Cell-type diversity and regionalized gene expression in the planarian intestine
Physical trauma , disease , and aging can damage the digestive tract , causing numerous human gastrointestinal ( GI ) pathologies ( Li and Jasper , 2016; Andersson-Rolf et al . , 2017; Peery et al . , 2019 ) . Mice and Drosophila can repair damage to the digestive epithelium , and recent studies have elucidated cellular and molecular mechanisms underpinning these abilities ( Gehart and Clevers , 2019; Jiang et al . , 2016; Zwick et al . , 2019 ) . Some animals are endowed with much greater regenerative capacity , and can repair or even completely replace severely damaged or missing GI tissue ( Goodchild , 1956; O'Steen , 1958; Takeo et al . , 2008 ; Kaneko et al . , 2010; Zattara and Bely , 2011; Mashanov et al . , 2014; Okano et al . , 2015 ) , but the underlying mechanisms are far less understood . Regeneration requires precise spatial and temporal control over the differentiation of distinct cell types , as well as remodeling of uninjured tissue . Furthermore , individual cell types can respond uniquely to injury and play specialized roles that promote regeneration ( Gehart and Clevers , 2019; Jiang et al . , 2016; Kumar et al . , 2007; Witchley et al . , 2013; Gemberling et al . , 2015; Mokalled et al . , 2016; Tanaka , 2016 ) . Therefore , characterization of an organ’s composition and gene expression at a cellular level in the uninjured state is an essential step in unraveling the mechanisms required for faithful re-establishment of organ morphology and physiology . Driven by the recent application of genomic and molecular methods , the planarian flatworm Schmidtea mediterranea has become a powerful model in which to address the molecular and cellular underpinnings of organ regeneration ( Newmark and Sánchez Alvarado , 2002; Robb et al . , 2015; Brandl et al . , 2016; Grohme et al . , 2018; Reddien , 2018 ) . In response to nearly any type of surgical amputation injury , pluripotent stem cells called neoblasts proliferate and differentiate , regenerating brain , intestine , and other tissues lost to injury ( Reddien and Sánchez Alvarado , 2004; Rink , 2018 ) . In addition , pre-existing tissue undergoes extensive remodeling and re-scaling through both collective migration of post-mitotic cells in undamaged tissues , as well as proportional loss of cells through apoptosis ( Pellettieri , 2019 ) . These processes are coordinated to achieve re-establishment of proportion , symmetry , and function of planarian organ systems within a few weeks after injury ( Roberts-Galbraith and Newmark , 2015 ) . The planarian intestine is a prominent organ whose highly branched morphology , simple cellular composition , and likely cell non-autonomous role in neoblast regulation make it a compelling model for addressing fundamental mechanisms of regeneration . In uninjured planarians , a single anterior and two posterior primary intestinal branches project into the head and tail , respectively , with secondary , tertiary , and quaternary branches extending toward lateral body margins ( Hyman , 1951; Forsthoefel et al . , 2011 ) . Growth and regeneration of intestinal branches require considerable remodeling of pre-existing tissue ( Forsthoefel et al . , 2011 ) . Remodeling is governed by axial polarity cues ( Pellettieri , 2019; Forsthoefel and Newmark , 2009 ) , extracellular-signal-regulated kinase ( ERK ) and epidermal growth factor receptor ( EGFR ) signaling pathways ( Umesono et al . , 2013; Hosoda et al . , 2016; Barberán et al . , 2016 ) , cytoskeletal regulators ( Forsthoefel et al . , 2012 ) , and interactions with muscle ( Adler and Sánchez Alvarado , 2017; Seebeck et al . , 2017; Bonar and Petersen , 2017; Scimone et al . , 2018 ) . However , the mechanisms by which post-mitotic intestinal cells sense and respond to extrinsic signals are only superficially understood . New intestinal cells ( the progeny of neoblasts ) differentiate at the severed ends of injured gut branches , as well as in regions of significant remodeling , providing an intriguing example of how differentiation and remodeling must be coordinated to achieve integration of old and new tissue ( Forsthoefel et al . , 2011 ) . Only three cell types comprise the intestinal epithelium: secretory goblet cells , absorptive phagocytes ( Willier et al . , 1925; Ishii , 1965; Bowen et al . , 1974 ) , and a recently identified population of basally located ‘outer’ intestinal cells ( Fincher et al . , 2018 ) . Transcription factors expressed by intestinal progenitors ( ‘gamma’ neoblasts ) and their progeny have been identified ( Forsthoefel et al . , 2012; Fincher et al . , 2018; Wagner et al . , 2011; van Wolfswinkel et al . , 2014; Labbé et al . , 2012; Zeng et al . , 2018 ) . However , only the EGF receptor egfr-1 ( Barberán et al . , 2016 ) has been shown definitively to be required for integration of intestinal cells into gut branches , and therefore the functional requirements for differentiation of new intestinal cells are largely undefined . The intestine may also play a niche-like role in modulating neoblast dynamics . Knockdown of several intestine-enriched transcription factors ( nkx2 . 2 , gata4/5/6-1 ) causes reduced blastema formation and/or decreased neoblast proliferation ( Forsthoefel et al . , 2012; Flores et al . , 2016 ) . Similarly , knockdown of the intestine-enriched HECT E3 ubiquitin ligase wwp1 causes disruption of intestinal integrity , reduced blastema formation , and neoblast loss ( Henderson et al . , 2015 ) . Conversely , knockdown of egfr-1 causes hyperproliferation and expansion of several neoblast subclasses ( Barberán et al . , 2016 ) . Because these genes are also expressed by neoblasts and their progeny , careful analysis will be required to distinguish their functions in the stem cell compartment from cell non-autonomous roles in the intestine . Nonetheless , because so few extrinsic signals ( Miller and Newmark , 2012; Gaviño et al . , 2013; Dingwall and King , 2016; Lei et al . , 2016 ) controlling neoblast proliferation have been identified , further investigation of the intestine as a potential source of such cues is warranted . Addressing these aspects of intestine regeneration and function necessitates development of approaches for purification of intestinal tissue . Previously , we developed a method for purifying intestinal phagocytes from single-cell suspensions derived from planarians fed magnetic beads , enabling characterization of gene expression by this cell type ( Forsthoefel et al . , 2012 ) . More recently , single-cell profiling of whole planarians has distinguished individual intestinal cell types , as well as transitional markers for neoblasts differentiating along endodermal lineages ( Fincher et al . , 2018; Labbé et al . , 2012; Zeng et al . , 2018; Plass et al . , 2018 ) . Both approaches have advanced our understanding of intestinal biology . However , methods that ( a ) avoid the potentially confounding effects of feeding and dissociation on gene expression and ( b ) overcome the need to sequence tens of thousands of planarian cells to identify intestinal cells ( only 1–3% of all planarian cells , [Baguñá and Romero , 1981] ) , would further enhance the experimental accessibility of the intestine . Laser-capture microdissection ( LCM ) was developed as a precise method for obtaining enriched or pure cell populations from tissue samples , including archived biopsy and surgical specimens ( Emmert-Buck et al . , 1996 ) . Since its introduction , LCM has been used to address a vast array of basic and clinical problems requiring genome , transcriptome , or proteome analysis in specific tissues or cell types ( Mahalingam , 2018; Bevilacqua and Ducos , 2018 ) . LCM requires sample preparation including fixation , histological sectioning , and tissue labeling or staining ( Espina et al . , 2006 ) . For subsequent expression profiling , tissue processing must be optimized to maintain morphology and labeling of cells of interest , as well as RNA integrity ( Espina et al . , 2006; Goldsworthy et al . , 1999; Gillespie et al . , 2002; Golubeva and Warner , 2018 ) . Excision and capture of tissue with infrared and/or ultraviolet lasers is then performed using one of several commercial LCM systems ( Bevilacqua and Ducos , 2018 ) . Here , we report the application of LCM for expression profiling of the planarian intestine . We first identified appropriate tissue-processing conditions for extraction of intact RNA from planarian tissue sections . Then , using RNA-Seq , bioinformatics approaches , and whole-mount in situ hybridization , we characterized the intestinal transcriptome . We discovered previously unappreciated regionalization and diversity of intestinal cell types and subtypes , especially amongst goblet cells , and hundreds of intestine-enriched transcripts not identified in recent single-cell profiling efforts . In addition , we identified 22 intestine-enriched transcription factors , including several required for production and/or maintenance of goblet cells , setting the stage for further studies of this cell type . The planarian intestinal transcriptome is a foundational resource for investigating numerous aspects of intestine regeneration and physiology . Furthermore , the LCM methods we introduce offer an additional , complementary strategy for assessing tissue-specific gene expression in planarians .
