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Multiview light-sheet microscope for rapid in toto imaging

Authors:

Abstract

We present a multiview selective-plane illumination microscope (MuVi-SPIM), comprising two detection and illumination objective lenses, that allows rapid in toto fluorescence imaging of biological specimens with subcellular resolution. The fixed geometrical arrangement of the imaging branches enables multiview data fusion in real time. The high speed of MuVi-SPIM allows faithful tracking of nuclei and cell shape changes, which we demonstrate through in toto imaging of the embryonic development of Drosophila melanogaster.
Multi-view light-sheet microscope for rapid in toto imaging
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We present a multi-view selective-plane illumination microscope (MuVi-SPIM), comprised of two
detection and illumination objective lenses, that allows rapid in toto fluorescence imaging of
biological specimens with subcellular resolution. The fixed geometrical arrangement of the
imaging branches enables multi-view data fusion in real-time. The high speed of MuVi-SPIM
enables faithful tracking of nuclei and cell shape changes, which we demonstrate by in toto
imaging the embryonic development of Drosophila melanogaster.
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3@-"07(S#$S#E($)4."% 6.(@)4.1+% 7(-% ;.$#1:."."% Q1M.1:31?%03/% 2#@:"3;(1?@u$."B% Ann. Phys.%315+%
*TUJ%V*J\5WB%
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:(7.1$(#10@%(70?(1?%#/%70)"#$)#E()%;(#@#?()0@%$E.)(7.1$B%J Microsc%170+%55JTUI%V*JJUWB%
IB% >3($S.1+%<B+%,M#?."+%<B+%G.@%D.1.+%]B+%f(--;"#:-+%<B%m%,-.@'."+%9B%>B%&B%_E-()0@%,.)-(#1(1?%G..E%Y1$(:.%
=(P.%97;"8#$%;8%,.@.)-(P.%X@01.%Y@@37(10-(#1%F()"#$)#E8B%Science%305+%*\\KT*\\J%V5\\ZWB%
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M4#@.%7#3$.%;"0(1B%Nat Meth%4+%UU*TUUI%V5\\KWB%
[B% &.@@."+% XB% <B+% ,)47(:-+% QB% GB+% f(--;"#:-+% <B% m% ,-.@'."+% 9B% >B% &B% d.)#1$-"3)-(#1% #/% n.;"0/($4% 90"@8%
97;"8#1()%G.P.@#E7.1-%;8%,)011.:%=(?4-%,4..-%F()"#$)#E8B%Science%322+%*\I^T*\IJ%V5\\[WB%
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*\B%6"3#1?+%6B%`B+%,3E0--#+%fB+% &##$+%GB%,B+%C4#(+%<B% FB% m% ]"0$."+%,B%9B%G..E%01:% /0$-%@(P.%(70?(1?%M(-4%
-M#HE4#-#1%$)011.:%@(?4-H$4..-%7()"#$)#E8B%Nat Meth%8+%K^KTKI\%V5\**WB%
**B%C0E#3@0:.+% <B+% f0)4$73-4+% FB+% >3/10?.@+% =B% m% &1#E+%FB% l301-(-0-(P.% /@3#".$).1).% (70?(1?% #/%
E"#-.(1%:(//3$(#1%01:%(1-."0)-(#1%(1%@(P(1?%).@@$B%Nat Biotech%29+%[U^T[UJ%V5\**WB%
*5B%C.@@0%n010))4(+%]B%et al.%=(P.H).@@%UG%$3E."H".$#@3-(#1%(70?(1?%(1%-4()S%;(#@#?()0@%$07E@.$B%Nat Meth%
8+%*\ZKT*\ZJ%V5\**WB%
*UB%,M#?."+%<B+%`."P.."+%XB+%2".?."+%&B+%>3($S.1+%<B%m%,-.@'."+%9B%>B%&B%F3@-(HP(.M%(70?.%/3$(#1%(7E"#P.$%
".$#@3-(#1%(1%-4"..H:(7.1$(#10@%7()"#$)#E8B%Opt. Express%15+%[\5JT[\Z5%V5\\KWB%
