Picard Lab

The lab has spent a significant effort in trying to understand the correlations between insect genomes and their associated phenotypes, with a particular interest in understanding the variation present in insect phenotypes. These have some forensic applications, especially forensic entomology, as these abundant insects are at the mercy of natural phenotypic variation in their development rates.

As such, the lab has generated genomes of Cochliomyia macellaria under selection experiments for development rate, and is extracting genotypes linked to this phenotype. This will have wide-ranging applications to increase accuracy in minimum postmortem interval estimations. Furthermore, understanding genetic variation across the landscape (population genetics) will give us a more thorough view of blow fly population dynamics and the ability to estimate abundances in different environments, and the potential for the prediction of variation rates of development.

The lab currently has MPS data (including short and long read technologies) for the following species: Cochliomyia macellaria, Phormia regina, Chrysomya rufifacies, Lucilia cuprina and Lucilia sericata.

Manuscripts

• AA Andere, ML Pimsler, AM Tarone, CJ Picard.  (2020) The genomes of a monogenic fly: Views of primitive sex chromosomes.  Scientific Reports, 10, 15728, https://doi.org/10.1038/s41598-020-72880-0.  https://www.nature.com/articles/s41598-020-72880-0 
• NH Mahmoudzadeh, A Fitt, DB Schwabb, N Martenis, L Neese, CG Owings, GJ Brinkley, H Li, J Karty, S Sudarshan, RW Hardy, AP Mozcek, CJ Picard, JM Tennessen. The oncometabolite L-2-hydroxyglutarate is a common product of Dipteran larval development. Insect Biochemistry and Molecular Biology. 127 (2020): 103493.  
• Y Yan, M Williamson, RJ Davis, AA Andere, CJ Picard and MJ Scott. (2019) Improved transgenic sexing strains for genetic control of the Australian sheep blow fly Lucilia cuprina using embryo-specific gene promoters. Molecular Genetics and Genomics.  https://link.springer.com/article/10.1007/s00438-019-01622-3 
• CJ Picard, JD Wells, A Ullyot, K Rognes. (2017) "Amplified fragment length polymorphism analysis supports the valid species status of Lucilia caesar and L. illustris (Diptera: Calliphoridae)." Forensic Science Research DOI: 10.1080/20961790.2017.1398286  
  https://www.tandfonline.com/doi/full/10.1080/20961790.2017.1398286
• AA Andere, RN Platt II, DA Ray, CJ Picard (2016) "Genome sequence of Phormia regina: Implications for medical, veterinary and forensic research." BMC Genomics (17) 1-17.
  https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-016-3187-z
• AM Salam, FK Adham, CJ Picard (2015) "Survey of the genetic diversity of forensically important Chrysomya blow flies from Egypt." Journal of Medical Entomology, 1-9.
  https://academic.oup.com/jme/article/52/3/320/1007280

Grants

• National Institute of Justice 2013-DN-BX-K019: Species and age determination of blow fly pupae based upon headspace analysis. 2014-2016 (PI: John Goodpaster, IUPUI)
• National Institute of Justice 2012-DN-BX-K024: Genomic tools to reduce error in PMI estimates derived from entomological evidence. 2013-2015. (PI: Aaron Tarone, Texas A&M University)

Imagine a single blow fly, one of countless many, is out there in the environment doing the only thing it knows how to do - send its genetic material to the next generation. This fly in its attempts to complete this task has essentially become a scientist sampling its environment in a way that traditional human scientists would have a very difficult time doing. Contained within this single fly is information about animals that have died, animals that are still living, abundance and diversity of those animals, and information about the chemistry of the environment (such land use practices).

A single fly giving rise to a multitude of data that is capable of painting a picture of the ecosystems' conditions in time and space. Now multiple this information by tens, or hundreds, or thousands of flies carrying this information, and the fly can now monitor any environment for large scale environmental processes. The fly can monitor the environment for the presence of potentially rare animals (conservation areas), or alternatively, invasive animals, how changing climates affect the overall makeup of the animal ecosystem, if wildlife corridors really restore the original conditions, what animals become crucial in a food web system, etc.The fly is able to determine each and every one of these parameters under their natural conditions.

Our lab has been working towards extracting this information from flies in our environments to evaluate the impact of humans and other changes on the entire ecosystem.