Successful application of laser microdissection requires identification of sample preparation conditions that balance the need to extract high-quality total RNA with preservation of specimen morphology and the ability to identify tissues or cells of interest . Fixation of whole planarians requires an initial step to relax/kill animals and remove mucus , followed by fixation ( Forsthoefel et al . , 2014; Ross et al . , 2015 ) . We tested three commonly used relaxation/mucus-removal treatments and two fixatives ( formaldehyde and methacarn ) , separately and together , using short treatment times in order to minimize potential deleterious effects on RNA ( Figure 1—figure supplement 1A ) . None of the relaxation treatments detrimentally affected RNA quality , but methacarn ( a precipitating fixative ) enabled much better RNA recovery than formaldehyde ( a cross-linking fixative ) ( Figure 1—figure supplement 1A–B ) . Next , we assessed how mucus removal affected morphology and staining of cryosections taken from methacarn-fixed planarians , again using a rapid protocol to minimize RNA degradation ( Figure 1—figure supplement 1C ) . For all three mucus-removal methods , Eosin Y alone or with Hematoxylin enabled superior demarcation of the intestine , as compared to Hematoxylin alone ( Figure 1—figure supplement 1C ) . For preservation of morphology , magnesium relaxation was superior; NAc and HCl treatment caused tearing and detachment of intestine from the slide ( Figure 1—figure supplement 1C ) . Finally , we assessed RNA integrity from laser-microdissected intestine and non-intestine from magnesium-treated , methacarn-fixed tissue ( Figure 1A–B and Figure 1—figure supplement 1D ) , stained only with Eosin Y to further minimize processing time ( Figure 1—figure supplement 1C ) . Although additional freezing , cryosectioning , staining , and drying steps required for LCM caused a modest decrease in RNA integrity relative to whole animals ( compare Figure 1—figure supplement 1A with 1D ) , prominent 18S/28S rRNA peaks ( which co-migrate in planarians , as in some other invertebrates [Ishikawa , 1977; Matz , 2002; Winnebeck et al . , 2010; Asai et al . , 2015; Figure 1—figure supplement 1D] ) indicated that the combination of magnesium-induced relaxation , brief methacarn fixation , and rapid Eosin Y staining were suitable for LCM and extraction of RNA of sufficient quality for RNA-Seq . Using our optimized conditions , we laser microdissected intestinal and non-intestinal tissue from four individual planarians ( biological replicates ) ( Figure 1A–B and Figure 1—figure supplement 1D ) . For this study , we isolated tissue from the anterior of the animal ( rostral to the pharynx , planarians' centrally located feeding organ ) , where intestinal tissue is more abundant . We microdissected tissue from medial and lateral intestine separately , since the intestine ramifies into secondary , tertiary , and quaternary branches along the mediolateral axis , but whether gene expression varies along this axis has not been addressed systematically . We then extracted total RNA , conducted RNA-Seq , and identified transcripts that were preferentially expressed in intestinal vs . non-intestinal tissue ( Figure 1C–F and Supplementary files 1 and 2 ) . Altogether , we detected 13 , 136 of 28 , 069 transcripts in the reference transcriptome ( 46 . 8% coverage ) in non-intestine , medial intestine , and/or lateral intestine ( Figure 1C ) . Of these , 1844 were upregulated in either medial or lateral intestine , or both ( Figure 1C ) . Specifically , in medial intestine , 1748 transcripts were significantly upregulated ( fold-change >2 and FDR-adjusted p-value<0 . 01 ) compared to non-intestine ( Figure 1D ) . In lateral intestine , 1627 transcripts were upregulated ( Figure 1D ) . Although most ( 1 , 531/1 , 844 ) transcripts were upregulated in both medial and lateral intestine , a small subset of transcripts was significantly upregulated only in medial ( 217/1 , 844 ) or lateral ( 96/1 , 844 ) intestine ( Figure 1D ) , relative to non-intestine . To further define medial and lateral transcript enrichment , we calculated a ‘mediolateral ratio’ of the medial and lateral intestine/non-intestine fold-changes ( Figure 1E and Supplementary file 1 ) . Although most transcripts were only modestly enriched ( <1 . 5X fold-change enrichment ) in medial ( 1 , 124 ) or lateral ( 567 ) intestine , a small number of transcripts was >1 . 5X enriched in medial ( 97 ) or lateral ( 56 ) intestine ( Figure 1E and Supplementary file 1 ) . We validated RNA-Seq results using whole-mount in situ hybridization ( WISH ) to test expression in fixed , uninjured planarians ( Umesono et al . , 1997; Pearson et al . , 2009; King and Newmark , 2013; Figure 1F and Figure 1—figure supplement 2 ) . 143/162 transcripts ( ~88% ) had detectable expression in the intestine ( Figure 1—figure supplement 2 and Supplementary file 1 ) . Most transcripts were expressed uniformly throughout the intestine ( e . g . ATPase H+-transporting accessory protein 2 ( atp6ap2 ) , cytochrome P450 2B19 ( cyp2b19 ) , cytochrome P450 2A6 ( cyp2a6 ) , and prosaposin ( psap ) ; Figure 1F , blue borders , and Figure 1—figure supplement 2 ) . By contrast , transcripts predicted by RNA-Seq to be most enriched ( >1 . 5X ) in medial intestine branches ( e . g . carboxypeptidase A2 ( cpa2 ) , rapunzel 4 ( rpz4 ) , and gastric triacylglycerol lipase ( lipf ) , green borders , Figure 1F ) or lateral intestine branches ( e . g . a carboxypeptidase homolog ( ct14378 ) , serine peptidase inhibitor Kunitz type 3 ( spint3 ) , and a novel gene ( ‘novel’ ) , orange borders , Figure 1F ) were indeed expressed at higher levels in these regions . Additionally , although we did not explicitly compare anterior and posterior gene expression , we also discovered anteriorly ( a C-type lectin ( Zgc:171670/dd_79 ) , Figure 1—figure supplement 2 ) and posteriorly ( lysosomal acid lipase ( lipa/dd_122 ) , Figure 1—figure supplement 2 ) enriched transcripts , consistent with the influence of anteroposterior polarity cues on intestinal morphology ( Gurley et al . , 2008; Petersen and Reddien , 2008; Iglesias et al . , 2008; Reuter et al . , 2015; Thi-Kim Vu et al . , 2015; Stückemann et al . , 2017 ) . In summary , using LCM together with RNA-Seq identified >1800 intestine-enriched transcripts , and revealed previously unappreciated regional gene expression domains in the intestine . Previously , we identified genes preferentially expressed by intestinal phagocytes ( Forsthoefel et al . , 2012 ) . To distinguish transcripts expressed by phagocytes and other intestinal cell types , such as goblet cells ( Ishii , 1965; Garcia-Corrales and Gamo , 1986; Garcia-Corrales and Gamo , 1988 ) , we directly compared log2 fold-change values for 1317 transcripts represented in our sorted phagocyte data ( Forsthoefel et al . , 2012 ) as well as laser-microdissected intestinal tissue ( this study ) ( Figures 2A , C and E , and Figure 2—source data 1 ) . 900/1 , 317 transcripts were significantly upregulated in both phagocytes and laser-microdissected intestine ( Figure 2A ) . We analyzed expression of 82 of these transcripts using WISH ( Figure 2B , Supplementary file 1 , and Figure 1—figure supplement 2 ) . As expected , the majority ( 74/82 ) of these transcripts , which included previously identified intestinal markers hnf-4 and nkx2 . 2 ( Wagner et al . , 2011; Forsthoefel et al . , 2012; Garcia-Fernàndez et al . , 1993 ) , displayed uniform , ubiquitous expression throughout the intestine , consistent with enrichment in phagocytes ( Figure 2B and Figure 1—figure supplement 2 ) . 358 intestine-enriched transcripts were not significantly up- or down-regulated in phagocytes ( Figure 2C , Figure 1—figure supplement 2 , and Supplementary file 1 ) . WISH analysis suggested these transcripts are enriched in multiple intestinal cell types ( Figure 2D ) . Some transcripts in this group were expressed ubiquitously throughout the intestine ( ral guanine nucleotide dissociation stimulator-like 1 ( rgl1 ) and family with sequence similarity 21 member C ( fam21c ) , a homolog of WASH complex subunit 2 , Figure 2D ) , suggesting expression in phagocytes , possibly in addition to other cell types . However , others were expressed in a distinct subset of less abundant intestinal cells ( peptidase inhibitor 16 ( pi16 ) and serine peptidase inhibitor , Kunitz type 3 ( spint3 ) , Figure 2D ) . These transcripts are enriched in goblet cells , since their WISH expression pattern is highly similar to labeling of this subpopulation by lectins ( Zayas et al . , 2010 ) , antibodies ( Ross et al . , 2015; Reuter et al . , 2015; Bueno et al . , 1997 ) , and other recently identified transcripts ( Fincher et al . , 2018; Plass et al . , 2018; Reuter et al . , 2015 ) . A third set of transcripts was enriched in basal regions of the intestine ( zgc:172053 , a homolog of human C-type lectin collectin-10 , and calmodulin-3 ( calm3 ) , Figure 2D ) . This pattern resembles that of a planarian gli-family transcription factor ( Rink et al . , 2009 ) and several solute carrier-family transporters ( Thi-Kim Vu et al . , 2015 ) , and indicates expression by ‘outer intestinal cells’ ( which we refer to as ‘basal cells’ because of their proximity to the basal region of phagocytes ) that were also recently identified in a large-scale , single-cell sequencing effort ( Fincher et al . , 2018 ) . Finally , 59 intestine-enriched transcripts were significantly downregulated in phagocytes ( Figure 2E , Figure 1—figure supplement 2 , and Supplementary file 1 ) . As expected , we never observed uniform , phagocyte-like expression patterns for these transcripts ( Figure 2F and Figure 1—figure supplement 2 ) . Rather , transcripts in this group were enriched only in goblet cells ( e . g . epididymal secretory protein E1/Niemann-Pick disease type C2 protein ( npc2 ) ) or basal cells ( e . g . solute carrier family 22 member 6 ( slc22a6 ) ) . Furthermore , some goblet-cell-specific transcripts also appeared to be either medially ( e . g . metalloendopeptidase ( cg7631 ) ) or laterally ( e . g . , eppin ) enriched ( Figure 2F and Figure 1—figure supplement 2 ) , suggesting possible specialization of this cell type along the mediolateral axis . Overall , validation by WISH identified 91 transcripts with a ubiquitous intestinal expression pattern; nearly all of these were upregulated in our sorted phagocyte data ( Figure 1—figure supplement 2 and Figure 2—figure supplement 1A ) . By contrast , most of the 25 validated goblet-cell-enriched transcripts ( Figure 2—figure supplement 1B ) and 25 basal-cell-enriched transcripts ( Figure 2—figure supplement 1C ) were not upregulated in sorted phagocytes . We have made all WISH expression patterns and RNA-Seq data available in an interactive website , https://plangut . omrf . org . To further characterize intestinal cell types and subtypes , we used fluorescence in situ hybridization ( FISH ) to investigate co-expression of intestine-enriched transcripts . First , we verified the existence of three distinct cell types , using highly expressed phagocyte , goblet , and basal-specific markers ( Figure 3A–C ) . Expression of the most phagocyte-enriched transcript , cathepsin La ( ctsla ) , was ubiquitous throughout intestinal branches , but did not overlap with npc2 , a goblet-cell-enriched mRNA ( Figure 3A ) , or with slc22a6 , a basally enriched transcript ( Figure 3B ) . Goblet cell-enriched npc2 was expressed by cells with minimal slc22a6 expression ( Figure 3C ) , further reinforcing that npc2+ goblet cells are distinct