This list is meant to help with that step.

The topics are grouped into current areas of microbiology, from microbiome and antimicrobial resistance to food microbiology, environmental microbiology, bioinformatics, and emerging technologies.

Before choosing a topic, first check:

• whether you have access to the samples or data;
• whether the methods are available in your lab;
• whether the project can be completed within your thesis period;
• and whether the question is narrow enough to answer properly.

The topics below are starting points. Each one can be adjusted depending on your university, supervisor, available samples, and research facilities.

Fig. 1. Illustration created with BioRender.

1–10 | Gut Microbiome, Diet and Metabolic Health

1. Diet-Responsive Gut Microbiome Changes in Obesity

Research focus: Study whether normal-weight and overweight or obese individuals respond differently to the same dietary intervention at the microbiome level.

Possible approach: Compare microbiome samples collected before and after the diet and relate microbial changes to body weight, dietary intake or metabolic markers.

Best suited for: Bioinformatics / Nutrition / Clinical data
Level: ★★☆ Moderate

2. Can the Baseline Microbiome Predict Diet Response?

Research focus: Investigate whether the gut microbiome before an intervention can help predict which individuals respond more strongly to the diet.

Possible approach: Use baseline microbial profiles together with treatment outcomes and compare responders with non-responders.

Best suited for: Bioinformatics / Statistics
Level: ★★★ Advanced

3. Dietary Fibre and Short-Chain Fatty Acid-Producing Microbes

Research focus: Examine how fibre intake is associated with microbial groups involved in short-chain fatty acid production.

Possible approach: Combine dietary data with 16S, metagenomic or metabolomic measurements and compare different fibre types where possible.

Best suited for: Nutrition / Microbiome research
Level: ★★☆ Moderate

4. Ultra-Processed Food Intake and the Gut Microbiome

Research focus: Study whether high intake of ultra-processed foods is associated with differences in gut microbial composition or function.

Possible approach: Combine dietary records with microbiome profiles and adjust for important factors such as age, total energy intake and medication use.

Best suited for: Epidemiology / Bioinformatics
Level: ★★☆ Moderate

5. Why Do People Respond Differently to the Same Diet?

Research focus: Investigate why individuals following the same dietary intervention can show different microbiome responses.

Possible approach: Examine baseline microbiota, body composition, age, medication or other host factors as possible explanations.

Best suited for: Longitudinal microbiome studies
Level: ★★★ Advanced

6. Gut Microbiome Recovery After Antibiotic Treatment

Research focus: Follow how the microbiome changes during and after antibiotic exposure.

Possible approach: Analyse repeated samples to study microbiome resilience, recovery time and taxa that do not return to baseline.

Best suited for: Microbial ecology / Bioinformatics
Level: ★★☆ Moderate

7. Taxonomic Composition Versus Microbial Function

Research focus: Compare whether taxonomic profiles and functional profiles provide the same biological interpretation.

Possible approach: Compare species-level or amplicon-based results with functional pathways from shotgun metagenomic data.

Best suited for: Bioinformatics / Metagenomics
Level: ★★★ Advanced

8. Gut Microbiome and Glucose Regulation

Research focus: Examine whether microbial features are associated with fasting glucose, insulin or other metabolic markers.

Possible approach: Combine microbiome data with metabolic measurements and test associations using appropriate statistical models.

Best suited for: Clinical microbiome research
Level: ★★☆ Moderate

9. Microbiome–Metabolome Associations in Metabolic Health

Research focus: Study relationships between microbial features and metabolites such as bile acids, amino-acid metabolites or short-chain fatty acids.

Possible approach: Integrate microbiome and metabolomics data using multivariable or correlation-based approaches.

Best suited for: Multi-omics / Bioinformatics
Level: ★★★ Advanced

10. Is Higher Microbiome Diversity Always Better?

Research focus: Test the common assumption that a more diverse microbiome always means better health.

Possible approach: Compare different diversity measures with health-related outcomes while adjusting for diet, age, medication and other factors.

