Molecular Functional Diversity of Foliar Endophytic Fungi and Their Contributions to Seedling Survival in a Subtropical Forest.

We present a method for the global analysis of the function of genes in budding yeast based on hierarchical clustering of the quantitative sensitivity profiles of the 4756 strains with individual homozygous deletion of nonessential genes to a broad range of cytotoxic or cytostatic agents. This method is superior to other global methods of identifying the function of genes involved in the various DNA repair and damage checkpoint pathways as well as other interrogated functions. Analysis of the phenotypic profiles of the 51 diverse treatments places a total of 860 genes of unknown function in clusters with genes of known function. We demonstrate that this can not only identify the function of unknown genes but can also suggest the mechanism of action of the agents used. This method will be useful when used alone and in conjunction with other global approaches to identify gene function in yeast.

Foliar endophytic fungi (FEF) live within leaves without causing visible signs of disease. FEF occur in all vascular plants, yet the exact nature of interactions between specific FEF and their hosts is not well understood. Some FEF are associated with enhanced water use efficiency, nutrient acquisition, and defense. However, others may have negative effects under high-stress conditions. We examined a series of gas exchange traits in sweet birch (Betula lenta, Fagaceae) along an elevation gradient in the Pisgah National Forest Asheville, North Carolina, USA. From these leaves, we cultured surface-sterilized samples to examine FEF frequency and diversity. FEF cultures were categorized by morphotype and identified through analysis of internal transcribed spacer (ITS) sequences. FEF colonization frequency was 100% across all sites, and we identified 68 distinct morphotypes. Genetic identification of a subset of cultures suggests highly diverse FEF communities within this study system. Leaf gas exchange traits showed significant correlations with elevation at the site level, supporting the hypothesis that water stress increases with increasing elevation. However, further research is needed to determine associations between FEF communities and elevation. These findings, especially considering the limited sample size and small spatial scale of this study, indicate that the southern Appalachians are a promising region for future studies of FEF in forest systems.

Motivation and Objectives Biomedical professionals have at their disposal a huge amount of literature. But when they have a precise question, they often have to deal with too many documents to efficiently find the appropriate answers in a reasonable time. Faced to this literature overload, the need for automatic assistance has been largely pointed out, and PubMed is argued to be only the beginning on how scientists use the biomedical literature (Hunter and Cohen, 2006). Ontology-based search engines began to introduce semantics in search results. These systems still display documents, but the user visualizes clusters of PubMed results according to concepts which were extracted from the abstracts. GoPubMed (Doms and Schroeder, 2005) and EBIMed (Rebholz-Schuhmann et al, 2007) are popular examples of such ontology-based search engines in the biomedical domain. Question Answering (QA) systems are argued to be the next generation of semantic search engines (Wren, 2011). QA systems no more display documents but directly concepts which were extracted from the search results; these concepts are supposed to answer the user’s question formulated in natural language. EAGLi (Gobeill et al, 2009), our locally developed system, is an example of such QA search engines. Thus, both ontology-based and QA search engines, share the crucial task of efficiently extracting concepts from the result set, i.e. a set of documents. This task is sometimes called macro reading, in contrast with micro reading – or classification, categorization – which is a traditional Natural Language Processing task that aims at extracting concepts from a single document (Mitchell et al, 2009). This paper focuses on macro reading of MEDLINE abstracts. Several experiments have been reported to find the best way to extract ontology terms out of a single MEDLINE abstract, i.e. micro reading. In particular, (Trieschnigg et al, 2009) compared the performances of six classification systems for reproducing the manual Medical Subject Headings (MeSH) annotation of a MEDLINE abstract. The evaluated systems included two morphosyntactic classifiers (sometimes also called thesaurus-based), which aim at literally finding ontology terms in the abstract by alignment of words, and a machine learning (or supervised) classifier, which aims at inferring the annotation from a knowledge base containing already annotated abstracts. The authors concluded that the machine learning approach outperformed the morphosyntactic ones. But the macro reading task is fundamentally different, as we look for the best way to extract then combine ontology terms from a set of MEDLINE abstracts. The issue investigated in this paper is: to what extent the differences observed between two classifiers for a micro reading task are observed for a macro reading one? In particular, the redundancy hypothesis claims that the redundancy in large textual collections such as the Web or MEDLINE tends to smoothe performance differences across classifiers (Lin, 2007). To address this question, we compared a morphosyntactic and a machine learning classifiers for both tasks, focusing on the extraction of Gene Ontology (GO) terms, a controlled vocabulary for the characterization of proteins functions. The micro reading task consisted in extracting GO terms from a single MEDLINE abstract, as in the Trieschnigg et al’s work; the macro reading task consisted in extracting GO terms from a set of MEDLINE abstracts in order to answer to proteomics questions asked to the EAGLi QA system.

