The Role of Whole-Genome Sequencing in Quality Assurance of Antimicrobial

By Dr. Zubair Khalid, DVM, MS, PhD · 2026-08-27

Quick Answer

Whole-genome sequencing (WGS) serves as a supplementary quality assurance tool that verifies phenotypic antimicrobial susceptibility testing (AST) results by detecting resistance genes and mutations.
Laboratories should implement WGS as a confirmatory method when phenotypic AST results are discrepant, unusual, or require epidemiological investigation.
WGS cannot replace phenotypic AST because it cannot detect all resistance mechanisms, particularly those involving gene expression, and requires careful interpretation of genotype-phenotype discordance.

The Role of Whole-Genome Sequencing in Quality Assurance of Antimicrobial Susceptibility Testing

Antimicrobial resistance represents one of the most pressing challenges in modern medicine and public health. The World Health Organization identifies antimicrobial resistance as a global health threat that requires coordinated surveillance and stewardship efforts across human, animal, and environmental sectors. Within this context, clinical and research laboratories face the ongoing challenge of ensuring that antimicrobial susceptibility testing results are accurate, reproducible, and clinically meaningful. Whole-genome sequencing has emerged as a powerful tool that can strengthen quality assurance programs by providing a genetic basis for observed phenotypic resistance patterns.

The integration of WGS into laboratory quality assurance requires a clear understanding of what the technology can and cannot accomplish. WGS detects the presence of genetic determinants associated with antimicrobial resistance, including acquired resistance genes and chromosomal mutations. Phenotypic AST measures the observable response of a bacterial isolate to antimicrobial agents under standardized conditions. These two approaches provide complementary information, and their combined use can identify discrepancies that would otherwise go undetected.

This article provides laboratory professionals, researchers, and life-science practitioners with a practical framework for incorporating WGS into quality assurance programs for antimicrobial susceptibility testing. The content covers the scientific basis for WGS-based resistance prediction, the practical workflow for integration, interpretation of discordant results, and the limitations that laboratories must acknowledge when using this technology.

At a Glance

The following table summarizes the key considerations for using WGS in quality assurance of antimicrobial susceptibility testing.

Aspect	Phenotypic AST	WGS-Based Prediction	Integration into QA
What it measures	Observable bacterial growth inhibition	Presence of resistance genes and mutations	Cross-verification of results
Result type	Quantitative (MIC) or qualitative (S/I/R)	Genetic determinants with predicted phenotype	Concordance assessment
Turnaround time	16-24 hours typically	1-3 days depending on workflow	Dependent on both methods
Cost per isolate	Low to moderate	Higher initial investment	Cost-effective for targeted use
Strengths	Detects expressed resistance	Detects silent and acquired genes	Identifies discrepancies
Limitations	Requires viable culture	Cannot assess gene expression	Requires interpretation

Understanding the Quality Assurance Problem

The Need for Verification in Antimicrobial Susceptibility Testing

Antimicrobial susceptibility testing forms the foundation of clinical decision-making for infectious disease management. The Clinical and Laboratory Standards Institute provides standards-based methodology for antimicrobial susceptibility testing, establishing the framework that laboratories use to generate reliable and reproducible results. These standards address the selection of antimicrobial agents, testing conditions, quality control organisms, and interpretive criteria that laboratories must follow to produce clinically meaningful data.

Quality assurance in the microbiology laboratory encompasses all activities that ensure test results are accurate, reliable, and reproducible. For antimicrobial susceptibility testing, quality assurance includes the use of authenticated reference strains, standardized testing conditions, and regular verification of test performance. The American Type Culture Collection provides authenticated biological materials that serve as quality control strains for susceptibility testing, ensuring that laboratory results can be compared across time and across facilities.

The challenge facing modern laboratories is that phenotypic testing alone cannot always detect the full complexity of antimicrobial resistance. Bacteria may carry resistance genes that are not expressed under standard testing conditions, or they may express resistance through mechanisms that are difficult to detect phenotypically. WGS offers a complementary approach that can identify the genetic potential for resistance, providing a more complete picture of the isolate's resistance profile.

