Results

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Dry Lab Results 💻

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Summary

The glucagon sequence analysis provides a comprehensive view of evolutionary conservation, variability, and functional constraints within the glucagon family. Using entropy, conservation, and alignment-based metrics, our study characterizes how selective pressure has shaped key structural and receptor-binding residues. Conserved sites correspond to functional anchors necessary for receptor activation, while variable regions likely represent positions that can tolerate mutations without compromising function. These insights help distinguish essential residues from adaptable ones, guiding peptide engineering and comparative evolutionary studies across species.

Overall, our analysis demonstrates that glucagon maintains a tightly conserved structural and functional core with limited sequence flexibility. Variable regions, mostly located near terminal or loop positions, may enable functional fine-tuning across homologs like GLP-1 and GLP-2. Together, these results reinforce the idea that evolutionary conservation reflects the structural and biochemical constraints required for glucagon’s hormone activity, while sequence diversity reflects adaptive optimization across species.

GLP-1 Structure

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Data statistics

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I. Shannon Entropy Profile

This plot is fundamental for identifying functionally critical regions in glucagon. Since glucagon is a hormone with specific receptor-binding requirements, positions with low entropy (<1.0 bits) likely represent conserved residues essential for maintaining the peptide's structural integrity or biological activity. The high entropy positions (>2.0 bits) may indicate regions that tolerate variation across species or potentially contribute to species-specific functional adaptations. Understanding this entropy landscape helps prioritize which residues to target for mutagenesis studies or drug design, as conserved positions are likely critical for function while variable positions might offer opportunities for engineering modified glucagon analogs with improved properties.

Shannon Entropy Profile Across Glucagon Alignment

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II. Conservation Score Profile

The conservation score provides a normalized measure that directly relates to functional importance. In our glucagon project, positions with conservation scores ≥0.8 are prime candidates for being part of the receptor-binding interface or structurally essential core. The moderate conservation regions (0.5–0.8) might represent positions that maintain the overall fold but allow some evolutionary flexibility. This profile is particularly valuable for comparative studies across different glucagon-family peptides (GLP-1, GLP-2) to identify shared conserved motifs versus unique specificity-determining residues that differentiate their biological functions and receptor specificities.

Conservation Score Profile (1 - Normalized Entrophy)

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III. Gap Percentage Distribution

Gap analysis reveals the quality and reliability of the multiple sequence alignment. Positions with high gap percentages (>50%) indicate regions where sequences are poorly aligned or have insertions/deletions, which could complicate structural interpretations. For glucagon, which has a relatively conserved length across species, high gap regions might represent genuine biological variations or alignment artifacts. This information helps determine which regions of the alignment are most reliable for downstream analyses and which might require manual inspection or exclusion from certain analyses to avoid misleading conclusions.

Gap Distribution Across Glucagon Alignment

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IV. Sequence Variability

This visualization directly shows the diversity of amino acid substitutions tolerated at each position. In glucagon research, positions with only 1–2 unique amino acids across 372 sequences represent absolutely conserved features likely critical for function. The highly variable positions (≥10 unique AAs) indicate regions that can accommodate substantial sequence variation, which could be exploited for engineering glucagon analogs with modified properties like increased stability, altered receptor affinity, or reduced immunogenicity. This analysis helps identify both the constraints and opportunities for glucagon protein engineering.

Space Variability - Unique Amino Acids per Position

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V. Entropy vs Conservation Correlation

The expected strong negative correlation between entropy and conservation validates the reliability of our alignment and conservation metrics. Any deviations from this expected relationship could indicate interesting biological phenomena. For glucagon, positions that show unexpectedly high conservation despite moderate entropy might indicate co-evolution or compensatory mutations. This analysis provides quality control for conservation calculations and can reveal complex evolutionary patterns that simple conservation scores might miss, potentially uncovering important structural or functional relationships within the glucagon sequence.

Entropy vs Conservation Correlation Analysis

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VI. Entropy Distribution Histogram

The overall distribution pattern reveals whether glucagon is predominantly conserved (left-skewed histogram) or variable (right-skewed). A bimodal distribution might indicate distinct functional domains with different evolutionary constraints. Understanding the global conservation pattern helps set appropriate thresholds for defining conserved versus variable positions and informs decisions about how stringent to be when selecting conserved positions for functional studies or designing consensus sequences for synthetic glucagon variants.

