Imaging and Analysis of Tissue Orientation and Growth Dynamics in the Developing <em>Drosophila</em> Epithelia During Pupal Stages

Within multicellular organisms, mature tissues and organs display high degrees of order in the spatial arrangements of their constituent cells. A ...

Parc Científic de Barcelona

The fusion of epithelial sheets is an essential morphogenetic event. Here, we study the development of the abdomen of Drosophila as a model of bounded epithelia expansion and uncover a complex multistep process for the generation of the adult epidermis from histoblasts, founder cells that replace the larval cells during metamorphosis. We find that histoblasts experience a biphasic cell cycle and emit apical projections that direct their invasive planar intercalation in between larval cells. Coordinately, the larval cells extrude from the epithelia by apical constriction of an actomyosin ring and as a consequence die by apoptosis and are removed by circulating haemocytes. We demonstrate that the proliferation of histoblasts and the death of larval cells are triggered by two independent extrinsic Ecdysone hormonal pulses. Finally, we show that histoblast spreading and the death of larval cells depend on a mutual exchange of signals and are non-autonomous processes.

Extrinsic and intrinsic mechanisms directing epithelial cell sheet replacement during Drosophila metamorphosis.

During larval stages of Drosophila development, the abdominal epidermis is composed of histoblasts (adult precursors) and larval epidermal cells (LECs). During metamorphosis, histoblasts proliferate and colonize the territories occupied by the LECs, which die and become engulfed by macrophages. This morphogenetic process is an excellent model for in vivo analysis of epithelial migration, cell division, cell death, patterning and differentiation. Here, we describe a protocol for time-lapse recording of the developing epidermis during metamorphosis. The protocol describes the removal of the pupal case (which acts as an opaque barrier to effective imaging) and mounting and imaging of specimens of different stages so that normal developmental processes are preserved. This method enables high-resolution studies over long time periods using fluorescent markers and confocal microscopy. The protocol requires 1 h for pupal dissection and mounting and, depending on the stages and genotypes to be analyzed, several more hours for preprocessing and aging and developmental staging of flies and pupae.

Live imaging of epidermal morphogenesis during the development of the adult abdominal epidermis of Drosophila.

Collective cell movement is a mechanism for invasion identified in many developmental events. Examples include the movement of lateral-line neurons in Zebrafish, cells in the inner blastocyst, and metastasis of epithelial tumors [1]. One key model to study collective migration is the movement of border cell clusters in Drosophila. Drosophila egg chambers contain 15 nurse cells and a single oocyte surrounded by somatic follicle cells. At their anterior end, polar cells recruit several neighboring follicle cells to form the border cell cluster [2]. By stage 9, and over 6 hr, border cells migrate as a cohort between nurse cells toward the oocyte. The specification and directionality of border cell movement are regulated by hormonal and signaling mechanisms [3]. However, how border cells are held together while they migrate is not known. Here, we show that a negative-feedback loop controlling JNK activity regulates border cell cluster integrity. JNK signaling modulates contacts between border cells and between border cells and substratum to sustain collective migration by regulating several effectors including the polarity factor Bazooka and the cytoskeletal adaptor D-Paxillin. We anticipate a role for the JNK pathway in controlling collective cell movements in other morphogenetic and clinical models.

JNK signaling controls border cell cluster integrity and collective cell migration.

Cellular signaling networks have evolved to enable swift and accurate responses, even in the face of genetic or environmental perturbation. Thus, genetic screens may not identify all the genes that regulate different biological processes. Moreover, although classical screening approaches have succeeded in providing parts lists of the essential components of signaling networks, they typically do not provide much insight into the hierarchical and functional relations that exist among these components. We describe a high-throughput screen in which we used RNA interference to systematically inhibit two genes simultaneously in 17,724 combinations to identify regulators of Drosophila JUN NH(2)-terminal kinase (JNK). Using both genetic and phosphoproteomics data, we then implemented an integrative network algorithm to construct a JNK phosphorylation network, which provides structural and mechanistic insights into the systems architecture of JNK signaling.

Phosphorylation networks regulating JNK activity in diverse genetic backgrounds.