Why Phenotypic Results Sometimes Need Genetic Confirmation

Phenotypic AST results can be ambiguous or misleading in several situations. An isolate may appear susceptible to an antimicrobial agent in vitro but carry a resistance gene that could be expressed under different conditions. Conversely, an isolate may demonstrate phenotypic resistance that cannot be explained by known resistance mechanisms. These situations create uncertainty for clinicians and require additional investigation.

The integration of WGS into quality assurance programs addresses these uncertainties by providing a genetic basis for observed phenotypic results. When phenotypic and genotypic results are concordant, the laboratory can have greater confidence in the accuracy of the susceptibility report. When results are discordant, the laboratory must investigate the cause and determine whether the discrepancy reflects a technical issue, a novel resistance mechanism, or a limitation of one of the testing methods.

Core Principles of WGS-Based Resistance Prediction

Genetic Basis of Antimicrobial Resistance

Antimicrobial resistance arises from two primary genetic mechanisms: the acquisition of resistance genes through horizontal gene transfer and the accumulation of chromosomal mutations. Acquired resistance genes often encode enzymes that inactivate antimicrobial agents, efflux pumps that expel drugs from the cell, or modified target sites that prevent drug binding. Chromosomal mutations can alter drug targets, reduce drug uptake, or increase efflux activity.

WGS identifies these genetic determinants by sequencing the entire bacterial genome and comparing the sequence against databases of known resistance genes and mutations. The presence of a specific resistance gene or mutation provides evidence that the isolate has the genetic potential to resist the corresponding antimicrobial agent. This information can be used to predict the phenotypic resistance profile of the isolate.

Bioinformatics Analysis and Resistance Gene Databases

The interpretation of WGS data requires bioinformatics analysis to identify resistance determinants. This analysis involves assembling the raw sequencing reads into a complete or partial genome sequence and then comparing the sequence against curated databases of resistance genes and mutations. The quality of the analysis depends on the completeness of the databases and the accuracy of the bioinformatics pipeline.

The accuracy of WGS-based resistance prediction depends on the quality of the reference databases and the bioinformatics tools used. Laboratories must validate their bioinformatics pipelines and ensure that they are using current, well-curated databases. The interpretation of WGS results also requires an understanding of the genetic context of resistance genes, including whether they are located on mobile genetic elements that could facilitate their spread.

Limitations of Genotype-Based Prediction

The most significant limitation of WGS-based resistance prediction is that it cannot detect all resistance mechanisms. Some resistance mechanisms involve gene expression instead of gene presence, and these cannot be detected by DNA sequence analysis alone. For example, a resistance gene may be present but not expressed under standard conditions, or a gene may be expressed at levels that do not produce clinically significant resistance.

WGS also cannot detect resistance mechanisms that involve post-transcriptional or post-translational modifications. These mechanisms may be important in certain bacterial species or for certain antimicrobial agents. The limitations of WGS-based resistance prediction must be acknowledged when interpreting discordant genotype-phenotype results.

Practical Workflow for Integrating WGS into Quality Assurance

Step 1: Establish the Quality Assurance Framework

The first step in integrating WGS into a quality assurance program is to establish the framework for how WGS will be used. This includes defining the purpose of WGS testing, the types of isolates that will be sequenced, and the criteria for when WGS will be used to verify phenotypic AST results. The framework should be documented in the laboratory's quality manual and should be consistent with the laboratory's overall quality assurance policies.

The laboratory should also establish the criteria for when WGS will be used as a confirmatory method. This may include situations where phenotypic results are discordant with clinical expectations, where the isolate is from a patient with a serious infection, or where the isolate is suspected of carrying a novel resistance mechanism. The criteria should be specific and should be applied consistently.

Step 2: Establishing the WGS Workflow

The WGS workflow involves several steps, including DNA extraction, library preparation, sequencing, and bioinformatics analysis. Each step must be validated and controlled to ensure that the results are reliable. The laboratory should establish standard operating procedures for each step and should use authenticated reference strains to verify the performance of the workflow.

The American Type Culture Collection provides authenticated biological materials that can be used to validate the WGS workflow. These reference strains have known resistance profiles and can be used to verify that the WGS analysis correctly identifies the expected resistance determinants. The use of authenticated reference strains is essential for ensuring the quality of WGS results.

Step 3: Interpreting WGS Results

The interpretation of WGS results requires a systematic approach that considers the genetic determinants identified, the predicted resistance profile, and the phenotypic AST results. The laboratory should establish criteria for classifying results as concordant, discordant, or indeterminate. The interpretation should be documented and reviewed by qualified personnel.