Many mitotic proteins are assembled into protein super complexes in three regions - midbody, centrosome and kinetochore (MCK) - with distinctive roles in modulating the mitosis process. However, more than 16% of the mitotic proteins are in multiple regions. Advance identification of mitotic proteins will be helpful to realize the molecular regulatory mechanisms of this organelle. Few ensemble-classifier methods can solve this problem but these methods often fuse various complementary features. In which, Gene ontology (GO) terms play an important role but the GO-term search space is massive and sparse. This motives this work to present an easily implemented method, namely mMck-GO, by identifying a small number of GO terms with support vector machine (SVM) andk-nearest neighbor (KNN) in predicting single-and multiple-region MCK proteins. The mMck-GO method using a simple grouping scheme based on a SVM classifier assembles the GO terms into several groups according to their numbers of annotated proteins in the training dataset, and then measures which top-grouped GO terms performs the best. A new MCK protein dataset containing 701 (611 single-and 90 multiple-region) is established in this work. None of the MCK proteins has a 25% pair-wise sequence identity with any other proteins in the same region. When performing on this dataset, we find that the GO term with the maximum annotation number annotates 49.2% of the training protein sequences; contrarily, 56.5% of the GO terms annotate single one protein sequence. This shows the sparse character of GO terms and the effectiveness of top-grouped GO terms in distinguishing MCK proteins. Accordingly, a small group of top 134 GO terms is identified and mMck-GO fuses the GO terms with amino acid composition (AAC) as input features to yield and independent-testing accuracies of 71.66% and 69.18%, respectively. Top 30 GO terms contain eight, eight, and 14 GO terms belonging to molecular function, biological process and cellular component branches, respectively. The 14 GO terms in cellular-component ontology in addition to centrosome and kinetochore are reverent to subcellular compartments, microtubule, membrane, and spindle, where GO:0005737 (cytoplasm) is ranked first. The eight GO terms enabling molecular functions comprise GO:0005515 (protein binding), GO:0000166 (nucleotide binding), and GO:0005524 (ATP binding). Most of the eight GO terms in biological-process ontology are reverent to cell cycle, cell division and mitosis but two GO terms, GO:0045449 and GO:0045449, are reverent to regulation of transcription and transport processes, which helps us to clarify the molecular regulatory mechanisms of this organelle. The top-grouped GO terms can be as an indispensable feature set when concerning other feature types to solve multiple-class problems in the investigation of biological functions.

Disentangling the effects of biotic neighbors and habitat heterogeneity on seedling survival in a deciduous broad-leaved forest

Seasonal and inter-annual variations in net ecosystem exchange of two old-growth forests in southern China

Disease heterogeneity presents a formidable challenge for clinical medicine. We are unlikely to develop successful, targeted treatments unless diagnostic schemes begin to reflect the biological complexity underlying superficially similar disease phenotypes. To address heterogeneity, there is an increasing recognition that realistic disease models need to be built on a foundation of quantitative molecular information.1 Such a “systems medicine” approach should ultimately allow classification into biologically more homogeneous groups, with similar prognosis and treatment response. Article see p 371 Oncology has been among the first specialties to embrace molecular profiling to improve clinical decision making. Today, a wealth of expression profiling information exists for tumors, and early efforts are being made to classify patients into likely treatment responders for specific chemotherapeutics.2 The investigation of complex multisystem pathologies, such as cardiovascular disease, has been slower to incorporate molecular profiling, in part, because of the involvement of multiple tissues, many of which are not readily accessible. Moreover, cardiovascular disease, unlike cancer, is not clonal in origin, making experimental analyses more challenging. It is clear, however, that broadly defined diseases such as the cardiomyopathies are the product of diverse genetic and environmental agents3; one can expect that quantitative molecular profiling will shed light on distinct, pathological activities underlying these conditions, thus allowing more meaningful classification schemes beyond those that are solely based on anatomic or hemodynamic considerations. The article by Barth et al4 in this issue of Circulation: Cardiovascular Genetics represents such a broadened search for molecular correlates of cardiovascular disease. The authors focus on the problem of heart failure with mechanical dyssynchrony (DHF) and its treatment by cardiac resynchronization therapy (CRT). Clinically, CRT has been a remarkable success, with significant gains in quality of life and mortality.5 Multiple studies have investigated the physiological consequences of dyssynchrony and …

