Biology subjects

Gomez, J. P.

Publications and source records attributed to Gomez, J. P..

6 recordsLinked to original sources

bioRxiv2024

Inferring stability and persistence in the vaginal microbiome: A stochastic model of ecological dynamics

The vaginal microbiome is dynamic, yet the ecological and stochastic forces shaping its stability and persistence remain poorly understood. We developed a multi-species stochastic population model to analyze time-series data from 135 individuals sampled daily over 70 days, integrating ecological theory with microbial dynamics. Our framework explicitly incorporates stochasticity, ecological feedback, and sampling error to quantify community stability. We show that intra- and inter-species interactions and environmental fluctuations critically shape microbial population trajectories. This approach enabled the estimation of species competition coefficients and the identification of distinct stability regimes across individuals. We also introduce a Risk Prediction Monitoring (RPM) tool to track persistence probabilities of key taxa, particularly Lactobacillus spp., mirroring extinction risk models in conservation biology. Our findings challenge static "healthy" vs. "dysbiotic" categorizations and offer a quantitative framework for assessing microbiome resilience. This has direct implications for microbiome-targeted therapies aimed at promoting ecological stability in vaginal bacterial communities.

ecology↗

bioRxiv2023

Deregulation cascades in carcinogenesis

BackgroundThe construction of realistic gene regulatory networks is currently hindered by the complex, often redundant, combinatorial and multi-layered nature of gene interdependencies, the limited availability of functional annotations, and the intrinsic shortcomings of co-expression-based approaches. Here, we introduce Gene Deregulation Networks (GDNs), a new structure in which linked genes indicate that an expression deregulation in one is likely to propagate to the other. GDNs are inferred directly from gene expression data using a probabilistic theory of causation, without requiring prior functional annotation or other domain knowledge. MethodsUsing highly specific tissue markers--N-genes specifically expressed in normal tissues and T-genes specifically expressed in tumors--we construct separate GDNs for normal and tumor tissues. Data are obtained from TCGA RNA-Seq profiles of bulk tumor and normal tissue samples across multiple cancer localizations. GDN links are preliminarily identified via a statistical test of causal sufficiency between gene expression deregulation events, and then reassessed as spurious or redundant using additional causal criteria. A simple scheme based on the GDNs is implemented in order to describe the evolution dynamics. ResultsThe T-GDN in prostate adenocarcinoma comprises 6138 genes and 102362 directed edges (0.27% of possible connections). Genes with low expression deregulation frequency (< 0.2) exhibit high out-degrees, indicating high deregulation potential, while high-frequency genes (> 0.4) show high in-degrees, suggesting they are convergence points of deregulation cascades. EPHA10 (frequency 0.74, in-degree 182) and ENSG00000275479 (out-degree 209) represent these extremes. The N-GDN contains 1097 genes and 4984 edges, featuring compressed nodes reflecting the multi-step nature of somatic evolution. Analysis of tumor samples reveals that early-stage tumors rely primarily on spontaneous gene activations, while advanced tumors exhibit extensive cascade-driven deregulation. Preliminary simulations show qualitative agreement with experiments on gene knockdown in tumor cellular lines. ConclusionsGDNs provide a robust framework to understand cancer progression through deregulation cascades. The separation into N and T networks, connected by NT-genes, i.e. genes common to both networks, offers a systematic basis for modeling carcinogenesis and the possible outcomes of therapeutic interventions.

systems biology↗

bioRxiv2019

Exploring Environmental Coverages of Species: A New Variable Selection Methodology for Rulesets from the Genetic Algorithm for Ruleset Prediction

Variable selection for, and determination of variable importance within, species distribution models (SDMs) remain an important area of research with continuing challenges. Most SDM algorithms provide normally exhaustive searches through variable space, however, selecting variables to include in models is a first challenge. The estimation of the explanatory power of variables and the selection of the most appropriate variable set within models can be a second challenge. Although some SDMs incorporate the variable selection rubric inside the algorithms, there is no integrated rubric to evaluate the variable importance in the Genetic Algorithm for Ruleset Production (GARP). Here, we designed a novel variable selection methodology based on the rulesets generated from a GARP experiment. The importance of the variables in a GARP experiment can be estimated based on the consideration of the prevalence of each environmental variable in the dominant presence rules of the best subset of models and its coverage. We tested the performance of this variable selection method based on simulated species with both weak and strong responses to simulated environmental covariates. The variable selection method generally performed well during the simulations with over 2/3 of the trials correctly identifying most covariates. We then predict the distribution of Bacillus anthracis (the bacterium that causes anthrax) in the continental United States (US) and apply our variable selection procedure as a real-world example. We found that the distribution of B. anthracis was primarily determined by organic content, soil pH, calcic vertisols, vegetation, sand fraction, elevation, and seasonality in temperature and moisture.

