Comps advisors for 2026-2027:

  • Dan Hernandez
  • Amanda Hund
  • Mark McKone (Winter/spring only)
  • Raka Mitra
  • Matt Rand
  • Angel Solis
  • Rou-Jia Sung
  • Debby Walser-Kuntz (Winter/spring only)
  1. Bacterial immunity beyond CRISPR (Mitra)

Bacteria are constantly exposed to bacteriophages and other mobile genetic elements, and have evolved diverse immune strategies to detect and neutralize these threats. While CRISPR–Cas systems have long served as a model for bacterial immunity, recent work has revealed a much broader repertoire of defense systems. Advances in comparative genomics, functional studies, and AI-driven approaches have enabled the discovery of many previously unknown bacterial immune mechanisms, including systems such as CBASS, BREX, DISARM, and retrons. Many of these employ unexpected molecular strategies, including cyclic nucleotide signaling and programmed cell death, and in some cases share parallels with eukaryotic innate immunity.

A better understanding of these systems has implications for biotechnology, phage therapy, and microbial ecology. Choose a specific non-CRISPR bacterial immune system and investigate how it detects and responds to invading genetic elements. Focus on the cellular, molecular, and biochemical mechanisms underlying its function, and highlight open questions in the field.

Recommended courses:
Biochemistry, Genetics, and/or Microbiology

Suggested Readings:
Bernheim, A., and Sorek, R. (2020). The pan-immune system of bacteria: antiviral defence as a community resource. Nat Rev Microbiol 18, 113–119. https://doi.org/10.1038/s41579-019-0278-2

Hampton, H.G., Watson, B.N.J., and Fineran, P.C. (2020). The arms race between bacteria and their phage foes. Nature 577, 327–336. https://doi.org/10.1038/s41586-019-1894-8

Athukoralage, J.S., and White, M.F. (2022). Cyclic nucleotide signaling in phage defense and counter-defense. Annu Rev Virol 9, 451–468. https://doi.org/10.1146/annurev-virology-100120-010228

Baca, C.F., et al. (2025). Nucleic acid recognition during prokaryotic immunity. Mol Cell. https://doi.org/10.1016/j.molcel.2024.12.007

Ledvina, H.E., and Whiteley, A.T. (2024). Conservation and similarity of bacterial and eukaryotic innate immunity. Nat Rev Microbiol 22, 420–434. https://doi.org/10.1038/s41579-024-01017-1

Huiting, E., and Bondy-Denomy, J. (2023). Defining the expanding mechanisms of phage-mediated activation of bacterial immunity. Curr Opin Microbiol 74, 102325. https://doi.org/10.1016/j.mib.2023.102325

Laub, M.T., and Typas, A. (2024). Principles of bacterial innate immunity against viruses. Curr Opin Immunol 89, 102445. https://doi.org/10.1016/j.coi.2024.102445

  1. Biology and Mechanisms of Atypical Post-Translational Modifications (Solis)

Upon successful sequencing of the human genome, biologists of the time were surprised to find only 20,000 protein coding sequences. However, scientists quickly recognized the ability to modify and regulate the functions of these proteins via chemical modifications that occur following their translation. The proteins in your genome can be regulated by many different post-translational modifications (PTMs). Common post-translational modifications, such as phosphorylation, may lead to activation or inactivation of protein, while others such as ubiquitination results in a protein’s removal. With the advent of sensitive chemical-detection assays, such as protein mass spectrometry, we are discovering that the network of post-translational modifications is more vast than we initially thought. For this question, you will explore a biological, cellular, or physiological process, and describe how uncommon forms of PTMs (i.e. not phosphorylation, glycosylation, or ubiquitination) of specific proteins or family of proteins (anything except histones) regulate this process.

Recommended Courses:

Cell Biology, Genetics, and/or Biochemistry

Suggested Readings:

Komatsu, M., Noda, N.N., & Inada, T. (2026). The mechanistic basis and cellular functions of UFMylation. Nat. Rev. Mol. Cell Biol.

Chen, B., Sun, Y., Niu, J., Jarugumilli, G.K., & Wu, X. (2019). Protein lipidation in cell signaling and diseases: function, regulation and therapeutic opportunities. Cell Chem. Biol.

Mesquita, F.S., Abrami, L., Linder, M.E., Bamji, S.X., Dickinson, B.C., & van der Groot, F.G. (2024). Mechanisms and functions of protein S-acylation. Nat. Rev. Mol. Cell Biol.

