| Literature DB >> 36015130 |
Joana T Rosa1,2, Marco Tarasco1, Paulo J Gavaia1,3,4, M Leonor Cancela1,3,5, Vincent Laizé1,2.
Abstract
Bone disorders affect millions of people worldwide and treatments currently available often produce undesirable secondary effects or have limited efficacy. It is therefore of the utmost interest for patients to develop more efficient drugs with reduced off-target activities. In the long process of drug development, screening and preclinical validation have recently gained momentum with the increased use of zebrafish as a model organism to study pathological processes related to human bone disorders, and the development of zebrafish high-throughput screening assays to identify bone anabolic compounds. In this review, we provided a comprehensive overview of the literature on zebrafish bone-related assays and evaluated their performance towards an integration into screening pipelines for the discovery of mineralogenic/osteogenic compounds. Tools available to standardize fish housing and feeding procedures, synchronize embryo production, and automatize specimen sorting and image acquisition/analysis toward faster and more accurate screening outputs were also presented.Entities:
Keywords: bone anabolic compounds; drug discovery; high throughput; screening pipeline; technological innovation; zebrafish Danio rerio
Year: 2022 PMID: 36015130 PMCID: PMC9412667 DOI: 10.3390/ph15080983
Source DB: PubMed Journal: Pharmaceuticals (Basel) ISSN: 1424-8247
Figure 1Overview of the zebrafish assays currently available for the screening of osteoactive extracts or compounds. (A) Zebrafish models of bone development [22,23,30,42,51]. (B) Zebrafish models of bone repair and regeneration. R, number of experimental units; E, exposure duration; S, set-up; L, low; M, medium; H, high; dpf, days post-fertilization; IP, intraperitoneal injection; * Cell line developed from a mixture of calcified tissues from juvenile zebrafish and composed of osteoprogenitor cells [55,58,70,72,73].
Figure 2Zebrafish pre-discovery pipeline (A) and technological innovation applied to the standardization and automation to improve zebrafish screening throughput and data accuracy (B).
Optimal parameters to standardize zebrafish housing conditions according to refs. [39,96,97,98,99,100,101,102,103].
| Parameters | Description | |
|---|---|---|
| Filters | Mechanical | Filter pads; cleaned daily and changed monthly |
| Chemical | Activated charcoal; changed every 6 months | |
| Biological | Bio-balls or ceramic rings hosting nitrifying bacteria ( | |
| Germicidal light | Ultraviolet light at 254 nm; bulbs changed after 6000 h of use | |
| Temperature | 24–29 °C (ideally 28.5 ± 0.5 °C) | |
| Photoperiod | 14 h of light|10 h of dark (automated light system to be checked regularly) | |
| Water | Type | Dechlorinated water (ideally filtered reverse osmosis water) |
| pH | 6.5–8.0 adjusted with sodium bicarbonate | |
| Conductivity | 150 to 1700 µS adjusted with commercial salts | |
| Hardness | 3–8 d (ideally 4–5 d) | |
| Ammonia | < 0.1 mg/L (as close to 0 mg/L as possible) | |
| Nitrites | < 0.3 mg/L (as close to 0 mg/L as possible) | |
| Nitrates | <25 mg/L | |
| Renewal | 5–10% in a daily basis (occasionally up to 15%) | |
| Fish density | 5 adults/L, 25 juveniles/L and 100 larvae/L | |
Tools to improve the throughput and accuracy of in vivo screenings in zebrafish (all web pages accessed on 22 May 2022).
| Tool | ZF Standardized Production | ZF Mass Production | ZF Sorting | Compound Handling | ZF Exposure | ZF Handling | Signal Acquisition | Imaging | Data Analysis | URL/Reference * |
|---|---|---|---|---|---|---|---|---|---|---|
| ZEBRAFEED ( | X |
| ||||||||
| GemmaMicro ( | X |
| ||||||||
| MEPS—Mass embryo production systems ( | X |
| ||||||||
| iSPAWN ( | X |
| ||||||||
| COPAS FP-1000/2000 ( | X |
| ||||||||
| ZebraFactor ( | X | [ | ||||||||
| Dispensing/sorting robot for small aquatic organisms | X | X |
| |||||||
| ARQiv—Automated reporter quantification system in vivo | X | X | X | X | [ | |||||
| ScreenCube | X | [ | ||||||||
| Microinjection robot | X |
| ||||||||
| VAST BioImager ( | X | X | X | X |
| |||||
| Imaging robot for small aquatic organisms | X | X | X |
| ||||||
| HCS LCI ( | X | X | X |
| ||||||
| Imaging Machine ( | X | X | X |
| ||||||
| ImageXpress ( | X | X | X |
| ||||||
| EnSight multimode plate reader ( | X | X | X |
| ||||||
| IN Cell Analyzer ( | X | X | X |
| ||||||
| COPAS Vision ( | X | X | X | X |
| |||||
| Micro computed tomography ( | X | X |
| |||||||
| ZebrafishMiner | X | [ | ||||||||
| ZFIQ zebrafish image quantitator | X | [ | ||||||||
| ZFBONE toolset | X | [ | ||||||||
| ImageJ | X |
| ||||||||
| Image-Pro ( | X |
|
* all web pages accessed on 22 May 2022.