Best suited for: Bioinformatics / Statistical methodology
Level: ★★☆ Moderate

11–20 | Human, Animal and One Health Microbiomes

11. Do Dogs and Their Owners Share Gut Microbes?

Research focus: Investigate whether people and dogs living in the same household share more microbial features than unrelated individuals.

Possible approach: Compare paired owner–dog samples while considering diet, environment and host species.

Best suited for: Comparative microbiome research
Level: ★★☆ Moderate

12. Pet Dogs Versus Free-Roaming Dogs

Research focus: Compare gut microbiomes of household pets and free-roaming dogs living under different dietary and environmental conditions.

Possible approach: Collect detailed information on diet, antibiotic exposure, environment and lifestyle together with fecal microbiome samples.

Best suited for: Veterinary microbiology / Field sampling
Level: ★★☆ Moderate

13. Raw, Mixed and Commercial Diets in Dogs

Research focus: Study whether different feeding patterns are associated with different canine gut microbiome profiles.

Possible approach: Compare dogs consuming raw, mixed or commercial diets while considering age, breed, medication and lifestyle.

Best suited for: Veterinary nutrition / Microbiome
Level: ★★☆ Moderate

14. Early-Life Microbiome Development in Puppies or Kittens

Research focus: Follow how the gut microbiome develops during the first months of life.

Possible approach: Analyse repeated samples and examine maternal factors, weaning, diet changes, deworming and antibiotic exposure.

Best suited for: Veterinary microbiome research
Level: ★★★ Advanced

15. Livestock Microbiomes and Feed Efficiency

Research focus: Examine whether animals with better feed efficiency have different gut microbial profiles from less efficient animals.

Possible approach: Combine microbiome data with feed intake and growth-performance measurements.

Best suited for: Animal science / Microbiome
Level: ★★☆ Moderate

16. Microbiome Effects of Antibiotic Alternatives in Livestock

Research focus: Study how probiotics, prebiotics, organic acids, phages or other alternatives affect gut microbial communities.

Possible approach: Compare treatment groups and examine both beneficial and unintended changes in the microbiome.

Best suited for: Veterinary microbiology
Level: ★★☆ Moderate

17. One Health Spread of Antimicrobial-Resistance Genes

Research focus: Compare resistance genes found in humans, animals and shared environments.

Possible approach: Analyse isolates or metagenomic data from several compartments and compare resistance patterns.

Best suited for: AMR / Genomics / One Health
Level: ★★★ Advanced

18. Farms as Reservoirs of Antimicrobial Resistance

Research focus: Investigate resistant bacteria or resistance genes in manure, soil, water or animal housing environments.

Possible approach: Combine culture-based testing with PCR, sequencing or metagenomic methods.

Best suited for: Environmental microbiology / One Health
Level: ★★☆ Moderate

19. Wildlife as Indicators of Environmental AMR

Research focus: Study whether wildlife carries resistance patterns associated with human or agricultural activity.

Possible approach: Compare animals from areas with different levels of urban, agricultural or wastewater exposure.

Best suited for: One Health / Field ecology
Level: ★★★ Advanced

20. Comparing Human and Animal Microbiome Responses to Similar Diets

Research focus: Examine whether similar dietary exposures lead to comparable microbial changes across different host species.

Possible approach: Compare carefully matched human and animal datasets without assuming that their microbiomes are directly equivalent.

Best suited for: Comparative microbiology
Level: ★★★ Advanced

21–30 | Antimicrobial Resistance and Phage Research

21. Genomic Profiles of Multidrug-Resistant Bacteria

Research focus: Identify resistance genes and mobile genetic elements in multidrug-resistant bacterial isolates.

Possible approach: Combine genome-sequence analysis with available antimicrobial susceptibility results.

Best suited for: AMR / Genomics
Level: ★★☆ Moderate

22. Do Resistance Genes Predict Antibiotic Susceptibility?

Research focus: Test how well known resistance genes predict laboratory susceptibility results.

Possible approach: Compare genotype-based predictions with phenotypic testing and investigate discordant isolates.