As mycorrhizal fungi, endophytic fungi are ubiquitous in natural forest ecosystems. A great number of foliar endophytic fungi (FEFs) have been isolated from leaves of forest trees, and some metabolites are also isolated and characterized from the FEFs. These metabolites show strong potential to inhibit or kill insects and pathogenic fungi, especially those causing decline or damage of forest trees. In addition, FEFs can inhabit in leaf litter for a short or long period depending on endophytic species, thus they affect decomposition rate of leaf litter. Some FEFs can colonize in plant roots and promote plant growth. In the review, we provide an overview of the ecological roles of FEFs and hope the resources of FEFs can be developed and be used in forestry and agriculture to reduce use of insectcides and fungicides and in pharmacology to maintain human health.

In chromosome 11, 71 out of its 1254 proteins remain functionally uncharacterized on the basis of their existence evidence (uPE1s) following the latest version of neXtProt (release 2020-01-17). Because in vivo and in vitro experimental strategies are often time-consuming and labor-intensive, there is a need for a bioinformatics tool to predict the function annotation. Here, we used I-TASSER/COFACTOR provided on the neXtProt web site, which predicts gene ontology (GO) terms based on the 3D structure of the protein. I-TASSER/COFACTOR predicted 2413 GO terms with a benchmark dataset of the 22 proteins belonging to PE1 of chromosome 11. In this study, we developed a filtering algorithm in order to select specific GO terms using the GO map generated by I-TASSER/COFACTOR. As a result, 187 specific GO terms showed a higher average precision-recall score at the least cellular component term compared to 2413 predicted GO terms. Next, we applied 65 proteins belonging to uPE1s of chromosome 11, and then 409 out of 6684 GO terms survived, where 103 and 142 GO terms of molecular function and biological process, respectively, were included. Representatively, the cellular component GO terms of CCDC90B, C11orf52, and the SMAP were predicted and validated using the overexpression system into 293T cells and immunofluorescence staining. We will further study their biological and molecular functions toward the goal of the neXt-CP50 project as a part of C-HPP. We shared all results and programs in Github (https://github.com/heeyounh/I-TASSER-COFACTOR-filtering.git).

The dynamics of conspecific tree and seedling neighbors on seedling survival in a subtropical forest

Tuberculosis, caused by Mycobacterium tuberculosis, remains one of the leading causes of death worldwide despite extensive research, directly observed therapy using multidrug regimens, and the widespread use of a vaccine. The majority of patients harbor the bacterium in a state of metabolic dormancy. New drugs with novel modes of action are needed to target essential metabolic pathways in M. tuberculosis; ATP-competitive enzyme inhibitors are one such class. Previous screening efforts for ATP-competitive enzyme inhibitors identified several classes of lead compounds that demonstrated potent anti-mycobacterial efficacy as well as tolerable levels of toxicity in cell culture. In this report, a probe-based chemoproteomic approach was used to selectively profile the M. tuberculosis ATP-binding proteome in normally growing and hypoxic M. tuberculosis. From these studies, 122 ATP-binding proteins were identified in either metabolic state, and roughly 60% of these are reported to be essential for survival in vitro. These data are available through ProteomeXchange with identifier PXD000141. Protein families vital to the survival of the tubercle bacillus during hypoxia emerged from our studies. Specifically, along with members of the DosR regulon, several proteins involved in energy metabolism (Icl/Rv0468 and Mdh/Rv1240) and lipid biosynthesis (UmaA/Rv0469, DesA1/Rv0824c, and DesA2/Rv1094) were found to be differentially abundant in hypoxic versus normal growing cultures. These pathways represent a subset of proteins that may be relevant therapeutic targets for development of novel ATP-competitive antibiotics.

Molecular defense responses to natural enemies determine seedling survival in a subtropical forest

Regeneration and survival of tree seedlings and sprouts in tropical deciduous and sub-tropical forests of Meghalaya, India

Editor's evaluation: A CRISPR screen in intestinal epithelial cells identifies novel factors for polarity and apical transport