*ZB%X".(;($)4+% ,B+% ,00@/.@:+% ,B+% ,)4(1:.@(1+% <B% m% 6#701)0S+% XB% ,#/-M0".%/#"% ;.0:H;0$.:% ".?($-"0-(#1% #/%
$.@.)-(P.%E@01.%(@@37(10-(#1%7()"#$)#E8%:0-0B%Nat Meth%7+%Z*[TZ*J%V5\*\WB%
*^B%&"'()+% !B% F3@-(E@.HP(.M%7()"#$)#E8% M(-4% @(?4-H$4..-% ;0$.:%/@3#".$).1).% 7()"#$)#E.B% X4G% 64.$($+%
!1(P."$(-8%#/%>.(:.@;."?%V5\\JW%
*IB%>3($S.1+% <B% m% ,-0(1(."+% GB% oB% dB% 9P.1% /@3#".$).1).% .N)(-0-(#1% ;8% 73@-(:(".)-(#10@% $.@.)-(P.% E@01.%
(@@37(10-(#1%7()"#$)#E8%V7,XYFWB%Opt. Lett.%32+%5I\[T5I*\%V5\\KWB%
*KB%]#.+%`B%9B% m% Q@;."-$+%DB% FB% ,-3:(.$%#/% 13)@.0"% 01:% )8-#E@0$7()%;.40P(#3"%:3"(1?%-4.%/(P.%7(-#-()%
)8)@.$%-40-% E".).:.% ?0$-"3@0-(#1%(1%G"#$#E4(@0%.7;"8#?.1.$($B%Journal of Cell Science%61+%U*TK\%
V*J[UWB%
*[B%2#$4-0$;8+% QB% 2-D and 3-D image registration for medical, remote sensing, and industrial
applicationsB%V<#41%f(@.8%01:%,#1$c%5\\^WB%
*JB%X@01)4#1+%6B% QB% et al.%d0E(:%-4"..H:(7.1$(#10@%($#-"#E()%(70?(1?%#/%@(P(1?%).@@$%3$(1?%D.$$.@%;.07%
E@01.%(@@37(10-(#1B%Nat Meth%8+%Z*KTZ5U%V5\**WB%
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@0"?.%$#@(:%01?@.B%J. Opt. Soc. Am. A%16+%5I^[T5II^%V*JJJWB%
5*B%l3077.1+% CB% fB+% ].1?+% GB% m% 608@#"% YY+% dB% FB% X."/#"701).% #/% UG% G.)#1P#@3-(#1% Q@?#"(-47$% #1%
F3@-(HC#".%01:%F018HC#".%Q")4(-.)-3".$B%University of North Carolina at Chapel Hill, Department
of Computer Science, Tech. Rep%V5\\JWB%
55B%d()40":$#1+%fB%>B%D08.$(01HD0$.:%Y-."0-(P.%F.-4#:%#/%Y70?.%d.$-#"0-(#1B%J. Opt. Soc. Am.%62+%^^T
^J%V*JK5WB%
5UB%2#1'0@.'+% dB% CB+% f##:$+% dB% 9B% m%9::(1$+% ,B% =B% Digital image processing using MATLABB% VX".1- ().%
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5^B%d0//.@+%FB+%f(@@."-+%CB%9B%m%&#7E.1401$+%<B%Particle image velocimetry: a practical guideB%V,E"(1?."c%
D."@(1R%e.M%o#"S+%*JJ[WB%
List of supplementary items
Supplementary File Title
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,3EE@.7.1-0"8%](?3".%Z% F3`(H,XYF%(70?.%$81-4.$($
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).@@%7.7;"01.$%(1%G"#$#E4(@0%.7;"8#%
,3EE@.7.1-0"8%](?3".%J% G.-0(@.:%P(.M%#/%-4.%?0EZUH7C4.""8%G"#$#E4(@0%.7;"8#%
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;0"%($%SZ%e7E%c(?4-%C01.@_%)@#$.G3C%#/%-4.%U4(-.%".)-01?3@0"%;#R%(1%O0PE%N1:(M(:30@%-(7.%
C#(1-$%HWZ%$+%HJW%$+%JZZ%$%01:%J5W%$%0".%$4#U1+%U(-4%$.@.)-.:%13)@.(%)#@#3".:E%!C#1%
:(M($(#1+%#1.%#/%-4.%:03?4-."%).@@$%($%0$$(?1.:%0%1.U%)#@#3"E%6"0)X$%0".%)#@#3"%)#:.:%/#"%
-(7.%0$%(1:()0-.:%;8%-4.%$)0@.%;0"%O;#--#7P%"01?(1?%/"#7%WZZ%$%-#%J5W%$E%(d)%64.%$4#"-.$-%
:($-01).% %;.-U..1%018%-U#%13)@.(%0$%0%/31)-(#1%#/%-(7.%O;@0)X%:(07#1:$P%01:%:#3;@.%
70R(737%:($C@0).7.1-% %:3"(1?%0%-(7.%$-.C% %O".:%$]30".$PE%D.01%:($-01).% %
($%$4#U1%0$%;@0)X%$#@(:%@(1.%U(-4%?"08%$40:.%$4#U(1?%-4.%$-01:0":%:.M(0-(#1% E%(e)%
D.:(01%13)@.0"%$C..:%0$%0%/31)-(#1%#/%-(7.E%%c.:+%;@3.%01:%?"..1%)#@#3"$%)#"".$C#1:%-#%
7(-#-()%)8)@.$%**+%*5%01:%*S+%".$C.)-(M.@8E%,..%K(?E%5;%/#"%)#7C0"($#1E%%%
%
Supplementary!Figure!7!
