What is Dr. Zubair Khalid's research focus?

Dr. Zubair Khalid specializes in molecular virology, mRNA vaccine development, and computational biology, with a focus on avian pathogens like IBDV and Avian Reovirus.

Where is Dr. Zubair Khalid currently working?

Dr. Zubair Khalid is a Postdoctoral Research Associate at the University of Maryland (UMD), specifically within the Department of Animal and Avian Sciences.

How to Set Up Positive and Negative Controls in a Microbiology Experiment

Q: 1. Can I use the same sample as both a positive and negative control?

No. A positive control must be known to produce the expected effect, and a negative control must be known to produce no effect. Using the same sample for both purposes defeats the logic of control design. If your experimental sample happens to show the expected effect, it still cannot serve as a positive control because you do not know a priori that it will work.

Q: 2. How many controls do I need for a typical microbiology experiment?

At minimum, include one positive control and one negative control per experimental run. For quantitative assays, include at least two technical replicates of each control. For experiments with multiple variables (e.g., different concentrations, time points, or organisms), include a separate positive and negative control for each variable if the assay conditions differ.

Q: 3. What should I do if my negative control shows a weak signal that is above background but below the positive control threshold?

A weak signal in the negative control is still a failure. It indicates either low-level contamination or non-specific binding. Investigate the source before proceeding. Common fixes include using fresh reagents, changing filter tips more frequently, or increasing the stringency of wash steps in binding assays.

Q: 4. Can I omit controls if I am using a commercial kit that claims to be validated?

No. Commercial kits are validated by the manufacturer under specific conditions, but your laboratory environment, reagents, and operator technique may differ. Always include your own positive and negative controls to verify that the kit performs as expected in your hands. This is especially important for PCR-based kits, where contamination is a persistent risk.

The Science Laboratory at the Aspatria Agricultural college — Image by Unknown author Unknown author, Wikimedia Commons, licensed under Public domain.

Positive and negative controls are essential reference points that validate the performance of a microbiology experiment by demonstrating that the experimental system can detect the target effect (positive control) and that no unintended effects arise from the reagents or procedures (negative control). These controls are useful in virtually any microbiology experiment—from growth inhibition assays and gene expression studies to microbiome profiling and metabolic labeling—because they distinguish genuine biological signals from artifacts, contamination, or procedural errors. Without proper controls, experimental results lack interpretability and reproducibility, as emphasized by best-practice frameworks for microbiome research that call for "appropriate positive and negative controls" to facilitate cross-study comparisons [1].

At a Glance

Aspect	Positive Control	Negative Control
Purpose	Demonstrates that the experimental system can produce the expected effect	Demonstrates that no effect occurs when the target stimulus is absent
Expected outcome	Known positive result (e.g., growth inhibition, gene knockdown, fluorescence signal)	No effect or baseline signal (e.g., no growth, no fluorescence, no amplification)
Typical composition	A known active agent, a validated bacterial strain, or a confirmed target sequence	Sterile water, empty vector, non-targeting guide RNA, or uninoculated medium
When to include	Every experiment where a positive result is possible	Every experiment without exception
What it controls for	Reagent activity, instrument function, assay sensitivity	Contamination, reagent cross-reactivity, non-specific signals
Common failure mode	No signal → assay failure or degraded reagents	Signal detected → contamination or non-specific binding

Scientific Principle of Experimental Controls

The foundation of experimental control in microbiology rests on the concept of falsification: a hypothesis can only be supported if the experimental system is capable of producing both a positive and a null result under appropriate conditions. Positive controls confirm that the assay components—growth medium, enzymes, detection reagents, and instruments—are functional. Negative controls confirm that observed effects are attributable to the experimental variable rather than to extraneous factors such as microbial contamination, reagent impurities, or environmental noise.

In molecular microbiology, the principle extends to genetic perturbation experiments. For example, a CRISPR interference (CRISPRi) exercise designed for an upper-level laboratory course uses a positive control (a validated guide RNA targeting a known essential gene) to confirm that the Cas9-dCas9 system is repressing transcription, and a negative control (a non-targeting guide RNA) to demonstrate that the observed growth defect is sequence-specific rather than due to off-target effects or toxicity from the CRISPR machinery itself [2]. This dual-control structure allows students to "identify, design, and rationalize proper experimental controls" [2].

In microbial ecology and metabolic labeling studies, controls serve a similar gatekeeping function. The dual-BONCAT (bio-orthogonal non-canonical amino acid tagging) method uses a no-ncAA control to establish the background fluorescence threshold; only signals significantly above this background are interpreted as evidence of anabolic activity [3]. This approach prevents false positives from autofluorescence or non-specific dye binding.