The interpretation of WGS results should also consider the clinical context of the isolate. The presence of a resistance gene does not always mean that the isolate will be resistant to the corresponding antimicrobial agent in the clinical setting. The laboratory should provide the clinician with the WGS results and the interpretation of the results, including any limitations of the analysis.

Step 4: Documenting and Reporting Results

The laboratory should document all WGS results and the interpretation of those results. The documentation should include the WGS data, the bioinformatics analysis, the resistance determinants identified, and the interpretation of the results. The documentation should be retained in accordance with the laboratory's quality assurance policies.

The reporting of WGS results should be clear and concise, and should include the limitations of the analysis. The laboratory should report the WGS results in a format that is useful to the clinician, including the resistance determinants identified and the predicted resistance profile. The report should also include the interpretation of the results and any recommendations for further testing.

Interpreting Discordant Genotype-Phenotype Results

Understanding the Sources of Discordance

Discordance between WGS-based resistance prediction and phenotypic AST results can arise from several sources. The most common source is the presence of a resistance gene that is not expressed under the conditions of the phenotypic test. This can occur when the gene is present but not transcribed, or when the gene is transcribed but the protein is not functional.

Another source of discordance is the presence of a resistance mechanism that is not detected by the WGS analysis. This can occur when the resistance mechanism is not included in the database used for the analysis, or when the resistance mechanism is not detectable by DNA sequencing. The laboratory should investigate the cause of the discordance and determine whether the WGS analysis needs to be repeated or the database needs to be updated.

Interpreting Discordant Results

When WGS results and phenotypic AST results are discordant, the laboratory must determine the cause of the discordance and decide how to proceed. The laboratory should first verify that the WGS analysis was performed correctly and that the results are reliable. The laboratory should also verify that the phenotypic AST was performed correctly and that the results are reliable.

If the discordance cannot be resolved, the laboratory should consider the clinical context of the isolate and the potential impact of the discordance on patient care. The laboratory should communicate the discordance to the clinician and provide guidance on how to interpret the results. The laboratory should also consider whether additional testing is needed to resolve the discordance.

When to Use WGS for Confirmation

WGS should be used for confirmation when the phenotypic AST results are discordant with the expected resistance profile, when the isolate is suspected of carrying a novel resistance mechanism, or when the isolate is from a patient with a serious infection. The use of WGS for confirmation should be based on the criteria established in the laboratory's quality assurance framework.

The use of WGS for confirmation should also be considered when the phenotypic AST results are ambiguous or when the results are not reproducible. In these cases, WGS can provide a genetic basis for the observed phenotype and can help to resolve the ambiguity. The laboratory should document the use of WGS for confirmation and the results of the analysis.

Practical Implementation Steps

Step 1: Assess Laboratory Readiness

Before integrating WGS into the quality assurance program, the laboratory should assess its readiness for WGS. This includes evaluating the laboratory's infrastructure, the availability of WGS equipment and expertise, and the laboratory's budget for WGS. The laboratory should also consider the regulatory and accreditation requirements for WGS.

The laboratory should also assess the need for WGS in its quality assurance program. This includes evaluating the types of isolates that are tested, the frequency of discordant results, and the clinical impact of the discordance. The laboratory should determine whether WGS is a cost-effective addition to its quality assurance program.

Step 2: Validate the WGS Workflow

The laboratory should validate the WGS workflow before using it for quality assurance. This includes validating the DNA extraction, sequencing, and bioinformatics analysis steps. The laboratory should use authenticated reference strains to verify that the WGS workflow correctly identifies the expected resistance determinants.

The validation should also include a comparison of WGS results with phenotypic AST results for a set of well-characterized isolates. The laboratory should determine the concordance between the WGS results and the phenotypic results and should establish the criteria for acceptable concordance.

Step 3: Establish the Quality Assurance Protocol

The laboratory should establish a quality assurance protocol for WGS that includes the criteria for when WGS will be used, the workflow for WGS, the interpretation of WGS results, and the reporting of WGS results. The protocol should be documented and should be reviewed and updated on a regular basis.

The protocol should also include the criteria for when WGS results will be used to verify phenotypic AST results. The laboratory should establish the criteria for concordance and discordance and should define the actions to be taken when discordance is observed.