&#x7EC6;&#x80DE;&#x4FE1;&#x53F7;&#x8F6C;&#x5BFC;&#x7F51;&#x7EDC;&#x7684;&#x53D1;&#x5C55;&#x4F7F;&#x8FC5;&#x901F;&#x800C;&#x51C6;&#x786E;&#x7684;&#x7B54;&#x590D;&#xFF0C;&#x5373;&#x4F7F;&#x9762;&#x5BF9;&#x9057;&#x4F20;&#x6216;&#x73AF;&#x5883;&#x7684;&#x6270;&#x52A8;&#x3002;&#x56E0;&#x6B64;&#xFF0C;&#x9057;&#x4F20;&#x5C4F;&#x5E55;&#x4E0D;&#x53EF;&#x80FD;&#x786E;&#x5B9A;&#x6240;&#x6709;&#x8C03;&#x63A7;&#x57FA;&#x56E0;&#x7684;&#x4E0D;&#x540C;&#x751F;&#x7269;&#x5904;&#x7406;&#x5DE5;&#x827A;&#x3002;&#x6B64;&#x5916;&#xFF0C;&#x867D;&#x7136;&#x53E4;&#x5178;&#x7B5B;&#x67E5;&#x65B9;&#x6CD5;&#x6210;&#x529F;&#x5730;&#x63D0;&#x4F9B;&#x57FA;&#x672C;&#x7684;&#x4FE1;&#x4EE4;&#x7F51;&#x7EDC;&#x7EC4;&#x4EF6;&#x7684;&#x90E8;&#x4EF6;&#x5217;&#x8868;&#xFF0C;&#x5B83;&#x4EEC;&#x901A;&#x5E38;&#x4E0D;&#x63D0;&#x4F9B;&#x66F4;&#x6DF1;&#x5165;&#x4E86;&#x89E3;&#x5B58;&#x5728;&#x8FD9;&#x4E9B;&#x7EC4;&#x4EF6;&#x4E4B;&#x95F4;&#x7684;&#x5C42;&#x6B21;&#x7ED3;&#x6784;&#x4E0E;&#x529F;&#x80FD;&#x7684;&#x5173;&#x7CFB;&#x3002;&#x6211;&#x4EEC;&#x63CF;&#x8FF0;&#x4E2D;&#xFF0C;&#x6211;&#x4EEC;&#x91C7;&#x7528; RNA &#x5E72;&#x6270;&#x6280;&#x672F;&#xFF0C;&#x6709;&#x7CFB;&#x7EDF;&#x5730;&#x6291;&#x5236;&#x540C;&#x65F6;&#x5728; 17,724 &#x7684;&#x7EC4;&#x5408;&#x6765;&#x6807;&#x8BC6;&#x7684;&#x679C;&#x8747;&#x541B; NH 2 &#x672B;&#x7AEF;&#x6FC0;&#x9176; (JNK) &#x76D1;&#x7BA1;&#x673A;&#x6784;&#x7684;&#x4E24;&#x4E2A;&#x57FA;&#x56E0;&#x7684;&#x9AD8;&#x541E;&#x5410;&#x91CF;&#x5C4F;&#x5E55;&#x3002;&#x540C;&#x65F6;&#x4F7F;&#x7528;&#x8FD9;&#x4E8C;&#x8005;&#x57FA;&#x56E0;&#x548C;&#x86CB;&#x767D;&#x8D28;&#x7EC4;&#x7814;&#x7A76;&#x6570;&#x636E;&#xFF0C;&#x7136;&#x540E;&#x6267;&#x884C;&#x4E00;&#x4F53;&#x5316;&#x7F51;&#x7EDC;&#x7B97;&#x6CD5;&#x6765;&#x6784;&#x9020;&#x4E00;&#x4E2A; JNK &#x78F7;&#x9178;&#x5316;&#x7F51;&#x7EDC;&#xFF0C;&#x63D0;&#x4F9B;&#x4E86;&#x7ED3;&#x6784;&#x548C;&#x673A;&#x68B0;&#x7684;&#x89C1;&#x89E3; JNK &#x4FE1;&#x53F7;&#x7CFB;&#x7EDF;&#x4F53;&#x7CFB;&#x7ED3;&#x6784;&#x3002;

&#x8C03;&#x8282;&#x4E0D;&#x540C;&#x9057;&#x4F20;&#x80CC;&#x666F; JNK &#x6D3B;&#x6027;&#x7684;&#x78F7;&#x9178;&#x5316;&#x7F51;&#x7EDC;&#x3002;

Les r&eacute;seaux de signalisation cellulaires ont &eacute;volu&eacute; pour permettre des r&eacute;ponses rapides et pr&eacute;cises, m&ecirc;me en pr&eacute;sence de perturbations g&eacute;n&eacute;tiques ou environnementale. Ainsi, &eacute;crans g&eacute;n&eacute;tiques ne peuvent pas identifier tous les g&egrave;nes qui r&eacute;gulent les processus biologiques diff&eacute;rents. En outre, bien que les approches classiques de d&eacute;pistage ont r&eacute;ussi &agrave; fournir des listes de pi&egrave;ces des composantes essentielles de la signalisation des r&eacute;seaux, ils g&eacute;n&eacute;ralement ne fournissent pas autant sur les relations hi&eacute;rarchiques et fonctionnelles qui existent entre ces composantes. Nous d&eacute;crivons un &eacute;cran haut-d&eacute;bit dans lequel nous avons utilis&eacute; l&#39;interf&eacute;rence ARN pour inhiber syst&eacute;matiquement deux g&egrave;nes simultan&eacute;ment dans 17 724 combinaisons afin d&#39;identifier les responsables de la r&eacute;glementation de la drosophile JUN NH 2-terminale kinase (JNK). Utilisant &agrave; la fois g&eacute;n&eacute;tique et phosphoprot&eacute;omique donn&eacute;es, nous avons impl&eacute;ment&eacute; puis un algorithme de r&eacute;seau int&eacute;grative pour construire un r&eacute;seau de phosphorylation de JNK, qui donne un aper&ccedil;u structural et m&eacute;canique &agrave; l&#39;architecture de syst&egrave;mes de signalisation de JNK.