Materials and Instrumentation Choices

The specific materials for controls depend on the experimental system, but general categories apply across most BSL-1 microbiology experiments.

Culture Media and Reagents

Sterile broth and agar: Use freshly prepared, autoclaved media. For negative controls, the medium itself must be verified as sterile by incubation before use.
Sterile water or buffer: Phosphate-buffered saline (PBS) or molecular-grade water serves as a no-template or no-treatment negative control.
Positive control agents: For growth inhibition assays, use a known antibiotic (e.g., 100 µg/mL ampicillin for E. coli). For gene expression studies, use a validated inducer (e.g., 1 mM IPTG for lac promoter systems). For metabolic labeling, use a confirmed non-canonical amino acid such as L-azidohomoalanine (AHA) at a concentration known to produce detectable incorporation [3].

Bacterial Strains

Positive control strain: A well-characterized strain with a known phenotype. For example, E. coli MG1655 is commonly used for growth assays, and E. coli with a plasmid-borne fluorescent reporter serves as a positive control for microscopy or flow cytometry.
Negative control strain: The same genetic background without the experimental modification (e.g., wild-type E. coli transformed with an empty vector) [2].

Instruments and Consumables

Incubators: Verify temperature stability (±1°C) with a calibrated thermometer. Temperature drift can cause false negatives in growth-based assays.
Spectrophotometer or plate reader: Calibrate with a standard (e.g., 0.5 McFarland standard for turbidity measurements).
Pipettes and tips: Use filter tips to prevent aerosol contamination. Calibrate pipettes quarterly.
PCR thermocycler: For molecular controls, include a no-template control (NTC) in every run.

Decision Points

When to use a commercial positive control: Use a commercial control (e.g., a validated qPCR positive control plasmid) when the experimental target is a specific gene or sequence and you lack an in-house validated standard.
When to prepare in-house controls: Prepare in-house controls when the experiment involves a novel organism, custom reagent, or non-standard condition. Document the preparation and validation in your laboratory notebook.

Types of Controls in Microbiology Experiments

Positive Controls

A positive control is a treatment that is known to produce the expected effect. Its role is to confirm that the experimental system is capable of detecting that effect. Common examples include:

Growth inhibition assay: A disk impregnated with a known antibiotic (e.g., 30 µg chloramphenicol) placed on a lawn of a susceptible strain.
Gene knockdown: A guide RNA targeting an essential gene (e.g., rpoA in E. coli) that causes a growth defect when expressed with dCas9 [2].
Metabolic labeling: A culture incubated with a known non-canonical amino acid that produces a fluorescence signal above background [3].
PCR amplification: A template containing the target sequence at a known concentration.

Negative Controls

A negative control is a treatment that should produce no effect. It detects contamination, non-specific signals, and procedural errors. Common examples include:

No-treatment control: The experimental organism exposed to sterile water or buffer instead of the test agent.
No-template control: PCR reaction with water instead of DNA template.
Empty vector control: Cells transformed with a plasmid lacking the experimental insert [2].
Uninoculated medium control: Sterile medium incubated alongside experimental cultures to detect contamination.
No-ncAA control: For BONCAT experiments, a sample processed identically but without the non-canonical amino acid [3].

Process Controls

Process controls monitor the entire workflow from sample collection through analysis. In microbiome studies, process controls include extraction blanks (sterile water processed through DNA extraction) and PCR blanks (no-template controls) to identify contamination introduced during sample handling [1]. These are distinct from experimental controls because they assess the method rather than the hypothesis.

Replicate Controls

While not a separate type, technical replicates (multiple measurements of the same sample) and biological replicates (independent cultures or samples) serve as internal controls for variability. Include at least three biological replicates for each experimental condition and control.

Conceptual Workflow for Setting Up Controls

Step 1: Define the Expected Outcome

Before preparing any control, write down the specific, measurable outcome you expect from a positive result and from a negative result. For example:

Positive: ≥90% reduction in colony-forming units (CFUs) compared to untreated control.
Negative: CFU count indistinguishable from the inoculum control (no killing).

Step 2: Select Control Types

Choose positive and negative controls that match your experimental system. For a typical BSL-1 growth inhibition assay:

Positive control: A disk with a known antibiotic to which the test organism is susceptible.
Negative control: A disk with sterile water or solvent only.
Additional negative control: An uninoculated agar plate incubated alongside to detect airborne contamination.