Best suited for: Clinical microbiology / Genomics
Level: ★★☆ Moderate

23. AMR Surveillance Through Wastewater

Research focus: Study whether wastewater can reveal changes in resistance genes or resistant bacteria at the community level.

Possible approach: Compare samples across locations or time points using culture, PCR or metagenomic data.

Best suited for: Environmental surveillance
Level: ★★☆ Moderate

24. Phage–Antibiotic Combination Effects

Research focus: Investigate whether bacteriophages and antibiotics work better together than when used separately.

Possible approach: Compare bacterial growth or killing under single and combined treatments using an established laboratory system.

Best suited for: Phage biology / Wet lab
Level: ★★★ Advanced

25. What Happens When Bacteria Become Phage Resistant?

Research focus: Study whether phage-resistant bacteria show changes in growth, fitness, virulence-related traits or antibiotic susceptibility.

Possible approach: Compare phage-resistant derivatives with their original bacterial strain.

Best suited for: Experimental microbiology
Level: ★★★ Advanced

26. Phages Against Bacterial Biofilms

Research focus: Investigate whether biofilm-associated bacteria respond differently to phages compared with free-living bacteria.

Possible approach: Compare phage activity under planktonic and biofilm growth conditions.

Best suited for: Biofilm research / Phage biology
Level: ★★★ Advanced

27. How Broad Is a Phage's Host Range?

Research focus: Determine whether one phage can infect several strains of the same bacterial species.

Possible approach: Test an existing collection of bacterial strains and compare susceptibility patterns with genomic information.

Best suited for: Phage biology / Genomics
Level: ★★☆ Moderate

28. Why Does Phage Therapy Work in Some Studies but Not Others?

Research focus: Examine why phage therapy produces different outcomes across experimental and clinical studies.

Possible approach: Conduct a systematic review comparing bacterial species, phage preparation, treatment timing and outcome measures.

Best suited for: Literature-based thesis / Evidence synthesis
Level: ★★☆ Moderate

29. Plasmids and Other Mobile Elements in AMR Spread

Research focus: Investigate how plasmids, integrons and other mobile elements contribute to the spread of resistance genes.

Possible approach: Analyse bacterial genome or metagenome assemblies using established annotation tools.

Best suited for: Bioinformatics / Genomics
Level: ★★★ Advanced

30. Antibiotic Use and Resistome Changes in Livestock

Research focus: Study whether antimicrobial exposure is followed by changes in resistance genes in the animal microbiome.

Possible approach: Compare longitudinal or intervention datasets and account for farm, age and treatment effects.

Best suited for: One Health / Metagenomics
Level: ★★★ Advanced

31–40 | Pathogen Genomics and Clinical Microbiology

31. Whole-Genome Sequencing for Hospital Outbreak Investigation

Research focus: Determine whether bacterial isolates from suspected hospital outbreaks are genetically related.

Possible approach: Analyse existing whole-genome sequences using phylogenetic or genomic-distance methods.

Best suited for: Pathogen genomics
Level: ★★☆ Moderate

32. Clinical Metagenomics for Pathogen Detection

Research focus: Evaluate whether metagenomic sequencing can identify infectious agents that are missed by targeted diagnostic tests.

Possible approach: Analyse existing clinical metagenomic datasets or compare published diagnostic studies.

Best suited for: Clinical bioinformatics
Level: ★★★ Advanced

33. Rapid Sequencing for Outbreak Surveillance

Research focus: Study whether rapid sequencing can shorten the time needed to identify and characterize outbreak pathogens.

Possible approach: Compare sequencing workflows in terms of turnaround time, accuracy and information gained.

Best suited for: Genomics / Diagnostic research
Level: ★★☆ Moderate

34. Genomic Epidemiology of a Local Bacterial Pathogen

Research focus: Investigate population structure and genetic relationships among isolates collected within a region, hospital or country.

Possible approach: Use public or institutional genome sequences together with time and location data.

Best suited for: Bioinformatics
Level: ★★☆ Moderate

35. Virulence Gene Diversity Among Clinical Isolates

Research focus: Examine whether virulence-associated genes differ among strains from different clinical backgrounds.