A.@@%-"0)X(1?%(1%-4.%Drosophila%M.1-"0@%.)-#:."7E%=./-%)#@371%$4#U$%70R(737%(1-.1$(-8%
C"#^.)-(#1$%#/%-4.%M.1-"0@%$(:.%#/%0%4($5\MG7A4.""8%Drosophila%.7;"8#%0-%/#3"%:(//.".1-%
-(7.$%O6% g%Z% 4%:./(1.:% 0$%$-0"-% #/%(70?(1?PE% ,(R%13)@.(% 0".%)4#$.1% /#"%-"0)X(1?% O/(M.%
?"#3C.:% )@#$.% -#?.-4."% 01:% #1.% /3"-4."% 0C0"-P% 01:% /#@@#U.:% -4"#3?4% /(M.% 4#3"$% #/%
:.M.@#C7.1-E%F03?4-."%13)@.(%0".%@0;.@@.:%(1%-4.%$07.%)#@#3"%0$%-4.%C0".1-%13)@.3$E%
D(::@.% )#@371% )#"".$C#1:$% -#% -4.% ".?(#1% 4(?4@(?4-.:% ;8% -4.% U4(-.% ;#R% (1% -4.% @./-%
)#@371E%6"0).$%#/% -4.%13)@.0"%-"0^.)-#"(.$% 0".%0@$#%$4#U1% (1%-4.%$07.%)#@#3"%0$% -4.%
)#"".$C#1:(1?%13)@.3$E% 64.% "(?4-% )#@371% $4#U$% 0% )@#$.% 3C% M(.U% #/% -4.%/(M.%)@#$.@8%
?"#3C.:%).@@$E%A.@@%70"X."$%0".%).1-".:%#1%-4.%C#$(-(#1%#/%70R(737%(1-.1$(-8%/#"%.0)4%
).@@E%%
%
%
Supplementary!Figure!8!
9//.)-$% #/% 01($#-"#C()% C#(1-G$C".0:% /31)-(#1% #1% -4.% (70?(1?% #/% ).@@% 7.7;"01.$% (1%
Drosophila%.7;"8#E%(a)%L#(1-G$C".0:%/31)-(#1%OL,KP%#/%-4.%D3Q(G,LND%($%.@#1?0-.:%0@#1?%
-4.%7()"#$)#C.h$% :.-.)-(#1%0R($E%(b)% N1%01% .0"@8% Drosophila%.7;"8#+%7#$-% ).@@$%0/-."%
).@@3@0"($0-(#1%@(.%)@#$.%-#%-4.%.7;"8#h$%$3"/0).i%-4.%7.7;"01.$%;.-U..1%-4.%).@@$%0".%
-43$% 1.0"@8% C."C.1:()3@0"% -#% -4.% .7;"8#h$% $3"/0).E% 64.% (@@3$-"0-(#1% $4#U$% 0% )"#$$G
$.)-(#1%-4"#3?4%0%Drosophila%.7;"8#%C."C.1:()3@0"%-#%-4.%.7;"8#h$%@#1?%0R.$E%=./-%-U#%
)#@371$%$4#U% -4.%#"(.1-0-(#1% #/%-4.%L,K% ".@0-(M.%-#% -4.%.7;"8#+% U(-4% -4.%.7;"8#h$%
01?3@0"% C#$(-(#1% #/% Zj% 01:% IZj+% ".$C.)-(M.@8E% 64.% /3$.:% (70?.% O"(?4-% )#@371P% ($%
)#1$-"3)-.:%/"#7%-4.%(1C3-%(70?.$%$3)4%-40-%-4.%7.7;"01.$%01:%-4.%7()"#$)#C.h$%L,K%
0".%.M."8U4.".%)@#$.%-#%C0"0@@.@E%(c)%k"(.1-0-(#1%#/%-4.%7()"#$)#C.h$%L,K%".@0-(M.%-#%-4.%
#"(.1-0-(#1%#/%-4.%/@3#".$).1-% 7.7;"01.$%:.-."7(1.$%(70?.%]30@(-8%O.7;"8#%$3"/0).%
U0$%l31"#@@.:l%0$%:.$)"(;.:%(1%,3CC@.7.1-0"8%1#-.%WPE%N1%0%$(1?@.%D3Q(G,LND%(70?.%$.-%
U(-4#3-%$C.)(7.1%"#-0-(#1%O@./-%-U#%)#@371$P+%7.7;"01.$%U(@@%;.%;.$-%".$#@M.:%U4.".%
-4.8% 0".% 1.0"@8% C0"0@@.@% -#% -4.% 7()"#$)#C.h$% L,K+% U4(@.% (1% -4.% 0".0$% U4.".% -4.%
7.7;"01.$%0".% 1.0"@8% C."C.1:()3@0"% -#% -4.% L,K+% (70?.% )#1-"0$-% 01:%".$#@3-(#1%0".%
$(?1(/()01-@8%".:3).:E%N1%0%/3$.:%(70?.%C"#:3).:%/"#7%-U#%"#-0-.:%D3Q(G,LND%:0-0$.-$%
O"(?4-%)#@371P+%-4.%L,K% ($%1.M."%C."C.1:()3@0"%-#% -4.%).@@% 7.7;"01.$i%-4.% ".$3@-(1?%
(70?.%)#1-"0$-%01:%".$#@3-(#1%0".%-4."./#".%$3//()(.1-%-#%".$#@M.%(1:(M(:30@%).@@$%0@7#$-%
018U4.".%#1%-4.%.7;"8#h$%$3"/0).%O,..%,3CC@.7.1-0"8%Q(:.#%*ZPE%
Supplementary!Figure!9!