Step 3: Prepare Controls Simultaneously with Experimental Samples

Prepare all controls using the same batch of media, reagents, and instruments as the experimental samples. This ensures that any variability in reagent quality or instrument performance affects controls and samples equally.

Step 4: Include Controls at Every Stage

Pre-experiment: Verify that positive control strains are viable and that negative control media are sterile.
During experiment: Process controls alongside experimental samples (e.g., extract DNA from a blank control in parallel with samples).
Post-experiment: Analyze controls before interpreting experimental data. If a control fails, do not proceed with interpretation.

Step 5: Document Everything

Record the identity, preparation date, lot number, and storage conditions of each control. Note any deviations from the standard protocol. This documentation is essential for troubleshooting and for reproducibility [1].

Quality Checks for Controls

Pre-Experimental Quality Checks

Positive control strain viability: Streak the positive control strain on non-selective agar 24 hours before the experiment. Confirm pure, healthy colonies.
Negative control medium sterility: Incubate a sample of each medium batch at 35°C for 48 hours. No turbidity or colony formation indicates sterility.
Reagent integrity: Check expiration dates and storage conditions. For example, antibiotics should be stored at -20°C and protected from light.

During-Experiment Quality Checks

Positive control response: The positive control must produce the expected result (e.g., a clear zone of inhibition, a fluorescence signal >3× background, or a Ct value within the expected range).
Negative control response: The negative control must produce no signal or a signal indistinguishable from background. Any signal in the negative control indicates contamination or non-specific binding.
Replicate consistency: Technical replicates should have a coefficient of variation (CV) <15% for quantitative assays.

Post-Experiment Quality Checks

Control failure analysis: If a control fails, determine whether the failure is due to reagent degradation, instrument malfunction, or procedural error. Do not use experimental data from a failed run.
Cross-contamination check: If the negative control shows a signal, test the reagents and workspace for contamination using swabs or contact plates.

Interpreting Results with Controls

When Positive Control Works and Negative Control Works

This is the ideal scenario. The experimental system is validated, and any observed effect in the experimental samples can be attributed to the test variable with confidence. Proceed to statistical analysis and interpretation.

When Positive Control Fails

A failed positive control indicates that the assay is not capable of detecting the target effect. Common causes include:

Degraded or expired reagents (e.g., antibiotic stock, enzyme, antibody).
Incorrect storage or handling (e.g., repeated freeze-thaw cycles).
Instrument malfunction (e.g., incubator temperature out of range, plate reader lamp failure).
Wrong strain or concentration (e.g., using a resistant strain as the positive control).

Action: Do not interpret experimental data. Troubleshoot and repeat the experiment.

When Negative Control Fails

A failed negative control indicates contamination, non-specific binding, or reagent cross-reactivity. Common causes include:

Aerosol contamination during pipetting.
Contaminated reagents or water.
Non-specific primer binding in PCR.
Autofluorescence in fluorescence assays.

Action: Do not interpret experimental data. Identify and eliminate the contamination source, then repeat.

When Both Controls Fail

This suggests a systemic problem such as contaminated media, incorrect incubation conditions, or a fundamental error in protocol execution. Review the entire workflow, consult your laboratory supervisor, and repeat the experiment after corrective action.

Troubleshooting Common Control Failures

Observation	Likely Cause	Discriminating Check
Positive control shows no effect	Degraded reagent (e.g., antibiotic, inducer, enzyme)	Test reagent with a known sensitive system; check expiration date and storage log
Positive control shows no effect	Incorrect concentration or volume	Verify preparation calculations; repeat with fresh stock at recommended concentration
Positive control shows no effect	Resistant strain used inadvertently	Confirm strain identity by 16S rRNA sequencing or biochemical tests
Negative control shows growth or signal	Contaminated medium or buffer	Incubate a sample of the same medium batch at 35°C for 48 hours; check for turbidity
Negative control shows growth or signal	Aerosol contamination during pipetting	Use fresh filter tips; repeat with new aliquots of all reagents
Negative control shows growth or signal	Non-specific binding in molecular assay	Run a no-template control; test with a different primer set or probe
Both controls show no signal	Incubation temperature out of range	Check incubator with calibrated thermometer; verify set point
Both controls show no signal	Instrument malfunction (e.g., plate reader, thermocycler)	Run a calibration standard; test with a known positive sample
Positive control works but experimental samples show no effect	Experimental variable is inactive at tested concentration	Test a range of concentrations; verify compound stability in the assay medium
Negative control works but positive control shows weak signal	Reagent partially degraded	Prepare fresh reagent; test at higher concentration if safe and appropriate

Limitations of Controls

Controls are powerful but not infallible. Understanding their limitations prevents overinterpretation.