Step 4: Train Personnel and Implement the Protocol

The laboratory should train personnel on the WGS workflow and the quality assurance protocol. The training should include the principles of WGS, the interpretation of WGS results, and the use of WGS in quality assurance. The training should be documented and should be updated as needed.

The laboratory should implement the quality assurance protocol and should monitor the performance of the WGS workflow. The laboratory should also monitor the concordance and discordance of WGS results with phenotypic AST results and should take corrective action when the concordance is not acceptable.

Records and Measurements

Essential Records for WGS Quality Assurance

The laboratory should maintain records of all WGS activities, including the WGS workflow, the bioinformatics analysis, the results of the WGS, and the interpretation of the results. The records should be retained and maintained in accordance with the laboratory's quality assurance policies.

The records should also include the validation of the WGS workflow, the training of personnel, and the monitoring of the WGS performance. The records should be reviewed on a regular basis to ensure that the WGS workflow is performing as expected.

Measurements and Metrics for WGS Quality Assurance

The laboratory should measure the performance of the WGS workflow and the quality assurance program. The measurements should include the concordance of WGS results with phenotypic AST results, the turnaround time for WGS, and the cost of WGS. The laboratory should also measure the rate of discordance and the rate of indeterminate results.

The measurements should be used to evaluate the performance of the WGS workflow and to identify areas for improvement. The laboratory should also use the measurements to determine whether the WGS workflow is meeting the needs of the quality assurance program.

Common Failure Patterns and Troubleshooting

Failure Pattern 1: Discordant Results Due to Gene Expression

A common failure pattern is the presence of a resistance gene that is not expressed under the conditions of the phenotypic AST. This can result in a discordant result where the WGS predicts resistance but the phenotypic AST shows susceptibility. The laboratory should investigate the cause of the discordance and determine whether the resistance gene is expressed under the conditions of the test.

The laboratory should also consider whether the resistance gene is present in a context that could affect its expression, such as the presence of a promoter or a regulatory element. The laboratory should also consider whether the resistance gene is present in a mobile genetic element that could affect its expression.

Failure Pattern 2: Discordant Results Due to Novel Resistance Mechanisms

Another common failure pattern is the presence of a resistance mechanism that is not detected by the WGS analysis. This can occur when the resistance mechanism is not included in the database used for the analysis, or when the resistance mechanism is not detectable by DNA sequencing. The laboratory should investigate the cause of the discordance and determine whether the resistance mechanism is present in the isolate.

The laboratory should also consider whether the resistance mechanism is a novel mechanism that has not been described in the literature. The laboratory should consider whether the resistance mechanism is a known mechanism that is not included in the database. The laboratory should also consider whether the resistance mechanism is a mechanism that is not detectable by DNA sequencing.

Failure Pattern 3: Discordant Results Due to Phenotypic AST Errors

A third common failure pattern is the presence of a discordant result due to an error in the phenotypic AST. This can occur when the phenotypic AST is performed incorrectly, when the results are interpreted incorrectly, or when the results are not reproducible. The laboratory should investigate the cause of the discordance and determine whether the phenotypic AST was performed correctly.

The laboratory should also consider whether the phenotypic AST was performed using the correct method and the correct conditions. The laboratory should also consider whether the phenotypic AST was performed using the correct quality control strains. The laboratory should also consider whether the phenotypic AST was performed using the correct interpretation criteria.

Limitations of WGS in Quality Assurance

Inability to Detect All Resistance Mechanisms

WGS cannot detect all resistance mechanisms. Some resistance mechanisms are not detectable by DNA sequencing, and some resistance mechanisms are not included in the databases used for the analysis. The laboratory should acknowledge this limitation and should not rely solely on WGS for the detection of antimicrobial resistance.

The laboratory should also consider the limitations of WGS when interpreting the results. The laboratory should consider the possibility that the WGS analysis may not detect a resistance mechanism that is present in the isolate. The laboratory should also consider the possibility that the WGS analysis may detect a resistance mechanism that is not expressed in the isolate.

The Need for Phenotypic Confirmation

WGS should not be used as a replacement for phenotypic AST. The laboratory should use WGS as a supplementary tool to verify the results of phenotypic AST. The laboratory should also use WGS to investigate discordant results and to identify novel resistance mechanisms.