Distribution of Shannon Entropy Values

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VII. Conservation Heatmap

The heatmap provides a color-coded overview that quickly identifies conserved blocks and variable regions along the glucagon sequence. Clusters of highly conserved positions likely represent the structural core or critical functional residues, while variable regions might correspond to surface-exposed loops that can tolerate variation. This view helps generate hypotheses about structure–function relationships.

Conservation Heatmap Visualization

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VIII. Top 10 Conserved vs Variable Positions

Focusing on the extremes of conservation identifies the most promising candidates for experimental investigation. The top conserved positions in glucagon are almost certainly critical for function and should be preserved in engineered variants. Conversely, the most variable positions represent the best opportunities for introducing modifications to create novel glucagon analogs. This targeted analysis efficiently prioritizes residues for site-directed mutagenesis.

Top 10 Conserved vs Variable Positions

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IX. Gap vs Variability Analysis

This quadrant analysis distinguishes between genuine biological diversity and potential alignment artifacts. Positions in the upper-left quadrant (low gaps, high variability) represent authentic sequence diversity that evolution has tolerated, making them ideal targets for engineering studies. Positions in the lower-right quadrant (high gaps, low variability) suggest alignment problems in otherwise conserved regions, which might require manual correction. This helps ensure that conclusions about sequence conservation and variability are based on reliable alignment data.

Gap Percentage vs Sequence Variability

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X. Cumulative Entropy Distribution

This statistical tool helps set evidence-based thresholds for conservation analysis. By showing what percentage of positions fall below specific entropy values, it provides a quantitative basis for defining conservation cutoffs. For example, if targeting the most conserved 25% of positions for functional studies, this plot gives the entropy threshold corresponding to that percentile, ensuring design decisions are data-driven.

Cumulative Distribution of Entrophy Values

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Wet Lab Results 🧪

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Cycle 1: Foundational Skills & Initial Design (August - May 2025)

Design: The initial goal was to engineer Lactobacillus species. The first step involved designing a plasmid by recodonizing the human GLP-1 gene to have a GC content suitable for expression in both Lactobacillus and E. coli. Students explored modular cloning techniques and alternative BioBrick designs using the Benchling software.

Build: Team members were trained in fundamental microbiology skills, including aseptic technique and how to perform a quadrant streak to isolate single bacterial colonies.

Learn: Students learned to navigate the Benchling software and apply principles of synthetic biology to plasmid design. This phase was focused on acquiring the theoretical and practical skills necessary for the project.

Test: This initial cycle was primarily focused on design and training, with no formal experimental testing conducted.

iGEM Engineering Cycle

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Cycle 2: Preparing Media & Acquiring Strains (June 2025)

Design: The plan was to create chemically competent Lactobacillus cells. This required designing and preparing the correct growth media and chemical solutions based on established protocols. The team ordered two key strains: Lactobacillus acidophilus (ATCC 4356) and Lactiplantibacillus plantarum (ATCC 8014).

Build: The team prepared several chemical solutions (1M MgCl₂, 1M KCl, 1M MOPS), specialized Lactobacillus MRS broth and agar plates, standard LB agar plates, and a 50% glycerol solution for long-term bacterial storage.

Compounds Chemcial Structure

Test: Upon arrival, the Lactobacillus cultures were found at room temperature. When streaked on standard LB plates, they failed to grow.

Learn: The initial failure led to two key insights. First, the viability of the bacteria was compromised, likely due to improper shipping temperatures. Second, Lactobacillus has specific nutritional requirements that are not met by standard LB medium. This prompted the switch to the specialized MRS medium, which was successful for growing the bacteria.

Date of experiment: 6/24/2025

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Cycle 3: Chemical Transformation of Lactobacillus (Late June - Early July 2025)

Design: The team planned to transform Lactobacillus using a standard heat-shock protocol (Prest RbCl₂ method) that is common for E. coli. They designed a multi-faceted troubleshooting experiment to test several variables simultaneously: varying DNA concentrations; varying antibiotic (chloramphenicol) concentrations on the plates; using different plasmids from the iGEM distribution kit.

Build: Chemically competent cells of both L. acidophilus and L. plantarum were prepared. Multiple transformation experiments were performed using the heat-shock protocol with different amounts of plasmid DNA and plated on MRS agar with varying drug concentrations.