Controls Do Not Validate Every Variable

A positive control confirms that the assay can detect the target effect under ideal conditions, but it does not guarantee that the experimental variable is active at the tested concentration or that the assay is optimized for the experimental sample matrix. For example, a positive control antibiotic disk works on a lawn of E. coli, but the same antibiotic might be less effective in a complex sample containing binding proteins or competing organisms.

Negative Controls Cannot Prove Absence of All Contamination

A sterile negative control at the start of an experiment does not guarantee that contamination did not occur during later steps. Process controls at each stage (e.g., extraction blanks, PCR blanks) are necessary to monitor contamination throughout the workflow [1].

Controls Do Not Replace Replication

A single positive control and a single negative control provide only a snapshot of assay performance. Biological and technical replicates are needed to assess variability and to ensure that the control results are reproducible.

Controls Are System-Specific

A positive control that works for one organism or assay may not work for another. For example, a guide RNA that knocks down an essential gene in E. coli may have no effect in a different bacterial species due to differences in dCas9 expression or target sequence conservation [2]. Always validate controls in your specific experimental system.

Documentation and Record-Keeping

Proper documentation of controls is essential for reproducibility and for troubleshooting when experiments fail. The following elements should be recorded in your laboratory notebook or electronic laboratory notebook (ELN):

For Each Control

Identity: Unique identifier (e.g., "PC-2025-03-15-Amp")
Preparation date and person
Reagent lot numbers and expiration dates
Storage conditions (temperature, light protection)
Concentration or dilution factor
Expected outcome (quantitative or qualitative)
Observed outcome (attach images, raw data, or instrument printouts)
Any deviations from the standard protocol

For the Experiment as a Whole

Experimental design: Include a table listing all experimental groups and their corresponding controls.
Control placement: For plate-based assays, record the well positions of controls.
Incubation conditions: Temperature, time, atmosphere (aerobic, anaerobic, CO₂).
Instrument settings: Wavelength, gain, cycle parameters.
Data analysis parameters: Thresholds, normalization method, statistical tests.

Example Documentation Entry

Experiment: Growth inhibition of E. coli MG1655 by test compound X
Date: 2025-03-15
Performed by: J. Smith

Controls:
- Positive control: 30 µg chloramphenicol disk (BD, lot #12345, exp. 2026-01)
  Expected: Zone of inhibition ≥18 mm
  Observed: 20 mm (pass)
- Negative control: Sterile water disk (10 µL)
  Expected: No zone of inhibition
  Observed: No zone (pass)
- Uninoculated control: Plate incubated without bacteria
  Expected: No growth
  Observed: No growth (pass)

Conclusion: Assay system validated. Proceed to test compound X at 50, 100, and 200 µg/mL.

Biosafety Considerations

All procedures described in this article are intended for BSL-1 organisms (e.g., E. coli K-12, Bacillus subtilis, Saccharomyces cerevisiae) under standard teaching-laboratory conditions. The following biosafety practices apply:

General Practices

Hand washing: Wash hands after handling cultures and before leaving the laboratory.
Personal protective equipment (PPE): Wear a lab coat, safety glasses, and gloves when handling microbial cultures.
Work surface decontamination: Clean benches with 70% ethanol or 10% bleach before and after work.
Waste disposal: Autoclave all contaminated materials (cultures, used plates, pipette tips) before disposal.

Control-Specific Considerations

Positive controls: Use only BSL-1 organisms. Do not use pathogenic strains as positive controls in a BSL-1 laboratory.
Negative controls: Sterile water and uninoculated media pose no biological hazard, but treat them with the same care as experimental samples to avoid cross-contamination.
Recombinant DNA: If your positive control involves a plasmid or CRISPR construct, follow the NIH Guidelines for Research Involving Recombinant or Synthetic Nucleic Acid Molecules [5]. For BSL-1 work, this typically requires Institutional Biosafety Committee (IBC) registration but no additional containment.

Emergency Procedures

Spill: Cover with absorbent material, apply 10% bleach for 30 minutes, then clean and autoclave the waste.
Exposure: Wash exposed skin with soap and water for 15 minutes. Report to your supervisor and seek medical attention if needed.
Instrument malfunction: If an incubator or centrifuge malfunctions during a run, do not open it until the problem is assessed by a qualified technician.

For comprehensive biosafety guidance, consult the CDC/NIH Biosafety in Microbiological and Biomedical Laboratories (BMBL), 6th Edition [4].

Frequently Asked Questions

1. Can I use the same sample as both a positive and negative control?