The laboratory should also consider the limitations of WGS in the context of the clinical setting. The laboratory should not use WGS to make clinical decisions without considering the phenotypic AST results. The laboratory should also consider the clinical context of the isolate and the potential impact of the WGS results on patient care.

The Need for Continuous Database Updates

The WGS analysis depends on the quality of the database used for the analysis. The laboratory should ensure that the database is current and that it includes the most recent resistance genes and mutations. The laboratory should also ensure that the database is updated on a regular basis.

The laboratory should also consider the limitations of the database. The database may not include all resistance genes and mutations, and the database may not include the most recent resistance mechanisms. The laboratory should consider the limitations of the database when interpreting the results.

Safety and Regulatory Context

Laboratory Biosafety Considerations

The laboratory should follow the biosafety guidelines for the handling of bacterial isolates and the performance of WGS. The Biosafety in Microbiological and Biomedical Laboratories provides the guidelines for the safe handling of microorganisms and the containment of biological materials. The laboratory should follow these guidelines to ensure the safety of personnel and the environment.

The laboratory should also follow the guidelines for the decontamination of the WGS equipment and the disposal of the WGS waste. The laboratory should also follow the guidelines for the handling of the WGS reagents and the disposal of the WGS reagents.

Regulatory and Accreditation Requirements

The laboratory should consider the regulatory and accreditation requirements for WGS. The laboratory should ensure that the WGS workflow is consistent with the requirements of the regulatory and accreditation bodies. The laboratory should also ensure that the WGS workflow is consistent with the requirements of the laboratory's quality assurance program.

The laboratory should also consider the regulatory and accreditation requirements for the reporting of WGS results. The laboratory should ensure that the WGS results are reported in a manner that is consistent with the requirements of the regulatory and accreditation bodies.

Professional Escalation Criteria

The laboratory should establish the criteria for when to escalate the WGS results to a higher level of authority. The escalation criteria should include the following situations:

The WGS results are discordant with the phenotypic AST results and the discordance cannot be resolved.
The WGS results are discordant with the clinical results and the discordance cannot be resolved.
The WGS results are discordant with the results of other laboratories and the discordance cannot be resolved.
The WGS results are discordant with the results of the reference laboratory and the discordance cannot be resolved.

The laboratory should also escalate the WGS results when the WGS results are not reproducible, or when the WGS results are not consistent with the results of the quality control strains. The laboratory should also escalate the WGS results when the WGS results are not consistent with the results of the reference strains.

A Practical Decision Framework for WGS-Based Verification of Phenotypic AST Results

Laboratories that adopt whole-genome sequencing for resistance prediction often struggle with a specific operational problem: when should WGS be used to verify a phenotypic antimicrobial susceptibility testing result, and what actions should follow when the two methods disagree? A structured decision framework provides a consistent, defensible approach that moves beyond ad hoc sequencing decisions and supports reproducible quality assurance outcomes.

The Verification Trigger Matrix

The first component of a practical decision framework is a trigger matrix that defines the specific situations in which WGS should be initiated as a verification tool. This matrix should be documented in the laboratory quality manual and applied consistently by all personnel. The triggers fall into four categories: result-based triggers, isolate-based triggers, clinical triggers, and surveillance triggers.

Result-based triggers include phenotypic AST results that are unusual for the bacterial species, results that fall outside the expected resistance profile for the specimen source, and results that change the clinical management of a patient. For example, a carbapenem-resistant Enterobacterales isolate from a urine specimen that has no prior history of carbapenem exposure would trigger WGS verification. Similarly, a vancomycin-resistant Staphylococcus aureus result, which is extremely rare, should always trigger WGS confirmation before the result is reported.

Isolate-based triggers include isolates from sterile body sites, isolates from patients with recurrent infections, and isolates that demonstrate unusual colony morphology or growth characteristics. Isolates that produce inconsistent results on repeat testing also qualify for WGS verification. The American Type Culture Collection provides authenticated reference strains that can be used to verify the performance of the WGS workflow when these triggers are activated, ensuring that the sequencing and analysis pipeline is functioning correctly.

