Molecular & PH Interview Quiz
PCR control checks, sequencing interpretation, NGS pipelines, and reference laboratory actions.
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Molecular Diagnostics and Public Health Microbiology Interview Questions: NGS, Genomic Epidemiology, Outbreak Response, and AMR Surveillance
Molecular diagnostics and public health microbiology represent two of the fastest-growing and most consequential areas in the entire field. The COVID-19 pandemic brought both into the sharpest possible focus: PCR testing at unprecedented scale, whole-genome sequencing to track variant emergence, and genomic epidemiology to reconstruct transmission chains. Roles at the intersection of these two fields, in national reference laboratories, public health agencies, and academic-health system partnerships, are among the most demanding and impactful in microbiology.
This page prepares you for interviews for molecular diagnostics roles (clinical molecular scientist, diagnostics development scientist), public health laboratory roles (public health microbiologist, surveillance scientist), and genomic epidemiology positions. The questions cover NGS principles and clinical applications, bioinformatics concepts accessible to non-computational specialists, genomic epidemiology, AMR surveillance programmes, and the ability to communicate complex scientific findings to non-specialist public health and clinical audiences.
Core Interview Question Categories
Next-Generation Sequencing in Clinical and Public Health Microbiology
Be prepared to explain the basic principle of Illumina short-read sequencing: DNA is fragmented, adaptors are ligated, fragments are amplified on a flow cell by bridge amplification, and millions of fragments are sequenced simultaneously by synthesis (each incorporation of a fluorescently labelled reversible terminator nucleotide is detected by imaging). Reads of 150 to 300 base pairs are generated. Bioinformatic pipelines then assemble the reads into longer contigs and, where a reference genome is available, map them to the reference to identify variant positions (single nucleotide polymorphisms, or SNPs).
Oxford Nanopore sequencing (long-read) generates much longer reads (up to hundreds of kilobases) by threading DNA through a protein nanopore and measuring changes in ion current as each base passes through. It enables real-time sequencing without the assembly complexity introduced by short reads, and is particularly valuable for sequencing through repetitive regions and for rapid turnaround in outbreak situations. The Oxford Nanopore MinION is a portable sequencer about the size of a USB drive, which has been used for field sequencing in Ebola outbreak zones and during COVID-19.
Clinical applications of NGS in microbiology include: whole-genome sequencing of bacterial isolates for high-resolution typing and outbreak investigation, metagenomics for direct pathogen detection from clinical samples without culture (particularly valuable for unusual or unculturable pathogens), antimicrobial resistance gene detection and resistome characterisation, and viral variant tracking (as performed globally for SARS-CoV-2 throughout the pandemic).
Genomic Epidemiology
Genomic epidemiology uses whole-genome sequencing data from pathogen isolates to reconstruct transmission events, identify outbreak clusters, and understand the global spread of infectious diseases. The key concept is phylogenetics: constructing a tree that represents the evolutionary relationships between pathogen genomes. Genomes that are closely related (differing by only a few SNPs) have probably diverged recently from a common ancestor, suggesting recent transmission or a common source. The interpretation of phylogenetic trees requires careful attention to the time frame (a difference of 5 SNPs might represent months of evolution in a rapidly evolving virus like influenza but decades in a slowly evolving bacterium like M. tuberculosis), the sequencing error rate, and the epidemiological context.
The COVID-19 pandemic produced the most ambitious genomic epidemiology project in history. The SARS-CoV-2 Global Initiative on Sharing All Influenza Data (GISAID) database accumulated over 15 million SARS-CoV-2 genome sequences, enabling real-time tracking of the emergence and spread of variants of concern including Alpha, Delta, and Omicron.
AMR Surveillance Programmes
Global AMR surveillance programmes provide the population-level data needed to understand how antimicrobial resistance is distributed and changing over time. The WHO Global Antimicrobial Resistance and Use Surveillance System (GLASS) collates national AMR surveillance data from member countries. In Europe, the European Antimicrobial Resistance Surveillance Network (EARS-Net) monitors resistance in invasive isolates of key priority pathogens including E. coli, Klebsiella pneumoniae, Staphylococcus aureus, Streptococcus pneumoniae, Enterococcus faecalis, and Enterococcus faecium from bacteraemia in EU/EEA countries. The WHO priority pathogen list (2017, updated 2024) classifies priority pathogens for antibiotic research and development into critical, high, and medium priority groups.
Mock Interview Questions and Model Answers
What is a SNP and how is it used in molecular epidemiology?
