Cross-species comparative analysis of single presynapses
© 2023. Springer Nature Limited..
Comparing brain structure across species and regions enables key functional insights. Leveraging publicly available data from a novel mass cytometry-based method, synaptometry by time of flight (SynTOF), we applied an unsupervised machine learning approach to conduct a comparative study of presynapse molecular abundance across three species and three brain regions. We used neural networks and their attractive properties to model complex relationships among high dimensional data to develop a unified, unsupervised framework for comparing the profile of more than 4.5 million single presynapses among normal human, macaque, and mouse samples. An extensive validation showed the feasibility of performing cross-species comparison using SynTOF profiling. Integrative analysis of the abundance of 20 presynaptic proteins revealed near-complete separation between primates and mice involving synaptic pruning, cellular energy, lipid metabolism, and neurotransmission. In addition, our analysis revealed a strong overlap between the presynaptic composition of human and macaque in the cerebral cortex and neostriatum. Our unique approach illuminates species- and region-specific variation in presynapse molecular composition.
Medienart: |
E-Artikel |
---|
Erscheinungsjahr: |
2023 |
---|---|
Erschienen: |
2023 |
Enthalten in: |
Zur Gesamtaufnahme - volume:13 |
---|---|
Enthalten in: |
Scientific reports - 13(2023), 1 vom: 24. Aug., Seite 13849 |
Sprache: |
Englisch |
---|
Beteiligte Personen: |
Berson, Eloïse [VerfasserIn] |
---|
Links: |
---|
Themen: |
Journal Article |
---|
Anmerkungen: |
Date Completed 28.08.2023 Date Revised 21.11.2023 published: Electronic Citation Status MEDLINE |
---|
doi: |
10.1038/s41598-023-40683-8 |
---|
funding: |
|
---|---|
Förderinstitution / Projekttitel: |
|
PPN (Katalog-ID): |
NLM361186525 |
---|
LEADER | 01000naa a22002652 4500 | ||
---|---|---|---|
001 | NLM361186525 | ||
003 | DE-627 | ||
005 | 20231226210813.0 | ||
007 | cr uuu---uuuuu | ||
008 | 231226s2023 xx |||||o 00| ||eng c | ||
024 | 7 | |a 10.1038/s41598-023-40683-8 |2 doi | |
028 | 5 | 2 | |a pubmed24n1203.xml |
035 | |a (DE-627)NLM361186525 | ||
035 | |a (NLM)37620363 | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
041 | |a eng | ||
100 | 1 | |a Berson, Eloïse |e verfasserin |4 aut | |
245 | 1 | 0 | |a Cross-species comparative analysis of single presynapses |
264 | 1 | |c 2023 | |
336 | |a Text |b txt |2 rdacontent | ||
337 | |a ƒaComputermedien |b c |2 rdamedia | ||
338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
500 | |a Date Completed 28.08.2023 | ||
500 | |a Date Revised 21.11.2023 | ||
500 | |a published: Electronic | ||
500 | |a Citation Status MEDLINE | ||
520 | |a © 2023. Springer Nature Limited. | ||
520 | |a Comparing brain structure across species and regions enables key functional insights. Leveraging publicly available data from a novel mass cytometry-based method, synaptometry by time of flight (SynTOF), we applied an unsupervised machine learning approach to conduct a comparative study of presynapse molecular abundance across three species and three brain regions. We used neural networks and their attractive properties to model complex relationships among high dimensional data to develop a unified, unsupervised framework for comparing the profile of more than 4.5 million single presynapses among normal human, macaque, and mouse samples. An extensive validation showed the feasibility of performing cross-species comparison using SynTOF profiling. Integrative analysis of the abundance of 20 presynaptic proteins revealed near-complete separation between primates and mice involving synaptic pruning, cellular energy, lipid metabolism, and neurotransmission. In addition, our analysis revealed a strong overlap between the presynaptic composition of human and macaque in the cerebral cortex and neostriatum. Our unique approach illuminates species- and region-specific variation in presynapse molecular composition | ||
650 | 4 | |a Journal Article | |
650 | 4 | |a Research Support, Non-U.S. Gov't | |
650 | 4 | |a Research Support, N.I.H., Extramural | |
700 | 1 | |a Gajera, Chandresh R |e verfasserin |4 aut | |
700 | 1 | |a Phongpreecha, Thanaphong |e verfasserin |4 aut | |
700 | 1 | |a Perna, Amalia |e verfasserin |4 aut | |
700 | 1 | |a Bukhari, Syed A |e verfasserin |4 aut | |
700 | 1 | |a Becker, Martin |e verfasserin |4 aut | |
700 | 1 | |a Chang, Alan L |e verfasserin |4 aut | |
700 | 1 | |a De Francesco, Davide |e verfasserin |4 aut | |
700 | 1 | |a Espinosa, Camilo |e verfasserin |4 aut | |
700 | 1 | |a Ravindra, Neal G |e verfasserin |4 aut | |
700 | 1 | |a Postupna, Nadia |e verfasserin |4 aut | |
700 | 1 | |a Latimer, Caitlin S |e verfasserin |4 aut | |
700 | 1 | |a Shively, Carol A |e verfasserin |4 aut | |
700 | 1 | |a Register, Thomas C |e verfasserin |4 aut | |
700 | 1 | |a Craft, Suzanne |e verfasserin |4 aut | |
700 | 1 | |a Montine, Kathleen S |e verfasserin |4 aut | |
700 | 1 | |a Fox, Edward J |e verfasserin |4 aut | |
700 | 1 | |a Keene, C Dirk |e verfasserin |4 aut | |
700 | 1 | |a Bendall, Sean C |e verfasserin |4 aut | |
700 | 1 | |a Aghaeepour, Nima |e verfasserin |4 aut | |
700 | 1 | |a Montine, Thomas J |e verfasserin |4 aut | |
773 | 0 | 8 | |i Enthalten in |t Scientific reports |d 2011 |g 13(2023), 1 vom: 24. Aug., Seite 13849 |w (DE-627)NLM215703936 |x 2045-2322 |7 nnns |
773 | 1 | 8 | |g volume:13 |g year:2023 |g number:1 |g day:24 |g month:08 |g pages:13849 |
856 | 4 | 0 | |u http://dx.doi.org/10.1038/s41598-023-40683-8 |3 Volltext |
912 | |a GBV_USEFLAG_A | ||
912 | |a GBV_NLM | ||
951 | |a AR | ||
952 | |d 13 |j 2023 |e 1 |b 24 |c 08 |h 13849 |