Existing disparities in vaccination rates across different social and demographic groups in the US may have been exacerbated during the Coronavirus Disease 2019 (COVID) pandemic, leaving some children at risk for vaccine-preventable diseases. This study examined sociodemographic and risk factors of PCV13 infant primary series vaccination completion, before and during COVID. Retrospective data from the Optum’s de-identified Clinformatics Data Mart Database were used to create 3 cohorts: C1, Pre-COVID; C2, During COVID; C3, Cross-COVID . C1 and C3 (C1&3) were combined and compared with C2 for primary dosing completion before and during COVID according to infant/caregiver characteristics. Full completion (FC) was defined as receipt of 3 doses of PCV13 within 8 months of birth. Multivariable logistic regression was used to compare FC vs. partial completion or no vaccine. Descriptive analyses were used to compare FC before and during COVID within subgroups. Figure 1: Study population and inclusion criteriaA total of 132,183 and 16,522 infants with at least 8 months of follow up time were enrolled in C1&3 and C2, respectively. FC was significantly higher before COVID-19 . Adjusting for COVID, FC was significantly lower in infants who were Black, with co-morbidities or risk factors, living in households with >1 children or no children, household annual income < &99k, residing in a neighborhood with median education of high school or below, and whose primary caregiver was aged <25 years (Table 1). Comparing FC before and during COVID, the % decline relative to pre-COVID was > 2% among infants who were White, residing in the Mountain, New England or Pacific regions, in a household with 2 children, >&100k annual income, employer-based insurance or HMO, and median neighborhood education of bachelor degree plus (Table 2). Table 1. Multivariable binomial logistic regression results for PCV13 full primary dosing completion vs. not full completion , N=144,799*Table 2. Primary dosing full completion rate pre-COVID vs. during COVID by social, demographic, and clinical risk factorsHealth inequities in PCV13 primary series completion existed prior to COVID-19 and have remained during the pandemic. Our results, however, suggest that during the pandemic, groups traditionally considered to have better healthcare access  had more impact on vaccine uptake. Further research is needed to confirm these trends as COVID mitigation measures subside. Liping Huang, MD, MA, MS, Pfizer Inc (Employee) Jennifer L Nguyen, ScD, MPH, Pfizer Inc. (Employee) Johnna Perdrizet, MPH, Pfizer Inc (Employee) Tamuno Alfred, PhD, Pfizer Inc. (Employee) Adriano Arguedas, MD, Pfizer (Employee)


In this systematic review, we aim to highlight existing literature devoted to the study of an association between medical imaging radiomics and cancer biological endpoints. The use of radiomics as an ancillary tool in cancer treatment would allow for a non-invasive, inexpensive, three-dimensional characterization of the tumor phenotype, contributing to the delivery of precision medicine. Nonetheless, its clinical application remains a challenge, as extensive, multi-center validation studies of radiomic features connection with tumor biology are required. In this review, we performed a search in PubMed database for peer-reviewed studies which evaluate the association between radiomic features and the following set of clinically relevant tumor markers: anaplastic lymphoma kinase (ALK), v-raf murine sarcoma viral oncogene homolog B1 (BRAF), epidermal growth factor (EGFR), human epidermal growth factor receptor 2 (HER-2), isocitrate dehydrogenase (IDH), antigen Ki-67, kirsten rat sarcoma viral oncogene homolog (KRAS), programmed cell death ligand 1 (PD-L1), tumor protein p53 (TP-53) and vascular endothelial growth factor (VEGF).Radiomics supposes an alternative non-invasive tumor characterization tool, which has experienced increased interest with the advent of more powerful computers and more sophisticated machine learning algorithms. Nonetheless, the incorporation of radiomics in cancer clinical-decision support systems still necessitates a thorough analysis of its relationship with tumor biology. Herein, we present a systematic review focusing on the clinical evidence of radiomics as a surrogate method for tumor molecular profile characterization. An extensive literature review was conducted in PubMed, including papers on radiomics and a selected set of clinically relevant and commonly used tumor molecular markers. We summarized our findings based on different cancer entities, additionally evaluating the effect of different modalities for the prediction of biomarkers at each tumor site. Results suggest the existence of an association between the studied biomarkers and radiomics from different modalities and different tumor sites, even though a larger number of multi-center studies are required to further validate the reported outcomes. Cancer precision medicine involves