Article Figures and data Abstract Editor's evaluation Introduction Results Discussion Materials and methods Data availability References Decision letter Author response Article and author information Metrics Abstract Epithelial polarization and polarized cargo transport are highly coordinated and interdependent processes. In our search for novel regulators of epithelial polarization and protein secretion, we used a genome-wide CRISPR/Cas9 screen and combined it with an assay based on fluorescence-activated cell sorting (FACS) to measure the secretion of the apical brush-border hydrolase dipeptidyl peptidase 4 (DPP4). In this way, we performed the first CRISPR screen to date in human polarized epithelial cells. Using high-resolution microscopy, we detected polarization defects and mislocalization of DPP4 to late endosomes/lysosomes after knockout of TM9SF4, anoctamin 8, and ARHGAP33, confirming the identification of novel factors for epithelial polarization and apical cargo secretion. Thus, we provide a powerful tool suitable for studying polarization and cargo secretion in epithelial cells. In addition, we provide a dataset that serves as a resource for the study of novel mechanisms for epithelial polarization and polarized transport and facilitates the investigation of novel congenital diseases associated with these processes. Editor's evaluation In this work, Klee et al. carried out a genome-wide CRISPR/Cas9-based screen in human intestinal cell line CaCo2 to uncover factors regulating apical localization of a brush border enzyme. Their findings identified dozens of genes and characterized novel players in apical membrane transport including TM9SF4, anocatmin 8, and ARGAP33. This work provides a useful resource for the study of apical polarity and may aid in the understanding of digestive diseases. https://doi.org/10.7554/eLife.80135.sa0 Decision letter Reviews on Sciety eLife's review process Introduction Epithelia are highly specialized tissues that line inner and outer surfaces of various organs of metazoans, performing absorption, secretion, and barrier functions. During polarization, epithelial cells assume their characteristic shape by building specialized apical- and basolateral plasma membrane (PM) domains (Rodriguez-Boulan and Macara, 2014; Apodaca et al., 2012), which are separated by junctional complexes and characterized by a specific composition of lipids and proteins (Martin-Belmonte et al., 2007). The asymmetric distribution of polarity complexes and the mutual exclusion of proteins from one domain by proteins from the other domain are critical for the maintenance of apico- basolateral domains at the cell cortex (Rodriguez-Boulan and Macara, 2014; Román-Fernández and Bryant, 2016). Additionally, tightly orchestrated transport mechanisms and machineries, as Rab-GTPases, motor proteins, soluble NSF attachment receptor (SNARE)-proteins, and specific adapter proteins, ensure the establishment and maintenance of specialized membrane domains (Gaisano et al., 1996; Low et al., 1996; Weimbs et al., 1997; Li et al., 2002). Defects in polarization and polarized traffic often cause diseases, such as congenital diarrhea and enteropathies (Thiagarajah et al., 2018; Berni Canani et al., 2010; Apodaca et al., 2012). Microvillus inclusion disease (MVID) is an autosomal-recessive enteropathy (Cutz et al., 1989), characterized by intractable diarrhea in neonates (Cutz et al., 1989; Ruemmele et al., 2006). Enterocytes of MVID patients show loss of brush-border microvilli, formation of so-called microvillus inclusions and subapical accumulation of so-called 'secretory granules' (Cutz et al., 1989; Phillips et al., 2000). Our studies identified mutations in MYO5B, STX3, and STXBP2 to be causative for MVID (Müller et al., 2008; Ruemmele et al., 2010; Wiegerinck et al., 2014; Vogel et al., 2017b); they revealed that a molecular transport machinery involving myosin Vb (myo5b), the small Rab-GTPases Rab11a and Rab8a, the t-SNARE syntaxin3 (stx3), and the v-SNAREs slp4a and vamp7 is essential for apical cargo delivery (Vogel et al., 2015b; Vogel et al., 2017b). This cascade is required for the delivery of apical transmembrane transporters that are important for proper physiological function of enterocytes, such as sodium-hydrogen exchanger 3 (NHE3), glucose transporter 5 (GLUT5), and cystic fibrosis transmembrane conductance receptor (CFTR), but not for dipeptidyl-peptidase-4 (DPP4), sucrase-isomaltase (SI), and amino-peptidase-N (APN). This suggests the presence of additional trafficking routes and transport mechanisms for these apical cargos. Because the molecular signals for sorting and transport of apical cargo are thought to vary widely, several mechanisms have been proposed to underlie epithelial protein secretion (Levic and Bagnat, 2021). A common, characteristic feature of apical cargo is the presence of post-translational modifications, such as N- and O-linked glycosylations that are recognized by specific lectins, as well as GPI-anchors that allow sorting