Possible approach: Analyse genome assemblies using established virulence databases.

Best suited for: Comparative genomics
Level: ★★☆ Moderate

36. Molecular Versus Culture-Based Diagnosis

Research focus: Compare conventional culture with PCR or sequencing for detection of a defined pathogen.

Possible approach: Analyse retrospective diagnostic data or conduct a systematic review.

Best suited for: Clinical microbiology
Level: ★★☆ Moderate

37. Microbial Coinfections in Clinical Disease

Research focus: Study whether patients with multiple microbial infections show different outcomes from those with a single pathogen.

Possible approach: Analyse existing clinical or diagnostic datasets.

Best suited for: Clinical epidemiology
Level: ★★☆ Moderate

38. Pathogen Evolution During Antimicrobial Treatment

Research focus: Examine genomic changes that appear as resistance develops during treatment.

Possible approach: Compare sequential isolates collected from the same patient or experimental system.

Best suited for: Evolutionary microbiology
Level: ★★★ Advanced

39. Genomic Surveillance of Zoonotic Pathogens

Research focus: Compare pathogen populations from humans, animals, food and environmental sources.

Possible approach: Use publicly available genome collections with source and location metadata.

Best suited for: One Health genomics
Level: ★★★ Advanced

40. Bias in Public Pathogen Genome Databases

Research focus: Investigate whether public genomic databases overrepresent certain countries, hosts or outbreak settings.

Possible approach: Analyse the geographic, temporal and host distribution of available genome records.

Best suited for: Bioinformatics / Research methodology
Level: ★★☆ Moderate

41–50 | Bioinformatics, AI and Microbiome Data Science

41. Can Microbiome Profiles Predict Host Phenotype?

Research focus: Test whether microbiome features can predict disease status, diet group or another host phenotype.

Possible approach: Compare statistical or machine-learning models using proper cross-validation.

Best suited for: Machine learning / Microbiome
Level: ★★★ Advanced

42. Does Microbiome Data Improve Clinical Prediction?

Research focus: Ask whether adding microbiome information improves prediction beyond standard clinical variables.

Possible approach: Compare models with and without microbiome features using held-out data.

Best suited for: Statistics / Machine learning
Level: ★★★ Advanced

43. Comparing Differential-Abundance Methods

Research focus: Investigate whether different statistical methods give the same biological conclusions from the same microbiome dataset.

Possible approach: Compare tools such as ANCOM-BC, multivariable association methods and compositional approaches.

Best suited for: Biostatistics / Bioinformatics
Level: ★★★ Advanced

44. Effects of Sequencing Depth on Microbiome Results

Research focus: Study how lower sequencing depth affects diversity estimates and differential-abundance findings.

Possible approach: Subsample an existing dataset to different depths and compare the stability of the results.

Best suited for: Bioinformatics methodology
Level: ★★☆ Moderate

45. Amplicon Versus Shotgun Metagenomics

Research focus: Compare what biological information is gained or lost between amplicon sequencing and shotgun metagenomics.

Possible approach: Use matched datasets where available or perform a controlled comparison.

Best suited for: Bioinformatics
Level: ★★☆ Moderate

46. Long-Read Sequencing for Strain-Level Microbiome Analysis

Research focus: Test whether long-read sequencing improves species- or strain-level resolution.

Possible approach: Compare long-read data with short-read or amplicon datasets using the same samples.

Best suited for: Genomics / Bioinformatics
Level: ★★★ Advanced

47. Batch Effects in Microbiome Studies

Research focus: Investigate how DNA extraction, sequencing batch or laboratory protocol can create artificial differences between samples.

Possible approach: Analyse technical metadata and compare results before and after batch adjustment.

Best suited for: Data science / Quality control
Level: ★★☆ Moderate

48. Can Published Microbiome Results Be Reproduced?

Research focus: Test whether the main findings of a published study can be reproduced from the available data and methods.

Possible approach: Rebuild the analysis workflow and compare your results with the original publication.