from ctsla+ phagocytes as well as slc22a6+ basal cells . Additional markers validated the distinct identity of these cell types ( Figure 3—figure supplement 1A–B ) . We also found that slc22a6+ basal cells were distinct from visceral muscle fibers that surround intestinal branches , occupying basal regions around digestive cells ( Kobayashi et al . , 1998; Orii et al . , 2002 ) , consistent with another study ( Scimone et al . , 2018; Figure 3D–E ) . Thus , slc22a6+ cells represent a novel cell type in the intestine that is distinct from visceral muscles , phagocytes , and goblet cells , and that has , to our knowledge , not been described by numerous previous histological and ultrastructural studies . Our data independently confirm the identification of this cell type in a recent single-cell sequencing effort ( Fincher et al . , 2018 ) . Using additional markers , we also characterized previously unappreciated heterogeneity in gene expression amongst both goblet and basal cells . These included a subpopulation of goblet cells restricted to medial regions of the intestine , mainly localized to primary branches ( Figure 4A and C ) , and a lateral subpopulation within secondary , tertiary , and quaternary branches ( Figure 4B–C ) . Only rarely did goblet cells in these medial and lateral domains co-mingle , or co-express both markers at the mediolateral boundaries between primary and secondary branches ( Figure 4C ) . We also identified subpopulations of basal cells in lateral regions of the intestine ( Figure 4D and Figure 3—figure supplement 1B ) . Finally , we also identified transcripts expressed by multiple cell types in different combinations and levels ( Figure 4E–G and Figure 3—figure supplement 1C–D ) , illustrating the complexity of gene expression even in a tissue with relatively few cell types . We also compared transcript enrichment in phagocytes/enterocytes , goblet cells , and basal cells/outer intestinal cells reported in three recent single-cell RNA-Seq ( scRNA-Seq ) analyses of planarian cells ( Fincher et al . , 2018; Plass et al . , 2018; Swapna et al . , 2018 ) . There was considerable agreement between our verified in situ expression patterns and cell-type enrichment predicted by scRNA-Seq studies , although we did identify numerous additional cell-type-specific transcripts ( Figure 5A ) . In addition , phagocyte- , goblet- , and basal-cell-specific transcripts from scRNA-Seq studies mapped to similar quadrants in our phagocyte vs . laser-captured intestine plots ( Figure 2—figure supplement 1D–H ) . Similarly , the majority of phagocyte-enriched transcripts detected in our earlier study ( Forsthoefel et al . , 2012 ) were also enriched in laser-captured intestine ( Figure 5B ) . Furthermore , we identified 809 intestine-enriched transcripts that single-cell studies did not find to be enriched in the intestine ( or for some , any planarian cell type ) ( Figure 5C ) . Using WISH , we validated intestine enrichment for 22/28 of these mRNAs ( Figure 5D–H ) , including transcripts with a uniform/phagocyte-like expression pattern ( Figure 5D ) , and others with expression in goblet and basal cells ( Figure 5E–F ) . We also note that over 1000 intestine-enriched transcripts in scRNA-Seq studies were not included in our LCM-generated transcriptome ( Figure 5C ) . However , the vast majority ( >80% ) of these were enriched in multiple cell types ( Fincher et al . , 2018; Plass et al . , 2018; Supplementary file 2 ) , suggesting considerable expression in non-intestinal tissue , consistent with our data . The incomplete overlap between various scRNA-Seq studies and our results could be explained , in part , by different log-fold enrichment criteria used to identify cell-type-specific transcripts . However , the detection of transcripts exclusively enriched in laser-captured intestine suggests that expression profiling of laser-captured bulk tissue is more sensitive than current single-cell profiling approaches , and that LCM may be a preferable method for assessing tissue-specific gene expression when single-cell resolution is not required . In order to globally characterize functional classes of genes expressed in the planarian intestine , we assigned Gene Ontology ( GO ) Biological Process ( BP ) terms to planarian transcripts based on homology to human , mouse , zebrafish , Drosophila , and C . elegans genes , and then identified over-represented terms among intestine-enriched transcripts ( Figure 6 , Figure 6—source data 1A , and Supplementary file 3 ) . Highly represented terms fell broadly into seven groups ( Figure 6 ) , all of which are related to the intestine’s roles in digestion , nutrient storage and distribution , as well as innate immunity . Metabolic processes were among the most highly represented: hundreds of transcripts were predicted to regulate catabolism , biosynthesis , and transport of a variety of macromolecules ( e . g . lipids and carbohydrates ) and small molecules ( e . g . amino acids and ions ) ( Supplementary file 3A ) . Hundreds of upregulated transcripts were also predicted to regulate molecular transport , vesicular trafficking , and organelle-based import and export ( Figure 6—figure supplement 3A ) . These included over 70 members of the solute carrier family of transmembrane transporters ( Supplementary file 3B ) , reinforcing the intestine’s central role in metabolite transport , and also suggesting a potential role supporting the excretory system in maintaining extracellular solute concentration ( Thi-Kim Vu et al . , 2015; Andrikou et al . , 2019 ) . Enriched regulators of vesicular trafficking also included nearly 30 Ras-related Rab GTPase proteins ( Supplementary file 3C ) . Among regulators of organelle and cellular physiology , transcripts predicted to coordinate phagosome , endosome , and lysosome physiology were among the most highly represented ( Supplementary file 3A ) . These included several vacuolar protein sorting-associated protein ( vps ) homologs required for lysosome tethering to late endosomes and autophagosomes ( Spang , 2016 ) , and homologs of the autophagy-related proteins atg3 and atg7 , ubiquitin ligases that are required for autophagosome formation during nutrient starvation ( Komatsu et al . , 2005; Sou et al . , 2008 ) , and which may contribute to planarians’ ability to survive extended fasting ( Felix et al . , 2019 ) . As in our previous study of phagocyte expression ( Forsthoefel et al . , 2012 ) , here we also identified many intestine-enriched genes predicted to regulate cell shape , motility , polarity , and adhesion , including numerous cytoskeletal regulators , regulators of interactions with extracellular matrix , and partitioning defective 6 ( pard6b ) , which we previously demonstrated was required for planarian intestinal remodeling ( Forsthoefel et al . , 2012; Supplementary file 3A ) . Finally , transcripts predicted to regulate responses to stress , microorganisms , and other stimuli were also intestine enriched ( Figure 6 ) . Prominent among these were regulators of innate immunity , including over 30 tumor necrosis factor receptor-associated factor homologs ( TRAFs ) , a family of adaptor proteins that is expanded in S . mediterranea ( Swapna et al . , 2018 ) and function as effectors of receptor signaling in innate and adaptive immunity ( Xie , 2013; Arnold et al . , 2016; Supplementary file 3D ) . Notably , 62 intestine-enriched transcripts ( from this study ) were previously found to be upregulated in response to shifting planarians from recirculating to static culture conditions , which causes microbiome dysbiosis ( Arnold et al . , 2016; Figure 6—figure supplement 1A and Figure 6—source data 2A ) . Further supporting a role for the intestine in innate immunity and/or inflammatory responses , homologs of 99 S . mediterranea intestine-enriched transcripts were also upregulated by ingestion of pathogenic bacteria in Dugesia japonica , a related planarian species ( Abnave et al . , 2014; Figure 6—figure supplement 1B and Figure 6—source data 2B ) . In order to understand whether putative functional roles above are performed by specific intestinal cell types or domains , we also analyzed GO term over-representation among transcripts enriched in scRNA-Seq data ( Fincher et al . , 2018 ) , and in laser-captured medial and lateral intestinal tissue . Most functional categories predicted by LCM transcript analysis ( Figure 6 ) were also enriched among phagocyte scRNA-Seq transcripts ( Figure 6—figure supplement 2A and Figure 6—source data 1B–D ) . Furthermore , GO analysis suggested that basal cells may play a significant role in metabolism and energy processing , and that goblet cells may influence extracellular matrix organization and play specialized roles in lipid metabolism ( Figure 6—figure supplement 2A and Figure 6—source data 1B–D ) . Analysis of biological process GO term enrichment among all 1221 medial and 623 lateral transcripts – without regard to cell-type specificity – identified numerous putative regulators of innate immunity and macromolecular catabolism among medial transcripts , and of extracellular matrix organization among lateral transcripts ( Figure 6—figure supplement 2B–D and Figure 6—source data 1E–H ) . Intriguingly , many transcripts with the greatest medial ( 97 ) or lateral ( 56 ) enrichment ( e . g . >1 . 