R&eacute;seaux de phosphorylation r&eacute;glementant l&#39;activit&eacute; JNK dans diverses origines g&eacute;n&eacute;tiques.

Signalisierung Mobilfunknetze haben entwickelt, um schnelle und genaue Antworten, auch angesichts der genetischen oder &ouml;kologische St&ouml;rung zu erm&ouml;glichen. Somit genetische Schirme k&ouml;nnen nicht alle Gene identifizieren, die verschiedene biologische Prozesse regulieren. Dar&uuml;ber hinaus Obwohl klassische Screening Ans&auml;tze Verf&uuml;gung St&uuml;cklisten der wesentlichen Komponenten Netzwerke zu signalisieren gelungen, bieten sie in der Regel nicht viel Einblick in die hierarchischen und funktionalen Beziehungen, die zwischen diesen Komponenten bestehen. Wir beschreiben einen Hochdurchsatz-Bildschirm, in dem wir RNA-Interferenz verwendet, um zwei Gene gleichzeitig in 17.724 Kombinationen Regler der Taufliege JUN NH 2-Terminal Kinase (JNK) identifizieren systematisch zu hemmen. Mit den beiden genetische und Phosphoproteomics Daten, wir dann umgesetzt, einen integratives Netzwerk-Algorithmus, um eine JNK-Phosphorylierung-Netzwerk zu erstellen, die strukturelle und mechanistische Einblicke in die Systemarchitektur der JNK Signalisierung bietet.

Phosphorylierung Netzwerke Regulierung JNK Aktivit&auml;t in unterschiedlichen genetischen Hintergr&uuml;nden.

Reti di segnalazione cellulari si sono evoluti per attivare risposte rapida e accurate, anche a fronte delle perturbazioni ambientali o genetiche. Cos&igrave;, schermi genetici possono non identificare tutti i geni che regolano i processi biologici diversi. Inoltre, anche se lo screening classici approcci sono riusciti a fornire elenchi delle parti dei componenti essenziali di reti di segnalazione, in genere non forniscono molta comprensione le relazioni gerarchiche e funzionali che esistono tra questi componenti. Descriviamo un schermo di alto-rendimento in cui abbiamo utilizzato l&#39;interferenza del RNA per inibire sistematicamente due geni simultaneamente in 17.724 combinazioni per identificare i regolatori della drosofila JUN NH (2)-terminale chinasi (JNK). Utilizzando sia genetica e phosphoproteomics dati, abbiamo quindi implementato un algoritmo rete integrativa per costruire una rete di fosforilazione di JNK, che fornisce intuizioni strutturali e meccanicistiche dell&#39;architettura di sistemi di segnalazione JNK.

Reti di fosforilazione che regolano attivit&agrave; JNK in diversi background genetico.