therapy adaptation to improve clinical outcome based on patient-specific characteristics as well as the tumor-specific molecular profile. The advent of high-throughput gene-sequencing techniques in the last decade has allowed for the identification of multiple tumor molecular markers, also known as signature molecules, which correspond to genomic changes that affect gene and protein expression ,2. TheseOn the other hand, the fast-evolving field of radiomics has experienced an increased interest in the past decade, especially within cancer research, due to accumulating evidence of an association between quantitative medical imaging features and clinical and biological endpoints . The undThe purpose of this systematic review was to determine which radiomic features have been linked to tumor biology in peer-reviewed studies and, thus, could be potentially incorporated in cancer precision medicine. To this end, we chose to summarize current findings assessing the potential association of radiomics with ten classic proteins or genes which are relevant clinical prognostic markers, and which may be targeted by either small molecular inhibitors or antibodies. These are: anaplastic lymphoma kinase (ALK), v-raf murine sarcoma viral oncogene homolog B1 (BRAF), epidermal growth factor (EGFR), human epidermal growth factor receptor 2 (HER-2), isocitrate dehydrogenase (IDH), antigen Ki-67, kirsten rat sarcoma viral oncogene homolog (KRAS), programmed cell death ligand 1 (PD-L1), tumor protein p53 (TP-53) and vascular endothelial growth factor (VEGF).These factors, when mutated or over-expressed, play important roles in cancer progression and growth , angiogenesis (VEGF), cell cycle regulation and cell death (TP-53), the immune response (PD-L1), and metabolic regulation (IDH). At the same time, it is important to understand the proliferation kinetics (Ki-67 proliferation marker) of the respective cancer types as that can also influence the treatment response.EGFR, HER-2 and ALK are all receptor tyrosine kinases, located on the cell surface and activated through the binding of ligands, mostly growth factors. This leads to the activation of a whole range of downstream signaling cascades and results in cell survival, proliferation and migration ,6.KRAS and BRAF are the genes responsible for making the proteins K-ras and B-raf, which are, amongst others, involved in important signaling pathways  ,8. MutatVEGF is a signaling factor promoting the formation of new blood vessels. To grow and metastasize, solid cancers require blood supply, which they attain by expressing VEGF to form supporting vasculature .TP-53 is involved in the regulation and progression through the cell cycle; monitors genomic stability and can induce apoptosis. It is one of the most prominent tumor-suppressors .PD-L1 is involved in suppressing the adaptive arm of the immune system. By upregulating PD-L1 expression, cancer cells may evade the host immune system .IDH catalyzes the decarboxylation of isocitrate. Through this metabolic deregulation, cancer progression can be initiated or supported .Ki-67 is a protein that is present during all active phases of the cell cycle but absent in resting (quiescent) cells . TherefoThroughout this review, the term “biomarker” refers, for the sake of simplicity, to any of the above-mentioned biological endpoints. This is also in accordance with the World Health Organization (WHO), which defines biomarker as “any substance, structure, or process that can be measured in the body, or its products and influences or predicts the incidence of outcome or disease” .https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020207220 (accessed on 11 June 2021). No amendments were performed with respect to the published protocol.The analysis was conducted according to the PRISMA-P Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement . The proThe search was conducted in PubMed database. According to PRISMA guidelines, article selection was carried out via multiple steps. The literature search was performed using the query “Radiomics [All Fields] AND keyword [All Fields]”, where keyword corresponded to one of the ten molecular markers under study  and the possible variations in its naming . The full list of queries is provided in the For each independent search, all retrieved studies were collected, and duplicates were posteriorly removed using the open-source reference management software Zotero .During the first screening phase, those studies which did not fulfil the following requirements were excluded: (1) the article had to be written in English, (2) the study had to be a scientific article excluding reviews, (3) the topic had to be related to biomarkers in cancer. Following this step, every article was assigned to one of the following categories, depending on the cancer site: breast, central nervous system (CNS), gastrointestinal, liver, lung and others.The full-text articles were then assessed for eligibility. An article was