5X in medial vs . lateral tissue or vice versa ) in the intestine were expressed by goblet cells ( Figure 2C–F , Supplementary file 1 , and Figure 1—figure supplement 2 ) . GO analysis of these transcripts suggested possible functional specialization with respect to lipid metabolism , protein processing , extracellular matrix organization , and innate immunity ( Figure 6—figure supplement 2E and Figure 6—source data 1I–J ) . Analysis of expression in situ supported these predictions ( Figure 6—figure supplement 3A–D ) . For example , in support of previous suggestions that goblet cells promote luminal digestion ( Arnold , 1909; Pedersen , 1961; Jennings , 1962 ) , we identified several goblet-enriched transcripts predicted to encode secreted regulators of protein catabolism ( pancreatic carboxypeptidase A2 ) and triglyceride catabolism ( lipase F/gastric triacylglycerol lipase ) ( Figure 6—figure supplement 3A ) . Second , we also identified three goblet-enriched kallikreins ( klk ) ( Figure 6—figure supplement 3A and Figure 1—figure supplement 2 ) , secreted proteases whose mammalian homologs produce vasoactive plasma kinin , but also hydrolyze extracellular matrix molecules , growth factors , hormone proteins , and antimicrobial peptides in numerous tissues ( Prassas et al . , 2015 ) . Kallikreins are expressed by goblet cells in rat , cat , and mouse intestines ( Schachter et al . , 1986; Grün et al . , 2016 ) , and have been implicated in inflammatory bowel disease and gastrointestinal cancers ( Stadnicki , 2011; Kontos et al . , 2013 ) , suggesting additional conservation of planarian goblet cell physiology . Third , goblet cells express peptidoglycan recognition protein ( pgrp-1b ) ( Figure 6—figure supplement 3A ) , whose vertebrate and invertebrate homologs modulate innate immune signaling and play direct bactericidal roles ( Kurata , 2014; Dziarski and Gupta , 2018 ) , suggesting goblet cells may coordinate immune responses and/or regulate microbiome composition . Consistent with this idea , a second planarian paralog , pgrp-1e ( Figure 1—figure supplement 2 ) , is upregulated in the intestine ( but not restricted to goblet cells ) in response to Pseudomonas infection ( Arnold et al . , 2016 ) . Fourth , a homolog of prohormone convertase ( pcsk1 ) is enriched in goblet cells , as well as peripharyngeal cells surrounding the pharynx ( Figure 6—figure supplement 3C ) . Prohormone convertases ( PCs ) cleave neuropeptide and peptide hormone preproteins to generate bioactive peptides . In both vertebrates and invertebrates , PCs function in neurons , but also in endocrine cell types such as pancreatic islet cells and digestive tract enteroendocrine cells , where they regulate glucose levels , energy homeostasis , and appetite ( Grün et al . , 2016; Pauls et al . , 2014; Stijnen et al . , 2016 ) . Although another planarian pcsk paralog , Smed-pc2 , processes neuropeptides required for germline development ( Collins et al . , 2010 ) , to our knowledge , no intestine-enriched prohormones have been reported . Nonetheless , pcsk1 expression suggests goblet cells may play an enteroendocrine-like role , as in other organisms . Finally , we were surprised to find that genes encoding planarian homologs of gel-forming mucins ( which we identified in separate bioinformatic searches ) were expressed not by goblet cells , but by peripharyngeal cells that send projections into the pharynx ( Forsthoefel et al . , 2014; Figure 6—figure supplement 3D ) . While additional goblet-enriched proteins with mucin-like roles might exist ( Bocchinfuso et al . , 2012; Syed et al . , 2008 ) , these expression patterns suggest that some planarian gel-forming mucin proteins are delivered to the intestinal lumen through the pharynx , and indicate a possible difference between planarian and vertebrate intestinal goblet cells ( Birchenough et al . , 2015; Chang et al . , 1994; Johansson et al . , 2011 ) . Further illustrating the conservation of physiological roles , we found that the intestine expresses numerous homologs of transcripts that are enriched in human GI tissues ( Figure 7A–E , Supplementary file 4 , and Figure 7—source data 1 ) . To make this comparison , we conducted reciprocal best homology ( RBH ) searches ( Bork et al . , 1998; Tatusov et al . , 1997 ) to identify 5583 planarian transcripts encoding predicted open reading frames ( ORFs ) with high homology to ORFs in UniProt human transcripts ( The UniProt Consortium , 2018 ) , and vice versa ( Figure 7A–B ) . Of these , we then identified 5561 transcripts ( including 699 gut-enriched transcripts ) with human transcripts represented in the Human Protein Atlas ( Figure 7B–C ) , in which transcripts whose unique or highly enriched tissue-specific expression defines 32 human tissues or organs ( Uhlén et al . , 2015 ) . Next , we calculated the percentage of all ( 5 , 561 ) and gut-enriched ( 699 ) RBH transcripts that were enriched in human tissues ( Figure 7D ) , then expressed these percentages as a fold-enrichment ratio ( planarian intestine vs . non-intestine ) to estimate similarity between the planarian intestine transcriptome and the transcriptomes of human tissues ( Figure 7E ) . Strikingly , four of the five tissues to which the planarian intestine was most similar are involved in digestion ( duodenum , small intestine , and gallbladder ) or energy storage/metabolism ( liver ) ( Figure 7E ) . The intestine was also similar to other human digestive tissues ( esophagus , colon , and rectum ) , as well as kidney , possibly suggesting a role supporting the planarian protonephridial system in filtration or processing of extracellular solutes ( Figure 7E; Thi-Kim Vu et al . , 2015; Rink et al . , 2011; Scimone et al . , 2011 ) . Duodenum- and small intestine-enriched RBH transcripts included predicted regulators of endodermal specification , bile transport , lipid metabolism , and glucose transport ( Supplementary file 4 ) . In addition , RBH homologs enriched in liver included several predicted regulators of glucose , amino acid , lipid , and xenobiotic compound metabolism ( Supplementary file 4 ) . These observations reinforce the evolutionary conservation of intestinal gene expression and indicate that physiological roles performed by multiple human digestive organs are consolidated in the planarian intestine . Definition of the intestinal transcriptome enables identification of genes required for regeneration and functions of distinct intestinal cell types . Here , to initiate this effort , we focused on goblet cells , which expressed the majority of medially and laterally enriched transcripts we identified ( Supplementary file 1 , Figure 1—figure supplement 2 ) . Ultrastructurally , planarian goblet cells possess numerous large proteinaceous granules and abundant rough endoplasmic reticulum ( Willier et al . , 1925; Ishii , 1965; Garcia-Corrales and Gamo , 1986; Pascolini and Gargiulo , 1975 ) , resembling mammalian goblet cells that produce a protective mucous barrier and mount innate immune responses ( Birchenough et al . , 2015; Dalton , 1952; Freeman , 1966; McCauley and Guasch , 2015; Knoop and Newberry , 2018 ) . However , although numerous markers and reagents have been identified that label planarian goblet cells ( Fincher et al . , 2018; Plass et al . , 2018; Ross et al . , 2015; Reuter et al . , 2015; Zayas et al . , 2010; Bueno et al . , 1997 ) , to our knowledge , genes required for goblet cell differentiation , maintenance , or physiological roles have not been reported . Initially , we used RNAi to assess the roles of 16 of the most medial and 8 of the most lateral goblet-enriched transcripts ( Supplementary file 5A-B ) . However , we did not observe failure to feed , decreased viability , or defects in blastema formation , even after 8 weeks of knockdown ( feeding 1x/week ) ( Supplementary file 5A-B ) . This might be due to functional redundancy , since multiple lipases , carboxypeptidases , and kallikriens are expressed by goblet cells . Alternatively , other intestinal cell types might play overlapping roles with respect to some functions . Reasoning that transcription factors ( TFs ) would regulate goblet cell generation and/or maintenance , we next focused on transcripts encoding 22 intestine-enriched TFs , only 10 of which were previously known to be enriched in intestinal cells ( Supplementary file 5C ) . Using FISH , we validated expression of all but one of these TFs in the intestine ( Figure 8—figure supplement 1 ) . In a dsRNA-mediated RNA interference screen to specifically assess goblet cell regeneration , we found that knockdown of three TFs dramatically reduced expression of a goblet cell marker in regenerating head , trunk , and tail fragments ( Figure 8A–B , Figure 8—figure supplement 2 , and Supplementary file 5C ) . Knockdown of mediator of RNA polymerase II transcription subunit 21 ( med 21 ) reduced goblet cells and blastema formation ( Supplementary file 5C ) , but also caused severe disruption of intestinal integrity in our previous study ( Forsthoefel et al . , 2012 ) . This suggested a non-goblet-cell-specific role , and we did not investigate med21 further . Knockdown of a second transcription factor , gli-1 ( a transducer of hedgehog signaling [Rink et al . , 2009; Glazer et al . , 2010] ) , caused failure of goblet cells to regenerate at the midline of the new anterior branch in amputated tail fragments regenerating a new head ( Figure 8A–B , Supplementary file 5C , and Figure 8—figure supplement 2A ) . In addition , goblet cells were less abundant in pre-existing regions of the intestine , particularly in lateral intestinal branches ( Figure 8A–B , Figure 8—figure supplement 2A–C ) . Regeneration of goblet cells was also reduced in new tail branches of gli-1 ( RNAi ) head fragments ( Figure 8—figure supplement 2B ) and in anterior and posterior branches in gli-1 ( RNAi ) trunk fragments ( Figure 8—figure supplement 2C ) . These effects on goblet cells were specific , since phagocytes ( Figure 8A , Figure 8—figure supplement 2A–C ) and basal cells ( Figure 8B ) regenerated normally . Although we infrequently observed smaller posterior blastemas characteristic of reduced hedgehog signaling ( Rink et al . , 2009; Glazer et al . , 2010; Yazawa et al . , 2009 ) , phagocytes regenerated normally in this region ( Figure 8—figure supplement 2C ) . By contrast to the gli-1 phenotype , goblet cells appeared to differentiate normally in regenerating intestine upon knockdown of a third TF , ras-responsive element binding protein 2 ( RREB2 ) , including at the midline of anterior intestinal branches in tail fragments ( Figure 8A–B; Figure 8—figure supplement 2A ) , in posterior branches in head fragments ( Figure 8—figure supplement 2B ) , and in both anterior and posterior branches in trunk fragments ( Figure 8—figure supplement 2C ) . However , in tail and trunk regenerates , new goblet cells were largely restricted to the midline/primary branches ( Figure 8A–B , Figure 8—figure supplement 2A and C ) , and were less abundant in posterior branches of head fragments ( Figure 8—figure supplement 2B ) . Furthermore , in pre-existing intestinal regions ( especially lateral branches ) , goblet cell numbers were dramatically reduced or even completely absent . These included the posterior of tail fragments ( Figure 8A–B; Figure 8—figure supplement 2A ) , the anterior of head fragments ( Figure 8—figure supplement 2B ) , and central regions of trunk fragments ( Figure 8—figure supplement 2C ) . As with gli-1 , phagocytes and basal cells were unaffected ( Figure 8A–B; Figure 8—figure supplement 2A–C ) . Together , these results suggest that gli-1 regulates neoblast fate specification