ecology↗

bioRxiv2018

Asymmetric effects of environmental filtering on the assembly of tropical bird communities along a moisture gradient

The species-sorting hypothesis (SSH) states that environmental factors influence local community assembly of metacommunities by selecting for species that are well adapted to the specific conditions of each site. Along environmental gradients, the strength of selection against individuals that are marginally adapted to the local conditions increases towards the extremes of the environment where the climate becomes harsh. In rainfall gradients, the strength of selection by the environment has been proposed to decrease with rainfall. Under this scenario SSH would predict that immigration of individuals from the metacommunity should be restricted into the dry end of the gradient creating a positive relationship between immigration and rainfall. However, if the selection is strong in both ends of the gradient, the restriction should be expected to be in both directions such that the ends behave as independent metacommunities even in the absence of geographical barriers. In this study we used models based on neutral theory to evaluate if SSH can explain the distribution of bird species along a steep rainfall gradient in Colombia. We found a strong positive relationship between immigration rates and precipitation suggesting that the dry forests impose stronger challenges for marginally adapted bird populations. However, a two-metacommunity model separating dry and wet forests was a better fit to the observed data, suggesting that both extremes impose strong selection against immigrants. The switch from the dry forest to the wet forest metacommunities occurred abruptly over a short geographic distance in the absence of any apparent geographic barrier; this apparent threshold occurs where the forest becomes mostly evergreen. The relative number of rare species in dry forest was lower than in wet forests suggesting that the selection against marginally adapted populations is stronger in the dry forests. Overall, our analyses are consistent with SSH at the regional scales, but the rarity analysis suggests that the mechanisms at the local scales are substantially different. Based on these results, we hypothesize that abiotic (climatic) factors limit immigration into dry forest communities and whereas biotic factors such as competition and predation may limit immigration into bird communities in the wet forest.

ecology↗

bioRxiv2018

Effects of shade-coffee certification programs on bird, trees and butterfly diversity in Colombia

In the last decade coffee certification programs have grown rapidly in Latin America, encouraging producers to harvest coffee based on production standards intended to enhance biodiversity conservation. However, few studies have tested whether such programs have a positive conservation impact. To date, research has focused on comparing community similarity between forests and plantations, but the question of whether certified plantations provide refuges for biodiversity in regions where all the forest has been lost remains untested. Here, we compare bird, butterfly and plant communities in highly deforested regions in Santander, Colombia, to determine the potential conservation role of two certification programs: Rainforest Alliance and Rainforest Alliance+Organic. We used 13 farms to census birds, butterflies, and trees, and quantified structural characteristics of the shade. We found little difference in most measures of diversity and composition of birds, butterfly and plant communities between types of plantations. However, despite high variation across farms, butterfly richness and abundance increased with the decrease in the use of pesticides in plantations. These results suggest that reduced use of chemical compounds in certified coffee plantations might enhance conservation of butterfly communities. The biodiversity associated with these coffee plantations and the high deforestation rates in Santander, suggest that irrespective of their certification type they provide the last refuges for biodiversity conservation in this region.

ecology↗

bioRxiv2018

Climatic effects on turnover of lowland forest bird communities across a precipitation gradient

One of the main goals of community ecology is to understand the influence of the abiotic environment on the abundance and distribution of species. It has been hypothesized that dry forests are harsher environments than wet forests, which leads to the prediction that environmental filtering should be a more important determinant of patterns of species abundance and composition than in wet forest, where biotic interactions or random assembly should be more important. We attempt to understand the influence of rainfall on the abundance and distribution of bird species along a steep precipitation gradient in an inter-Andean valley in Colombia. We gathered data on species distributions, abundance, morphological traits and phylogenetic relationships to determine the influence of rainfall on the taxonomic, functional and phylogenetic turnover of species along the Magdalena Valley. We demonstrate that there is a strong turnover of community composition at the limit of the dry forest. The taxonomic turnover is steeper than the phylogenetic turnover, suggesting that replacement of closely related species accounts for a disproportionate number of changes along the gradient. We found evidence for environmental filtering in dry forest as species tend to be more tolerant of higher temperature ranges, stronger rainfall seasonality and lower minimum rainfall. On the other hand, wet forest species tend to compete actively for nest space but not for the resources associated with the axes we measured. Our results suggest that rainfall is a strong determinant of community composition when comparing localities above and below the 2400 mm rainfall isocline.

ecology↗