Best suited for: Bioinformatics / Open science
Level: ★★☆ Moderate

49. Metadata Quality in Public Microbiome Datasets

Research focus: Examine whether important information such as age, diet, medication or sampling method is sufficiently reported.

Possible approach: Audit a selected group of public microbiome datasets against reporting guidelines.

Best suited for: Data stewardship / Bioinformatics
Level: ★★☆ Moderate

50. Contamination in Low-Biomass Microbiome Studies

Research focus: Study how contamination can affect interpretation of samples containing very little microbial DNA.

Possible approach: Reanalyse datasets with negative controls and compare different contamination-filtering strategies.

Best suited for: Microbiome methodology
Level: ★★★ Advanced

51–60 | Environmental Microbiology and Climate

51. Microbial Communities Along Pollution Gradients

Research focus: Study how microbial communities change as environmental contamination increases.

Possible approach: Compare soil, sediment or water samples collected across a defined pollution gradient.

Best suited for: Environmental microbiology
Level: ★★☆ Moderate

52. Microbial Degradation of Plastic-Associated Compounds

Research focus: Investigate microorganisms associated with degradation of specific plastic components or additives.

Possible approach: Analyse enrichment cultures or public metagenomic datasets and identify candidate degradation pathways.

Best suited for: Environmental biotechnology
Level: ★★☆ Moderate

53. Wastewater Microbiomes as Indicators of Community Health

Research focus: Explore whether wastewater microbial patterns can provide information about population-level health or exposure.

Possible approach: Analyse longitudinal wastewater samples together with environmental or epidemiological data.

Best suited for: Environmental surveillance
Level: ★★☆ Moderate

54. Microbial Responses to Heat and Drought

Research focus: Investigate how increasing temperature or reduced moisture affects soil or plant-associated microbes.

Possible approach: Compare field sites or controlled experimental datasets under different stress conditions.

Best suited for: Soil microbiology / Climate research
Level: ★★☆ Moderate

55. Microbial Contributions to Methane Cycling

Research focus: Study microbial groups or genes involved in methane production and methane consumption.

Possible approach: Analyse environmental metagenomes together with chemical or ecosystem measurements.

Best suited for: Environmental genomics
Level: ★★★ Advanced

56. Nitrogen-Cycling Microbes Under Different Farming Practices

Research focus: Examine how fertilizer use or land management affects microorganisms involved in nitrification and denitrification.

Possible approach: Combine soil chemistry with microbial community or functional-gene data.

Best suited for: Soil microbiology
Level: ★★☆ Moderate

57. Microbial Recovery After Environmental Disturbance

Research focus: Study how microbial communities recover after drought, pollution, fire or another major disturbance.

Possible approach: Use longitudinal or chronosequence data to assess resilience and recovery.

Best suited for: Microbial ecology
Level: ★★★ Advanced

58. Urban Versus Rural Environmental Microbiomes

Research focus: Compare microbial communities across environments with different levels of urbanization.

Possible approach: Collect or analyse soil, air-associated or surface samples using the same sampling method.

Best suited for: Field microbiology
Level: ★★☆ Moderate

59. Microbial Indicators of Water Quality

Research focus: Examine whether microbial community features can complement conventional indicators of water contamination.

Possible approach: Combine microbiological, molecular and physicochemical measurements.

Best suited for: Water microbiology
Level: ★★☆ Moderate

60. Environmental Resistomes Under Human Influence

Research focus: Compare resistance genes in environments with high and low levels of human activity.

Possible approach: Analyse metagenomic data from wastewater, farms, urban water or relatively undisturbed environments.

Best suited for: One Health / Environmental genomics
Level: ★★★ Advanced

61–70 | Food, Fermentation and Agricultural Microbiology

61. Microbial Succession During Food Fermentation

Research focus: Follow how microbial communities change during different stages of fermentation.

Possible approach: Analyse time-series samples from yogurt, sourdough, vegetables or another fermented food.

Best suited for: Food microbiology
Level: ★★☆ Moderate

62. Traditional Fermented Foods as Sources of Microbial Diversity

Research focus: Characterize microorganisms present in traditional or region-specific fermented foods.