and/or differentiation of neoblast progeny into goblet cells in new intestinal branches , while RREB2 may control maintenance or survival of goblet cells after they initially differentiate . For both knockdowns , the reduction of goblet cells in lateral and pre-existing primary branches could be a consequence of reduced differentiation ( gli-1 ) or maintenance/survival ( RREB2 ) in these regions prior to amputation , during regeneration , or both . In uninjured animals , both gli-1 and RREB2 also reduced goblet cell numbers . Knockdown of gli-1 reduced goblet cell numbers in uninjured animals , especially in anterior , posterior , and lateral intestine branches ( Figure 8C ) , but many goblet cells remained in medial , primary intestinal branches . In RREB2 ( RNAi ) animals , goblet cells were more dramatically reduced in all regions of the intestine ( Figure 8C ) . Although these phenotypes were broadly consistent with observations in regenerates , they also suggested that gli-1 and RREB2 might be required for differentiation and/or maintenance of distinct mediolateral goblet cell subpopulations in uninjured animals . Indeed , we found ( using additional goblet cell markers ) that almost no lateral goblet cells remained in gli-1 ( RNAi ) uninjured animals , while again , medial goblet cells were much less affected ( Figure 8—figure supplement 3A ) . By contrast , in RREB2 ( RNAi ) uninjured animals , reduction of both medial and lateral goblet cell numbers was pronounced , but nonetheless some lateral goblet cells remained ( Figure 8—figure supplement 3A ) . These differential effects on mediolateral subpopulations were not observed in regenerates . For example , both subpopulations failed to differentiate in the primary anterior intestinal branch in gli-1 ( RNAi ) tail regenerates ( Figure 8—figure supplement 3B ) , and both subpopulations were severely reduced in pre-existing , posterior branches of RREB2 ( RNAi ) tail regenerates ( Figure 8—figure supplement 3B ) . Taken together , these results suggest that , in uninjured animals undergoing normal homeostatic growth and renewal , gli-1 is primarily required for differentiation of new lateral intestinal cells . Alternatively , as goblet cells fail to renew , remaining goblet cells might somehow migrate to more medial intestinal branches , or survival of goblet cells in primary branches could be prolonged . Conversely , RREB2 seems to be required for maintenance of both medial and lateral goblet cells , although lateral cell numbers are slightly less affected by RREB2 knockdown , compared to gli-1 . Finally , in regenerates , gli-1 and RREB2 knockdown affects medial and lateral goblet cells similarly ( but in regenerating vs . pre-existing intestine ) . These complex observations suggest that mechanisms regulating goblet cell differentiation and maintenance may differ during homeostasis and regeneration , or that compensatory mechanisms capable of sustaining goblet cell production/survival in uninjured gli-1 ( RNAi ) and RREB2 ( RNAi ) animals are insufficient to meet the increased demand for new tissue during regeneration . Despite their specific effects on goblet cells , neither gli-1 nor RREB2 mRNAs are specifically enriched in this cell type . In fact , gli-1 , which was previously shown to be expressed by intestine-associated cells ( Rink et al . , 2009; Currie et al . , 2016 ) , was most highly enriched in phagocytes , basal cells , and intestine-associated muscle cells ( visceral muscle ) , but was also expressed at lower levels in some goblet cells ( Figure 8—figure supplement 4A ) . RREB2 was enriched in goblet cells and basal cells , but expression was also observed in some phagocytes and intestine-associated muscle ( Figure 8—figure supplement 4B ) . Intriguingly , we found that knockdown of two other TFs , 48 related 1 ( fer1 ) ( also called pancreas transcription factor one subunit alpha or PTF1A [Fincher et al . , 2018] ) , and LIM homeobox 2 ( lhx2b ) , also modestly reduced goblet cells in pre-existing branches ( Figure 8—figure supplement 5A–C and Supplementary file 5 ) . mRNAs encoding these TFs are enriched in basal regions of the intestine ( Figure 6—figure supplement 1 ) . In addition , single-cell transcriptome data suggest PTF1A expression is elevated in differentiating neoblast progeny in the basal cell lineage ( Fincher et al . , 2018 ) , and PTF1A also reduces basal intestinal cell numbers ( Fincher et al . , 2018 ) . Thus , although our data support a role for gli-1 and RREB2 in goblet cells and/or their precursors , they also raise the possibility that basal cells ( and possibly phagocytes or muscle cells ) may non-autonomously influence goblet cell differentiation and/or survival . We asked whether goblet cell depletion affected planarian viability , behavior , or regeneration . Over a 6 week dsRNA feeding regimen , some uninjured gli-1 ( RNAi ) and RREB2 ( RNAi ) planarians refused food and failed to eat after 4–5 weeks ( Figure 8D ) . In both gli-1 ( RNAi ) and RREB2 ( RNAi ) animals , some animals eventually lysed , curled , or died ( Figure 8—figure supplement 6A ) , suggesting that goblet cells are required for viability . Additionally , we observed a modest ( but insignificant ) decrease in animal size ( Figure 8—figure supplement 6B–C ) in RREB2 ( RNAi ) planarians relative to controls . Interestingly , we only observed feeding failure and other phenotypes in animals fed the dsRNA/liver mix 1x/week ( every 7 days ) for 6 weeks; animals that were fed 2x/week ( every 3–4 days ) , but still six times , did not refuse to eat , lyse , curl , or die ( not shown ) . This suggests that goblet cells may regulate hunger ( or other aspects of digestive physiology ) primarily in starved animals , consistent with expression of prohormone convertase ( Figure 6—figure supplement 3C ) , above . Next , to assess regeneration , we amputated planarians fed 2x/week for eight feedings , in order to eliminate the influence of feeding failure on possible regeneration phenotypes . In both gli-1 ( RNAi ) and RREB2 ( RNAi ) regenerates , goblet cell depletion was robust ( Figure 8A–B ) , but neither gene was required more generally for regeneration ( with the infrequent exception of reduced posterior blastemas in gli-1 ( RNAi ) regenerates , mentioned above ) , as the brain ( Figure 8E ) , pharynx ( Figure 8E ) , other intestinal cell types ( Figure 8A–B ) , and new intestinal branches ( Figure 8A–B ) all regenerated without noticeable defects . Together , these results suggest that goblet cells are broadly dispensable for regeneration , and that their primary role may be to regulate appetite or other aspects of intestinal physiology that contribute to viability . Alternatively , it is possible that functions in other cell types may underlie the gli-1 and RREB2 feeding and viability phenotypes . In addition , some goblet cell functions may be required only when planarians are challenged by stresses like bacterial infection or extended starvation , possibilities that will require further investigation .
We have developed methods for applying laser-capture microdissection to planarian tissue , which we used to define gene expression and cell types in the intestine ( Figure 9A–C ) . The intestine expresses genes involved in metabolism , nutrient storage and transport , innate immunity , and other physiological roles , demonstrating considerable functional homology with digestive systems of other animals , including humans . Comparison of gene expression in microdissected tissue to that of intestinal phagocytes ( previously isolated by sorting ) enabled identification of transcripts enriched in two other cell types: goblet cells and basal cells . We also discovered previously unappreciated intestinal cell-type diversity , especially amongst goblet cells , which reside in distinct medial and lateral intestinal domains . Identification of medially and laterally enriched transcripts suggests an additional paradigm for addressing axial influences on organ regeneration , as well as evolution of patterning mechanisms influencing the regionalization of bilaterian digestive systems ( Martindale and Hejnol , 2009; Telford et al . , 2015 ) . Finally , we identified intestine-enriched transcription factors that play distinct roles in goblet cell differentiation and maintenance , and found that depletion of goblet cells reduces planarians' willingness to feed and viability , with only negligible effects on regeneration of other intestinal cell types or non-intestinal tissues . Characterization of the planarian intestinal transcriptome provides a framework for several next steps . First , a detailed description of intestinal cell types will facilitate further studies of digestive cell types . Here , we identified two transcription factors , gli-1 and RREB2 , whose RNAi phenotypes suggest that distinct mechanisms govern differentiation and maintenance of goblet cells . We are unaware of studies in other organisms that have uncovered direct roles for either gli-1 or RREB2 in goblet cells . However , in mice , modulation of Sonic Hedgehog ( an upstream activator of Gli-family TFs ) levels affects goblet cell numbers ( Gagné-Sansfaçon et al . , 2014; Liang et al . , 2012 ) , and RREB1 cooperatively regulates expression of the peptide hormone secretin in enteroendocrine cells ( Ray et al . , 2003 ) . By contrast , in the Drosophila midgut , Hedgehog ( Hh ) signaling promotes intestinal stem cell proliferation ( Tian et al . , 2015 ) , while the RREB-1 ortholog hindsight/pebbled suppresses midgut intestinal stem cell proliferation and is required for differentiation of absorptive enterocytes ( Baechler et al . , 2016 ) . In planarians , hedgehog ( Hh ) regulates anteroposterior polarity , neoblast proliferation , and neurogenesis ( Rink et al . , 2009; Yazawa et al . , 2009; Currie et al . , 2016; Wang et al . , 2016 ) ; our data suggest a possible additional role for Hh in intestinal morphogenesis . Similarly , although a second planarian RREB paralog , RREBP1 , is partially required for eye regeneration and may promote differentiation ( Mihaylova et al . , 2018 ) , implication of RREB2 in goblet cell maintenance/survival suggests that Ras-mediated signaling could also influence cellular composition in the intestine ( although direct links to Ras remain to be established ) . Thus , although characterization of the precise roles of gli-1 and RREB2 will be required , our results suggest broad similarity between planarians and other animals with respect to evolutionarily conserved signaling pathways that govern cell dynamics in the digestive tract . Furthermore , although we focused on goblet cells , previous studies suggest that several genes ( gata4/5/6-1 , hnf4 , egfr-1 , PTF1A ) expressed by cycling neoblast subpopulations ( Barberán et al . , 2016; Wagner et al . , 2011; van Wolfswinkel et al . , 2014; Zeng et al . , 2018 ) may be required for differentiation of multiple intestinal cell types ( Barberán et al . , 2016; Fincher et al . , 2018; Flores et al . , 2016; González-Sastre et al . , 2017 ) . Thus , enumeration of intestinal cell types and subtypes here , along with endoderm-specific progenitors in several recent single-cell analyses ( Fincher et al . , 2018; Zeng et al . , 2018; Plass et al . , 2018 ) , provides a rich list of candidate regulators for further elucidation of differentiation , maintenance , and functions of planarian digestive cells and their progenitors . Second , functional analysis of intestine-enriched transcripts will help to resolve the intestine’s role in regulation of the stem cell microenvironment . Knockdowns of the intestine-enriched TFs nkx2 . 