Zhang, M., Li, J., Yan, H., Huang, J., Wang, F., Liu, T., Zeng, L., & Zhou F. (2021). ISGylation in Innate Antiviral Immunity and Pathogen Defense Responses: A Review. Front. Cell. Dev. Biol.

Celen, A.B., & Sahin, U. (2020). Sumoylation on its 25th anniversary: mechanisms, pathology, and emerging concepts. FEBS J.

Guccione, E. & Richard, S. (2019). The regulation, functions and clinical relevance of arginine methylation. Nat. Rev. Mol. Cell Biol.

Narita, T., Weinert, B.T., & Choudhary, C. (2018). Functions and mechanisms of non-histone protein acetylation. Nat. Rev. Mol. Cell Biol.

  1. The AI revolution in protein structure and function (Sung)

The connection between protein structure and function is fundamental to understanding the molecular basis for nearly all biological processes. The ability to accurately predict the 3D structure of a protein from its amino acid sequence only has been a holy grail for the biochemistry community. The development of artificial intelligence (AI)-powered tools such as Alphafold, which can predict 3D protein (with additional work being developed for nucleic acid structure prediction) structures with an unprecedented degree of accuracy, has completely changed the field of protein biochemistry. The work that led to Alphafold in particular was awarded the Nobel Prize in Chemistry in 2024. How have these tools advanced our understanding of protein structure and function? Have they solved everything? What are the limitations of these tools and what is the “next” holy grail for studying protein structure and function?

For this question, I’d like you to explore how AI tools have facilitated and truly advanced our understanding of protein structure and function. Your comps should address the following prompts:

1)    What is a biological question (that you are interested in exploring) that researchers have tried to study with existing biochemistry/structural techniques? From a historical perspective, what were the limitations of previous techniques and how did that constrain our ability to study that biological question across biochemical, molecular, and cellular scales?

2)    How have AI tools changed the way researchers have been able to study this question? How have these tools allowed researchers to circumvent or move past those limitations above? Although much of the literature has focused on Alphafold, there are also new software programs focused on predicting protein-protein interactions, drug-binding sites, nucleic acid structure, disordered proteins, etc. You are free to explore any of these advances as part of your comps.

3)    Looking ahead to the future, what are the limitations of currently available AI tools? What remains unknown/difficult to know or study?

Recommended courses: 

Biochemistry, Cell Biology, Genetics, or Immunology 

Suggested readings: 

Kovalevskiy, et al. AlphaFold two years on: Validation and impact. PNAS 2024. https://www.pnas.org/doi/epdf/10.1073/pnas.2315002121

Artificial Intelligence Methodology in Structural Biology, special collection for Nature

Bertoline, et al. Before and after AlphaFold2: An overview of protein structure prediction. Frontiers in Bioinformatics 2023. https://doi:10.3389/fbinf.2023.1120370

Watson, et al. De novo design of protein structure and function with RFdiffusion. Nature 2023, https://doi.org/10.1038/s41586-023-06415-8

Brotzakis, et al. AlphaFold prediction of structural ensembles of disordered proteins. Nature 2025. https://doi-org/10.1038/s41467-025-56572-9

Wicky, et al. Hallucinating symmetric protein assemblies. Science 2022. https://www.science.org/doi/epdf/10.1126/science.add1964

Odai, et a. The Viral AlphaFold Database of monomers and homodimers reveals conserved protein folds in viruses of bacteria, archaea, and eukaryotes. Science 2025. https://www.science.org/doi/epdf/10.1126/sciadv.adz8560

  1.  Gut-to-Brain Signaling (Rand)

For the past few decades, the dominant model of gut-to-brain communication focused on the systemic release of gut hormones into the bloodstream. Recent studies reveal an important neural connection via the vagus nerve (cranial nerve X) that allows the brain to rapidly sense a variety of specific gut stimuli. These vagal signaling pathways mediate behavioral modifications, such as satiety, sugar cravings, anxiety, and depression, and may be involved in disorders like Irritable Bowel Syndrome and potentially Parkinson’s Disease. Critically review and evaluate the anatomical and physiological evidence for specific sensory cells (e.g. “neuropod” cells) and their stimuli, which function as the primary transducers of the gut-brain neural circuit.