excluded from the final analysis if at least one of the following criteria applied: (1) only one of the two groups, biomarker-negative or biomarker-positive, patients were included in the study, (2) the total number of patients was less than 40, (3) the association between the biomarker and radiomics features was not investigated, (4) the biomarker analyzed was not among the ten biomarkers defined in the search and (5) less than 20 image features were investigated.Those articles that satisfied the screening and eligibility criteria were included in the following analysis, with each tumor site corresponding to a dedicated subsection in this review. First, the distribution of the number of patients included within all the studies was evaluated. The frequency of investigation of a given biomarker for each tumor site was collected in a dedicated table, together with the total number of studies on each tumor site and on each biomarker.For each study, we gathered the following information when available: the studied biological endpoint and its alteration, e.g., mutation on a specific exon, over-expression, etc.; the imaging modality; the origin of the dataset; the training set size; the validation set size and type of validation, i.e., internal, temporally independent, external, leave-one-out-, 3-, 5- and 10-fold cross-validation  or bootstrap methods; the initial number of studied radiomic features; the application of feature reduction and feature robustness analysis methods; the reported performance, i.e., the area under the receiver-operating characteristic curve (AUC), classification accuracy or c-index; the public availability of the code and/or data; the reported quality score of the radiomics study, e.g., the transparent reporting of a multivariable prediction modelling for individual prognosis or diagnosis (TRIPOD) score  or RadioFurthermore, radiomic features of the best performing models on the training set were identified for each combination of tumor site, biomarker and image modality, in order to provide, when possible, a visual interpretation of the findings. For consistency, performance on the training set was evaluated since external validation was only performed on a small fraction of the studies. Moreover, in this comparison, the selection was limited to models based solely on radiomic features, i.e., mixed models including clinical-radiological data were excluded. This process was done independently by each of the authors in the systematic review. If the study provided a visual interpretation of such features, it was recorded. Otherwise, whenever possible, the missing interpretation was provided by the authors.In accordance with PRISMA guidelines, a strategy for bias risk minimization was adopted as follows: the processes of screening, eligibility evaluation and extraction of data for the meta-analysis were performed independently by authors ALG, DV, FT, RDB and VW. Each author analyzed one specific tumor site. The more experienced authors JEvT, ST-L, MG and MP supervised the process and guaranteed a uniform and unbiased analysis throughout the different tumor sites. A detailed description of this process can be found on the PRISMA checklist in the A diagram summarizing the study selection workflow following PRISMA guidelines is shown in The size of the dataset under study varied significantly among the reported papers (43–1010 patients). As above-mentioned, studies including less than 40 patients in total were excluded from the analysis during the screening phase. The mean number of patients included was 198. The distribution is shown in n = 125) is greater than the number of full-text papers included in the systematic review (n = 104). Similarly, those articles that investigated more than one tumor site were included in each of the corresponding subsections. The most frequently studied entity was lung cancer, followed by CNS tumors and breast cancer. The most frequently analyzed biomarker was EGFR, followed by Ki-67 and IDH. The association between EGFR and radiomics in lung cancer was the most frequently investigated (n = 26).The frequency of investigation of a given biomarker with respect to each tumor site is presented in n = 21) [n = 11) [n = 3) [n = 1) imaging [n = 35) [n = 20) [n = 9) [n = 24) [n = 5) [n = 5) [n = 2) [n = 1) [A total of thirty-six studies were found which associated CNS tumor molecular markers with clinical imaging radiomic features, using conventional magnetic resonance imaging (MRI) alone n =  [21,22,2n = 21) ,36,37,38[n = 11) ,47,48,49 [n = 3) ,51,52 or imaging . Glioma [n = 35) ,51,52,53 [n = 9) ,50,51,52 [n = 9) ,37,38,39 [n = 5) ,39,40,41 [n = 5) ,35,44,51 [n = 2) ,36 and Vn = 5) [n = 3) [n = 2) [n = 1) [A total of fifteen studies were found which investigated the power of MR radiomics to predict IDH genotype in glioma  ,29,30,38n = 5) ,25,26,27 [n = 3) ,29,30, d [n = 2) ,27, and  [n = 1) , another [n = 1)  and the  [n = 1) . Three o [n = 1) ,27,29.The best predictive