Biology subjects

Ortiz-Zuazaga, H.

Publications and source records attributed to Ortiz-Zuazaga, H..

3 recordsLinked to original sources

bioRxiv2025

Gut microbiota as a modulator of circadian neural development in the honey bee model.

Disruption in gut microbiota during the early postnatal period can disrupt normal neural development and result in long-term behavioral alterations1. Similar to other neural systems, the circadian clock mechanism continues to mature after birth2, yet how microbial disturbances in the early period influence the onset of circadian rhythms and the development of central clock mechanisms remains poorly understood. Here we studied whether early-life gut dysbiosis affects the ontogeny of behavioral circadian rhythms and the maturation of clock neurons using the honey bee (Apis mellifera), a model organism that shares features of postnatal development of behavioral circadian rhythm and clock system3-5 with humans6. Our findings demonstrate that antibiotic-treated and gnotobiotic-reared bees display reduced rhythmicity compared to controls. These treatments also impair the development of the circadian pacemaker, marked by fewer Pigment-Dispersing Factor (PDF)-expressing neurons. Additionally, antibiotic exposure increased the expression of the Insulin-like Growth Factor Binding Protein Acid Labile Subunit (IGFALS) in early ages, which stabilizes the IGF-1/27, a hormone important for neurodevelopmental processes42. Together, these results identify gut microbiota as a modulator of circadian development. Our work provides an understanding of how early-life microbial disruptions influence the development of circadian rhythms, providing information that may extend to other animals, including humans.

neuroscience↗

bioRxiv2020

Transcriptomic Analysis of Early Stages of Intestinal Regeneration in Holothuria glaberrima

Echinoderms comprise a group of animals with impressive regenerative capabilities. They can replace complex internal organs following injury or autotomy. In holothurians or sea cucumbers, cellular processes of intestinal regeneration have been extensively studied. The molecular machinery behind this faculty, however, remains to be understood. Here we assembled and annotated a de novo transcriptome using RNA-seq data consisting of regenerating and non-regenerating intestinal tissues from the sea cucumber Holothuria glaberrima. Comparisons of differential expression were made using the mesentery as a reference against 24 hour and 3 days regenerating intestine, revealing a large number of differentially expressed transcripts. Gene ontology and pathway enrichment analysis showed evidence of increasing transcriptional activity. Further analysis of transcripts associated with transcription factors revealed diverse expression patterns with mechanisms involving developmental and cancer-related activity that could be related to the regenerative process. Our study demonstrates the broad and diversified gene expression profile during the early stages of the process using the mesentery as the focal point of intestinal regeneration. It also establishes the genes that are the most important candidates in the cellular processes that underlie regenerative responses.

bioinformatics↗

bioRxiv2017

Patternize: An R Package For Quantifying Color Pattern Variation

O_LIThe use of image data to quantify, study and compare variation in the colors and patterns of organisms requires the alignment of images to establish homology, followed by color-based segmentation of images. Here we describe an R package for image alignment and segmentation that has applications to quantify color patterns in a wide range of organisms.\nC_LIO_LIpatternize is an R package that quantifies variation in color patterns obtained from image data. patternize first defines homology between pattern positions across specimens either through manually placed homologous landmarks or automated image registration. Pattern identification is performed by categorizing the distribution of colors using an RGB threshold, k-means clustering or watershed transformation.\nC_LIO_LIWe demonstrate that patternize can be used for quantification of the color patterns in a variety of organisms by analyzing image data for butterflies, guppies, spiders and salamanders. Image data can be compared between sets of specimens, visualized as heatmaps and analyzed using principal component analysis (PCA).\nC_LIO_LIpatternize has potential applications for fine scale quantification of color pattern phenotypes in population comparisons, genetic association studies and investigating the basis of color pattern variation across a wide range of organisms.\nC_LI

bioinformatics↗