Manuscripts

• S Dowling, C Skaggs, CG Owings, K Moctar, CJ Picard, NE Manicke. Insects as Chemical Sensors: Detection of Chemical Warfare Agent Simulants and Hydrolysis Products in the Blow Fly using LC-MS/MS. Environmental Science and Technology. (Accepted)
• CG Owings, WP Gilhooly III, CJ Picard. (2021) Blow fly stable isotopes reveal larval diet: a case study in community level anthropogenic effects.  PLoS One, 16(4), e0249422. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0249422
• CG Owings, A Banerjee, T Asher, WP Gilhooly III, A Tuceryan, M Huffine, C Skaggs, I Adebowale, NE Manicke, CJ Picard. (2019) Female blow flies as vertebrate resource indicators. Scientific Reports, 9: 10594 doi:10.1038/s41598-019-46758-9.
  https://www.nature.com/articles/s41598-019-46758-9
• CG Owings, CJ Picard. (2018) "New Distribution Record for Lucilia cuprina Wiedemann (Diptera: Calliphoridae) in Indiana, USA". Journal of Insect Science. 18(4): 8.
  https://academic.oup.com/jinsectscience/article/18/4/8/5060814
• CG Owings, C Skaggs, W Sheriff, N Manicke, CJ Picard. (2018) "Chemical assay for the detection of vertebrate fecal metabolites in adult blow flies (Diptera: Calliphoridae)." Environmental Entomology, Mar 9. doi: 10.1093/ee/nvy027.
  https://academic.oup.com/ee/article-abstract/47/3/586/4925379

Grants

• US Army Research Laboratory’s Environmental Chemistry Program. Using blow flies to determine the fate and transport of insensitive munitions. (PI: Nicholas Manicke, IUPUI)
• Defense Advanced Research Project Agency (DARPA). Blow Flies as Ubiquitous Chemical Sensors. 2019-2020. (Co-PI: Nicholas Manicke, IUPUI)
• National Geographic Society Explorers Grant. Environmental drones: blow flies as indicators of vertebrate diversity and abundance. 2018-2019. (Co-PIs: Nicholas Manicke, William Gilhooly III, Rudy Banerjee, IUPUI)
• National Geographic Society: Support for Women and Dependent Care: Travel award to attend International Conference on Conservation Biology. 2019.

Insects are the most numerous and diverse animals on Earth, and through millions of years of evolution, they have learned to adapt to anything, literally, anything. Therefore, it is no surprise that insects will eventually save humankind. Insects as food and feed is a new area of research, but one that builds upon the previously and continuing efforts of the lab's research goals. Understanding the correlations between genomes and their associated traits and behaviors will propel this growing industry of the mass production of insects as an environmentally sustainable alternative to protein. You might not want to eat insects just yet, but eventually the globe will need this industry to supply the growing demands of increased populations and the climate changes impacting current protein industries.

Our research is focused on developing new genetic and genomic-based techniques to enhance currently production, and to produce new alternatives.

Manuscripts

• Tomberlin, J. K., CJ Picard, Jordan, H. R., Preyer, C., Warburton, C., Crowley, P., ... & Eljendy, M. (2022). Government and industry investment plays crucial role in further establishment, evolution, and diversification of insect agriculture: a case example from the United States. Journal of Insects as Food and Feed, 8(2), 109-111.
  https://www.wageningenacademic.com/doi/pdf/10.3920/JIFF2022.x001
• C Kaya, TN Generalovic, G Stahls, M Hauser, AC Samayoa, CG Nunes-Silva, H Roxburgh, J Wohlfahrt, EA Ewuise, M Kenis, Y Hanboonsong, J Orozco, N Carrejo, S Nakamura, L Gasco, S Rojo, CM Tanga, R Meier, C Rhode, CJ Picard, C Jiggins, F Lieber, JK Tomberlin, M Hasselmann, WU Blanckenhorn, M Kapun, C Sandrock. (2021) Global population genetic structure and demographic trajectories of the black soldier fly, Hermetia illucens. BMC Biology, 19(1): 1-22. https://link.springer.com/article/10.1186/s12915-021-01029-w
• T Eriksson, AA Andere, H Kelstrup, V Emery, CJ Picard. (2020)  The yellow mealworm (Tenebrio molitor) genome: Implications for an emerging industry.  Journal of Insects as Food and Feed, https://doi.org/10.3920/jiff2019.0057.  https://www.wageningenacademic.com/doi/abs/10.3920/jiff2019.0057
• C Rhode, R Badenhorst, KL Hull, MP Greenwood, AE Bester-van der Merwe; AA Andere, CJ Picard, C Richards. (2020)  Genetic and phenotypic consequences of early domestication in mass reared black soldier flies (Hermetia illucens).  Animal Genetics, 51: 752-762.   
• T Eriksson, and CJ Picard. "Genetic and genomic selection in insects as food and feed." Journal of Insects as Food and Feed (2020): 1-22. https://doi.org/10.3920/JIFF2020.0097 
• S-S Yang, W-M Wu, AM Brandon, H-Q Fan, JP Receveur, Y Li, Z-Y Wang, R Fan, RL McClellan, S-H Gao, D Ning, DH Phillips, B-Y Peng, H Wang, S-Y Cai, P Li, W-M Cai, L-Y Ding, J Yang, J Ren, Y-L Zhang, J Gao, D Xing, N-Q Ren, RM Waymouth, J Zhou, H-C Tao, CJ Picard, ME Benbow, CS Criddle. (2018) Ubiquity of polystyrene digestion and biodegradation within yellow mealworms, larvae of Tenebrio molitor Linnaeus (Coleoptera: Tenebrionidae). Chemosphere, 212: 262-271.
  https://www.sciencedirect.com/science/article/pii/S0045653518315509
• JK Tomberlin...CJ Picard, et al. (+ 54 authors). (2015) "Protecting the environment through insect farming as a means to produce protein for use as livestock, poultry, and aquaculture feed". Journal of Insects as Food and Feed 1(4): 307-309.
  https://www.wageningenacademic.com/doi/abs/10.3920/JIFF2015.0098