&#x7D30;&#x80DE;&#x30B7;&#x30B0;&#x30CA;&#x30EB;&#x4F1D;&#x9054;&#x30CD;&#x30C3;&#x30C8;&#x30EF;&#x30FC;&#x30AF;&#x306F;&#x3001;&#x8FC5;&#x901F;&#x304B;&#x3064;&#x6B63;&#x78BA;&#x306A;&#x5FDC;&#x7B54;&#x3001;&#x907A;&#x4F1D;&#x3084;&#x74B0;&#x5883;&#x306E;&#x6442;&#x52D5;&#x306E;&#x9854;&#x3067;&#x3082;&#x6709;&#x52B9;&#x306B;&#x3059;&#x308B;&#x306E;&#x306B;&#x9032;&#x5316;&#x3057;&#x3066;&#x304D;&#x305F;&#x3002;&#x3057;&#x305F;&#x304C;&#x3063;&#x3066;&#x3001;&#x907A;&#x4F1D;&#x5B50;&#x30B9;&#x30AF;&#x30EA;&#x30FC;&#x30CB;&#x30F3;&#x30B0;&#x306F;&#x7570;&#x306A;&#x308B;&#x751F;&#x7269;&#x5B66;&#x7684;&#x904E;&#x7A0B;&#x3092;&#x8ABF;&#x7BC0;&#x3059;&#x308B;&#x907A;&#x4F1D;&#x5B50;&#x3092;&#x8B58;&#x5225;&#x53EF;&#x80FD;&#x6027;&#x304C;&#x3042;&#x308A;&#x307E;&#x3059;&#x3002;&#x53E4;&#x5178;&#x306E;&#x30B9;&#x30AF;&#x30EA;&#x30FC;&#x30CB;&#x30F3;&#x30B0;&#x306E;&#x30A2;&#x30D7;&#x30ED;&#x30FC;&#x30C1;&#x306E;&#x30B7;&#x30B0;&#x30CA;&#x30EB;&#x4F1D;&#x9054;&#x30CD;&#x30C3;&#x30C8;&#x30EF;&#x30FC;&#x30AF;&#x306E;&#x5FC5;&#x9808;&#x30B3;&#x30F3;&#x30DD;&#x30FC;&#x30CD;&#x30F3;&#x30C8;&#x306E;&#x30D1;&#x30FC;&#x30C4;&#x4E00;&#x89A7;&#x3092;&#x63D0;&#x4F9B;&#x3059;&#x308B;&#x3053;&#x3068;&#x306B;&#x6210;&#x529F;&#x3057;&#x3066;&#x3044;&#x308B;&#x304C;&#x3001;&#x307E;&#x305F;&#x3001;&#x5F7C;&#x3089;&#x306F;&#x901A;&#x5E38;&#x3053;&#x308C;&#x3089;&#x306E;&#x30B3;&#x30F3;&#x30DD;&#x30FC;&#x30CD;&#x30F3;&#x30C8;&#x306E;&#x9593;&#x3067;&#x5B58;&#x5728;&#x3059;&#x308B;&#x968E;&#x5C64;&#x304A;&#x3088;&#x3073;&#x6A5F;&#x80FD;&#x7684;&#x95A2;&#x4FC2;&#x306B;&#x591A;&#x304F;&#x306E;&#x6D1E;&#x5BDF;&#x63D0;&#x4F9B;&#x3057;&#x307E;&#x305B;&#x3093;&#x3002;&#x6211;&#x3005; &#x306F;&#x3001;&#x6211;&#x3005; &#x4F7F;&#x7528; RNA &#x5E72;&#x6E09;&#x30B7;&#x30E7;&#x30A6;&#x30B8;&#x30E7;&#x30A6;&#x30D0;&#x30A8; JUN NH &#x306E;&#x30EC;&#x30AE;&#x30E5;&#x30EC;&#x30FC;&#x30BF; (2) &#x3092;&#x8B58;&#x5225;&#x3059;&#x308B; 17,724 &#x7D44;&#x307F;&#x5408;&#x308F;&#x305B;&#x3067;&#x540C;&#x6642;&#x306B; 2 &#x3064;&#x306E;&#x907A;&#x4F1D;&#x5B50;&#x3092;&#x4F53;&#x7CFB;&#x7684;&#x306B;&#x963B;&#x5BB3;&#x3059;&#x308B;&#x9AD8;&#x30B9;&#x30EB;&#x30FC;&#x30D7;&#x30C3;&#x30C8;&#x753B;&#x9762;&#x306B;&#x3064;&#x3044;&#x3066;&#x8AAC;&#x660E;&#x3057;&#x307E;&#x3059;-&#x30BF;&#x30FC;&#x30DF;&#x30CA;&#x30EB; &#x30AD;&#x30CA;&#x30FC;&#x30BC; (JNK)&#x3002;&#x907A;&#x4F1D;&#x306E;&#x4E21;&#x65B9;&#x3092;&#x4F7F;&#x7528;&#x3057;&#x3066;&#x30C1;&#x30BF;&#x30CB;&#x30A2; &#x30C7;&#x30FC;&#x30BF;&#x3001;&#x6211;&#x3005; &#x304B;&#x3089; JNK &#x30B7;&#x30B0;&#x30CA;&#x30EB;&#x4F1D;&#x9054;&#x306E;&#x30B7;&#x30B9;&#x30C6;&#x30E0; &#x30A2;&#x30FC;&#x30AD;&#x30C6;&#x30AF;&#x30C1;&#x30E3;&#x306E;&#x69CB;&#x9020;&#x3068;&#x6A5F;&#x68B0;&#x7684;&#x306A;&#x6D1E;&#x5BDF;&#x3092;&#x63D0;&#x4F9B;&#x3057;&#x307E;&#x3059;&#x3001;JNK &#x30EA;&#x30F3;&#x9178;&#x5316;&#x30CD;&#x30C3;&#x30C8;&#x30EF;&#x30FC;&#x30AF;&#x3092;&#x69CB;&#x7BC9;&#x3059;&#x308B;&#x7D71;&#x5408;&#x30CD;&#x30C3;&#x30C8;&#x30EF;&#x30FC;&#x30AF; &#x30A2;&#x30EB;&#x30B4;&#x30EA;&#x30BA;&#x30E0;&#x5B9F;&#x88C5;&#x3057;&#x307E;&#x3059;&#x3002;

&#x591A;&#x69D8;&#x306A;&#x907A;&#x4F1D;&#x7684;&#x80CC;&#x666F;&#x306B; JNK &#x6D3B;&#x52D5;&#x3092;&#x898F;&#x5236;&#x3059;&#x308B;&#x30EA;&#x30F3;&#x9178;&#x5316;&#x30CD;&#x30C3;&#x30C8;&#x30EF;&#x30FC;&#x30AF;&#x3002;

