Lab Planning, Experimental Design, Data Management, and Staining Protocol Notes

Data Management and Backups

  • Highlighted importance of backing up sensitive results (e.g., HIV results) to prevent loss if hardware fails (laptop lost, etc.). Keep raw data in a centralized, accessible location as a backup strategy.
  • Always preserve raw data so you can re-run analyses with a different method if needed.
  • Save any pretty graphs or figures you create: export them and store them alongside the raw data.
  • Regarding graphs: confirm who is responsible for creating new graphs and ensure proper credit and versioning when multiple people contribute.

Experimental Design: Current Small Experiment and Planned Large Experiment

  • Current (“baby”) experiment: comparing two fungi treatments and two powdered fungi treatments (total of 4 treatments? the speaker mentions four, then notes three to eight reps in a later context).
    • Earlier in the talk, the group references a 24-pot setup with three treatments and eight replicates: 3 × 8 = 24 pots. This layout used color tape to distinguish treatments.
    • The quick calculation confirms: 3 treatments × 8 reps = 24 pots (24 total).
  • Planned larger experiment (next week): aim to set up a bigger experiment comparing multiple treatments:
    • Treatments named/mentioned: SCE, SCE a+, N7, MYCo+, plus additional formulations (e.g., several liquids vs. powders). The speaker notes four liquids (all with fungi and PGPR) and corresponding fungi-only powders; plus a control (water).
    • Ultimately, seven treatments are planned for the larger experiment, with eight replications each:
    • Total pots required: 7×8=567 \times 8 = 56
    • The group confirms they will need 56 pots and will plan soil preparation and autoclaving accordingly.
  • They emphasize planning before Tuesday (the day of counts) to ensure enough materials and containers are available.

Potting, Soil, Autoclaving, and Batch Planning

  • The bigger experiment requires 56 pots. First question: do we have 56 pots?
    • If not, buy more before next week.
  • Soil handling:
    • Soil from an autoclave was dried on a table; some pots are underfilled, others a bit low.
    • Plan: fill pots to an inch below the target line on the first pass (to the line that will later hold seed and grow to the intended level).
    • Determine how many pots can be filled from one autoclaved soil batch to estimate how many batches of soil autoclaving are needed.
    • If multiple autoclave batches are required, the start of the experiment might be delayed to Thursday rather than Tuesday.
  • Sterile technique check for soil: a proposed method to verify middles soil is sterile is to bury autoclave tape in the soil and see if the tape lines darken (a diagnostic marker of sterilization).
  • Planning for soil batches and timing is tied to autoclave throughput and batch size.

Labeling, Color Coding, and Replicate Strategy

  • Labeling plan for 56 pots:
    • Use tape to indicate treatment; assign a color to each treatment to distinguish replicates.
    • Include a number label (1 through 8) for replicates.
    • The speaker emphasizes adding color cues in addition to writing the treatment name to protect against loss of information if tape or writing fades (e.g., if ethanol washes off tape).
  • They discuss reuse and provenance of labeling materials (e.g., blue tape from last semester; need fresh tape for this run).
  • The rationale for color-coding: reduce the risk of cross-contamination or misidentification if labeling wears off.
  • They note that in past experiences (PhD program), restarting experiments due to label confusion is a hazard, hence robust labeling strategy.
  • Data structure in the lab notebook/spreadsheet:
    • Four data columns for current data (SCE, SCE a+, N7, MicroPlus, SCE a+ is mentioned again as a separate label); the point is to have columns corresponding to each treatment.
    • They plan to enter numerical values (e.g., CFU counts) for each replicate.
  • Data organization also includes planning to capture colony-forming units per milliliter as the primary metric: extCFU/mLext{CFU/mL}.