Grants

• Beta Hatch Inc./CDC SBIR, Rapid mass production of human influenza vaccine in insects using genome editing. 2022.
• Texas A&M AgriLife/NSF IUCRC, Nutrition, Microbial Enrichments and the Insects’ Interactomes. 2022-2023
• Texas A&M AgriLife/NSF IUCRC, Genomic Resource Database, 2022. 
• National Science Foundation IIP-1841482. I/UCRC Planning Grant: Center for Environmental Sustainability through Insects Farming (CEStIns). 2019-2020. (Co-PIs: Andrea Liceaga, Purdue University, Yunlong Liu, IUSM)
• Beta Hatch Inc./Department of Defense SBIR Phase II Subcontract. Genomics of Beetles. 2019-2021.
• Beta Hatch Contract.Population genomics of the mealworm beetle, Tenebrio molitor. 2018.

This work is focused on automated yet interpretable Artificial Intelligence (AI) solutions to insect species identification, emphasizing the classification of undescribed species. Our methods will extract subtle morphological characters from high-resolution insect images and integrate this information with published dichotomous keys and DNA information to potentially close the semantic knowledge gap between described and undescribed species using deep learning methods.

Our approach to species classification drastically improves over current traditional and automated methods on multiple fronts. First and foremost, current practices assume that the set of insect species can be exhaustively defined in a reference database. Every emerging insect instance originates from one insect species represented in this database. Because only 20% of insect species are currently described, such an assumption is far from realistic. It impedes the effective deployment of AI technologies toward addressing the problem of scale in insect identification. Our zero-shot learning approach readily acknowledges the non-stationary nature of this classification task. It can accommodate emerging and rare species whose samples cannot be included in a reference database for various reasons. Second, unlike existing automated approaches that use raw image features to perform identification without offering much insight for the human expert to interpret predictions, our algorithms are designed to optimize AI-human symbiosis by mapping low-level image features onto dichotomous keys readily interpretable by expert taxonomists while identifying missing keys on the fly. Third, current automated approaches use low-resolution images and coarse-grained feature learning techniques to make part-based dichotomous key prediction impossible. We show that identification accuracy can be significantly improved when part-based, fine-grained feature learning is performed with higher resolution images. Fourth, traditionally insect specimens are identified based on a similarity score between DNA barcodes of a specimen and samples of species present in a reference database. However, the difference in DNA information is not sufficient for species discovery unless a difference in morphology also accompanies it. Our preliminary studies pioneered the integration of imaging and DNA information for species discovery. We implement several fusion strategies to improve species identification and discovery and show that using both sources of information produce higher accuracy than imaging and DNA information alone.

Manuscripts

• Badirli S, Picard CJ, Mohler G, Akata Z, Dundar M. Classifying the Unknown: Identification of Insects by Deep Zero-shot Bayesian Learning. https://www.researchsquare.com/article/rs-1099185/v1
• S Balirli, Z Akata, G Mohler, CJ Picard, M Dundar. (2021) Fine-grained Bayesian zero-shot learning with DNA as side information. 35th Conference on Neural Information Processing Systems, NeurIPS 2021 Conference, Dec 7th, 2021.
  https://proceedings.neurips.cc/paper/2021/hash/a18630ab1c3b9f14454cf70dc7114834-Abstract.html