&#xC140;&#xB8F0;&#xB7EC; &#xC2E0;&#xD638; &#xB124;&#xD2B8;&#xC6CC;&#xD06C;&#xB294; &#xC720;&#xC804;&#xC801; &#xB610;&#xB294; &#xD658;&#xACBD;&#xC801; &#xC12D; &#xB3D9; &#xC5BC;&#xAD74;&#xC5D0; &#xC2E0;&#xC18D; &#xD558; &#xACE0; &#xC815;&#xD655; &#xD558; &#xAC8C; &#xC751;&#xB2F5; &#xC218; &#xC788;&#xB3C4;&#xB85D; &#xC9C4;&#xD654; &#xD588;&#xB2E4;. &#xB530;&#xB77C;&#xC11C;, &#xC720;&#xC804;&#xC790; &#xD654;&#xBA74; &#xB2E4;&#xB978; &#xC0DD;&#xBB3C; &#xD559;&#xC801; &#xACFC;&#xC815;&#xC744; &#xC870;&#xC808; &#xD558;&#xB294; &#xBAA8;&#xB4E0; &#xC720;&#xC804;&#xC790;&#xB97C; &#xC2DD;&#xBCC4; &#xD558;&#xC9C0; &#xC54A;&#xC744; &#xC218; &#xC788;&#xC2B5;&#xB2C8;&#xB2E4;. &#xB610;&#xD55C;, &#xD558;&#xC9C0;&#xB9CC; &#xD074;&#xB798;&#xC2DD; &#xC2EC;&#xC0AC; &#xC811;&#xADFC; &#xC2E0;&#xD638; &#xB124;&#xD2B8;&#xC6CC;&#xD06C;&#xC758; &#xD544;&#xC218; &#xAD6C;&#xC131; &#xC694;&#xC18C; &#xBD80;&#xD488; &#xBAA9;&#xB85D;&#xC744; &#xC81C;&#xACF5; &#xD558;&#xC5D0; &#xC131;&#xACF5;, &#xADF8;&#xB4E4;&#xC740; &#xC77C;&#xBC18;&#xC801;&#xC73C;&#xB85C; &#xC81C;&#xACF5; &#xD558;&#xC9C0; &#xC54A;&#xC2B5;&#xB2C8;&#xB2E4; &#xC774;&#xB7EC;&#xD55C; &#xAD6C;&#xC131; &#xC694;&#xC18C; &#xC911;&#xC5D0;&#xC11C; &#xC874;&#xC7AC; &#xD558;&#xB294; &#xACC4;&#xCE35;&#xC801; &#xBC0F; &#xAE30;&#xB2A5;&#xC801; &#xAD00;&#xACC4;&#xC5D0; &#xB300; &#xD55C; &#xB9CE;&#xC740; &#xD1B5;&#xCC30;&#xB825;. &#xC6B0;&#xB9AC;&#xB294; &#xC6B0;&#xB9AC;&#xAC00; &#xCCB4;&#xACC4;&#xC801;&#xC73C;&#xB85C; Drosophila 6 &#xC6D4; &#xB274; &#xD584;&#xD504;&#xC154; (2)-&#xD130;&#xBBF8;&#xB110; &#xD0A4; (JNK)&#xC758; &#xB808; &#xADE4; &#xB808;&#xC774; &#xD130;&#xB97C; &#xC2DD;&#xBCC4; &#xD558;&#xAE30; &#xC704;&#xD574; 17,724 &#xC870;&#xD569;&#xC73C;&#xB85C; &#xB3D9;&#xC2DC;&#xC5D0; &#xB450; &#xAC1C;&#xC758; &#xC720;&#xC804;&#xC790;&#xB97C; &#xC5B5;&#xC81C; &#xD558;&#xAE30; &#xC704;&#xD574; RNA &#xAC04;&#xC12D;&#xC744; &#xC0AC;&#xC6A9; &#xD558;&#xB294; &#xB192;&#xC740; &#xCC98;&#xB9AC;&#xB7C9; &#xD654;&#xBA74; &#xC124;&#xBA85;. &#xC720;&#xC804; &#xBAA8;&#xB450; &#xC0AC;&#xC6A9; &#xD558; &#xC5EC; phosphoproteomics &#xB370;&#xC774;&#xD130;, &#xC6B0;&#xB9AC; &#xB2E4;&#xC74C; &#xAD6C;&#xC870; &#xBC0F; &#xAE30;&#xACC4; JNK &#xC2E0;&#xD638; &#xC2DC;&#xC2A4;&#xD15C; &#xC544;&#xD0A4;&#xD14D;&#xCC98;&#xC5D0; &#xB300; &#xD55C; &#xD1B5;&#xCC30;&#xB825;&#xC744; &#xC81C;&#xACF5; &#xD558;&#xB294; JNK &#xC778; &#xC0B0;&#xD654; &#xB124;&#xD2B8;&#xC6CC;&#xD06C;&#xB97C; &#xAD6C;&#xC131; &#xD558;&#xB294; &#xD1B5;&#xD569; &#xB124;&#xD2B8;&#xC6CC;&#xD06C; &#xC54C;&#xACE0;&#xB9AC;&#xC998;&#xC744; &#xAD6C;&#xD604; &#xD558; &#xACE0; &#xC788;&#xC2B5;&#xB2C8;&#xB2E4;.

&#xC778; &#xC0B0;&#xD654; &#xB124;&#xD2B8;&#xC6CC;&#xD06C; &#xB2E4;&#xC591; &#xD55C; &#xC720;&#xC804;&#xC801; &#xBC30;&#xACBD;&#xC5D0;&#xC11C; JNK &#xD65C;&#xB3D9;&#xC744; &#xADDC;&#xC81C;.