F.-0(@.:%M(.U%#/%-4.%?0CVSG7A4.""8%Drosophila%.7;"8#%$3"/0).E%(a)",.?7.1-0-(#1%#/%-4.%
7.7;"01.$%(1%01% .7;"8#%:3"(1?%.0"@8% )8)@.%*V%O.R)@3:(1?% C#@0"%".?(#1$PE%2".8$)0@.%
:0-0%($%-4.%/3$.:%01:%31"#@@.:%(70?.%U(-4%".:%@(1.$%:.1#-(1?%$.?7.1-.:%).@@%;#":."$E%(b)"
A@#$.G3C%#/%-4.%4(?4@(?4-.:%".?(#1%(1%O0PE%(c)"6(7.G@0C$.%M(.U%#/%).@@%7#M.7.1-$%01:%
$40C.$% :3"(1?% .0"@8% Drosophila!7#"C4#?.1.$($E% 64.% @./-% $)4.70-()% :.$)"(;.$% -4.%
M(.UC#(1-$% O01:% )#@#"% $)4.7.P% $4#U1% (1% "(?4-% C01.@$% O(GR((PE% O(GR((P% A#@#".:% :#-$%
)#"".$C#1:%-#% ).@@%).1-".$% 0$% /#31:%/"#7% (70?.% $.?7.1-0-(#1E%64.% $3;$.]3.1-% -(7.%
C#(1-$%$4#U%).@@$%-"0)X.:%).@@$%/#"%3C%-#%5Z%7(13-.$E%(d)"K"#7%-4.%-"0)X(1?%:0-0%$4#U1%
(1%O)P+%).@@%$C..:$%)01%;.%)0@)3@0-.:E%6(7.%($%:./(1.:%/"#7%-4.%/("$-%(70?.%#/%-4.%-(7.G
@0C$.%O/#3"%7(13-.$%;./#".%#1$.-%#/%M.1-"0@%/3""#U%/#"70-(#1PE%\""#U$%@0;.@@.:%O*GSP%
:.1#-.%-(7.$%U4.".%:(//.".1-%7#"C4#@#?()0@%.M.1-$%#))3"_%-4.%#1$.-%#/%M.1-"0@%/3""#U%
/#"70-(#1% O*P+% -4.% #1$.-% #/% ).C40@()% /3""#U% /#"70-(#1% O5P% 01:% -4.% ;.?(11(1?% #/%
?."7;01:%.R-.1$(#1%OSPE%%
!
Supplementary!Figure!10!
=(?4-G$4..-%0@(?17.1-%3$(1?%0%/@3#".$).1-%7.:(37E%(a)%f4.1%1#%.7($$(#1%/(@-."%($%3$.:%
(1%-4.%:.-.)-(#1%0"7+%C0"-()@.$%/@#0-(1?%-4"#3?4%-4.%C0"X.:%(@@37(10-(#1%;.07%?.1."0-.%
)(")3@0"%$40C.$%(1%-4.%(70?.E%,('.%#/%-4.%)(")@.$%($%"#3?4@8%C"#C#"-(#10@%-#%-4.%:($-01).%#/%
-4.%C0"-()@.%O01:% -4."./#".%/"#7%-4.% C0"X.:%@0$."%;.07P% /"#7%-4.%/#)0@%C@01.%#/%-4.%
:.-.)-(#1%0"7E%=0"?.%M0"(0-(#1%(1% -4.%)(")@.$`% $('.$%(7C@(.$% 0R(0@%7($0@(?17.1-%#/% -4.%
(@@37(10-(#1%#;^.)-(M.%@.1$+%U4(@.%31(/#"7@8%$('.:%)(")@.$%O0$%($%-4.%)0$.%(1%-4.%/(?3".P%
C#(1-%-#%0R(0@%7($0@(?17.1-%#/%-4.%:.-.)-(#1%#;^.)-(M.%@.1$E%(b!c)%k1).%01%.7($$(#1%/(@-."%
($%(1$."-.:+%/@3#".$).1).%?.1."0-.:%(1%-4.%C0"X.:%@0$."%;.07%".M.0@$%C".)($.%C#$(-(#1%
01:%$40C.%#/%-4.%;.07`$%U0($-E%\R(0@@8%0$877.-"()%;.07%(7C@(.$%0R(0@%7($0@(?17.1-%#/%
-4.%(@@37(10-(#1%#;^.)-(M.%@.1$%O;P+%U4(@.% 0%$877.-"()%;3-%-4()X% ;.07%(1:()0-.$%0R(0@%
7($0@(?17.1-%#/%-4.%:.-.)-(#1%@.1$%O)PE%(d)%N1%0%U.@@%0@(?1.:%,LND+%0%C0"X.:%@0$."%;.07%
?.1."0-.$%01%(70?.%#/%-4.%;.07%U(-4%(-$%U0($-%1.0"%-4.%).1-".%#/%-4.%(70?.E%64()X1.$$%#/%
-4.%U0($-%($%7(1(70@+%(E.E%018%0R(0@%7#M.7.1-%#/%-4.%:.-.)-(#1%#;^.)-(M.%@.1$%U(@@%(1)".0$.%
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".0:(@8%7.0$3".:E%K#"%:.7#1$-"0-(#1%C3"C#$.$+%-4.%;.07%U0($-% (1%-4($%/(?3".%($%$3;G
