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Ayala-Ortiz, C. O.

Publications and source records attributed to Ayala-Ortiz, C. O..

2 recordsLinked to original sources

Stochastic Assembly and Metabolic Network Reorganization Drive Microbial Resilience in Arid Soils

Microbial resilience plays a pivotal role in ecosystems as environmental fluctuations impact community functioning and stability. Despite resilience emerging from both individual adaptations and community-level processes, integration of these mechanisms remains enigmatic, particularly in arid environments. These extreme ecosystems, spanning over 45% of Earths terrestrial surface, provide a natural laboratory for understanding microbial survival under harsh conditions. Here, we use time-resolved multi-omics to show that resilience results from dynamic microbial network reorganization enabling the coordination between stochastic processes that maintain community stability, and individual stress responses. Additionally, Thermoproteota emerged as a keystone taxon maintaining nitrogen cycling and fostering cross- feeding networks. Its ecological prominence highlights its central role in arid ecosystems, making it an ideal model organism for understanding microbial adaptation to environmental extremes. Our findings bridge the gap between individual adaptations and community-wide resilience, offering a framework for understanding microbial responses to environmental fluctuations and their implications for ecosystem function.

microbiology↗

MetaboDirect: An Analytical Pipeline for the processing of FTICR-MS-based Metabolomics Data

BackgroundMicrobiomes are now recognized as main drivers of ecosystem function ranging from the oceans and soils to humans and bioreactors. However, a grand challenge in microbiome science is to characterize and quantify the chemical currencies of organic matter (i.e. metabolites) that microbes respond to and alter. Critical to this has been the development of Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS), which has drastically increased molecular characterization of complex organic matter samples, but challenges users with hundreds of millions of data points where readily available, user-friendly, and customizable software tools are lacking. ResultsHere, we build on years of analytical experience with diverse sample types to develop MetaboDirect, an open-source, command-line based pipeline for the analysis, visualization, and presentation of metabolomics data by direct injection FTICR-MS after molecular formula assignment has been performed. When compared to all other available FTICR software, MetaboDirect is superior with respect to its compute time as it only requires a single line of code that launches a fully automated framework for the generation and visualization of a wide range of plots, with minimal coding experience required. Among the tools evaluated, MetaboDirect is also uniquely able to automatically generate biochemical transformation networks (ab initio) based on mass differences that provide a comprehensive experimental assessment of metabolite connectives within a given sample or a complex metabolic system, thereby providing important information about the nature of the samples and the set of the microbial reactions or pathways that gave rise to them. Finally, for more experienced users, MetaboDirect allows users to customize plots, outputs, and analyses. ConclusionApplication of MetaboDirect to FTICR-MS-based metabolomics datasets from a marine phage-bacterial infection experiment and a Sphagnum leachate microbiome incubation experiment showcase the exploration capabilities of the pipeline that will enable the FTICR-MS research community to evaluate and interpret their data in greater depth and in less time. It will further advance our knowledge of how microbial communities influence and are influenced by the chemical makeup of the surrounding system. Source code and Users guide of MetaboDirect are freely available through (https://github.com/Coayala/MetaboDirect) and (https://metabodirect.readthedocs.io/en/latest/) respectively.

bioinformatics↗