Redes de se&ntilde;alizaci&oacute;n celulares han evolucionado para permitir respuestas r&aacute;pidas y exactas, a&uacute;n frente a la perturbaci&oacute;n gen&eacute;tico o ambiental. As&iacute;, pantallas gen&eacute;ticos no pueden identificar todos los genes que regulan diferentes procesos biol&oacute;gicos. Por otra parte, aunque cl&aacute;sico enfoques han logrado proporcionar listas de piezas de los componentes esenciales de las redes de se&ntilde;alizaci&oacute;n, por lo general no ofrecen mucha penetraci&oacute;n en las relaciones jer&aacute;rquicas y funcionales que existen entre estos componentes. Describimos una pantalla de alto rendimiento en que utilizamos ARN de interferencia para inhibir sistem&aacute;ticamente dos genes simult&aacute;neamente en 17.724 combinaciones para identificar los reguladores de la cinasa de la terminal 2 de Drosophila NH JUN (JNK). Utilizando tanto gen&eacute;tica y datos de fosfoprote&oacute;mico, entonces hemos implementado un algoritmo de integrante de la red para construir una red de fosforilaci&oacute;n de JNK, que ofrece ideas estructurales y mec&aacute;nicas sobre la arquitectura de sistemas de se&ntilde;alizaci&oacute;n de JNK.

Redes de fosforilaci&oacute;n regulan la actividad JNK en diversos or&iacute;genes gen&eacute;ticos.

Although the molecular elements controlling cell cycle progression are well established, the mechanisms regulating how cell proliferation is triggered in response to extrinsic stimuli and how cell divisions change speed, particularly in stem or tumor cells or regenerative tissues, are poorly understood. One exceptional model system in which these events are precisely defined is Drosophila abdominal morphogenesis, in which stem-like histoblasts build the adult epidermis at metamorphosis by undergoing a series of sequential transitions from a non-proliferative to a growing, and finally to an invasive epithelium. We have recently uncovered in histoblasts an internal logic modulating cell cycle transitions that should constitute a reference paradigm for the study of other equivalent processes in stem cell, cancer or developmental biology.

Changing gears in the cell cycle: histoblasts and beyond.

Tissue remodeling in development and disease involves the coordinated invasion of neighboring territories and/or the replacement of entire cell populations. Cell guidance, cell matching, transitions from passive to migratory epithelia, cell growth and death, and extracellular matrix remodeling all impinge on epithelial spreading. Significantly, the extracellular signals that direct these activities and the specific cellular elements and mechanisms regulated by these signals remain in most cases to be identified. To address these issues, we performed an analysis of histoblasts (Drosophila abdominal epithelial founder cells) on their transition from a dormant state to active migration replacing obsolete larval epidermal cells (LECs). We found that during expansion, Decapentaplegic (Dpp) secreted from surrounding LECs leads to graded pathway activation in cells at the periphery of histoblast nests. Across nests, Dpp activity confers differential cellular behavior and motility by modulating cell-cell contacts, the organization and activity of the cytoskeleton, and histoblast attachment to the substrate. Furthermore, Dpp also prevents the premature death of LECs, allowing the coordination of histoblast expansion to LEC delamination. Dpp signaling activity directing histoblast spreading and invasiveness mimics transforming growth factor-beta and bone morphogenetic proteins' role in enhancing the motility and invasiveness of cancer cells, resulting in the promotion of metastasis.

Dpp signaling directs cell motility and invasiveness during epithelial morphogenesis.

Mechanical force is known to modulate the activity of the Jun N-terminal kinase (JNK) signaling cascade. However, the effect of mechanical stresses on JNK signaling activation has previously only been analyzed by in vitro detection methods. It still remains unknown how living cells activate the JNK signaling cascade in response to mechanical stress and what its functions are in stretched cells.We assessed in real-time the activity of the JNK pathway in Drosophila cells by Fluorescence Lifetime Imaging Microscopy (FLIM), using an intramolecular phosphorylation-dependent dJun-FRET (Fluorescence Resonance Energy Transfer) biosensor. We found that quantitative FRET-FLIM analysis and confocal microscopy revealed sustained dJun-FRET biosensor activation and stable morphology changes in response to mechanical stretch for Drosophila S2R+ cells. Further, these cells plated on different substrates showed distinct levels of JNK activity that associate with differences in cell morphology, integrin expression and focal adhesion organization.These data imply that alterations in the cytoskeleton and matrix attachments may act as regulators of JNK signaling, and that JNK activity might feed back to modulate the cytoskeleton and cell adhesion. We found that this dynamic system is highly plastic; at rest, integrins at focal adhesions and talin are key factors suppressing JNK activity, while multidirectional static stretch leads to integrin-dependent, and probably talin-independent, Jun sensor activation. Further, our data suggest that JNK activity has to coordinate with other signaling elements for the regulation of the cytoskeleton and cell shape remodeling associated with stretch.

Integrin-dependent activation of the JNK signaling pathway by mechanical stress.