#C-(70@@8% -4(1+% U4()4% ".$3@-$% (1% 0% 4(?4% ;.07% :(M."?.1).% 01:% 0% @(?4-G$4..-% -40-% ($%
)#1$(:."0;@8%-4()X."%0-%-4.%$(:.$%#/%-4.%/(.@:%#/%M(.U%-401%(1%-4.%7(::@.E%(e)%N-%($%#/-.1%
3$./3@%-#%:($C@0).%-4.%;#-4%@(?4-G$4..-$+%7#M(1?%.0)4%U0($-%/#"%0%/"0)-(#1%#/%-4.%@(?4-G
$4..-`$%3$0;@.%@.1?-4%(1%-4.%:(".)-(#1%#CC#$(-.%-#%-4.%:(".)-(#1%#/%@(?4-E%64($%-"()X%)01%3C%
-#%:#3;@.%@(?4-G$4..-`$%3$0;@.%@.1?-4%U(-4#3-%0//.)-(1?%(-$%-4()X1.$$E%N1%-4($%.R07C@.+%-U#%
@(?4-G$4..-$%U(-4%3$0;@.%@.1?-4$%O:./(1.:%0$%-U().%-4.%c08@.(?4%"01?.1P%#/%*SSe7%0".%
:($C@0).:%/#"%0CC"#R(70-.@8%*ZZe7+%".$3@-(1?%(1%01%.//.)-(M.%@(?4-G$4..-%U(-4%-4()X1.$$%
;.-U..1%5ESe7% 01:%SE5e7% #M."%-4.% U4#@.%Drosophila%.7;"8#E%(f)%k1).%-4.%,LND%($%
0@(?1.:+% ?0@M01#7.-"()% $)011."% ($% 3$.:% -#% $)01% -4.% ;.07% #M."% -4.% /(.@:% #/% M(.U+%
?.1."0-(1?% 0% 4#7#?.1.#3$% @(?4-G$4..-E% K#"% :.7#1$-"0-(#1% C3"C#$.$+% $)011(1?%
07C@(-3:.% ($% $.-% 0% ;(-% ;.@#U% #C-(70@% (1% -4($% /(?3".+% @.0M(1?% C0"-$% #/% -4.% (70?.% 1#-%
(@@37(10-.:E%%
%
Supplementary!Note!1!
Light!sheet"properties"
L"#C."-(.$%#/%-4.%@(?4-G$4..-%)01%;.%.0$(@8%#;-0(1.:%/"#7%-4.%(70?.%?.1."0-.:%;8%0%U.@@%
/#)3$.:% C0"X.:% ;.07% (@@37(10-(1?% 0% /@3#".$).1-% 7.:(37% O$..% 0@$#% ,3CC@.7.1-0"8%
L"#-#)#@% *% 01:% ,3CC@.7.1-0"8% K(?E% *Z:PE% N1% #3"% )0$.+% -4.% ;.07% U0($-% "0:(3$% U0$%
7.0$3".:%-#%;.%mno5ES%pq%Orst%"0:(3$*P+%U4()4%)#"".$C#1:$%-#%:.C-4%#/%/#)3$%O-U().%
-4.%c08@.(?4%"01?.P%#/%5uno *SS%pqE%\/-."%-4.%U0($-$%#/%-4.%;#-4%;.07$%0".%:($C@0).:%
/#"%"#3?4@8%*ZZ%e7%O,3CC@.7.1-0"8%K(?E%*Z.P+%.//.)-(M.%@(?4-G$4..-%-4()X1.$$%($%;.-U..1%
5ES%e7%01:%SE5%e7%#M."%-4.%U4#@.%Drosophila%.7;"8#%O0"#31:%5ZZe7%(1%:(07.-."PE%,('.%
#/%-4.%@(?4-G$4..-%(1%-4.%:(".)-(#1%C."C.1:()3@0"%-#%-4.%(@@37(10-(#1%0R($%($%:./(1.:%;8%-4.%
$)011(1?%"01?.%#/%-4.%?0@M01#7.-"()%$)011."$%01:%U0$%$.-%0-%0"#31:%WWZe7%/#"%(70?(1?%
#/%Drosophila%.7;"8#$%O0"#31:%WZZ%e7%(1%@.1?-4PE%
=0-."0@% ".$#@3-(#1% OU(-4(1% -4.% /#)0@% C@01.P% #/% -4.% 7()"#$)#C.% ($% :.-."7(1.:% ;8% -4.%
137."()0@%0C."-3".%#/%-4.%:.-.)-(#1%#;^.)-(M.%@.1$%01:%U(@@%;.%0"#31:%ZEVS%e72%(1%)0$.%#/%
-4.% VZRvZEYf% @.1$% 01:% H*Z% 17% .7($$(#1% O0$% 3$.:% /#"% Drosophila%(70?(1?PE%\R(0@%
".$#@3-(#1%O0@#1?%-4.%:.-.)-(#1%0R($P%U(@@%;.%:"(M.1%C"(70"(@8%;8%-4.%0R(0@%".$#@3-(#1%#/%
-4.%:.-.)-(#1%@.1$%O5E5Y%e7%U(-4%VZRvZEYfP+%0@-4#3?4%0%7(1#"%(7C"#M.7.1-%O0"#31:%
*Zw%0-%-4.%U0($-%#/%.0)4%@(?4-G$4..-P%($%.RC.)-.:%:3.%-#%-4.%@(?4-G$4..-%(@@37(10-(#13E%
!
Supplementary!Note!2!