into cholesterol-rich lipid microdomains (Weisz and Rodriguez-Boulan, 2009; Zurzolo and Simons, 2016). Additionally, recent studies have proposed that protein oligomerization coincides with sorting into specialized membrane domains in the trans-Golgi network (TGN), which depends on the pH regulation of the TGN lumen (Levic and Bagnat, 2021; Levic et al., 2020). To uncover protein functions for a wide range of cellular processes, genome-wide clustered regularly interspaced short palindromic repeats (CRISPR)-mediated screens have advanced to a state-of-the-art strategy (Shalem et al., 2014; Shalem et al., 2015; Kampmann, 2018). In addition to their application to understanding the regulation of tumor biology, viral infection, or miRNA processing, CRISPR-mediated screening approaches have recently proven highly effective in discovering novel factors for intracellular protein trafficking and secretion (He et al., 2021; Zhu et al., 2021; Hutter et al., 2020; Stewart et al., 2017; Popa et al., 2020; Bassaganyas et al., 2019). Additionally, the CRISPR-Cas9 technology has been successfully used in Madin–Darby canine kidney (MDCK) cells with the generation of a collection of Rab-GTPase knockouts, which has provided great value for phenotypic analyses of Rab-KOs in epithelial cells (Homma et al., 2019). In this study, we employed the CRISPR-screening technology as an unbiased experimental strategy to uncover novel regulators of epithelial cell polarization and trafficking by investigating factors required for the apical delivery of DPP4. The brush-border hydrolase DPP4 is a type II transmembrane protein. It is heavily modified with N- and O-linked glycans in its extracellular domain (Misumi et al., 1992; Baricault et al., 1995; Fan et al., 1997), which have been suggested to be critical apical sorting determinants of DPP4 (Alfalah et al., 2002). Even though several studies have suggested diverse trafficking routes for DPP4, the mechanisms and protein machineries underlying these processes remain enigmatic so far (Casanova et al., 1991; Baricault et al., 1993; Low et al., 1992; Sobajima et al., 2014). Here, we conducted the first CRISPR screen in human intestinal epithelial cells to date. We present an experimental strategy for applying the CRISPR screening system in polarized epithelial cells to study novel protein functions. We have developed an easy-to-use and adaptable, FACS-based assay to measure the efficiency of protein secretion in polarized epithelial cells after genome editing. In combination with a detailed characterization of selected proteins by immunofluorescence and cryo-based electron microscopy, we have identified novel factors required for proper apico-basolateral polarization and secretion of apical cargo. Therefore, our dataset serves as a foundation for future studies aimed at deciphering novel mechanisms underlying epithelial polarization and polarized cargo transport. In addition, it provides a powerful resource for the investigation and validation of new congenital disease genes to be identified. Results Development of a genome-wide CRISPR screen to identify factors required for plasma membrane localization of the apical cargo DPP4 We established an unbiased CRISPR-Cas9-loss-of-function screen to define factors involved in surface targeting of the apical model cargo DPP4 in the enterocyte like colon carcinoma cell line, CaCo2 (Figure 1). DPP4 is a type 2 transmembrane protein that can be detected with antibodies binding to the extracellular C-terminus of the protein (Figure 1A). We made use of this feature to read out the efficiency of endogenous DPP4 surface delivery by fluorescence-activated cell sorting (FACS) in CaCo2 cells after epithelial polarization. Here, we used a period of 18–21 days, during which surface DPP4 signal is significantly increased in the course of cell surface expansion and specialized polarized trafficking processes (Figure 1B). In this context, we aimed to define factors required for apical membrane differentiation and cargo trafficking, thereby leading to a strong reduction of DPP4 after surface polarization. First, we generated Cas9-expressing CaCo2 cells and then transduced two biological replicates at a low multiplicity of infection (MOI) (0.2) using the human lentiviral GeCKOv2 CRISPR-library, selecting for successful viral integration with antibiotic treatment with puromycin. We then seeded the infected CaCo2 cultures at high density and allowed the confluent monolayers to further polarize and differentiate for 18 days. Next, polarized cells were detached, stained for endogenous DPP4, and subjected to FACS, separating those cells with only 10% of surface signal left, due to CRISPR targeting (Figure 1C and D). To determine the abundance of gRNAs in sorted versus unsorted cell populations, genomic DNA was isolated and read counts were determined by next-generation sequencing. Subsequent analysis using GenePattern and Galaxy analysis tools enabled the identification of 89 gRNAs significantly enriched in the sorted cell