Data Entry, Statistics, and Analysis

  • Data entry: create columns for each treatment and input replicate values.
  • Statistical analysis choice:
    • If there are only two treatments: use a t-test.
    • If there are more than two treatments: use a one-way ANOVA (分析方):
    • One-way ANOVA tests one independent factor across multiple treatments.
    • The user should select ANOVA in the software when there are more than two treatments.
    • The user should verify approximately equal standard deviations across groups (Gaussian distribution assumption).
  • Interpreting results:
    • If the p-value is not significant (p-value not less than 0.05): there is no evidence of a difference between treatments; this is considered favorable if the goal is to show all solutions are equal.
    • If p-value < 0.05: means there is a significant difference between some treatments; proceed to a mean separation test to identify which treatments differ.
    • Mean separation test (post-hoc comparisons) can yield group labels (e.g., a, b, c) indicating which treatments are statistically different from others.
  • Post-hoc options (conceptual): the software may offer multiple comparisons to determine which pairs of treatments differ; if p < 0.05, you’d typically see letters indicating groups (e.g., treatments sharing the same letter are not significantly different).
  • Graphing options after ANOVA:
    • Box plots and violin plots are available; box-and-whisker (box-and-whisker plot) is highlighted as intuitive; other options include point plots with an average line across replicates.
    • Example axis label: “Colony Forming Units per mL” (extCFU/mLext{CFU/mL}).
    • It’s possible to include a legend or a separate figure title, but the presenter prefers to keep the internal figure title out and add a caption in Word or PowerPoint.
  • Exporting graphs:
    • In the software, File -> Export, exported as JPEG, then paste into Word documents or PowerPoint slides.
    • When presenting in slides, it may be convenient to use the PowerPoint title for the slide and a figure legend in Word for a figure caption.
  • Practical note: the speaker tests with a mock data set to illustrate ANOVA and post-hoc logic (example values entered to practice entering data and generating a graph).

Staining Protocols and Root Preparation (Practicals for the Day)

  • The team will practice a staining protocol on root tissue:
    • Materials: roots from stored plant material; chopsticks; test tubes; fume hood; safety glasses; gloves; two bottles of dye (one big bottle and one small bottle) for comparison.
    • Sample collection: take one root from a plant, cut into small pieces around 1.0–1.3 cm long (not including the main stem), for staining.
    • Tools: test tubes, chopsticks to position root pieces, scissor or scalpel for cutting, plastic dishes for post-staining handling.
    • Safety: must wear safety glasses and gloves; be mindful of chemical safety; avoid touching face, eyes, or mouth; keep waste contained in labeled waste beakers; avoid cross-contamination with lab surfaces and personal devices (e.g., cell phones).
  • Staining workflow (pseudo-sequence):
    • Prepare 2% KOH solution: convert from 10% KOH by dilution with DI water to achieve 2extKOH1002\frac{ ext{KOH}}{100}; use DI water for dilution.
    • Place root pieces at the bottom of each test tube and add 2% KOH to submerge them; incubate in a hot water bath at just below boiling for 15 minutes.
    • Decant 2% KOH into a designated waste beaker (two waste beakers are provided: one for Texas Stream Team and one for lab use); use a decant to avoid losing root pieces if they fall into the waste bottle.
    • Rinse roots 2–3 times with water inside the test tubes to remove excess KOH.
    • Add 0.1 N HCl and incubate for 3 minutes; do not rinse after with water; the residue of acid helps the dye to sink into the roots.
    • Add 0.5% Trypan Blue (TriPen Blue) solution prepared with acetic acid and glycerol; add only a small amount to cover the roots, as the dye is precious/difficult to prepare.
    • Incubate for another 15 minutes, then decant the dye into waste and rinse 2–3 times with water.
    • After staining, place the stained roots in a dish and gently agitate to allow roots to float and separate from debris for inspection under the microscope.
  • Experimental design within staining practice:
    • Two bottle sizes of dye are used to compare effectiveness; have two people use the big bottle and two people use the small bottle to assess which works better.
    • Pair up lab partners: one person handles pipetting, the other handles handling and safety; then rotate roles to reduce groupthink and distribute workload.
    • Additional safety emphasis: be mindful of where liquids go on test tubes to prevent spills; if liquid drips on outside of a test tube, wipe with a paper towel; if liquid touches gloves, replace the glove to prevent skin exposure.
    • Avoid using phones during staining; if you need to take a photo, do so with care and then put the phone away.
    • The team will attempt to complete the staining workflow within the available time (roughly 1 hour 15 minutes left) and may store prepared samples in the fridge for later analysis if not finished.
  • Equipment and lab safety reminders:
    • Proper PPE: safety glasses, gloves at all times around chemicals.
    • Use the hood for chemical handling; ensure hood is functioning (turn it on if needed).
    • If a spill or drip occurs outside the test tube, immediately clean with a paper towel and replace any contaminated gloves.
    • Keep track of waste streams: decant 2% KOH and dye waste into designated waste beakers; do not pour into brown bottles or shared containers where possible.
    • Maintain organized workspace; assign roles and keep track of who handles which step to minimize cross-contamination and ensure safety.