2 or gata4/5/6-1 result in reduced proliferation and blastema production ( Forsthoefel et al . , 2011; Flores et al . , 2016 ) . In addition , a subset of tetraspanin group-specific gene-1 ( tgs-1 ) -positive neoblasts likely to be pluripotent neoblasts resides near intestinal branches ( Zeng et al . , 2018 ) , further hinting at a niche-like role for the intestine . Numerous intestine-enriched transcripts encode regulators of metabolite processing and transport , as well as putatively secreted proteins , suggesting multiple possible cell non-autonomous influences on neoblast dynamics . Because gut-enriched TFs like nkx2 . 2 and gata4/5/6-1 are also expressed by neoblasts and other cell types ( Fincher et al . , 2018 ) , LCM also provides an efficient approach for clarifying which candidate stem cell regulators are dependent on these or other TFs for their intestine-specific expression . Third , LCM provides a complementary method for assessing injury-induced gene expression changes in the intestine and other planarian tissues that may overcome the shortcomings of other available methods . Previously , we developed a method for purification of intestinal phagocytes from planarians that ingested magnetic beads ( Forsthoefel et al . , 2012; Forsthoefel et al . , 2014 ) . Laser microdissection may be preferable , because it enables detection of transcripts expressed by other intestinal cell types ( not just phagocytes ) , and also eliminates potentially confounding gene expression changes caused by feeding . Similarly , although single-cell sequencing ( SCS ) approaches in planarians have driven significant advances in our understanding of planarian cell types and their responses to injury ( Fincher et al . , 2018; van Wolfswinkel et al . , 2014; Zeng et al . , 2018; Plass et al . , 2018; Wurtzel et al . , 2015; Wurtzel et al . , 2017 ) , LCM may provide a more direct and efficient way to assess gene regulation in tissues with rarer cell types . For example , because intestinal cells comprise only 1–3% of total planarian cells ( Baguñá and Romero , 1981 ) , without prior enrichment SCS would potentially require analysis of tens of thousands of cells to reliably detect gene expression changes in the intestine . In addition , although chemistry and computational approaches for SCS are improving rapidly ( Wu et al . , 2017; Soneson and Robinson , 2018 ) , LCM may enable more sensitive detection of low-copy transcripts or subtle fold changes in bulk tissue , and also bypass ‘noise’ caused by dissociation or other SCS-related technical artefacts . Regeneration of digestive organs is not well understood . Development of a robust method for isolating intestinal tissue , and characterization of the intestinal transcriptome , will facilitate mechanistic studies in planarians . To facilitate exploration of the planarian intestinal transcriptome as a resource , we have developed a website , plangut . omrf . org . The methods and resources presented here will also support comparative analyses , complementing current and future efforts to understand digestive tract regeneration in platyhelminths , sea cucumbers , annelids , ascidians , amphibians , and mammals ( Goodchild , 1956; O'Steen , 1958; Takeo et al . , 2008; Kaneko et al . , 2010; Zattara and Bely , 2011; Okano et al . , 2015; Ortiz-Pineda et al . , 2009; Sun et al . , 2011; Zhang et al . , 2017; Ayyaz et al . , 2019 ) . In addition , studies in planarians and other regeneration models are likely to generate new insights into cellular processes ( e . g . proliferation , differentiation , metabolism , and stress responses ) whose dysregulation underlies human gastrointestinal pathologies associated with aging and disease .
Asexual Schmidtea mediterranea ( clonal line CIW4 , RRID:NCBITaxon:79327 ) ( Sánchez Alvarado et al . , 2002 ) were maintained in 0 . 5 g/L Instant Ocean salts with 0 . 0167 g/L sodium bicarbonate dissolved in Type I water ( Roberts-Galbraith and Newmark , 2013 ) , and fed with beef liver paste . For all experiments , planarians were starved seven days prior to fixation . For LCM , planarians were 6–9 mm in length . For WISH and FISH , planarians were 2–4 mm in length . All animals were randomly selected from large ( 300–500 animals ) pools , with the exception that animals with blastemas ( e . g . those that had recently fissioned ) were excluded . Planarians were relaxed in 0 . 66 M MgCl2 or treated with 7 . 5% N-acetyl-L-cysteine or 2% HCl ( ice-cold ) for 1 min to remove mucus as described ( Forsthoefel et al . , 2014 ) . Planarians were fixed in 4% formaldehyde/1X PBS , or methacarn ( 6 mL methanol , 3 mL chloroform , 1 mL glacial acetic acid ) for 10 min at room temperature as described ( Forsthoefel et al . , 2014 ) . Formaldehyde-fixed samples were washed three times ( 5 min each ) in 1X PBS . Methacarn-fixed samples were first rinsed three times in methanol , then rehydrated in 1:1 methanol:PBS for 5 min , followed by three washes ( 5 min each ) in PBS . For analysis of RNA integrity , 5–10 planarians were immediately homogenized in Trizol , and RNA was extracted using two chloroform extractions and high-salt precipitation buffer according to the manufacturer’s instructions . RNA samples were analyzed using Agilent RNA ScreenTape on an Agilent TapeStation 2200 according to the manufacturer’s protocol . For histology on methacarn-fixed samples , animals were relaxed and fixed individually in glass vials to minimize adherence to other samples . After fixation and rehydration , animals were incubated in 5% , 15% , and 30% sucrose ( in RNAse-free 1X PBS ) , for 5–10 min each . Samples were then mounted and frozen in OCT medium , and cryosectioned at 20 μm thickness onto either Superfrost Plus glass slides ( Fisher 12-550-15 ) ( for staining optimization ) or PEN membrane slides ( Fisher/Leica No . 11505158 ) ( for LCM ) . Prior to cryosectioning , PEN membrane slides were treated for 1 min with RNAseZAP ( Invitrogen AM9780 ) , then rinsed by dipping 10 times ( 1–2 s per dip ) in three successive conical tubes filled with 30 mL DEPC-treated water , followed by 10 dips in 95% ethanol and air-drying for 5–10 min . After cryosectioning , slides were stored on dry ice for 2–4 hr prior to staining . Cryostat stage and blades were wiped with 100% ethanol prior to sectioning . For histological staining , slides were warmed to room temp . for 5–10 min . All slides were stained individually in RNAse-free conical tubes by manually dipping ( 1–2 s per dip ) in 30 mL solutions . Forceps used for dipping were treated with RNAseZAP and ethanol . All ethanol solutions were made with 200 proof ethanol and DEPC-treated water . For Hematoxylin staining: 70% ethanol ( 20 dips ) ; DEPC-treated water ( 20 dips ) ; Mayer’s Hematoxylin ( Sigma Aldrich MHS16-500ML ) ( 15 dips ) ; DEPC-treated water ( 10 dips ) ; Scott’s Tap Water ( 2 g sodium bicarbonate plus 10 g anhydrous MgSO4 per liter of nuclease-free water ) ( 10 dips ) ; 70% ethanol ( 10 dips ) ; 95% ethanol ( 10 dips ) ; 95% ethanol ( 10 dips ) ; 100% ethanol . For Eosin Y staining: 70% ethanol ( 20 dips ) ; DEPC-treated water ( 20 dips ) ; 70% ethanol ( 20 dips ) ; Alcoholic Eosin Y ( Sigma Aldrich HT110116-500ML ) ( 100% , 10% , or 2% diluted into 200 proof ethanol ) ( 15 dips ) ; 95% ethanol ( 10 dips ) ; 95% ethanol ( 10 dips ) ; 100% ethanol . In some cases , fewer dips ( 8-10 ) in Eosin Y were required for better differentiation of gut tissue . For combined Hematoxylin and Eosin Y staining: 70% ethanol ( 20 dips ) ; DEPC-treated water ( 20 dips ) ; Mayer’s Hematoxylin ( 15 dips ) ; DEPC-treated water ( 10 dips ) ; Scott’s Tap Water ( 10 dips ) ; 70% ethanol ( 10 dips ) ; 10% Alcoholic Eosin Y ( 15 dips ) ; 95% ethanol ( 10 dips ) ; 95% ethanol ( 10 dips ) ; 100% ethanol . The entire staining protocol was completed in less than 5 min . Slides were air dried for 5 min , then stored in plastic slide boxes on dry ice for 2–4 hr before LCM . Although we tested overnight storage at −80°C , we found that section morphology and RNA quality were best when conducting all steps , from fixation to LCM , on the same day . Stained PEN slides were removed from dry ice and immediately immersed for 30 s in ice-cold 100% ethanol , then room temperature 100% ethanol to minimize condensation/rehydration of sections and maintain RNAse inactivation during warming . Slides were then air dried for 2–3 min , and mounted in a Leica LMD7 laser microdissection microscope . Samples were dissected at 10X magnification using the following parameters: Power-30; Aperture-20; Speed-5; Specimen Balance-1; Head Current-100%; Pulse Frequency-392 Hz . Regions were dissected into empty RNAse-free 0 . 5 mL microcentrifuge caps ( Axygen PCR-05-C ) . We separately captured medial intestine , lateral intestine , and non-intestine regions from all sections ( 8-10 ) per slide within 45–50 min . After capture , 20 μL Buffer XB ( Arcturus PicoPure RNA Isolation Kit 12204–1 ) was added to captured tissue , then tubes were immediately frozen on dry ice and stored at −80°C prior to RNA extraction . For RNA extraction , samples were thawed for 5 min at room temperature . Next , tissue from two tubes/slides ( 16–20 sections from the same planarian ) was pooled for each biological replicate , incubated at 42°C for 30 min , and RNA was extracted using the Arcturus PicoPure RNA Isolation Kit following the manufacturer’s instructions . 