The capacity of tumour cells to maintain continual overgrowth potential has been linked to the commandeering of normal self-renewal pathways. Using an epithelial cancer model in Drosophila melanogaster, we carried out an overexpression screen for oncogenes capable of cooperating with the loss of the epithelial apico-basal cell polarity regulator, scribbled (scrib), and identified the cell fate regulator, Abrupt, a BTB-zinc finger protein. Abrupt overexpression alone is insufficient to transform cells, but in cooperation with scrib loss of function, Abrupt promotes the formation of massive tumours in the eye/antennal disc. The steroid hormone receptor coactivator, Taiman (a homologue of SRC3/AIB1), is known to associate with Abrupt, and Taiman overexpression also drives tumour formation in cooperation with the loss of Scrib. Expression arrays and ChIP-Seq indicates that Abrupt overexpression represses a large number of genes, including steroid hormone-response genes and multiple cell fate regulators, thereby maintaining cells within an epithelial progenitor-like state. The progenitor-like state is characterised by the failure to express the conserved Eyes absent/Dachshund regulatory complex in the eye disc, and in the antennal disc by the failure to express cell fate regulators that define the temporal elaboration of the appendage along the proximo-distal axis downstream of Distalless. Loss of scrib promotes cooperation with Abrupt through impaired Hippo signalling, which is required and sufficient for cooperative overgrowth with Abrupt, and JNK (Jun kinase) signalling, which is required for tumour cell migration/invasion but not overgrowth. These results thus identify a novel cooperating oncogene, identify mammalian family members of which are also known oncogenes, and demonstrate that epithelial tumours in Drosophila can be characterised by the maintenance of a progenitor-like state. 

The BTB-zinc finger transcription factor abrupt acts as an epithelial oncogene in Drosophila melanogaster through maintaining a progenitor-like cell state.

The transcription factor Tbx5 is expressed in the developing heart, eyes and anterior appendages. Mutations in human TBX5 cause Holt-Oram syndrome, a condition characterized by heart and upper limb malformations. Tbx5-knockout mouse embryos have severely impaired forelimb and heart morphogenesis from the earliest stages of their development. However, zebrafish embryos with compromised tbx5 function show a complete absence of pectoral fins, while heart development is disturbed at significantly later developmental stages and eye development remains to be thoroughly analysed. We identified a novel tbx5 gene in zebrafish--tbx5b--that is co-expressed with its paralogue, tbx5a, in the developing eye and heart and hypothesized that functional redundancy could be occurring in these organs in embryos with impaired tbx5a function. We have now investigated the consequences of tbx5a and/or tbx5b downregulation in zebrafish to reveal that tbx5 genes have essential roles in the establishment of cardiac laterality, dorsoventral retina axis organization and pectoral fin development. Our data show that distinct relationships between tbx5 paralogues are required in a tissue-specific manner to ensure the proper morphogenesis of the three organs in which they are expressed. Furthermore, we uncover a novel role for tbx5 genes in the establishment of correct heart asymmetry in zebrafish embryos.

Distinct tissue-specific requirements for the zebrafish tbx5 genes during heart, retina and pectoral fin development.

Biological imaging based on light microscopy comes at the core of the methods that let us understanding morphology and its dynamics in synergy to the spatiotemporal distribution of cellular and molecular activities as the organism develops and becomes functional. Non-linear optical tools and superesolution methodologies are under constant development and their applications to live imaging of whole organisms keep improving as we speak. Genetically coded biosensors, multicolor clonal methods and optogenetics in different organisms and, in particular, in Drosophila follow equivalent paths. We anticipate a brilliant future for live imaging providing the roots for the holistic understanding, rather than for individual parts, of development and function at the whole-organism level.

Live imaging in Drosophila: The optical and genetic toolkits.

Cells display versatile responses to mechanical inputs and recent studies have identified the mitogen-activated protein kinase (MAPK) cascades mediating the biological effects observed upon mechanical stimulation. Although, MAPK pathways can act insulated from each other, several mechanisms facilitate the crosstalk between the components of these cascades. Yet, the combinatorial complexity of potential molecular interactions between these elements have prevented the understanding of their concerted functions. To analyze the plasticity of the MAPK signaling network in response to mechanical stress we performed a non-saturating epistatic screen in resting and stretched conditions employing as readout a JNK responsive dJun-FRET biosensor. By knocking down MAPKs, and JNK pathway regulators, singly or in pairs in Drosophila S2R+ cells, we have uncovered unexpected regulatory links between JNK cascade kinases, Rho GTPases, MAPKs and the JNK phosphatase Puc. These relationships have been integrated in a system network model at equilibrium accounting for all experimentally validated interactions. This model allows predicting the global reaction of the network to its modulation in response to mechanical stress. It also highlights its context-dependent sensitivity. 

Plasticity of the MAPK signaling network in response to mechanical stress.

The principles underlying the biomechanics of morphogenesis are largely unknown. Epiboly is an essential embryonic event in which three tissues coordinate to direct the expansion of the blastoderm. How and where forces are generated during epiboly, and how these are globally coupled remains elusive. Here we developed a method, hydrodynamic regression (HR), to infer 3D pressure fields, mechanical power, and cortical surface tension profiles. HR is based on velocity measurements retrieved from 2D+T microscopy and their hydrodynamic modeling. We applied HR to identify biomechanically active structures and changes in cortex local tension during epiboly in zebrafish. Based on our results, we propose a novel physical description for epiboly, where tissue movements are directed by a polarized gradient of cortical tension. We found that this gradient relies on local contractile forces at the cortex, differences in elastic properties between cortex components and the passive transmission of forces within the yolk cell. All in all, our work identifies a novel way to physically regulate concerted cellular movements that might be instrumental for the mechanical control of many morphogenetic processes.