performance was achieved by Li et al. on MR images of glioblastoma patients by means of a random forests (RF) model based on gray-level co-occurrence matrix (GLCM), grey-level run-length matrix (GLRLM) and grey-level size zone matrix (GLSZM) textural features together with patient age  . Among MA total of seven studies were found which combined MR radiomics with diffusion weighted imaging (DWI), perfusion weighted imaging (PWI) and/or diffusion kinetic imaging (DKI) features to predict IDH mutation status in glioma patients AUC = 0.747–0.931) ,47,48,49–0.931 ,4Two studies were found which used PET radiomics in conjunction with clinical-radiological parameters to predict IDH status in gliomas. One of them used fluoroethyl-tyrosine (FET)-PET standard parameter slope and one texture feature  , while tIn total, two studies were found which investigated the relationship between MR radiomics and EGFR alterations in glioma, more precisely, between EGFR over-expression in LGG patients and EGFR mutation in GBM patients ,36. The Three studies were found which employed MR radiomics together with DWI and PWI radiomics to predict EGFR mutation status in GBM patients. Binder et al. studied a variety of EGFR missense mutations and concluded that EGFR mutation at alanine 289 (EGFR-A289D/T/V) presented a unique radiographic phenotype. Authors reported significantly lower average T1 signal, higher relative cerebral blood volume and longer major axis in EGFR-A289D/T/V-mutant tumors among other features . The twoThree studies were found which investigated the association between Ki-67 expression and MR radiomics in CNS tumors: one in lower grade glioma  , one in Among the five studies, different cut-off thresholds were employed to distinguish between low- and high-expressing tumors, with two studies using 10% ,51, two Two studies evaluated the power of MR radiomics for TP-53 mutation status prediction in LGGs with a varying performance  ,36. One One study was found which investigated the use of conventional MR radiomics to predict VEGF expression in LGGs  .n = 9) [n = 2) [n = 1) [n = 1) [n = 1) [n = 1) [n = 13) [n = 10), and all studies showed some degree of linkage between HER-2 status and radiomic features (AUC = 0.65–0.95) [n = 1) (AUC = 0.88) [Sixteen studies which assessed the relationship between breast tumor molecular markers and radiomic features were identified. The imaging modalities studied were PWI (n = 9) ,60,61,62 [n = 2) ,64, DWI  [n = 1) , DWI+PWI [n = 1) , Digital [n = 1) , PET/CT  [n = 1)  and stan [n = 1) . Most st[n = 13) ,66,67,69[n = 13) . HER-2 w65–0.95) ,69. Eigh65–0.95) . One stu = 0.88) . Thirteen = 7) [n = 1) [n = 1) [n = 1) [Ten studies focused on HER-2 status prediction based on radiomic features derived from PWI (n = 7) ,60,61,62 [n = 1) , PET/CT  [n = 1) , and con [n = 1) . The termean) and total lesion glycolysis (TLG) were independently associated with HER-2 status  [Among PWI radiomics analysis, the highest predictive performance was achieved by Fan et al. by means of a logistic regression model based on 15 features from dynamic contrast enhanced MRI (DCE-MRI) images  . Conventctively) . DMG radctively) . AuthorsThree studies investigated the relationship between Ki-67 expression levels and PWI radiomics (AUC = 0.74–0.81) ,57,62, wThe study using PET/CT could not find any radiomic features that were significantly associated with Ki-67 expression level . AnotherAmong the eight studies exploring an association of Ki-67 expression levels with breast cancer radiomics, four studies employed a cut-off threshold of 14% ,63,65,67The strongest association for breast cancer was found in PWI radiomics of 88 patients in which 13 radiomic features predicted TP-53 alterations with an AUC of 0.886 (95% CI: 0.817–0.955) after cross-validation [n = 22) [n = 8) [n = 2) [n = 1) [n = 15), whereas the other half used a mix of histologies. Research has predominantly focused on EGFR (n = 26) [n = 5) [n = 3) [n = 3) [n = 2) [n = 1) [In total, 33 studies investigating radiomics and biological endpoints for lung lesions were identified. The imaging modalities employed were CT (n = 22) ,89,90,91 [n = 8) ,97,98,99 [n = 2) ,101 and  [n = 1) . One stu(n = 26) ,101,102, [n = 5) ,101,102, [n = 3) ,98,102,  [n = 3) ,89,99, K [n = 1) . All stu [n = 1) . A summaThe power of CT radiomics to predict EGFR mutations status strongly varied among the studies using validation (AUC = 0.69–0.851) ,84,85,86CT radiomics was weakly predictive for KRAS mutation status in 763 lung adenocarcinoma patients from four institutions  . AuthorsFor ALK mutation status, CT radiomics showed an AUC of 0.80 on a temporally independent validation cohort . SelectePD-L1 expression levels were observed to associate with CT radiomic features in two studies  ,91.The association between CT radiomic features and TP-53 mutation was studied in . Authorsn = 6) [n = 2) [n = 2) [n = 1) [n = 2) [n = 3) [n = 2) [n = 3) [n = 7) [n = 2) [n = 3) [n = 2) [n = 1) together with KRAS