40–400 ng of total RNA was obtained from each sample , measured using a Denovix UV Spectrophotometer . RNA quality was analyzed using Agilent HS RNA ScreenTape on an Agilent TapeStation 2200 according to the manufacturer’s protocol . Concentration of RNA was ascertained using a Thermo Fisher Qubit fluorometer . RNA quality was verified using the Agilent Tapestation . Libraries were generated using the Lexogen Quantseq 3’ mRNA Library Prep Kit according to the manufacturer’s protocol , with 5 ng total RNA input for each sample . Briefly , first-strand cDNA was generated using 5’-tagged poly-T oligomer primers . Following RNase digestion , second strand cDNA was generated using 5’-tagged random primers . A subsequent PCR step with additional primers added the complete adapter sequence to the initial 5’ tags , added unique indices for demultiplexing of samples , and amplified the library . Final libraries for each sample were assayed on the Agilent Tapestation for appropriate size and quantity . Libraries were then pooled in equimolar amounts as ascertained by fluorometric analysis . Final pools were quantified using qPCR on a Roche LightCycler 480 instrument with Kapa Biosystems Illumina Library Quantification reagents . Sequencing was performed using custom primers on an Illumina Nextseq 500 instrument with High Output chemistry and 75 bp single-ended reads . Adapters and low quality reads were trimmed from fastq sequence files with BBDuk ( https://sourceforge . net/projects/bbmap/ , RRID:SCR_016969 ) using Lexogen data analysis recommendations ( https://www . lexogen . com/quantseq-data-analysis/ ) : k = 13 ktrim = r forcetrimleft = 11 useshortkmers = t mink = 5 qtrim = t trimq = 10 minlength = 20 . Sequence quality was assessed before and after trimming using FastQC ( RRID:SCR_014583 ) ( Andrews , 2010 ) . Reads were then mapped to a version of the de novo dd_Smed_v6 transcriptome ( Brandl et al . , 2016 ) restricted to 28 , 069 unique transcripts ( i . e . , those transcripts whose identifiers ended with the suffix ‘_1’ ) using Bowtie2 ( v2 . 3 . 1 ) ( Langmead and Salzberg , 2012 ) with default settings . Resulting SAM files were converted to BAM files , sorted , and indexed using Samtools ( v1 . 3 , RRID:SCR_002105 ) ( Li et al . , 2009 ) . Raw read counts per transcript were then generated for each BAM file using the ‘idxtats’ command in Samtools , and consolidated into a single Excel spreadsheet . The resulting read counts matrix was imported into R ( RRID:SCR_000432 ) , then analyzed in edgeR v3 . 8 . 6 ( RRID:SCR_012802 ) ( Robinson et al . , 2010 ) . First , all transcripts with counts per million ( CPM ) <1 in 4/12 samples ( e . g . lowly expressed transcripts ) were excluded from further analysis ( 13 , 136/28 , 069 transcripts were retained ) . Next , after recalculation of library size , samples were normalized using trimmed mean of M-values ( TMM ) method , followed by calculation of common , trended , and tagwise dispersions . Finally , differentially expressed transcripts in intestinal vs . non-intestinal samples were determined using the generalized linear model ( GLM ) likelihood ratio test . 1911 transcripts had a fold-change of more than 2 ( logFC >1 ) and an FDR-adjusted p value < 0 . 01 in either medial or lateral intestine , relative to non-intestinal tissue . We further limited to 1844 transcripts with a minimum transcripts-per-million ( TPM ) of 2 in 4 of any eight intestinal biological replicates ( medial or lateral ) , since transcripts with lower expression values were at the lower limit of detection by ISH , and their removal also modestly increased the robustness of LCM vs . phagocyte analysis . We queried ( TBLASTX , RRID:SCR_011823 ) 28 , 069 unique dd_Smed_v6 nucleotide sequences against 20 , 726 nucleotide sequences in the human reference proteome downloaded from UniProt ( www . uniprot . org ) ( Release 2017_12 , 20-Dec-2017 ) . 13 , 362 dd_Smed_v6 transcripts hit human sequences ( 7309 unique ) with E-value ≤1×10−3 . These human sequences were then used to conduct reciprocal TBLASTX queries against dd_Smed_v6 transcripts: 7220 hit 5808 unique dd_Smed_v6 sequences with E-value ≤1×10−3 . In total , 5583 dd_Smed_v6 transcripts had reciprocal best hits ( RBHs ) in the human proteome , with >94% having E-value ≤1×10−10 in either direction . Of 1844 intestine-enriched transcripts , 701 had RBHs in the human proteome . Next , using RBH UniProt Accession numbers , we extracted RNA-Seq tissue enrichment data from the Human Protein Atlas ( Uhlén et al . , 2015 ) . 699/701 intestinal transcripts’ RBH homologs were present in the HPA data; of these , 130 were enriched in one or more human tissues . 5 , 561/5 , 583 dd_Smed_v6 transcripts’ RBH homologs were present in the HPA data; of these , 1011 were enriched in one or more human tissues . The number of intestine and non-intestine RBH homologs enriched in each of 32 human tissues was calculated , and expressed as a percentage of total transcripts ( 699 intestine or 5561 non-intestine ) with RBH homologs . Finally , ratio of the percentage of intestine-enriched RBH homologs to the percentage of all dd_Smed_v6 RBH homologs was then calculated to determine fold-enrichment for each tissue . Two tissues ( ‘Appendix’ and ‘Smooth Muscle’ ) were excluded from final analysis since <0 . 1% ( 6/5561 ) of all dd_Smed_v6 transcripts had RBH homologs enriched in these tissues . TBLASTX queries were conducted using NCBI BLAST+ standalone suite . Extraction and analysis of tissue enrichment data from HPA was conducted in R and Excel . BLASTX ( RRID:SCR_001653 ) homology searches of UniProtKB protein sequences for H . sapiens , M . musculus , D . rerio , D . melanogaster , and C . elegans were conducted using all 28 , 069 unique transcripts in the ‘dd_Smed_v6’ transcriptome in PlanMine as queries . In all figures , gene names/abbreviations are based on the best ( lowest E-value ) UniProt homolog , except: ( 1 ) genes were named after the best human homolog for HPA analysis; and ( 2 ) we used Smed nomenclature when genes ( or paralogs ) were previously named by us or others , including hnf-4/dd_1694_0_1 ( 43 ) , nkx2 . 2/dd_2716_0_1 ( 34 ) , gata4/5/6/dd_4075_0_1 ( 43 ) , apob-1/dd_636_0_1 [DJF , unpublished] , apob-2/dd_194_0_1 [DJF , unpublished] , slc22a6/dd_1159_0_1 ( 75 ) , gli-1/dd_7470_0_1 ( 82 ) , and RREB2/dd_10103_0_1 ( 134 ) . Biological Process GO terms ( also obtained from UniProtKB ) from the top hit for each species ( with E-value ≤1×10−5 ) were assigned to each dd_Smed_v6 transcript . 9344 of 28 , 069 total transcripts and 1379 of 1844 intestine-enriched transcripts were annotated with GO terms . Enrichment for specific terms among all intestine-enriched transcripts , medially enriched transcripts , or laterally enriched transcripts was then evaluated with BiNGO ( RRID:SCR_005736 ) ( Maere et al . , 2005 ) . Regional transcript enrichment was calculated as a ratio of fold changes in medial and lateral intestinal tissue: transcripts were considered to be medially enriched if FCmedial/FClateral > 1 ( 1221 transcripts ) , or laterally enriched if FCmedial/FClateral < 1 ( 623 transcripts ) . All 13 , 136 ( of 28 , 069 ) transcripts detected in our experiment ( above ) were used as a background set , and hypergeometric testing with a Benjamini and Hochberg False Discovery Rate ( FDR ) of 0 . 05 was considered significant . We additionally restricted our summarization to terms that were annotated to more than one percent of transcripts that received annotations in each group: 1379/1844 intestine-enriched transcripts , 924/1221 medially enriched transcripts , or 455/623 laterally enriched transcripts . 1456 Dugesia japonica transcripts upregulated in response to either L . pneumophila or S . aureus infection ( Abnave et al . , 2014 ) were queried ( TBLASTX ) against 28 , 069 dd_Smed_v6_unique transcripts . 981 dd_smed_v6 transcripts hit with evalues < 1e-03 . After removing duplicate hits , 783 transcripts remained . 701/783 transcripts were present in the full 13 , 136 LCM dataset; 99/783 were intestine-enriched . 30 , 021 SMED_20140614 transcripts were mapped to 28 , 069 dd_smed_v6_unique transcripts , generating 22 , 889 dd_smed_v6_unique hits with evalues < 1e-03 . After removing duplicates , 19 , 338 transcripts remained . 741/19 , 338 transcripts were up- or down-regulated in planarians shifted to static culture ( Arnold et al . , 2016 ) . 447/741 transcripts were present in the full 13 , 136 LCM dataset , and 62 were intestine-enriched . 28 , 069 unique dd_Smed_v6 transcripts were blasted ( BLASTN ) against 11 , 589 ESTs and assembled contigs from the ‘SmedESTs3’ collection ( Zayas et al . , 2005 ) , which were used in microarray-based analysis of gene expression in sorted phagocytes ( Forsthoefel et al . , 2012 ) . 7927 hit with length >100 bp , >90% base identity , and E-value less than 1 × 10−50 . Of these , 6919 of 13 , 136 Smed_v6 transcripts detected in LCM samples mapped to unique Smed_ESTs3 contigs or ESTs with detectable expression in the sorted phagocyte data set . 2626/6919 transcripts had FDR-adjusted p values < 0 . 01 for logFC in either medial or lateral intestine ( vs . non-intestine , LCM data in this study ) , and 1498/2626 had FDR-adjusted p values < 0 . 05 for logFC in sorted phagocytes ( vs . all other cells ) ( phagocyte data in Forsthoefel et al . , 2012 ) . 1317/2626 had logFC >1 in either medial or lateral intestine . In the sorted phagocyte data , 900/1317 had a fold-change >0 and FDR-adjusted p value < 0 . 05 ( ‘high’ in phagocytes ) , 358/1317 had an FDR-adjusted p value > 0 . 05 ( ‘moderate’ in phagocytes ) , and 59/1317 had a fold-change <0 and FDR-adjusted p value < 0 . 05 ( ‘low’ in phagocytes ) . For Figure 5B , we identified 1067/1514 phagocyte-enriched transcripts with corresponding dd_Smed_v6 transcripts , including some with logFC 0 . 