A single nucleotide polymorphism (SNP) is a variation in a single DNA base pair position within a genome. In the context of molecular epidemiology, SNPs are used to measure the genetic distance between pathogen isolates. Two isolates that differ by only a small number of SNPs (the exact threshold depends on the organism and its mutation rate) have probably diverged recently from a common ancestor, suggesting they are part of the same transmission event or outbreak cluster. Isolates that differ by many SNPs are less likely to be epidemiologically linked. SNP-based phylogenetic analysis is the basis of WGS-based outbreak investigation for bacterial pathogens including MRSA, Clostridioides difficile, Salmonella, and E. coli.
How would you communicate a complex genomic epidemiology finding to a non-scientific audience?
A strong answer to this question demonstrates communication skills as much as technical knowledge. Good approaches include: using analogy (the genome is like a long sentence, and a mutation is like a changed word, so two sequences that are nearly identical are like two copies of the same sentence with one or two different words, strongly suggesting they came from the same source), using visual tools (a clear phylogenetic tree with coloured cluster highlighting, a map showing geographical distribution), focusing on the conclusion rather than the method (rather than explaining SNP calling and maximum likelihood phylogenetics, explain what the conclusion means for patient care or infection control), and using plain language throughout. Be specific about what you would say and what you would leave out.
Frequently Asked Questions
What is GISAID?
GISAID (originally the Global Initiative on Sharing All Influenza Data) is an international database for sharing pathogen genome sequences, originally created for influenza viruses and expanded to include SARS-CoV-2 during the COVID-19 pandemic. It operates under a data sharing agreement that requires users to acknowledge the submitting laboratories in publications using the data. GISAID hosted over 15 million SARS-CoV-2 genome sequences by 2023 and has been critical for global real-time surveillance of variant emergence and spread.
What is a metagenomics workflow for clinical diagnostics?
Metagenomic sequencing for clinical diagnostics involves: (1) extracting total nucleic acid (DNA or RNA) from the clinical specimen, (2) removing human host DNA (by depletion or bioinformatic subtraction, as human DNA can make up 99 per cent or more of the total DNA in some clinical samples), (3) preparing a sequencing library and sequencing on a suitable NGS platform, (4) bioinformatic classification of the sequencing reads by mapping against reference databases of known pathogen genomes, and (5) clinical interpretation of the findings in the context of the patient’s presentation. Metagenomic sequencing is most useful for diagnosing unusual infections, infections in immunocompromised patients where standard cultures are unreliable, and infections with organisms that are difficult or impossible to culture.
What is GLASS and why is it important?
GLASS is the WHO Global Antimicrobial Resistance and Use Surveillance System, launched in 2015. It provides a standardised approach to AMR surveillance globally, collecting and reporting data on resistance in priority pathogens from human clinical isolates, food-producing animals, food, and the environment. GLASS is important because AMR is a global problem that requires global surveillance data: resistance patterns in one country affect treatment options globally as resistant organisms travel with people, animals, and through food trade. GLASS data inform the WHO list of priority pathogens and guide global AMR policy.
What skills do you need for a role in genomic epidemiology?
Genomic epidemiology roles typically require: strong microbiology or virology foundational knowledge, understanding of molecular typing concepts (phylogenetics, SNP analysis, sequence databases), basic bioinformatics skills (ability to navigate Linux command line, understanding of common tools like SNIPPY, BEAST, or Nextstrain), familiarity with sequencing platforms (Illumina, Oxford Nanopore), understanding of epidemiological concepts (case definitions, incubation periods, transmission dynamics), and strong communication skills to translate genomic data into actionable public health information. Many roles also require experience with R or Python for data analysis and visualisation, though the depth of computational skills expected varies significantly by position.
What are the WHO priority pathogens for antibiotic research and development?
The WHO priority pathogen list classifies pathogens requiring new antibiotics into three priority tiers. Critical priority: carbapenem-resistant Acinetobacter baumannii, carbapenem-resistant Pseudomonas aeruginosa, and carbapenem-resistant and ESBL-producing Enterobacteriaceae (including E. coli and Klebsiella). High priority: vancomycin-resistant Enterococcus faecium, MRSA, clarithromycin-resistant Helicobacter pylori, fluoroquinolone-resistant Campylobacter and Salmonella, and cephalosporin and fluoroquinolone-resistant Neisseria gonorrhoeae. Medium priority: penicillin-non-susceptible Streptococcus pneumoniae, ampicillin-resistant Haemophilus influenzae, and fluoroquinolone-resistant Shigella. The list guides research funding, regulatory incentives, and global AMR control strategies.