Microscope"instrument"control"architecture"
64.%7()"#$)#C.%)#1-"#@%.@.)-"#1()$%($%;3(@:%0"#31:%-U#%4(?4G$C..:%010@#?%#3-C3-%)0":$%
O[N%LANGHJSS%01:%LAN.GH5WI+%[0-(#10@%N1$-"37.1-$%A#"CEPE%\10@#?%#3-C3-%)4011.@$%0".%
3$.:%-#% :(".)-@8%$.-% -4.%@0$."% (1-.1$(-(.$%O3$(1?%01% 0)#3$-#G#C-()0@%-310;@.% /(@-."+%$..%
kC-()0@% $.-3C"(1% D.-4#:$P+% C#$(-(#1$% #/% abGL(.'#% $-0?.% 01:% ?0@M01#7.-"()% $)011."$%
O-4"#3?4%D(1(,0R%B#0":$+%A07;"(:?.%6.)41#@#?8%N1)EPE%6#%.1$3".%7()"#$.)#1:%C".)($.%
-(7(1?+%M#@-0?.%-"0).$%/#"%-4.$.%:.M().$%0".%C".G)#7C3-.:%01:%-4.1%3C@#0:.:%#1-#%-4.%
)0":$%-#?.-4."%U(-4%)#"".$C#1:(1?%:(?(-0@%-"0).$%-#%-"(??."%)07."0+%\k6K%;@01X(1?%01:%
(@@37(10-(#1%$-.."(1?%/@(CG7(""#"E%K(@-."%U4..@+%$C.)(7.1%"#-0-(#1%01:%$C.)(7.1%M."-()0@%
-"01$@0-(#1%0".%)#1-"#@@.:%#M."%c,5S5%C#"-$+%0$%-4.("%#C."0-(#1%($%1#-%-(7.%)"(-()0@E%
\1%(7C#"-01-%C0"-%#/%D3Q(G,LND%($%-4.%.//()(.1-%01:%/0$-%401:@(1?%#/%-4.%@0"?.%07#31-$%#/%
:0-0E%64.%/3@@%(70?.%0)]3($(-(#1%01:%C"#).$$(1?%C(C.@(1.%)#7C"($.$%#/%/#3"%)#7C3-."$_%0%
7()"#$)#C.%)#1-"#@%)#7C3-."%ON1-.@%A#".5F3#%"311(1?%0-% SE*H%2>'+%V%2B%c\DPi%-U#%
)07."0%)#7C3-."$%O.0)4%/.0-3"(1?%-U#%]30:G)#".%5EV2>'%N1-.@%a.#1%AL!$+%5V%2B%#/%c\D%
01:%\".)0%\cA%*YYZN%c\NF%)#1-"#@@."%U(-4%/#3"%5%6B%40":%:"(M.$Pi%01:%0%:0-0%010@8$($%
)#7C3-."%O$..%N70?.%/3$(#1"(1%D.-4#:$PE%\1%YZ%6B%c\NFH%;0$.:%$-#"0?.%$8$-.7%O3$(1?%0%
Sf0".%IJWZGY(%c\NF%)#1-"#@@."P%($%3$.:%-#%$-#".%-4.%@0"?.%07#31-$%#/%:0-0%C"#:3).:%;8%
D3Q(G,LNDE%\%C"(M0-.% *Z%?(?0;(-%9-4."1.-% #C-()0@%1.-U#"X% 0@@#U$%/#"%/0$-% -"01$/."%#/%
(70?.$%;.-U..1%-4.%7()"#$)#C.+%$-#"0?.%$8$-.7%01:%(70?.%C"#).$$(1?%)#7C3-."+%01:%
)#7731()0-(#1%;.-U..1%-4.%7()"#$)#C.%)#7C3-."$E%
%
64.%7()"#$)#C.%($%)#1-"#@@.:%;8%0%)3$-#7GU"(--.1%C"#?"07%)#:.:%(1%=0;Q(.U%O[0-(#10@%
N1$-"37.1-$%A#"CEP%-40-%401:@.$%-4.%)#7731()0-(#1%U(-4%-4.%.@.)-"#1()$%01:%-4.%#-4."%
)#7C3-."$E%
!
Supplementary!Note!3!
Assessment"of"imaging"time"
\@@G0"#31:%(70?(1?%U(-4%D3Q(G,LND%($%/0$-."%-401%U(-4%0%".?3@0"%,LND4%#"%7,LND5%/#"%
-U#%:($-(1)-%".0$#1$E%64.%/("$-%($$3.%)#1)."1$%-4.%-(7.%-4.%$C.)(7.1%($%0)-30@@8%(70?.:%
O.R)@3:(1?% -4.% -(7.% ".]3(".:% /#"% "#-0-(#1P% 0-% .0)4% -(7.% C#(1-E% D3Q(G,LND% C"#:3).$%
M("-30@@8% ".?($-.".:% (70?.$+% U4(@.% "#-0-(#1% ;0$.:% 73@-(GM(.U% (70?(1?% U(-4% ,LND% #"%
7,LND% ".]3(".$% (70?.G;0$.:% (70?.% ".?($-"0-(#1E% 64.% @0--."% 1.).$$(-0-.$% $3//()(.1-%
#M."@0C%;.-U..1%-4.%:(//.".1-%M(.U$+%U4()4%(1.M(-0;@8%@.0:$%-#%$#7.%0".0$%;.(1?%(70?.:%
73@-(C@.%-(7.$E%64.%.R0)-%$('.%#/%-4.%1.).$$0"8%#M."@0C%:.C.1:$%#1%-4.%C"#C."-(.$%#/%-4.%
$C.)(7.1%O$C.)(7.1%U(-4%@#U% C.1.-"0-(#1% :.C-4% 01:v#"% @0)X(1?% $40"C% /.0-3".$% U(@@%
?.1."0@@8%".]3(".%@0"?."%#M."@0C%;.-U..1%-4.%M(.U$PE%N1%-4.#"8+%-4($%#M."@0C%)#3@:%;.%
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Supplementary!Note!4!