population (p<0.05) and represented genes whose downregulation had resulted in reduced DPP4 surface release (Figure 1D and E, Supplementary file 1A and B). Figure 1 with 1 supplement see all Download asset Open asset A CRISPR-mediated loss-of-function screen in polarized enterocytes. (A) Dipeptidylpeptidase 4 (DPP4) localizes to the apical brush-border of polarized enterocytes and can be detected with a specific antibody at its extracellular stalk domain. Top view (XZ) and lateral view (YZ) of a polarized CaCo2 monolayer. Scale = 5 µm. (B) During polarization, apical DPP4 is increased due to polarized traffic and surface expansion, which can be measured by flow cytometry (right panel, CaCo2 unpolarized versus polarized). HEK293T cells, not expressing DPP4, serve as quality control for staining specificity. (C) CaCo2-Cas9 cells are transduced with the lentiGuide-Puro library and selected with puromycin. After selection, CaCo2 cells are seeded to confluent monolayers and cultured for apico-basolateral polarization. Subsequently, cells are detached, stained, and subjected to fluorescence-activated cell sorting (FACS). Sorted and unsorted control cells are processed for gDNA extraction and genomically integrated CRISPR constructs are amplified by PCR. Finally, PCR products of sorted and unsorted cell populations are analyzed by next-generation sequencing and sgRNAs are ranked by their enrichment in the sorted vs. unsorted cell polpulation. (D) Sorting was performed for 10% of the cells, with lowest surface-signal intensity, thereby enriching for the cell population that had lost 90% of surface DPP4 signal, due to efficient CRISPR targeting. (E) 89 single-guide RNAs were significantly enriched in the sorted cell population. (F) Factors enriched in the sorted cell population could functionally be associated with secretory traffic, cytoskeletal architecture, or transcription, in a manual gene -ontology analysis. To exclude the possibility of aberrant effects caused by vacuolar apical compartment (VAC) formation in our screening workflow, we repeated the FACS screening assay with CaCo2 WT cells treated with colchicine (Gilbert and Rodriguez-Boulan, 1991). This treatment would induce VAC formation, but we found no change in apical DPP4 signaling (Figure 1—figure supplement 1A and B) and therefore concluded that VAC formation should not interfere with the FACS-based screening approach. A genome-wide CRISPR screen in polarized enterocytes identifies factors associated with secretory traffic Next, we wanted to get a comprehensive overview on the gene classes represented in our list of enriched gRNAs. However, automated KEGG pathway and gene enrichment analyses of our results were insufficient. Hence, we manually analyzed the 89 identified genes for common gene ontology (GO) terms and grouped them accordingly. We listed three GO terms from each category (biological process, molecular function, cellular compartment) for each hit, including the most common GO terms captured by the QuickGO -search database, focusing on including GO terms that indicate a role in the secretory pathway (Supplementary file 1C). Our analysis highlighted several genes, with functions related to the organization of the secretory pathway (Figure 1E and F, Figure 2A and B), including general organization and maintenance of organelles such as the endoplasmic reticulum (ER), the Golgi apparatus, or protein transport at early steps of the secretory pathway (e.g., KDELR2, RTN2, GOLGA8O). Further, identified hits were related to protein modification and transport at cis- and trans-Golgi compartments (GALNT2, SYS1), lipid-biosynthesis (MTMR2, PIP5K1C), and vesicle fusion and endocytic recycling (SNAP29, DSCR3). Two genes identified were associated with ER-plasma membrane (ER-PM) contact sites (TMEM110, ANO8). Furthermore, we found several factors required for various aspects of cytoskeletal organization such as actin-filament organization/polymerization (e.g., MARCKSL1, ARPC4-TTLL3), cell adhesion (e.g., ITGA5, FREM3, MPZ) but also microtubule organizing center (MTOC)/centriole- and cilium assembly and association (e.g., CCDC61, CCDC42B, C2CD3). Finally, we found numerous factors with functions related to DNA-templated transcription and cell differentiation (e.g., ETV7, NKX2-2, ERF), as well as mRNA processing/RNA splicing (e.g., SNRPE, SFSWAP), translation (e.g., RPL30, RPL2), and DNA repair/DNA replication (e.g., SFR1, ATAD5, REV1) (Figure 1E and F, Figure 2A). Figure 2 Download asset Open asset Gene ontology (GO) analysis of hits obtained in a CRISPR-mediated loss-of-function screen in polarized CaCo2 cells. (A) Schematic representation of significantly enriched genes obtained from a CRISPR screening approach, grouped and organized according to their associated GO terms. (B) GO association analysis of the seven factors that were chosen for CRISPR screen readout validation and further characterization. CC, cellular compartment; MF, molecular function; BP, biological process. Overall, in a CRISPR-mediated