The Southern Flounder (a flatfish) undergoes a dramatic transformation during the larval to juvenile transition (metamorphosis). The change in symmetry is astounding: the right eye migrates to the left side of the body (wow!), accompanied by restructuring of the cranium and jawbones towards the left side and development of dark pigmentation on the same side. 

As part of the Fuiman and Hofmann labs at UT, I am using bulk and single-nuclei RNA sequencing to investigate:

What signaling pathways and processes orchestrate early flounder development?

How do environmental and nutritional stressors affect development of the brain and body during metamorphosis? 

Many diseases with sex-specific incidence or pathology are also related to the gut microbiome (GM), and we know that the relationship between gut microbes and their host is bidirectional. The GM sexually differentiates during puberty and sex hormones are able to affect the GM in humans (and mouse models). 

Want to know more? See my review:

Sisk-Hackworth L, Kelley ST, & Thackray VG. Sex, puberty, and the gut microbiome. Reproduction, 165(2), R61-R74. (2023) https://doi.org/10.1530/REP-22-0303 

Working with Dr. Varykina Thackray and Dr. Scott Kelley, I used a GnRH1 knockout-mouse model and multi-omic analysis of GM community composition and function to show that hypothalamic-pituitary-gonadal (HPG) axis activation was the primary cause of sexual differentiation during puberty, but that sex chromosomes caused sex differentiation in certain intestinal niches (see publication) and of specific microbial functions (see preprint). 

Published:

Sisk-Hackworth L, Brown J, Sau L ...Kelley ST, and Thackray VG. Genetic hypogonadal mouse model reveals niche-specific influence of reproductive axis and sex on intestinal microbial communities. Biol Sex Differ 14, 79 (2023). https://doi.org/10.1186/s13293-023-00564-1  

Preprint:

Sisk-Hackworth, L., Akhavan SR, Krutkin DD, Kelley ST, and Thackray VG. Genetic hypogonadal (Gnrh1hpg) mouse model uncovers influence of reproductive axis on maturation of the gut microbiome during puberty. (2024) BioRxiv. https://doi.org/10.1101/2024.07.01.601610   

One issue with NGS sequencing data (metagenomics, amplicon sequencing, transcriptomics, etc) is that the data is compositional: counts of the features within each sample are relative to each other and sum to an arbitrary sequencing depth. 

This creates a number of statistical problems- TP Quinn et al. have a great review on this: https://doi.org/10.1093/bioinformatics/bty175 

Compositional data analysis (CoDA) techniques can reduce the effect of these statistical issues and can also facilitate "multi-omic" integration, which is increasingly popular. 

My work in the Kelley Lab at SDSU on CoDA has provided blueprints for researchers in how to implement CoDA for microbiome multi-omics studies. 

Sisk-Hackworth L and Kelley ST  An application of compositional data analysis to multiomic time-series data, NAR Genomics and Bioinformatics, Volume 2, Issue 4, (2020) lqaa079, https://doi.org/10.1093/nargab/lqaa079    

Sisk-Hackworth L, Ortiz-Velez A, Reed MB and Kelley ST (2021) Compositional Data Analysis of Periodontal Disease Microbial Communities. Front. Microbiol. 12:617949. https://doi.org/10.3389/fmicb.2021.617949