Possible approach: Combine culture-based identification with sequencing where available.

Best suited for: Food microbiology / Microbial ecology
Level: ★★☆ Moderate

63. Starter Cultures Versus Spontaneous Fermentation

Research focus: Compare controlled starter-culture fermentation with naturally occurring fermentation.

Possible approach: Measure microbial composition, product consistency and physicochemical changes over time.

Best suited for: Fermentation microbiology
Level: ★★☆ Moderate

64. Microbial Drivers of Food Spoilage

Research focus: Identify microbial changes associated with food spoilage during storage.

Possible approach: Compare samples collected under different temperatures, packaging conditions or storage periods.

Best suited for: Food safety
Level: ★★☆ Moderate

65. Biofilms in Food-Processing Environments

Research focus: Study why biofilms persist on food-contact surfaces and how they differ under different environmental conditions.

Possible approach: Use safe model organisms or environmental monitoring data from processing facilities.

Best suited for: Food hygiene / Biofilm research
Level: ★★☆ Moderate

66. Plant Root Microbiomes and Nutrient Uptake

Research focus: Examine whether root-associated microbial communities are linked to nutrient availability or plant performance.

Possible approach: Combine rhizosphere microbiome data with plant-growth and soil measurements.

Best suited for: Plant microbiology
Level: ★★☆ Moderate

67. Microbial Biofertilizers Under Realistic Conditions

Research focus: Test whether microbial inoculants consistently improve plant growth outside highly controlled laboratory conditions.

Possible approach: Compare inoculated and control plants while monitoring both plant growth and microbial establishment.

Best suited for: Agricultural microbiology
Level: ★★☆ Moderate

68. Soil Microbiomes in Organic and Conventional Farming

Research focus: Compare how different farming systems affect soil microbial communities.

Possible approach: Analyse matched field sites or long-term agricultural datasets.

Best suited for: Soil microbiome research
Level: ★★☆ Moderate

69. Food-Chain Transmission of Antimicrobial Resistance

Research focus: Examine resistant bacteria or resistance genes across different stages of food production.

Possible approach: Use surveillance data, food-associated isolates or genomic information.

Best suited for: Food safety / One Health
Level: ★★★ Advanced

70. Using Microbes to Convert Food Waste Into Useful Products

Research focus: Explore whether food-processing waste can be used as a substrate for microbial production of useful compounds.

Possible approach: Compare fermentation performance, yield and substrate utilization in an existing system.

Best suited for: Industrial microbiology
Level: ★★☆ Moderate

71–80 | Fungal Microbiology and the Mycobiome

71. Gut Mycobiome–Bacteriome Interactions

Research focus: Study whether changes in fungal communities are associated with changes in bacterial community structure.

Possible approach: Analyse fungal and bacterial sequencing data generated from the same samples.

Best suited for: Microbiome bioinformatics
Level: ★★★ Advanced

72. Candida Colonization and Bacterial Community Structure

Research focus: Investigate whether the presence or abundance of Candida is associated with particular bacterial profiles.

Possible approach: Analyse human or animal microbiome datasets containing both fungal and bacterial information.

Best suited for: Mycobiome research
Level: ★★☆ Moderate

73. Antifungal Resistance in Clinically Important Fungi

Research focus: Characterize antifungal resistance patterns or known resistance determinants in clinically important fungal isolates.

Possible approach: Analyse susceptibility results together with genomic or molecular data.

Best suited for: Medical mycology
Level: ★★★ Advanced

74. Environmental Reservoirs of Antifungal Resistance

Research focus: Study whether environmental exposure to antifungal compounds is associated with resistant fungal populations.

Possible approach: Compare isolates or surveillance data from environments with different exposure levels.

Best suited for: One Health mycology
Level: ★★★ Advanced

75. Fungal Biofilms and Treatment Tolerance

Research focus: Investigate whether fungal biofilm growth changes susceptibility to antifungal treatment.

Possible approach: Use an established laboratory model or analyse existing susceptibility datasets.