Clinical triggers include isolates from patients who have failed therapy despite apparent susceptibility, isolates from patients with severe or life-threatening infections, and isolates from patients with infections that are epidemiologically linked to outbreaks. The World Health Organization emphasizes the importance of surveillance and stewardship in addressing antimicrobial resistance, and WGS verification of isolates from these clinical scenarios supports both patient care and public health objectives.

Surveillance triggers include isolates that are part of a resistance surveillance program, isolates from food or environmental samples that show unexpected resistance patterns, and isolates that are being characterized for research purposes. The U.S. Food and Drug Administration's Bacteriological Analytical Manual provides context for how official food microbiology methods incorporate quality measures, and WGS can serve a similar verification role in food safety surveillance.

The Verification Decision Tree

Once a trigger has been identified, the laboratory follows a decision tree that guides the verification process. The decision tree has four decision points, each with defined actions and documentation requirements.

The first decision point asks whether the phenotypic AST result was generated using a validated method with appropriate quality control. The Clinical and Laboratory Standards Institute provides standards-based methodology for antimicrobial susceptibility testing, and the laboratory must confirm that the test was performed according to these standards. If the phenotypic test was not performed correctly, the laboratory should repeat the test before proceeding to WGS. If the test was performed correctly, the laboratory proceeds to the second decision point.

The second decision point asks whether the isolate is available for WGS analysis. The isolate must be viable, pure, and properly stored. If the isolate is not available, the laboratory should document the situation and consider whether the phenotypic result should be reported with a cautionary note. If the isolate is available, the laboratory proceeds to the third decision point.

The third decision point asks whether the WGS analysis has been validated for the bacterial species and the antimicrobial agents in question. The laboratory must have validated its WGS workflow using authenticated reference strains, and the bioinformatics pipeline must be appropriate for the species being tested. If the WGS analysis has not been validated for the species, the laboratory should not use WGS to verify the phenotypic result and should instead consider sending the isolate to a reference laboratory.

The fourth decision point asks whether the WGS result is concordant with the phenotypic result. If the results are concordant, the laboratory can report the phenotypic result with confidence. If the results are discordant, the laboratory must follow the discordance resolution protocol described in the next section.

Discordance Resolution Protocol

When WGS and phenotypic AST results are discordant, the laboratory must have a systematic protocol for resolving the discrepancy. The protocol should be documented and should include the following steps.

The first step is to verify both results. The laboratory should repeat the phenotypic AST using the same method and the same conditions, and should also repeat the WGS analysis using the same bioinformatics pipeline. If the repeat results are consistent with the original results, the laboratory proceeds to the second step.

The second step is to assess the genetic context of the resistance determinant. The laboratory should examine the WGS data to determine whether the resistance gene is intact, whether it is located on a mobile genetic element, and whether it is associated with a promoter or regulatory element that could affect expression. The American Type Culture Collection provides strain information that can help laboratories understand the genetic context of resistance determinants in reference strains.

The third step is to consider the mechanism of resistance. Some resistance mechanisms are not detectable by WGS, including those that involve gene expression, post-transcriptional modifications, or post-translational modifications. The laboratory should consider whether the discordance could be explained by one of these mechanisms.

The fourth step is to determine the clinical significance of the discordance. The laboratory should consider the clinical context of the isolate, the antimicrobial agent in question, and the potential impact of the discordance on patient care. The laboratory should communicate the discordance to the clinician and provide guidance on how to interpret the results.

The fifth step is to document the discordance and the resolution. The laboratory should maintain records of the discordance, the investigation, and the resolution. These records should be reviewed on a regular basis to identify patterns that may indicate a problem with the WGS workflow or the phenotypic AST method.

Concordance Categories and Reporting Actions

The decision framework should define clear concordance categories and the reporting actions associated with each category. The categories are concordant, minor discordance, major discordance, and indeterminate.

Concordant results occur when the WGS prediction and the phenotypic AST result are in agreement. The laboratory reports the phenotypic result without modification and documents the concordance in the quality assurance records.

Minor discordance occurs when the WGS prediction and the phenotypic AST result differ by one interpretive category, such as susceptible versus intermediate. The laboratory should investigate the discordance and should report the phenotypic result with a note indicating that WGS identified a resistance determinant that may affect the interpretation.

Major discordance occurs when the WGS prediction and the phenotypic AST result differ by two categories, such as susceptible versus resistant. The laboratory should repeat both tests, investigate the cause of the discordance, and report the results with a cautionary note. The laboratory should also consider whether the isolate should be sent to a reference laboratory for confirmation.