loss-of-function screen, we identified a variety of factors that affect surface transmission of an apical model cargo protein, DPP4, at different cellular levels. This underscores the value of our dataset and approach to identify novel factors for secretory membrane trafficking in polarized epithelial cells. Novel factors for surface localization of the apical cargo DPP4 After setting up a CRISPR-mediated screening platform in polarized CaCo2 cells, we validated our screening approach by further characterizing potentially novel factors for apical cargo traffic and membrane polarization. Since we had identified several genes with functions related to secretory trafficking (Figure 2A), we chose seven promising candidates for further analyses (Figure 2B). These factors function on various levels of the endomembrane system: the anoctamin family member anoctamin 8 (ANO8) and the stromal interaction molecule (STIM) enhancing tethering protein STIMATE (TMEM110) are involved in the formation and maintenance of ER-PM contact sites, and in turn, in apical PM-establishment in bile-canaliculi (Jha et al., 2019; Quintana et al., 2015; Chun Chung et al., 2020). The nonaspanin-family member TM9SF4 has been suggested to be required for transmembrane domain sorting in early steps of the secretory pathway but also in the generation of specialized membrane domains in the early cis-Golgi compartment (Perrin et al., 2015; Vernay et al., 2018; Yamaji et al., 2019). Polypeptide N-acetylgalactosaminyltransferase 2 (GALNT2) regulates O-linked glycosylation of transmembrane proteins in the Golgi and was chosen as a candidate for screen validation, with a potentially global effect on secretory traffic (Wandall et al., 1997; Moremen et al., 2012). Sorting nexin 26 (SNX26/ARHGAP33) was included since it has been described as a GTPase-activating protein for Cdc42, a major player in apical domain differentiation (Kim et al., 2013). Finally, we chose the lipid kinase subunit phosphatidylinositol 4-phosphate 5-kinase type-1 gamma (PIP5K1C) and the lipid phosphatase myotubularin-related protein 2 (MTMR2) for screen validation and further analysis since they are known regulators of apical phosphatidylinositolphosphate (PIP) pools (Xu et al., 2019; Román-Fernández et al., 2018). We generated knockout (KO) cell lines of those candidates using the CRISPR-technology and those gRNAs that had proven to efficiently target in our CRISPR screen (Figure 3A). We then analyzed KO cell lines for surface localization of DPP4 by flow cytometry using the previously described polarization assay from our CRISPR screen (Figure 3B). These measurements showed that targeting of the selected candidates indeed leads to reduced surface localization of DPP4, but to varying degrees (Figure 3C). The strongest effect on DPP4 surface localization was caused by interference with PIP5K1C (~75% reduction), followed by TM9SF4, TMEM110, and GALNT2 (~50% reduction). Interestingly, ANO8-, MTMR2-, and ARHGAP33-KOs showed the mildest phenotype (~30% reduction) (Figure 3B and C). Figure 3 Download asset Open asset Validation of selected candidates identified in a CRISPR-mediated loss-of-function screen. (A) Generation of clonal knockout (KO) cell lines of seven candidates chosen for primary CRISPR screen validation and further analysis. Any remaining protein levels in the KO clones after CRISPR targeting were determined by Western blotting compared with wild-type (WT) cells. Beta-actin was used as loading control. Molecular size markers are depicted in kDa. (B) The effect of the respective KOs on DPP4 surface transport, in KO cell lines. Cell lines were polarized for 18 days and then subjected to flow cytometry to determine the KO effect on DPP4 surface targeting. (C) Geometric means of DPP4-area (DPP4 intensity on the cellular surface) were determined of respective cell lines. All KO cell lines show varying extents of DPP4 surface reduction, with PIP5K1C-KO displaying the strongest and ANO8-KO the mildest effect. By growing KO cell lines of selected candidate genes and reanalyzing them for the effects of CRISPR targeting on PM localization of DPP4, we validated our primary CRISPR loss-of-function screen and thereby identified new players for surface localization of the apical cargo protein DPP4. For the subsequent analyses of epithelial phenotypes, we generated KO cell lines with a second set of gRNAs targeting the selected seven genes (Figure 1—figure supplement 1C) and included these cell lines in the analyses as indicated. 