The biobank ecosystem

LC Lieselot L. G. Carrette
GG Giordano de Guglielmo
MK Marsida Kallupi
LM Lisa Maturin
MB Molly Brennan
BB Brent Boomhower
DC Dana Conlisk
SS Sharona Sedighim
LT Lani Tieu
MF McKenzie J. Fannon
NV Nathan Velarde
AM Angelica R Martinez
JK Jenni Kononoff
AK Adam Kimbrough
SS Sierra Simpson
LS Lauren C. Smith
KS Kokila Shankar
FR Francisco J. Ramirez
AC Apurva S. Chitre
BL Bonnie Lin
OP Oksana Polesskaya
LW Leah C. Solberg Woods
AP Abraham A. Palmer
OG Olivier George
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The biobanks are currently collaborating on 27 independent research projects with major universities and research institutes in the United States and Europe, to which we have shipped out >1000 samples (Table 2). Current and past collaborative projects have used brain tissue for circuitry analysis, histology, proteomics, epigenetic analysis, and single-cell sequencing. Plasma is being used for exosome transcriptomics, metabolomics, and biomarker discovery. Feces have been analyzed in microbiome projects and for biomarker discovery. Pelvic floor muscle and semen were dissected by special request to study oxycodone’s and cocaine’s effect on their composition, respectively. Publications that result from the use of biobank samples will be tracked on the websites (https://www.cocainebiobank.org/ and https://www.oxycodonebiobank.org/).

Examples of ongoing collaborations with samples from the biobanks

An application example was recently published (Kallupi et al., 2020). Kallupi and colleagues were interested in investigating nociceptin/orphanin FQ peptide (N/OFQ, nociceptin) levels in the CeA of rats with high versus low addiction profiles for oxycodone to confirm a preliminary hypothesis. N/OFQ is an endogenous opioid-like peptide with an important role in opioid tolerance and reward (Ciccocioppo et al., 2000). Analysis of CeA punches from the oxycodone biobank selected with a high (HA, N = 7) or low (LA, N = 7) addiction phenotype based on their AI and naive controls (N = 7) by Western blot analysis (Fig. 4A) showed a significant reduction of the peptide in HA rats compared with naive rats (one-way ANOVA: p = 0.02, post hoc: p = 0.02; Fig. 4B). Moreover, individual N/OFQ levels correlated with the animals’ AI (r = −0.62, p = 0.017; Fig. 4C). These results confirmed that the N/OFQ levels in the CeA inversely correlate with addiction-like behaviors and illustrate these genetically-diverse samples’ utility.

Application example looking at N/OFQ levels in oxycodone biobank brain punches from rats with different addiction profiles. A, Immunoluminescent Western blottings that show nociceptin levels in naive, LA, and HA rats; n = 21 (n = 7 per group). B, Western blot analysis revealed a significant decrease in nociceptin levels (internally normalized to β-tubulin and a naive rat on the blot) in HA rats compared with naive rats; *p = 0.02 one-way ANOVA, error bars represent standard error of mean. C, Correlation between AI and the Z-score of nociceptin levels in the CeA; *p < 0.02 pearson correlation. Partial figure reproduced from Kallupi et al. (2020).

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