Practical Implications: Ethics, Real-World Relevance, and Lab Practice

  • Data integrity and reproducibility:
    • Central to backup strategy and raw data preservation; the ability to reanalyze with different methods is crucial when results are unexpected or to verify findings.
    • Clear labeling and color-coding are essential to prevent mix-ups and ensure reproducibility across experiments and semesters.
  • Experimental design ethics and safety:
    • Emphasizes proper chemical safety, disposal, and personal protective equipment usage.
    • Encourages teamwork to reduce single-point failure and to cultivate responsible lab practices (rotate roles, watch for drips, and monitor safety).
    • Acknowledges the gap between classroom safety practices and professional lab safety standards; aims to instill more cautious and rigorous safety habits.
  • Data interpretation and decision making:
    • Understanding when to use t-tests vs. one-way ANOVA is tied to the number of treatments being compared.
    • Interpreting p-values correctly to decide whether to perform post-hoc mean separation tests is critical for drawing valid conclusions about treatment differences.
    • Visualization choices (box vs. violin, etc.) can influence interpretation and communication of results; exporting graphs for reports or presentations helps in disseminating findings.
  • Real-world relevance and planning:
    • The planning process mirrors real-world experimentation where batching (soil autoclaving), labeling, and replication logistics drive timelines.
    • The workflow demonstrates how to design and execute multi-treatment experiments with careful consideration of replication, randomization, and data recording practices.

Quick Reference for Key Numbers and Formulas

  • Pot counts for plan if seven treatments with eight reps: 7×8=567 \times 8 = 56 pots.
  • Earlier window experiment: three treatments with eight reps: 3×8=243 \times 8 = 24 pots.
  • Staining reagents and concentrations (as used in protocol):
    • 2%KOH2\% \text{KOH}
    • 0.1 N HCl0.1\text{ N HCl}
    • 0.5%Trypan Blue (TriPen Blue)0.5\% \text{Trypan Blue (TriPen Blue)} (prepared with acetic acid and glycerol)
  • Data metric: Colony Forming Units per Milliliter: CFU/mL\text{CFU/mL}
  • Statistical thresholds and tests:
    • If two treatments: use a t-test.
    • If more than two treatments: use a one-way ANOVA.
    • Significance level: p < 0.05 indicates a significant difference; otherwise, differences are not considered statistically significant.
    • Post-hoc mean separation (when p < 0.05) to determine which treatments differ; results may show letter groupings (a, b, c) to denote non-overlapping groups.

Next Steps and Schedule (as discussed in the session)

  • Confirm pot inventory and acquire any missing pots to reach 56.
  • Finalize soil batch calculations: determine how many pots can be filled per autoclaved batch and whether multiple batches are needed before Tuesday.
  • Prepare labeling system with color-coded tape and permanent numbers for 56 pots.
  • Prepare staining protocol materials and assign roles for two-person teams per station to ensure safety and efficiency.
  • Run the staining workflow for as many samples as time allows today; save and store specimens if not completed.
  • Plan to generate a jumbo graph next week once all seven treatments have data; aim to have numbers for SCE, SCEa+, N7, MYCo+, and other treatments; create a final combined graph.
  • Ensure data backups are in place and that raw data and graphs are stored in a shared location with proper versioning and attribution.