Test: All heat-shock transformation attempts failed. No colonies grew on any of the selective plates.

Learn: The standard E. coli heat-shock protocol was ineffective for Lactobacillus. The cell wall is likely too thick for chemical transformation. Other potential issues identified were incorrect antibiotic dosage, incompatible plasmid origins of replication, or insufficient recovery time. This prompted a strategic shift toward electroporation.

Date of experiment: 7/9/2025

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Cycle 4: Electroporation of Lactobacillus (July 2025)

Design: The new plan was to use electroporation, a method that uses an electrical pulse to create temporary pores in the cell membrane. The team researched and designed an experiment with specific electroporation parameters (voltage, resistance, capacitance) for both Lactobacillus strains. They also planned to verify the integrity of their plasmids via restriction digest.

Build: The team prepared electrocompetent Lactobacillus cells. They then attempted numerous transformations using different voltage settings and DNA concentrations. In parallel, they set up restriction digests of their plasmids and attempted to pour an agarose gel for analysis.

Test: The electroporation attempts were plagued by technical failures. The use of old cuvettes caused electrical arcing, ruining the experiments. The attempts to prepare an agarose gel also failed, with the gel dissolving in the running buffer. While some later attempts did not arc, the resulting time constants were very low, and initial "colonies" were identified as defects in the petri dishes. Eventually, a few very small colonies of L. acidophilus were observed after a long incubation period.

Learn: This cycle revealed significant technical hurdles. The equipment (cuvettes) was a major source of failure. The protocol for making agarose gels needed to be revised. Most importantly, the electroporation parameters were still not optimized. The appearance of a few small colonies was a crucial, albeit small, sign of potential success, leading to a proposal to isolate and verify these potential transformants via MiniPrep or to just restart from E. coli.

Date: 8/1/2025

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Cycle 5: Shifting to E. coli as a Control (August 2025)

Design: Faced with continued difficulties in transforming Lactobacillus, the team decided to validate materials and methods using a standard, easy-to-transform lab strain: E. coli. The goal was to confirm that the iGEM plasmids and the general transformation protocol were sound. A series of electroporation experiments were designed using a panel of different plasmids from the kit.

Build: New batches of electrocompetent E. coli were prepared. Transformations were performed with multiple different plasmids, and recovery times were carefully controlled.

Test: Nearly all transformation attempts with E. coli failed, yielding either no colonies or lawns of untransformed bacteria. This was a critical negative result.

Learn: The failure to transform even a simple E. coli strain indicated a fundamental problem not specific to Lactobacillus. The issue was likely one of the core components: plasmid DNA, cell competency, transformation protocol, or the electroporator itself. This shifted the project into a deep troubleshooting phase.

Date of experiment: 8/16/2025

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Cycle 6: Systematic Troubleshooting of E. coli Transformation (September-October 2025)

Design: The team designed a systematic approach to isolate the point of failure. The plan involved:

• Using a known "gold-standard" GFP plasmid from another lab to rule out problems with the iGEM kit DNA.
• Testing multiple different electroporators in other labs to rule out a faulty machine.
• Switching from ampicillin to the more stable carbenicillin antibiotic to rule out degraded selection agents.
• Testing various heat-shock protocols as an alternative to electroporation.
• Using professionally prepared, commercially available competent cells to rule out errors in their cell preparation protocol.
• Trying different recovery broths (SOC medium).

Build: A series of transformations were performed, systematically changing one variable at a time: different plasmids, different machines, different antibiotics, different competent cells (both homemade and commercial), and different protocols (electroporation and heat shock).

Test: Despite exhaustive efforts, attempts at transformation yielded negligible results. No chromoproteins were being expressed by the bacteria, and while we tested commercial grade competent cells, we sadly did not have any successful transformants.

Learn: Due to timing, this cycle demonstrated that a persistent issue was present in our protocol that requires a more thorough exploration of protocols, parameters, and variables. Though systematic elimination of variables did provide momentary solace, the vast difference between having lawns of bacteria that were untransformed and plates with no colonies at all concerned us. Our team must take some time to regroup to assess protocol success and establish a rigorous and complete method for future teams.

Date of experiment: 8/29/2025

Date of experiment: 9/11/2025

Date of experiment: 9/19/2025

Date of experiment: 9/30/2025