Best suited for: Medical mycology
Level: ★★★ Advanced

76. Early-Life Mycobiome Development

Research focus: Follow how fungal communities change during infancy.

Possible approach: Analyse longitudinal fungal sequencing data and examine diet, delivery mode, antibiotic exposure or environment.

Best suited for: Human microbiome research
Level: ★★★ Advanced

77. Fungi in Inflammatory Bowel Disease

Research focus: Identify fungal changes that are repeatedly reported in Crohn's disease or ulcerative colitis.

Possible approach: Reanalyse public datasets or conduct a systematic review across several cohorts.

Best suited for: Bioinformatics / Evidence synthesis
Level: ★★☆ Moderate

78. Effects of Antibiotics on Intestinal Fungi

Research focus: Study whether reducing bacterial competition during antibiotic treatment is associated with fungal expansion.

Possible approach: Analyse longitudinal samples collected before, during and after antibiotic exposure.

Best suited for: Microbial ecology
Level: ★★☆ Moderate

79. Methodological Bias in Mycobiome Sequencing

Research focus: Investigate how DNA extraction, marker choice or reference database affects reported fungal composition.

Possible approach: Reanalyse the same fungal dataset using alternative workflows.

Best suited for: Bioinformatics methodology
Level: ★★★ Advanced

80. Beyond Candida: Understudied Members of the Human Mycobiome

Research focus: Examine fungal taxa that receive less attention than Candida but appear repeatedly in human gut studies.

Possible approach: Compare their occurrence and ecological associations across public datasets.

Best suited for: Exploratory bioinformatics
Level: ★★☆ Moderate

81–90 | Host–Microbe Interactions, Immunity and Biofilms

81. Microbiome–Immune Associations Across the Lifespan

Research focus: Investigate whether relationships between microbiome features and immune markers differ between age groups.

Possible approach: Integrate microbiome and immunological data while controlling for important host factors.

Best suited for: Immunology / Microbiome
Level: ★★★ Advanced

82. Microbial Metabolites and Host Responses

Research focus: Study whether microbial metabolites are associated with inflammatory or metabolic markers in the host.

Possible approach: Combine microbiome, metabolomics and host measurements.

Best suited for: Multi-omics
Level: ★★★ Advanced

83. Gut–Lung Microbiome Associations

Research focus: Examine whether gut microbial profiles are associated with respiratory health or disease.

Possible approach: Analyse matched gut, respiratory or clinical datasets while avoiding assumptions of direct microbial transfer.

Best suited for: Systems microbiology
Level: ★★★ Advanced

84. Oral–Gut Microbial Connections

Research focus: Study whether oral microorganisms detected in the gut are associated with health or disease.

Possible approach: Compare matched oral and fecal microbiome datasets.

Best suited for: Human microbiome
Level: ★★☆ Moderate

85. Microbial Community Changes During Inflammation

Research focus: Identify microbiome changes associated with inflammatory markers.

Possible approach: Use longitudinal data where possible to separate changes that appear before inflammation from those that follow it.

Best suited for: Host–microbe interactions
Level: ★★☆ Moderate

86. Mixed-Species Biofilms

Research focus: Investigate how interactions between several microbial species affect biofilm structure or tolerance.

Possible approach: Use established model communities rather than studying only one species.

Best suited for: Experimental microbiology
Level: ★★★ Advanced

87. Quorum Sensing in Multispecies Communities

Research focus: Study how microbial signalling affects behaviour within mixed microbial communities.

Possible approach: Use established model organisms or analyse transcriptomic data.

Best suited for: Molecular microbiology
Level: ★★★ Advanced

88. Microbial Competition and Colonization Resistance

Research focus: Investigate how resident microbial communities prevent new organisms from establishing themselves.

Possible approach: Use ecological datasets, safe model communities or computational analysis.

Best suited for: Microbial ecology
Level: ★★★ Advanced

89. Host Genetics and Microbiome Variation

Research focus: Examine whether host genetic variation explains part of the differences observed between individual microbiomes.

Possible approach: Analyse datasets containing both host-genetic and microbiome information.