Recommended courses: 

Cell Biology, Animal Physiology, Human Physiology, or Neurons, Circuits and Behavior

Suggested readings: 

Liu, W.W. and Bohórquez, D.V. (2022) The neural basis of sugar preference. Nat Rev Neurosci. (10):584-595. doi: 10.1038/s41583-022-00613-5.

Liu, W.W., et al. (2025) A gut sense for a microbial pattern regulates feeding. Nature 645(8081):729-736. doi: 10.1038/s41586-025-09301-7.

Touhara, K.K., et al. (2025) Topological segregation of stress sensors along the gut crypt-villus axis. Nature 640(8059):732-742. doi: 10.1038/s41586-024-08581-9.

Yamada, S., Natsubori, A., Harada, K., Tsuboi, T., and Monai, H. (2025) Immediate glucose signaling transmitted via the vagus nerve in gut-brain neural communication. iScience; 5, 28:112439. doi: 10.1016/j.isci.2025.112439.

  1. Novel approaches to invasive species management  (McKone, winter/spring only)

Human activities have introduced non-native species to habitats around the globe.  These sometimes become invasive, which can compromise conservation goals and bring significant economic costs.  Multiple innovative control techniques have been developed recently.  Explore the biological basis of one or more new techniques, and evaluate the potential for success in reducing or eliminating populations of introduced species.  

Recommended courses: 

Evolution, Population Ecology, Disease Ecology & Evolution, or Genomics & Bioinformatics

Suggested readings: 

Pennisi, E.  2024.  The global war on island rats.  Science 385:1290-1291.  

Waddle, A.W., et al.  2024.  Hotspot shelters stimulate frog resistance to chytridiomycosis.  Nature 631:344-349.

Westbrook et al. 2026.  Genomic approaches to accelerate American chestnut restoration.  Science 391:730-735.

Willis, K., and A. Burt.  2025.  Engineering drive-selection balance for localized population suppression with neutral dynamics.  PNAS 122:e2414207112.

  1. Aging and the Immune System (Walser-Kuntz/Winter spring only)

For most individuals, the ability of our immune system to mount a productive response to pathogens decreases with age. This decline is known as immunosenescence and impacts both innate and adaptive immunity. One well known characteristic of immunosenescence is thymus shrinkage, which reduces naïve T cell output. Chronic low-grade inflammation is also a consequence of immunosenescence and the term inflammaging has been coined to describe this outcome. Chronic viral infections, long-term nutrient excess which impacts metabolism, and  changes in the gut microbiota are all associated with inflammaging. Explore how decreased immune function may impact the response to vaccines, surveillance and destruction of tumor cells, and the risk of autoinflammatory disease while focusing on the factors, cell types, and mechanisms that contribute to immune aging.

Recommended courses: 

Immunology, Biochemistry, Human Physiology/ Integrative Animal Physiology

Suggested readings:

Delgado-Pulido, S.,  Yousefzadeh, M.,  Mittelbrunn, M. (2025) Aging reshapes the adaptive immune system from healer to saboteur. Nature Aging 5,  1393-1403.

https://doi.org/10.1038/s43587-025-00906-1

Franceschi, C., Garagnani, P., Parini, P. Giuliani, C., Santoro, A. (2018). Inflammaging: a new immune–metabolic viewpoint for age-related diseases. Nature Reviews Endocrinology 14, 576-590.

https://doi.org/10.1038/s41574-018-0059-4

Terekhova, M., Bohacova, P., Artyomov, M. (2025) Human immune aging. Immunity 58, 2646-2669.

https://doi.org/10.1016/j.immuni.2025.10.009

Wrona, M., Ghosh, R., Coll, K., Chun, C., Yousefzadeh, M. (2024) The 3 I’s of immunity and aging: immunosenescence, inflammaging, and immune resilience. Frontiers in Aging 5.

https://doi.org/10.3389/fragi.2024.1490302

7. Parasites and Host Behavior (Hund)

Host behavior is a primary filter for infection, influencing transmission dynamics, the evolution of virulence, and the selective pressures on host immunity. While behaviors like avoidance, grooming, and self medication serve as a “behavioral immune system” and are a first line of defense against parasites, behaviors like social interactions, mating, and living in large groups can increase transmission risk and lead to more virulent infections. Hosts often face tradeoffs between investing in parasite defense and other life-history traits such as energy reserves, reproduction, and predation risk, that can maintain variation in behaviors within a population. However, when it comes to infections, not all host behavior is adaptive. Some parasites have evolved to hijack hosts and manipulate host behavior to facilitate their own reproduction and transmission. Yet, it is notoriously difficult to distinguish between a parasite-evolved manipulation and a host-evolved compensatory behavior.