and NRAS as one mutation signature [A total of ten studies addressing the relationship of radiomics and biological tissue markers in gastrointestinal cancers were identified. The imaging modalities used were CT (n = 6) ,106,107, [n = 2) ,109, MRI [n = 2) ,111 and  [n = 1) . The tum [n = 2) ,104, rec [n = 3) ,111,112, [n = 2) ,108, col [n = 7) ,111,112  [n = 3) ,112 and  [n = 2) ,112. OneThe association of KRAS mutations with radiomic signatures was the most frequently assessed in gastrointestinal cancer. The strongest relationship was found in CE CT of CRC patients, where the mutation signature KRAS/BRAF/NRAS was significantly associated with three GLCM features , achieving a final AUC of 0.829 on an internal validation cohort .max) of the metabolic tumor volume (MTV) as well as for the GLCM-derived contrast .One group focused on the association of KRAS mutation to FDG-PET radiomics of pancreatic ductal adenocarcinoma patients , concludAnother study evaluated the association between KRAS mutation and CT imaging features, including hand-crafted and deep learning radiomics, of CRC patients . The comTwo studies evaluated the association between T2w MR radiomics and KRAS mutational status in rectal cancer. In the first one, authors reported a final AUC of 0.884 on the training cohort by means of a decision tree based on three textural features . In the One group found that an increased value of short-run low gray-level emphasis derived from the GLRLM in FDG-PET/CT was predictive for TP-53 mutation in CRC patients . Authors also reported higher heterogeneity and lower PET signal values in TP-53-mutant cases . On the The association of HER-2 status and CT radiomics in gastric cancer patients was investigated in . AuthorsThree studies investigated the potential association of Ki-67 index and radiomic signatures ,105,112.As explained in the KRAS biomarker subsection, one study investigated the relation between CE CT radiomics and the mutation signature KRAS/NRAS/BRAF together, which reported a final AUC of 0.829 on a temporally independent cohort .n = 2) or US (n = 2). The most common tumor type was hepatocellular carcinoma  [n = 1) [n = 3), PD-L1 (n = 2) and VEGF (n = 1) and all were shown to be significantly correlated to radiomics (AUC = 0.85–0.97). All studies employed a dataset limited to a single center; one study separated the dataset into a training and a validation cohort [Four studies were found which associated radiomics and tissue biomarkers in liver cancer patients, using either MR with contrast agents  ,114,115  [n = 1) . Three tn cohort . None ofThe best predictive performance overall for liver studies was obtained for PD-L1 in US images of HCC patients  . The expThe best AUC for Ki-67 expression prediction in HCC was obtained in  by meansThe relationship between VEGF expression and US radiomic features was analyzed only in CCA patients . Waveletn = 1) [n = 1) [n = 2) [n = 1) [In total, five studies were found which investigated the correlation between radiomics and molecular markers in other entities not included in the sections above: melanoma (n = 1) , thyroid [n = 1) , head an [n = 2) ,120, adr [n = 1) . All stuOne study explored the use of FDG-PET/CT radiomics to predict BRAFv600 mutation status in melanoma patients achieving a final AUC of 0.62 after 10-CV . AnotherIn Oftentimes, dysregulation of one specific biomarker led to similar tumor phenotype across entities and imaging modalities. This was the case for EGFR-mutant tumors, which exhibited greater textural heterogeneity in CNS MRI, PWI and DWI, as well as in lung CT and PET. Similarly, alteration of TP-53 status was associated with increased heterogeneity in CT of HN and PET of colorectal cancer. IDH-mutant tumors were reported to have greater textural homogeneity in MRI, DWI, PWI, DKI and FDG-PET in CNS. High Ki-67-expressing tumors were reported to be more homogenous in CT for lung cancer but more heterogeneous for gynecological tumors and head and neck tumors. KRAS+ was shown to be more homogeneous for CT in lung, but more heterogeneous for gastrointestinal cancer.An overview of the analyzed studies per biomarker can be found in In recent decades, extensive genomic studies have leveraged our understanding of cancer biology and pathophysiology. The identification of key genetic alterations that drive oncogenesis and their subsequent molecular markers has led to a more accurate and comprehensive patient-specific treatment planning and adaptation . Further, RNAs, proteins such as prostate-specific antigen (PSA) or circulating tumor DNA (ct-DNA) [For this purpose, we limited our search to ten cancer biological endpoints commonly investigated and used in clinical practice, which apply to a broad range of cancer types. Other, even though valid, biomarkers, such as methylation status or indicators for virus-born cancers were deliberately excluded as their origin and/or mechanism leading to malignant transformation of healthy cells is not trivially