Best suited for: Computational biology
Level: ★★★ Advanced

90. Microbiome and Vaccine Response

Research focus: Study whether baseline microbiome features are associated with variation in immune response after vaccination.

Possible approach: Analyse existing cohort data containing microbiome and immune-response measurements.

Best suited for: Immunology / Bioinformatics
Level: ★★★ Advanced

91–100 | Emerging Technologies and Future Microbiology

91. Single-Cell Approaches to Microbial Heterogeneity

Research focus: Investigate how genetically similar microbial cells can display different physiological states.

Possible approach: Analyse published single-cell datasets or compare single-cell and bulk measurements.

Best suited for: Computational microbiology
Level: ★★★ Advanced

92. Spatial Organization of Microbial Communities

Research focus: Examine whether the physical location of microorganisms influences how microbial communities function.

Possible approach: Analyse spatial imaging or spatial-omics datasets from host-associated or environmental samples.

Best suited for: Microbial ecology / Imaging
Level: ★★★ Advanced

93. Synthetic Microbial Communities as Simplified Microbiome Models

Research focus: Study whether small, defined microbial communities can reproduce important behaviours of complex natural microbiomes.

Possible approach: Analyse existing synthetic-community experiments or model community interactions computationally.

Best suited for: Systems microbiology
Level: ★★★ Advanced

94. Predicting Microbial Interactions From Multi-Omics Data

Research focus: Examine whether combining genomic, transcriptomic and metabolomic data improves prediction of microbial interactions.

Possible approach: Integrate public multi-omics datasets using network or multivariate methods.

Best suited for: Computational biology
Level: ★★★ Advanced

95. Reusing Public Microbiome Data for New Questions

Research focus: Test whether datasets collected for one study can be used to answer a different biological question.

Possible approach: Combine several public cohorts and carefully harmonize metadata and analytical methods.

Best suited for: Bioinformatics / Open science
Level: ★★★ Advanced

96. FAIR Data and Reproducibility in Microbiology

Research focus: Assess whether published datasets are easy to find, access, understand and reuse.

Possible approach: Audit a selected set of microbiology studies against established data-sharing and reporting principles.

Best suited for: Research methodology / Data science
Level: ★★☆ Moderate

97. AI-Assisted Microbial Classification

Research focus: Compare complex machine-learning models with simpler and more interpretable approaches for microbial classification.

Possible approach: Evaluate prediction accuracy together with model interpretability.

Best suited for: AI / Bioinformatics
Level: ★★★ Advanced

98. Can Large Language Models Help With Microbiology Data Curation?

Research focus: Test whether language models can accurately extract structured microbiological information from research papers or laboratory records.

Possible approach: Compare automatically extracted information with expert-curated data and record the types of errors that occur.

Best suited for: AI / Research informatics
Level: ★★★ Advanced

99. Digital Models of Microbial Ecosystems

Research focus: Build computational models that predict how a microbial community changes after an environmental or nutritional disturbance.

Possible approach: Start with a simple, well-defined system rather than trying to reproduce an entire natural microbiome.

Best suited for: Mathematical modelling
Level: ★★★ Advanced

100. Building a Reproducible Microbiome Analysis Workflow

Research focus: Develop a transparent workflow that takes microbiome data from raw sequences to statistical interpretation.

Possible approach: Use a public dataset, documented quality-control steps, version-controlled code and reproducible reporting.

Best suited for: Bioinformatics / Reproducibility
Level: ★★☆ Moderate

How to Narrow One of These Topics

A broad research area still needs to become a specific thesis question.

For example:

Broad area: Gut microbiome and obesity
Specific topic: Diet response in overweight individuals
Available data: Baseline and post-intervention microbiome samples
Possible thesis question: Does baseline weight status influence the gut microbiome response to a dietary intervention?

You can use the same approach for any topic in the list.

Before choosing your final topic, make sure you have:

• a clear research question;
• access to the required samples or data;
• suitable laboratory or computational methods;
• appropriate supervision;
• and enough time to finish the work properly.

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