6–1 , as in the original study ( Forsthoefel et al . , 2012 ) . We utilized data from gene expression analysis of single planarian cells from two recent studies ( Fincher et al . , 2018; Plass et al . , 2018 ) to identify dd_Smed_v6 transcripts enriched in specific intestinal cell types that were also represented in our 1844 intestine-enriched transcripts ( this study ) and phagocyte expression data ( Forsthoefel et al . , 2012; Figure 2—figure supplement 1 ) . For comparison to Fincher et al . ( 2018 ) , we identified 391 phagocyte-enriched transcripts ( subcluster four or ‘enterocytes’ in Table S2 ( intestine ) ; Fincher et al . , 2018 ) , 21 goblet-enriched transcripts ( subcluster eight in Fincher et al . , 2018 ) , and 30 basal-enriched transcripts ( subcluster eight or ‘outer intestinal cells’ in Fincher et al . , 2018 ) ; transcripts found in other intestinal subclusters were excluded . For comparison to Plass et al . ( 2018 ) , we identified 92 phagocyte-enriched ( but not goblet-enriched ) transcripts and 27 goblet cell-enriched ( but not phagocyte-enriched ) transcripts that were also represented in our 1844 intestine-enriched transcripts and phagocyte expression data . For global comparison of transcripts enriched in laser captured intestine ( Figure 5 ) , we included all transcripts enriched in intestinal cell types ( and intestinal precursors ) in single cell studies ( Fincher et al . , 2018; Plass et al . , 2018; Swapna et al . , 2018 ) , without regard to cell type or enrichment in non-intestinal cell types . For comparison to Swapna et al . ( 2018 ) data , BLASTN was used to identify dd_Smed_v6 transcripts orthologous to ‘SmedASXL’ transcripts ( with >95% identity and length >100 bp ) . Total RNA was extracted from planarians using Trizol with two chloroform extractions and high salt precipitation . After DNAse digestion , cDNA was synthesized using the iScript Kit ( Bio-Rad 1708891 ) . Genes were amplified by PCR with Platinum Taq ( Invitrogen 10966026 ) using primers listed in Supplementary file 1 . Amplicons were cloned into pJC53 . 2 ( RRID:Addgene_26536 ) digested with Eam1105I as described ( Collins et al . , 2010 ) and sequenced to verify clone identity and orientation . For some genes , expressed sequence tags ( ESTs ) in pBluescript II SK ( + ) were utilized ( Zayas et al . , 2005 ) , also listed in Supplementary file 1 . In situ hybridizations were performed as described ( King and Newmark , 2013 ) , with the following adjustments: NAc ( 7 . 5% ) treatment was for 15 min; 4% formaldehyde fixation was for 15 min; and animals were bleached for 3 hr . Samples were pre-incubated with tyramide solution without H2O2 for 10 min , then spiked with H2O2 ( . 0003% final concentration ) , then developed for 10 min . Immmunofluorescence with mAb 6G10 after FISH was conducted as described ( Ross et al . , 2015 ) , using 1x PBS , 0 . 3% Trition-X100 , 0 . 6% IgG-free BSA , 0 . 45% fish gelatin as the blocking buffer ( Forsthoefel et al . , 2014 ) . Images are representative of two independent in situ hybridizations on 4–6 animals per experiment . S . mediterranea mucin-like genes in PlanMine ( Brandl et al . , 2016 ) and SmedGD2 . 0 ( 20 ) were identified by TBLASTN searches with human refseq_protein and UniProt mucin sequences . Planarian sequences were translated with NCBI ORFinder ( https://www . ncbi . nlm . nih . gov/orffinder/ , RRID:SCR_016643 ) , and domain searches were conducted using NCBI CD-Search ( https://www . ncbi . nlm . nih . gov/Structure/cdd/cdd . shtml ) ( Marchler-Bauer et al . , 2015 ) , Pfam 31 . 0 ( https://pfam . xfam . org , RRID:SCR_004726 ) ( Finn et al . , 2016 ) , and SMART ( http://smart . embl-heidelberg . de , RRID:SCR_005026 ) ( Letunic and Bork , 2018 ) . Three planarian sequences were identified that encoded three N-terminal von Willebrand factor D domains and two or more N-terminal cysteine-rich and trypsin-inhibitor-like cysteine-rich domains characteristic of human mucins ( e . g . MUC-2 , MUC-5AC ) ( Lang et al . , 2007; Lang et al . , 2016 ) , but not von Willebrand factor A or Thrombospondin type I repeats found in closely related proteins ( e . g . SCO-spondin ) . Planarian mucin-like genes identified using this approach are: Smed-muc-like-1 ( dd_Smed_v6_17988_0_1/SMED30009111 ) , Smed-muc-like-2 ( dd_Smed_v6_18786_0_1/SMED30002668 ) , and Smed-muc-like-3 ( dd_Smed_v6_21309_0_1/dd_Smed_v6_38233_0_1/dd_Smed_35076_0_1/SMED30006765 ) . Putative transcription factors were identified by extracting intestine-enriched transcripts with ‘DNA’ and/or ‘transcription’ Biological Process and Molecular Function GO terms , then verifying that the best Uniprot homologs regulated transcription in published experimental evidence . Smed-gli-1 has been previously studied ( Rink et al . , 2009 ) . Smed-RREB2 was most homologous to another planarian zinc finger protein , Smed-RREBP1 ( 134 ) . However , we used the more common ‘RREB’ abbreviation ( rather than ‘RREBP’ ) for the second planarian paralog . RNAi experiments were conducted as described ( Rouhana et al . , 2013 ) by mixing one microgram of in vitro-synthesized dsRNA with 1 μL of food coloring , 8 μL of water , and 40 μL of 2:1 liver:water homogenate . For the primary regeneration screen , 10 animals were fed three times over 6 days , amputated 4–5 days after the last feeding , then fixed 6 days post amputation . For further analysis of gli-1 ( RNAi ) and RREB2 ( RNAi ) phenotypes in uninjured animals , planarians were fed 1X/week for 6 weeks or 2X/week for 3 weeks ( six feedings total ) . gli-1 ( RNAi ) and RREB2 ( RNAi ) animals were scored as ‘non-eaters’ if they refused food on two successive days ( 7 and 8 days after the previous feeding ) , and were removed the experiment . Non-eating and/or curling animals were excluded from FISH analysis . For experiments in regenerates , animals were fed 2X/week for 4 weeks ( eight feedings total ) . egfp dsRNA ( Forsthoefel et al . , 2012 ) was used as the negative control in all experiments . Confocal images were collected on a Zeiss 710 Confocal microscope , with the following settings: two tracks were used , one with both 405/445 ( excitation/emission nm , blue ) and 565/650 ( red ) , and the other with only 501/540 ( green ) to minimize bleed-through between channels . Detector gains were adjusted so that no pixels were saturated . Digital offset was set to 0 or −1 , to ensure that most pixel intensities were non-zero , with averaging set to 2 . Whole animals were captured with a single z-plane ( 5 µm section ) with a 10x objective , tiled , and stitched in Zen ( version 11 . 0 . 3 . 190 , 2012-SP2 , RRID:SCR_013672 ) . Magnified regions were captured with a 63x Oil immersion objective and a z-stack ( 50–100 slices , 0 . 31 µm/slice ) was collected from the tail and/or head of the animal . In some cases , after imaging min/max or linear best fit adjustments were made in Zen to improve contrast of final images . Profile graphs represent raw , unadjusted pixel intensity values from a single optical section . WISH images were collected on a Zeiss Stemi 508 with an Axiocam 105 color camera , an Olympus SZX12 dissection microscope with an Axiocam MRc color camera , or a Zeiss Axio Zoom . V16 with an Axiocam 105 camera . In some cases , brightness and/or contrast were adjusted in photoshop to improve signal contrast . Animals were separated into 35 mm x 10 mm petri dishes in groups of two , and imaged on a Zeiss Stemi 508 prior to the first dsRNA feeding , then again seven days after the fifth feeding ( animals were fed once per week ) . For area , images were processed with ImageJ ( RRID:SCR_002285 ) ( Schneider et al . , 2012 ) by first applying an Auto Threshold , using method = Intermodes , Huang , or Triangles with ‘White objects on black background’ selected , to highlight the planarian . Analyze Particles was then run , with size = 600000–10000000 µm2 , and ‘Display results’ and ‘Include holes’ selected . For length , a straight line was drawn manually from the tip of the head to the tip of the tail and then Measure was used to obtain the length . Numerical data were analyzed and plots generated in GraphPad Prism v8 . 3 . 0 ( RRID:SCR_002798 ) . No vertebrate organisms were used in this study .
Proper function and repair of the digestive system are vital to most animals . Deciphering the mechanisms involved in these processes requires an atlas of gene expression and cell types . Here , we applied laser-capture microdissection ( LCM ) and RNA-seq to characterize the intestinal transcriptome of Schmidtea mediterranea , a planarian flatworm that can regenerate all organs , including the gut . We identified hundreds of genes with intestinal expression undetected by previous approaches . Systematic analyses revealed extensive conservation of digestive physiology and cell types with other animals , including humans . Furthermore , spatial LCM enabled us to uncover previously unappreciated regionalization of gene expression in the planarian intestine along the medio-lateral axis , especially among intestinal goblet cells . Finally , we identified two intestine-enriched transcription factors that specifically regulate regeneration ( hedgehog signaling effector gli-1 ) or maintenance ( RREB2 ) of goblet cells . Altogether , this work provides resources for further investigation of mechanisms involved in gastrointestinal function , repair and regeneration .
The human body has a limited ability to regenerate and repair itself after major injuries . By contrast , flatworms – most notably planarians such as Schmidtea mediterranea – have exceptional regenerative abilities and can regrow large parts of their bodies . Regrowing body parts is a complex process involving the coordinated creation of many different types of cells , and thus an important first step in understanding tissue regeneration is to develop a detailed catalog of cell types in that tissue . Laser capture microdissection , or LCM for short , is a technology used to isolate and study subregions or even individual cells from within a tissue . This approach can help to identify different cell types and to examine what makes them unique . LCM can be used to create a detailed catalog of cells , their differences and the roles they perform . Forsthoefel et al . have now used LCM to study cells from the planarian digestive system . This approach found 1 , 800 genes that have high activity in cells from the gut and showed many similarities between planaria and humans . LCM made it possible to study these cells in a new level of detail , revealing several hundred new genes as well as new cell types . The study showed that regeneration and survival of cells known as goblet cells particularly depended on two genes , gli-1 and RREB2 . Irreversible gut damage in humans can result from surgeries and conditions such as acid reflux . Other animals are able to repair and regenerate the gut more successfully . Techniques like LCM can help researchers to understand the differences between humans and other species . In time , these insights may lead to technologies and therapies that can improve our own abilities to heal following injuries .