Calculation"of"transformation"parameters"
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Supplementary!Note!5!
Equirectangular"projection"of"Drosophila"embryo"surface"""
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Supplementary!Note!6!
Further"details"on"analysis"of"Drosophila"embryo"images"
Early!Drosophila!development!
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Supplementary!Protocol!2!
Diagnostic"specimen"preparation"
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Supplementary!Protocol!3!
Drosophila"embryo!preparation!and!mounting!!
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References!
*E% ,0@.4+%BE%9E%\E%³%6.()4+%DE%AE%Fundamentals!of!PhotonicsE%Of(@.8%³%,#1$_%5ZZJPE%
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... The presence of differentially attenuating/scattering structures in a mesoscale sample casts 'shadows', leading to concealed regions in the sample or distortion of the expected signal strength at the detector. As the typical strategies to address these problems are by multiview imaging 18,88,89 , it is unlikely to be corrected quantitatively. Using different angles for imaging will effectively decrease the thickness of the sample, therefore, limiting the effect of attenuation, but does not address the size and morphology of attenuating biological structures as such. ...
... While this helps to improve image quality, the problem is just diluted instead of being fully addressed. Multiview imaging of the sample can also reduce stripes to some extent (Figure 3C-E) 88,89 . ...
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Optical mesoscale imaging is a rapidly developing field that allows the visualization of larger samples than is possible with standard light microscopy, and fills a gap between cell and organism resolution. It spans from advanced fluorescence imaging of micrometric cell clusters to centimeter-size complete organisms. However, with larger volume specimens, new problems arise. Imaging deeper into tissues at high resolution poses challenges ranging from optical distortions to shadowing from opaque structures. This manuscript discusses the latest developments in mesoscale imaging and highlights limitations, namely labeling, clearing, absorption, scattering, and also sample handling. We then focus on approaches that seek to turn mesoscale imaging into a more quantitative technique, analogous to quantitative tomography in medical imaging, highlighting a future role for digital and physical phantoms as well as artificial intelligence. This article is protected by copyright. All rights reserved.
... To study embryonic morphogenesis on the cellular and subcellular level, light sheet fluorescence microscopy (LSFM) became the method of choice. It allows non-invasive live imaging of millimeter-sized specimens for time periods up to several days 2-8 and has already been successfully applied to characterize the embryonic morphogenesis of several insect species such as the fruit fly Drosophila melanogaster [9][10][11][12][13][14][15] , the scuttle fly Megaselia abdita 16 and the red flour beetle Tribolium castaneum [17][18][19][20] . Due to the intrinsic properties of LSFM 21 , e.g., a high signal-to-noise ratio and good depth penetration in conjunction with nearly no photobleaching and phototoxicity, the acquired datasets typically provide a profound collection of high-quality images with excellent temporal and good three-dimensional spatial resolutions. ...
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The Mediterranean fruit fly (medfly), Ceratitis capitata, is an important model organism in biology and agricultural research with high economic relevance. However, information about its embryonic development is still sparse. We share nine long-term live imaging datasets acquired with light sheet fluorescence microscopy (484.5 h total recording time, 373 995 images, 256 Gb) with the scientific community. Six datasets show the embryonic development in toto for about 60 hours at 30 minutes intervals along four directions in three spatial dimensions, covering approximately 97% of the entire embryonic development period. Three datasets focus on germ cell formation and head involution. All imaged embryos hatched morphologically intact. Based on these data, we suggest a two-level staging system that functions as a morphogenetic framework for upcoming studies on medfly. Our data supports research on wild-type or aberrant morphogenesis, quantitative analyses, comparative approaches to insect development as well as studies related to pest control. Further, they can be used to test advanced image processing approaches or to train machine learning algorithms and/or neuronal networks.
... In contrast, the E-LSBM geometry is inherently insensitive to these effects, and is thus better suited for more scattering or heterogeneous samples, yet has slightly lower axial resolution and a higher illumination light burden for large volumes. In the future, the symmetric design of the microscope described here can be employed for rapid, dual-view imaging by optically switching the illumination and detection paths, an approach that could mitigate shadowing effects and improve resolution through data fusion 31 . To conclude, we expect that the low phototoxicity and significantly improved acquisition speed of LSBM will open up exciting new possibilities for the field of mechanobiology. ...
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Brillouin microscopy (BM) can be used to assess the mechanical properties of biological samples in a 3D, all-optical, and hence non-contact fashion, but its weak signals require long imaging times and illumination dosages harmful to living organisms. Here, we present a line-scanning Brillouin microscope optimized for fast and high-resolution live-imaging of dynamic biological processes with low photo-toxicity. In combination with fluorescence light-sheet imaging, we demonstrate the capabilities of our microscope to visualize the mechanical properties of cells and tissues over space and time in living model organisms such as fruit flies, ascidians, and mouse embryos.