Indeterminate results occur when the WGS analysis cannot identify a resistance determinant that explains the phenotypic result, or when the WGS analysis identifies a resistance determinant that is not associated with a clear phenotypic prediction. The laboratory should report the phenotypic result and document the indeterminate WGS result in the quality assurance records.

Records and Measurements for the Decision Framework

The decision framework requires specific records and measurements to be effective. The laboratory should maintain a log of all WGS verification activities, including the trigger that initiated the verification, the date of the verification, the isolate identification, the WGS result, the phenotypic AST result, and the outcome of the verification.

The laboratory should also measure the performance of the decision framework. The key metrics include the concordance rate between WGS and phenotypic AST, the rate of minor discordance, the rate of major discordance, and the rate of indeterminate results. The laboratory should track these metrics over time and should investigate any trends that indicate a problem with the WGS workflow or the phenotypic AST method.

The laboratory should also measure the turnaround time for WGS verification. The turnaround time should be documented for each verification and should be compared to the target turnaround time established in the quality assurance protocol. The laboratory should investigate any delays in the WGS workflow that could affect the clinical utility of the verification.

Common Failure Patterns in the Decision Framework

The decision framework can fail in several ways. The most common failure pattern is the use of WGS for verification without a clear trigger. This can result in unnecessary sequencing and increased costs without a corresponding improvement in quality assurance. The laboratory should review the trigger matrix on a regular basis and should ensure that the triggers are being applied consistently.

A second failure pattern is the failure to document the decision framework. The laboratory should document all WGS verification activities, including the trigger, the decision tree, the concordance category, and the reporting action. The documentation should be reviewed on a regular basis to ensure that the framework is being followed.

A third failure pattern is the failure to update the decision framework. The framework should be reviewed and updated on a regular basis to reflect changes in the WGS workflow, the phenotypic AST method, the resistance databases, and the clinical context. The laboratory should also update the framework to reflect the lessons learned from the discordance resolution protocol.

A fourth failure pattern is the failure to train personnel on the decision framework. The laboratory should train all personnel on the trigger matrix, the decision tree, the discordance resolution protocol, and the concordance categories. The training should be documented and should be updated as needed.

Professional Escalation Criteria for the Decision Framework

The decision framework should include clear escalation criteria. The laboratory should escalate the WGS verification to a higher level of authority in the following situations:

The WGS result is discordant with the phenotypic AST result and the discordance cannot be resolved after the full resolution protocol.
The WGS result is discordant with the clinical presentation of the patient and the discordance cannot be resolved.
The WGS result is discordant with the results of a reference laboratory and the discordance cannot be resolved.
The WGS result is not reproducible across multiple runs of the same isolate.
The WGS result is not consistent with the results of the quality control strains used in the WGS workflow.

The laboratory should also escalate the WGS verification when the discordance rate exceeds the acceptable threshold established in the quality assurance protocol. The threshold should be based on the laboratory's historical performance and should be reviewed on a regular basis.

Safety and Regulatory Context for the Decision Framework

The decision framework should be implemented in accordance with the biosafety guidelines for the handling of bacterial isolates and the performance of WGS. The Biosafety in Microbiological and Biomedical Laboratories provides the guidelines for the safe handling of microorganisms and the containment of biological materials. The laboratory should follow these guidelines to ensure the safety of personnel and the environment.

The laboratory should also consider the regulatory and accreditation requirements for WGS verification. The laboratory should ensure that the decision framework is consistent with the requirements of the regulatory and accreditation bodies. The laboratory should also ensure that the WGS verification results are reported in a manner that is consistent with the requirements of the laboratory's quality assurance program.

The American Society for Microbiology provides professional education and laboratory practice resources that can support the implementation of the decision framework. The laboratory should use these resources to train personnel and to stay current with the best practices for WGS verification.

Implementation Steps for the Decision Framework

The laboratory should implement the decision framework in a structured manner. The first step is to establish the trigger matrix and to document the triggers in the quality manual. The second step is to establish the decision tree and the concordance categories. The third step is to establish the discordance resolution protocol. The fourth step is to establish the records and measurements for the framework. The fifth step is to train personnel on the framework. The sixth step is to implement the framework and to monitor its performance.

