but is dispensable for male fertility

Paternal chromatin undergoes extensive structural and epigenetic changes during mammalian spermatogenesis, producing sperm that contain an epigenome optimal for the transition to embryogenesis. Histone modifiers play an important role in this process by encoding specialized regulatory information in the sperm epigenome. Lysine demethylase 6a (KDM6A) promotes gene activation via demethylation of H3K27me3, a developmentally important repressive modification abundant throughout the epigenome of sperm and embryonic stem cells. Despite its developmental importance in pluripotent cells and germ cell progenitors, the function of KDM6A during spermatogenesis has not been described. Here, we show that Kdm6a is transiently expressed in the male germline in late spermatogonia and during the early stages of meiotic entry. Deletion of Kdm6a in the male mouse germline (Kdm6a cKO) yielded a modest increase in sperm head defects but did not affect fertility or the overall progression of spermatogenesis. However, hundreds of genes were deregulated upon loss of Kdm6a in spermatogenic cells and in an immortalized spermatogonia cell line (GC-1 spg) with a strong bias towards downregulation. Single cell RNA-seq revealed that most of these genes were deregulated in spermatogenic cells at the same stage when Kdm6a is expressed and encode epigenetic factors involved in chromatin organization and modification. A subset of these genes was persistently deregulated in the male germ line across two generations of offspring of Kdm6a cKO males. Our findings highlight KDM6A as a transcriptional activator in the mammalian male germline that is dispensable for spermatogenesis but important for safeguarding gene regulatory state intergenerationally. Author summaryOffspring viability and fitness relies upon the development of functional sperm and the integrity of information that they carry. Chromatin is modified and remodeled extensively throughout spermatogenesis to facilitate meiosis, DNA compaction, and to encode gene regulatory information for the next generation. In mice, a paternal germline lacking KDM6A, a histone modifier, yields offspring with reduced lifespans and increased cancer risk. How KDM6A functions in the paternal germline to support offspring health is unknown. Here, we show that Kdm6a expression is limited to a distinct developmental interval when differentiated spermatogonia transition from mitosis to meiosis. During this timepoint, KDM6A acts as a transcriptional activator for hundreds of genes, many of which encode meiotic factors and epigenetic modifiers. Nevertheless, this activity is dispensable for overall spermatogenesis and fertility. Surprisingly, we find a significant overlap in germline transcriptomes of Kdm6a cKO mice and wildtype offspring. We propose that KDM6A encodes gene regulatory information in the male germline that is retained across generations.

genetics↗

bioRxiv2022

Delayed processing of blood samples impairs the accuracy of mRNA-based biomarkers

BackgroundThe transcriptome of peripheral white blood cells (PWBCs) contains valuable physiological information, thus making them a prime biological sample for investigating mRNA-based biomarkers. However, prolonged storage of whole blood samples can alter gene transcript abundance in PWBCs, compromising the results of biomarker discovery. Here, we designed an experiment to interrogate the impacts of delayed processing of whole blood samples on gene transcript abundance in PWBCs. We hypothesized that storing blood samples for 24 hours at 4{degrees}C would cause RNA degradation resulting in altered transcriptome profiles. ResultsWe produced RNA-sequencing data for 30 samples collected from five estrus synchronized heifers (Bos taurus). We quantified transcript abundance for 12,414 protein-coding genes in PWBCs. Analysis of parameters of RNA quality revealed no statistically significant differences (P>0.05) between samples collected from the jugular vein and coccygeal vein, as well as among samples processed after one, three, six, or eight hours. However, samples processed after 24 hours of storage had a lower RNA integrity number value (P=0.03) in comparison to those processed after one hour of storage. Next, we analyzed RNA-sequencing data between samples using those processed after one hour of storage as the baseline for comparison. Interestingly, evaluation of 3/5 bias revealed no differences between genes with lower transcript abundance in samples stored for 24 hours relative to one hour. In addition, sequencing coverage of transcripts was similar between samples from the 24-hour and one-hour groups. We identified four and 515 genes with differential transcript abundance in samples processed after storage for eight and 24 hours, respectively, relative to samples processed after one hour. ConclusionsThe PWBCs respond to prolonged cold storage by increasing genes related to active chromatin compaction which in turn reduces gene transcription. This alteration in transcriptome profiles can impair the accuracy of mRNA-based biomarkers. Therefore, blood samples collected for mRNA-based biomarker discovery should be refrigerated immediately and processed within six hours post sampling.

genomics↗