3D cyst models and high-resolution microscopy reveal novel factors for proper epithelial polarization Because apical transport and the correct establishment of epithelial polarity are closely linked, we investigated the relevance of the newly identified factors for polarization. Therefore, we performed 3D cyst assays using WT and the corresponding KO cell lines (Figure 4). Cysts were analyzed by immunofluorescence microscopy (IF) to determine the targeting of DPP4 to apical membrane domains. We found that all KO cell lines had severe defects in forming a single, central lumen, but rather established multiple or no lumina (Figure 4A and B). Although DPP4 was localized in the apical PM domains in all KO cell lines, TM9SF4-, MTMR2-, and ANO8-KO cell lines additionally displayed aberrant intracellular accumulation of DPP4 (Figure 4A and C). Figure 4 Download asset Open asset 3D cyst cultures demonstrate disrupted epithelial polarity. (A) 3D cyst assay were performed with WT and KO cultures. Immunofluorescence micrographs of 3D cysts generated from WT and KO cell lines. All knockdown cell lines form multiple lumina or no lumina. DPP4 localizes to actin-rich structures in al KO cell lines and additionally, to intracellular, actin-negative compartments in TM9SF4-, MTMR2- and ANO8-KO clones (white arrowheads). Scale = 10 µm. (B) Single central lumen formation was quantified. The percentage of cysts with a single central lumen is substantially decreased in the respective KO cells lines (dot box plot, Mann–Whitney U test. ***p< 0.005, n ≥ 100 cells per condition). (C) Delocalized DPP4 in cysts was quantified (dot box plot, Mann–Whitney U test. ***p<0.005, n.s., not significant). To characterize the involvement of the selected candidates in apico-basolateral polarization and apical transport in greater detail, we complemented fluorescence microscopy with cryo-based electron microscopy and investigated the ultrastructural phenotype and the distribution of selected in the respective cell lines. To this TM9SF4-, ANO8-, MTMR2-, and cell lines were on for 18–21 days to cell were then subjected to and for transmission electron microscopy or to for and In to CaCo2 WT cells, all KO cell lines had of (Figure Figure 1—figure supplement 1D and as brush-border and intracellular lumina microvillus (Figure or as inclusions with of (Figure Figure 1—figure supplement as by (Figure and associated with and (Figure In addition, numerous were found the basolateral (Figure Figure 1—figure supplement All these in Supplementary file 2 and Supplementary file the highly polarity of all KO cell lines Figure 5 Download asset Open asset micrographs with various of polarity defects in cultures of selected CaCo2 knockout (KO) cell lines. (A) intracellular lumen, by brush-border and a microvillus inclusion a PIP5K1C-KO (B) intracellular of associated with a late endocytic (C) basolateral of associated in polarized (D) in polarized ANO8-KO cell (E) with and associated cell in polarized cell late endocytic Scale = 1 µm. ultrastructural also involved late endocytic and organelles (Figure In WT CaCo2 cells, the different of and as well as in and (Figure and B) and previously for other cell lines (e.g., Vogel et al., et al., 2019; and 2021). However, in most KO lines, the late endomembrane system was characterized not by organelles addition to at the of (Figure and E, Figure arrowheads). These compartments had stained, with a (Figure and E, Figure or different of to ultrastructural we these compartments as of or et al., et al., et al., 2014). Their size and the different KO lines. in and they of up to 2 in (e.g., Figure in other KO cell lines only of In CaCo2 WT cells, we found this type of as but they had rather (Figure and Supplementary 2 and Figure Download asset Open asset of late endocytic and organelles in CaCo2 (WT) cells versus selected knockout (KO) cell lines of polarized cultures B) WT CaCo2 cells with and with varying vesicle and staining different of all with stained, membrane of organelles with stained, only other as of et al., 2016). (C) the type of late endocytic organelles in KO at (D) and in PIP5K1C KO cells. (E) the type of late organelles in TM9SF4 KO cells. (F) with in KO cells. with in KO cells. lateral Scale = the general of the and fluorescence microscopy revealed or severe in in all KO cell lines included distribution or of apical microvilli, with the of (Figure We then combined with immunofluorescence microscopy using antibodies the apical DPP4 and (Figure Figure first we detected DPP4 in most monolayers at the apical plasma However, detailed analysis of revealed that DPP4 was also to intracellular sites in TM9SF4-, MTMR2-, and ANO8-KO cell lines (Figure F, and to varying DPP4 was to subapical compartments in TM9SF4-, and ANO8-KO cell lines, and displayed DPP4 localization to basolateral of microvillus by with these was detected at the apical brush-border in all KO cell lines (Figure F, and This was by additional localization of in TM9SF4-, MTMR2-, and with MTMR2- and basolateral compartments (Figure and structures were in apical in and cells (Figure and We further analyzed the localization of the apical membrane proteins and sucrase-isomaltase (Figure 1 and Interestingly, we found to actin-rich intracellular compartments only in cells (Figure supplement However, the apical localization of of the selected genes (Figure supplement Figure Download asset Open asset electron microscopy surface on apical of polarized CaCo2 (WT) cells versus knockout (KO) cells. (A) CaCo2 WT cells with