BACKGROUND: In early drug-discovery research, understanding the tissue distribution of drug at the site of action can help to predict the toxicity, efficacy and exposure level of the drug. The bottleneck of tissue analysis by LC-MS/MS is the time-consuming homogenization step. RESULTS: Both mechanical and enzymatic techniques for mouse tissue homogenization were evaluated, which included bead beater, polytron and enzymatic digestion. Brain, bone marrow, kidney, spleen and liver tissues can be homogenized effectively using the bead beater alone. Lung and heart tissues were best treated with collagenase first and then homogenized by the bead beater. CONCLUSION: Homogenization conditions for seven mouse tissues have been evaluated and optimized. These findings will expedite the preparation of tissue samples for analysis.
BACKGROUND: In early drug-discovery research, understanding the tissue distribution of drug at the site of action can help to predict the toxicity, efficacy and exposure level of the drug. The bottleneck of tissue analysis by LC-MS/MS is the time-consuming homogenization step. RESULTS: Both mechanical and enzymatic techniques for mouse tissue homogenization were evaluated, which included bead beater, polytron and enzymatic digestion. Brain, bone marrow, kidney, spleen and liver tissues can be homogenized effectively using the bead beater alone. Lung and heart tissues were best treated with collagenase first and then homogenized by the bead beater. CONCLUSION: Homogenization conditions for seven mouse tissues have been evaluated and optimized. These findings will expedite the preparation of tissue samples for analysis.
Authors: Elizabeth J Want; Perrine Masson; Filippos Michopoulos; Ian D Wilson; Georgios Theodoridis; Robert S Plumb; John Shockcor; Neil Loftus; Elaine Holmes; Jeremy K Nicholson Journal: Nat Protoc Date: 2012-12-06 Impact factor: 13.491
Authors: Manuel Garcia-Jaramillo; Melinda H Spooner; Christiane V Löhr; Carmen P Wong; Weijian Zhang; Donald B Jump Journal: PLoS One Date: 2019-04-03 Impact factor: 3.240
Authors: Elizabeth Stewart; Justina McEvoy; Hong Wang; Xiang Chen; Victoria Honnell; Monica Ocarz; Brittney Gordon; Jason Dapper; Kaley Blankenship; Yanling Yang; Yuxin Li; Timothy I Shaw; Ji-Hoon Cho; Xusheng Wang; Beisi Xu; Pankaj Gupta; Yiping Fan; Yu Liu; Michael Rusch; Lyra Griffiths; Jongrye Jeon; Burgess B Freeman; Michael R Clay; Alberto Pappo; John Easton; Sheila Shurtleff; Anang Shelat; Xin Zhou; Kristy Boggs; Heather Mulder; Donald Yergeau; Armita Bahrami; Elaine R Mardis; Richard K Wilson; Jinghui Zhang; Junmin Peng; James R Downing; Michael A Dyer Journal: Cancer Cell Date: 2018-08-23 Impact factor: 31.743
Authors: Elizabeth Stewart; Sara M Federico; Xiang Chen; Anang A Shelat; Cori Bradley; Brittney Gordon; Asa Karlstrom; Nathaniel R Twarog; Michael R Clay; Armita Bahrami; Burgess B Freeman; Beisi Xu; Xin Zhou; Jianrong Wu; Victoria Honnell; Monica Ocarz; Kaley Blankenship; Jason Dapper; Elaine R Mardis; Richard K Wilson; James Downing; Jinghui Zhang; John Easton; Alberto Pappo; Michael A Dyer Journal: Nature Date: 2017-08-30 Impact factor: 49.962