Polarized cortical tension drives zebrafish epiboly movements.

Precise tissue remodeling during development is essential for shaping embryos and optimal organ function. Epiboly is an early gastrulation event by which the blastoderm expands around the yolk to engulf it. Three different layers are involved in this process, an epithelial layer (the enveloping layer, EVL), the embryo proper, constituted by the deep cells (DCs), and the yolk cell. Although teleost epiboly has been studied for many years, a clear understanding of its mechanics was still missing. Here we present new information on the cellular, molecular and mechanical elements involved in epiboly that, together with some other recent data and upon comparison with previous biomechanical models, lets conclude that the expansion of the epithelia is passive and driven by active cortical contraction and membrane removal in the adjacent layer, the External Yolk Syncytial Layer (E-YSL). The isotropic actomyosin contraction of the E-YSL cortex generates an anisotropic stress pattern and a directional net movement consequence of the differences in the deformation response of the 2 opposites adjacent domains (EVL and the Yolk Cytoplasmic Layer - YCL). Contractility is accompanied by the local formation of membrane folds and its removal by Rab5ab dependent macropinocytosis. The increase in area of the epithelia during the expansion is achieved by cell-shape changes (flattening) responding to spherical geometrical cues. The counterbalance between the geometry of the embryo and forces dissipation among different elements is therefore essential for epiboly global coordination.

Contractility, differential tension and membrane removal lead zebrafish epiboly biomechanics.

Neurons allocated to sense organs respond rapidly to mechanical signals dictating behavioral responses at the organism level. The receptors that transduce these signals, and underlie these senses, are mechanically gated channels. Research on mechanosensation over the past decade, employing in many cases Drosophila as a model, has focused in typifying these receptors and in exploring the different ways, depending on context, in which these mechanosensors are modulated. In this review, we discuss first what we have learned from Drosophila on these mechanisms and we describe the different mechanosensory organs present in the Drosophila larvae and adult. Secondly, we focus on the progress obtained by studying the fly on the characterization of the mechanosensory crosstalk underlying complex behaviors like motor coordination. Finally, turning to a cellular level, we summarize what is known on the mechanical properties and sensing capabilities of neural cells and how they may affect neural physiology and pathology.

Mechanosensing in the Drosophila nervous system.

The achievement of the final form of an individual requires not only the control of cell size and differentiation but also integrative directional cues to instruct cell movements, positions, and orientations. In Drosophila, the adult epidermis of the abdomen is created de novo by histoblasts. As these expand and fuse, they uniformly orient along the anteroposterior axis. We found that the Dachsous/Fat/Four-jointed (Ds/Ft/Fj) pathway is key for their alignment. The refinement of the tissue-wide expression of the atypical cadherins Ds and Ft result in their polarization and directional adhesiveness. Mechanistically, the axially oriented changes in histoblasts respond to the redesign of the epithelial field. We suggest that the role of Ds/Ft/Fj in long-range oriented cell alignment is a general function and that the regulation of the expression of its components will be crucial in other morphogenetic models or during tissue repair.

The Dachsous/Fat/Four-Jointed Pathway Directs the Uniform Axial Orientation of Epithelial Cells in the Drosophila Abdomen.

During development, cells coordinate to organize in coherent structures. Although it is now well established that physical forces are essential for implementing this coordination, the instructive roles of mechanical inputs are not clear. Here, we show that the replacement of the larval epithelia by the adult one in Drosophila demands the coordinated exchange of mechanical signals between two cell types, the histoblasts (adult precursors) organized in nests and the surrounding larval epidermal cells (LECs). An increasing stress gradient develops from the center of the nests toward the LECs as a result of the forces generated by histoblasts as they proliferate and by the LECs as they delaminate (push/pull coordination). This asymmetric radial coordination of expansive and contractile activities contributes to epithelial replacement. Our analyses support a model in which cell-cell mechanical communication is sufficient for the rearrangements that implement epithelial morphogenesis.

Enrique Martin-Blanco

Instituto de Biología Molecular de Barcelona,
Consejo Superior de Investigaciones Científicas,
Instituto de Biología Molecular de Barcelona, Consejo Superior de Investigaciones Científicas

Parc Científic de Barcelona

Imaging and Analysis of Tissue Orientation and Growth Dynamics in the Developing Drosophila Epithelia During Pupal Stages

Enrique Martin-Blanco

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}Instituto de Biología Molecular de Barcelona,Consejo Superior de Investigaciones Científicas,Instituto de Biología Molecular de Barcelona, Consejo Superior de Investigaciones Científicas

Parc Científic de Barcelona

Imaging and Analysis of Tissue Orientation and Growth Dynamics in the Developing Drosophila Epithelia During Pupal Stages

Instituto de Biología Molecular de Barcelona,
Consejo Superior de Investigaciones Científicas,
Instituto de Biología Molecular de Barcelona, Consejo Superior de Investigaciones Científicas