For this question, you will explore a specific host-parasite behavior interaction and examine how the behavior influences host fitness and parasite transmission. You may choose to focus on a specific host-parasite system or compare a behavioral strategy across taxa. Possible approaches include analyzing the trade-offs that shape the evolution of that behavior and drive individual variation, evaluating whether a behavioral change represents parasite manipulation, host defense, or a by-product of host pathology, synthesizing how a behavioral interaction changes the evolutionary trajectory of parasite virulence or host immunity, or connecting the ultimate (evolutionary) causes of a parasite behavioral manipulation to the proximate physiological mechanisms within the host. 

Recommended Courses:
Disease Ecology and Evolution, Behavioral Ecology, Evolution, Integrative Animal Physiology, Immunology, Neurons Circuits and Behavior

Suggested Readings:

Miroliubov, Aleksei, Anastasia Lianguzova, and Frederic Libersat. “Neural strategies in parasitic manipulation.” Trends in Parasitology (2025). DOI: 10.1016/j.pt.2025.07.007 

Stockmaier, Sebastian, et al. “Infectious diseases and social distancing in nature.” Science 371.6533 (2021): eabc8881. https://doi.org/10.1126/science.abc8881

Sarabian, Cécile, et al. “Disgust in animals and the application of disease avoidance to wildlife management and conservation.” Journal of Animal Ecology 92.8 (2023): 1489-1508. DOI: 10.1111/1365-2656.13903

Kavaliers, Martin, et al. “Social factors and the neurobiology of pathogen avoidance.” Biology letters 18.2 (2022). https://doi.org/10.1098/rsbl.2021.0371

Gibson, Amanda K., and Caroline R. Amoroso. “Evolution and ecology of parasite avoidance.” Annual Review of Ecology, Evolution, and Systematics 53.1 (2022): 47-67. https://doi.org/10.1146/annurev-ecolsys-102220-020636

Gowda, Vishvas, Susha Dinesh, and Sameer Sharma. “Manipulative neuroparasites: uncovering the intricacies of neurological host control.” Archives of Microbiology 205.9 (2023): 314. https://link.springer.com/article/10.1007/s00203-023-03637-2

Masoudi, Abolfazl, Ross A. Joseph, and Nemat O. Keyhani. “Viral-and fungal-mediated behavioral manipulation of hosts: summit disease.” Applied Microbiology and Biotechnology 108.1 (2024): 492. https://link.springer.com/article/10.1007/s00253-024-13332-x

8. Too much of a good thing: the ecological causes and consequences of native species overabundance. (Hernández)

Human activities have altered ecosystem properties and species assemblages in ways that have led to increases in the abundance of some native species, altering their ecological role and creating novel management challenges. Explore the causes, ecological consequences, and management of native species overabundance.

Recommended courses: 

Global Change Biology, Ecosystem Ecology, Disease Ecology & Evolution, Population Ecology

Suggested readings:

Hernández-Castellano, C., et al. 2025. Overabundant populations of large wild herbivores disrupt plant–pollinator networks in a Mediterranean ecosystem. Plant Biology 27: 1047-1057. https://doi.org/10.1111/plb.70053

Jian, S., et al. 2025. Implications for the distributional range of the European bark beetles under future climate change. Scientific Reports 15: 29556 (2025). https://doi.org/10.1038/s41598-025-15546-z

Keen, R. M., et al. 2023. Impacts of riparian and non-riparian woody encroachment on tallgrass prairie ecohydrology. Ecosystems 26: 290–301. https://doi.org/10.1007/s10021-022-00756-7

Carter, N. A., et al. 2025. Braiding Inuit knowledge and Western science to understand light goose population dynamics under a changing climate. Ecology and Society 30:17. https://doi.org/10.5751/ES-16079-300217

Pouchet, C., et al. 2024. Linking weather conditions and winter tick abundance in moose. Journal of Wildlife Management 88:e22551. https://doi.org/10.1002/jwmg.22551

Saltré, F., K., et al. 2026. Balancing high densities and conservation targets to optimise koala management strategies. Ecology and Evolution 16: e72470. https://doi.org/10.1002/ece3.72470