The laboratory should also establish a schedule for reviewing the decision framework. The review should include an assessment of the trigger matrix, the decision tree, the concordance categories, the discordance resolution protocol, and the records and measurements. The review should also include an assessment of the performance metrics and the identification of areas for improvement.

The decision framework provides a practical and structured approach to using WGS for the verification of phenotypic AST results. The framework ensures that WGS is used consistently and appropriately, that discordant results are investigated systematically, and that the results are reported in a manner that is useful to the clinician. The framework also ensures that the laboratory is using WGS in a cost-effective manner and that the WGS workflow is performing as expected.

Frequently Asked Questions

What is the difference between WGS and phenotypic AST?

WGS detects the genetic determinants of antimicrobial resistance, including resistance genes and mutations, while phenotypic AST measures the observable growth of the isolate in the presence of antimicrobial agents. WGS provides a genetic basis for the resistance, while phenotypic AST provides a measure of the resistance.

How can WGS be used to verify phenotypic AST results?

WGS can be used to verify phenotypic AST results by comparing the genetic resistance determinants with the phenotypic resistance profile. When the WGS results and the phenotypic results are concordant, the laboratory can have high confidence in the results. When the results are discordant, the laboratory must investigate the cause of the discordance.

What are the limitations of WGS for resistance prediction?

WGS cannot detect all resistance mechanisms, and it cannot detect resistance mechanisms that are not included in the database. WGS also cannot detect resistance mechanisms that are not expressed under the conditions of the test. The laboratory should consider these limitations when interpreting the results.

When should WGS be used for confirmation of phenotypic AST results?

WGS should be used for confirmation when the phenotypic AST results are discordant with the clinical results, when the isolate is suspected of carrying a novel resistance mechanism, or when the isolate is from a patient with a serious infection. The laboratory should establish the criteria for when WGS will be used for confirmation.

What are the limitations of WGS in the clinical setting?

WGS cannot detect all resistance mechanisms, and it cannot detect the expression of resistance genes. WGS also cannot detect resistance mechanisms that are not included in the database. The laboratory should consider these limitations when interpreting the WGS results.

How should the laboratory interpret discordant genotype-phenotype results?

The laboratory should investigate the cause of the discordance and determine whether the discordance is due to a resistance gene that is not expressed, a resistance mechanism that is not detected by the WGS, or an error in the phenotypic AST. The laboratory should also consider the clinical context of the case.

What are the quality assurance requirements for WGS?

The laboratory should validate the WGS workflow, use authenticated reference strains, and establish a quality assurance protocol for WGS. The laboratory should also monitor the performance of the WGS workflow and the concordance of the WGS results with the phenotypic AST results.

How should the laboratory report WGS results?

The laboratory should report the WGS results in a clear and concise manner, including the resistance determinants identified and the interpretation of the results. The report should also include the limitations of the WGS analysis and the recommendations for further testing.

Using the Evidence

Source	Best use in this topic	Important limitation
Biosafety in Microbiological and Biomedical Laboratories	official guidance	Check the linked page for current local requirements
Microbiology Resources	official guidance	Check the linked page for current local requirements
Antimicrobial Resistance	official guidance	Check the linked page for current local requirements

Related Bacteriology Guides

References and Further Reading

Biosafety in Microbiological and Biomedical Laboratories. CDC and NIH.
Microbiology Resources. American Society for Microbiology.
Antimicrobial Resistance. World Health Organization.
Bacteriological Analytical Manual. U.S. Food and Drug Administration.
Antimicrobial Susceptibility Testing. Clinical and Laboratory Standards Institute.
Culture Collections. American Type Culture Collection.
NCBI Pathogen Detection. National Center for Biotechnology Information.
Performance of a quality control center supporting national antimicrobial resistance surveillance.. 2026.
Study Protocol for Genomic Epidemiology Investigation of Intensive Care Unit Patient Colonization by Antimicrobial-Resistant ESKAPE Pathogens.. 2025.
&lt,i&gt,Bacillus velezensis&lt,/i&gt, M4 from Northeast Chinese Soybean Paste Combines Nattokinase and Antibacterial Activities.. 2026.
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This article is educational and does not replace validated laboratory procedures, clinical diagnosis, institutional biosafety review, or public-health guidance.