... 1 These standard technologies suffer from a severe drawback because of their destructive nature, and thus, studies cannot be carried out in a live specimen. In addition, geometrical distortions and loss of sampling resolution persist inherently due to the mandated histological sectioning. 2 The advent of selective plane illumination microscopy (SPIM), also known as light sheet fluorescence microscopy, addresses the pertaining challenges of live sample imaging by generating highly resolved multidimensional images (3D or higher) of biological specimens, 3 ranging from single molecules (∼μm) 4-6 and cells [7][8][9] to organisms (∼mm), 10 nondestructively in real-time. [11][12][13] From technological aspects, SPIM adopts optical sectioning technique, wherein, for obtaining a 2D image of a particular section of the fluorophore-tagged specimen without physically slicing the sample, the target-specific fluorophores being tagged over the prespecified section of interest are selectively photoexcited by a thin sheet of light. ...
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Imaging technology at various scales of spatial resolution is crucial for understanding the physiological and morphological complexity of living organisms. The existing imaging technologies fail to facilitate images of a sample at different magnification levels at a given instant of time. We report the detailed design and instrumentation of an optical imaging system, namely, simultaneous multiple-level magnification selective plane illumination microscopy (with an acronym being given as sMx-SPIM), which addresses one of the technological challenges of imaging biological specimens at different magnification levels simultaneously. The simultaneous magnified views assist in perceiving biological activities occurring over a short period, especially in developmental biology, where the time scales (fraction of seconds) are critical. The proposed imaging system comprises one illumination arm and two detection arms, each of which uses a different magnification to attain multiple magnification levels simultaneously and overcomes the time consumption for changing the objective lens. The system is automated for image acquisition using a custom-built assembly of motion stages and external hardware. Experimental studies are carried out using biological specimens such as Danio rerio and Allium cepa to validate the home-built sMx-SPIM imaging system at an obtainable spatial (axial) resolution of ∼ 3 − 5μm.
... Light sheet fluorescence microscopy tends to be hindered by tissue-induced scattering, which deforms the light sheet itself and causes striping and deterioration in the resulting image. This can be combatted by using multi-view systems that allow for illumination and imaging from two sides of the sample (Huisken and Stainier, 2007;Krzic et al., 2012). A final image can be reconstructed by piecing together the two halves of the image. ...
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Rodents have been the dominant animal models in neurobiology and neurological disease research over the past 60 years. The prevalent use of rats and mice in neuroscience research has been driven by several key attributes including their organ physiology being more similar to humans, the availability of a broad variety of behavioral tests and genetic tools, and widely accessible reagents. However, despite the many advances in understanding neurobiology that have been achieved using rodent models, there remain key limitations in the questions that can be addressed in these and other mammalian models. In particular, in vivo imaging in mammals at the cell-resolution level remains technically difficult and demands large investments in time and cost. The simpler nervous systems of many non-mammalian models allow for precise mapping of circuits and even the whole brain with impressive subcellular resolution. The types of non-mammalian neuroscience models available spans vertebrates and non-vertebrates, so that an appropriate model for most cell biological questions in neurodegenerative disease likely exists. A push to diversify the models used in neuroscience research could help address current gaps in knowledge, complement existing rodent-based bodies of work, and bring new insight into our understanding of human disease. Moreover, there are inherent aspects of many non-mammalian models such as lifespan and tissue transparency that can make them specifically advantageous for neuroscience studies. Crispr/Cas9 gene editing and decreased cost of genome sequencing combined with advances in optical microscopy enhances the utility of new animal models to address specific questions. This review seeks to synthesize current knowledge of established and emerging non-mammalian model organisms with advances in cellular-resolution in vivo imaging techniques to suggest new approaches to understand neurodegeneration and neurobiological processes. We will summarize current tools and in vivo imaging approaches at the single cell scale that could help lead to increased consideration of non-mammalian models in neuroscience research.
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From individual cells to whole organisms, O2 transport unfolds across micrometer- to millimeter-length scales and can change within milliseconds in response to fluid flows and organismal behavior. The spatiotemporal complexity of these processes makes the accurate assessment of O2 dynamics via currently available methods difficult or unreliable. Here, we present “sensPIV,” a method to simultaneously measure O2 concentrations and flow fields. By tracking O2-sensitive microparticles in flow using imaging technologies that allow for instantaneous referencing, we measured O2 transport within (1) microfluidic devices, (2) sinking model aggregates, and (3) complex colony-forming corals. Through the use of sensPIV, we find that corals use ciliary movement to link zones of photosynthetic O2 production to zones of O2 consumption. SensPIV can potentially be extendable to study flow-organism interactions across many life-science and engineering applications.
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To master the fundamentals of image registration, there is no more comprehensive source than 2-D and 3-D Image Registration. In addition to delving into the relevant theories of image registration, the author presents their underlying algorithms. You'll also discover cutting-edge techniques to use in remote sensing, industrial, and medical applications. Examples of image registration are presented throughout, and the companion Web site contains all the images used in the book and provides links to software and algorithms discussed in the text, allowing you to reproduce the results in the text and develop images for your own research needs. 2-D and 3-D Image Registration serves as an excellent textbook for classes in image registration as well as an invaluable working resource.
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