- Contributed to the project Proteome Allocation Rules in Osmotrophic Eukaryotes, studying how non-conventional osmotrophic yeasts (K. marxianus and V. polyspora) reorganize proteome investment under carbon limitation.
- Generated high-resolution growth curves to characterize the physiological response of the study organisms across defined carbon regimes, establishing the growth phenotypes underlying the downstream analysis.
- Contributed to proteomics-based workflows, including sample preparation and integrative analysis linking molecular allocation to cellular physiology.
- Tested and calibrated an automated continuous-culture system to support controlled cultivation for the lab's steady-state experiments.
Sebastian
Correa-Gallego
B.Sc. in Biology
On how living systems organize under constraint — keeping the living organism at the center of the question.
Research Interests
Life assembles into order under constraint. A microbial community drawn from the same pool of organisms may converge on a single reproducible state or settle into one of several alternatives depending on the order in which its members arrive, and what decides between these outcomes — whether assembly follows rules or depends on history — remains among the open questions in ecology and evolution. This tension between predictability and contingency reaches beyond any single system: it echoes the broader problem of how autonomous parts come to form integrated wholes, from the structure of a community to the major transitions in the organization of life. I am drawn to these questions, and to the possibility that collective outcomes might be anticipated from measurable properties of the organisms themselves — such as how a cell divides its finite resources between growth and metabolic efficiency. I hope to pursue them with growing quantitative rigor while keeping the living organism, in its real environment, at the center of the inquiry.
Education
GPA: 4.44 / 5.00
Research Experience
Thesis: Cultivable Microbial Community Structure Along a Light Gradient in a Tropical Volcaniclastic Cave [permanent link] [defense slides]
- Characterized the cultivable microbial fraction of the Organal San Antonio, a tropical volcaniclastic cave at ~2350 m a.s.l. in Támesis, Antioquia, across a light-defined spatial gradient spanning Entrance, Transition, and Dark sectors.
- Found systematic differences in cultivable abundance and community composition across zonation: the aphotic sector supported markedly reduced densities and a distinct assemblage relative to photic sectors, while the Transition zone harbored a partially unique community of its own.
- Established a spatially resolved cultivable baseline for an organal-type pseudokarstic cave system, designing a tractable cultivation study in the absence of sequencing infrastructure.
Academic Service
- Led a student research group on microbiology, astrobiology, and extremophiles, working collaboratively with members to learn and apply microbiological techniques and explore the diversity of these organisms.
- Participated in a science-outreach initiative on the role of microorganisms in the maintenance of Andean forests, contributing science-communication material for the El Globo nature reserve (Támesis).
Conferences & Presentations
2nd Symposium of Biology, Universidad EAFIT
XXIII Encuentro Departamental de Semilleros de Investigación, RedCOLSI, Antioquia, Colombia
Feria de Semilleros de Investigación, Universidad EAFIT
Honors & Recognition
Fundación Fraternidad Medellín — UREP-C Program, Purdue University
2nd Symposium of Biology, Universidad EAFIT
Comfama and Fundación Fraternidad Medellín
Certifications & Training
CITI Program, Credential ID 71597371, valid through Aug 2029
Servicio Nacional de Aprendizaje (SENA), Colombia
Technical Skills
Laboratory and biological methods: microbial cultivation and isolation, continuous-culture operation, growth-curve measurement, environmental sampling and ecological field records, molecular biology and biochemistry techniques, proteomics sample preparation, and microscopy-based observation.
Quantitative and computational tools: R, Python, Linux/bash, LaTeX, and QGIS, applied to biological data analysis, statistics, and data visualization.
Scientific workflows: scientific writing, research communication, literature synthesis, and figure preparation.