comparable. Other examples of biomarkers excluded in this review are the loss of tumor suppressors in cancer such as breast cancer genes 1 and 2 Most of the studies included in this review reported some association between the selected biomarkers and radiomics, suggesting that mutated and non-mutated tumors have different growth patterns that are identifiable in high-throughput imaging. The association of textural, intensity, shape, size and wavelet image features with tumor biomarkers entails an advance in feature interpretability, as shown in In total, 96 out of 104 studies found a significant relationship between at least one of the studied biomarkers and one or more radiomic features. However, only 7 studies validated their models on external cohorts, 11 studies on temporally independent cohorts and 14 studies did not use any form of validation. Additionally, only 7 out of 104 included a prospectively collected dataset, which is necessary to confirm the clinical validity and usefulness of any radiomics signature. Along these lines, we believe greater effort should be made to employ larger, multi-institutional cohorts, either by means of new data-sharing agreements among research groups or through distributed learning. The feasibility of the latter has already been shown in a number of studies and entails new possibilities for training reliable radiomics models ,123. FurAnother factor that hindered results interpretation and studies comparison was the great variability in biomarker expression levels employed as cut-offs to stratify patients. Currently, there exist a lack of standardization of immunohistochemistry techniques for biomarker staining and scoring systems, leading to moderate intra/inter-laboratory and intra/inter-observer variabilities ,128. ThiIn an attempt to standardize the clinical utility evaluation of radiomics studies, as well as to increase transparency and minimize risk of bias, two rigorous reporting guidelines, the TRIPOD  and the In summary, radiomics from different modalities and cancer entities is a promising tool for tumor biology assessment. Nevertheless, a large majority of studies included in this review only employed internal validation datasets or bootstrap and cross-validation techniques to assess model performance. Thus, further multi-center, prospective studies are required to validate the reported outcomes. Moreover, none of the studies followed any reporting or quality assurance protocols. Hence, we would like to encourage the employment of reporting guidelines such as TRIPOD and RQS scores, as well as the use of IBSI-standardized radiomics software. As a closing remark, we would like to emphasize the utmost importance of transparency to ensure the reproducibility of radiomics studies.


Sargassum macrocarpum (MES) on dextran sulfate sodium (DSS)-induced colitis in mice and explore the possible mechanisms. Mice were given 4% DSS in drinking water for 7 days to induce colitis, followed by 3 days of regular water. MES (12 mg/kg body weight) or celecoxib (10 mg/kg body weight) was administrated orally to mice on a daily basis during these 10 days. Both MES and celecoxib supplementations significantly attenuated DSS-induced weight loss, shortening of colon length, elevated myeloperoxidase activity as well as histomorphological changes of colon. MES and celecoxib reduced the inflammation level of colon tissue, as indicated by its suppression on a panel of pro-inflammatory cytokines, including interleukin (IL)-1β, IL-17, tumor necrosis factor α, and interferon γ, and a group of inflammatory proteins, including intracellular adhesion molecule 1, vascular adhesion molecule 1, matrix metalloproteinase (MMP)-2, MMP-9, MMP-13, and inducible nitric oxidase. In addition, their administration down-regulated pro-inflammatory cytokines in serum. Moreover, the supplementation of MES suppressed the DSS-induced hyperactivation of Akt, JNK, and NF-κB signaling pathways. Taken together, our results demonstrate that MES ameliorates DSS-induced colitis in mice, suggesting that MES may have therapeutic implications for the treatment of colitis.Colitis is a colon mucosal disorder characterized by intestinal damage and inflammation. This current study aimed to evaluate the effect of meroterpenoid-rich ethanoic extract of a brown algae,  Inflammatory bowel disease (IBD), which includes Crohn’s disease (CD) and ulcerative colitis (UC), is a chronic and recurrent gastrointestinal disorder characterized by recruitment and undesired retention of immune cells in inflamed digestive track. Symptoms include weight loss, fever, diarrhea and bloody stools ,2. IBD aThe progress of IBD involve a variety of inflammatory-related proteins. For instance, activation of immune cells elevates the release of pro-inflammatory cytokines and chemokines, such as TNF-α, interleukin-1β (IL-1β), and IL-6, that drive the inflammatory process which leads to tissue damage . AdhesioLaminaria japonica [Lithothamnion corallioides [Fucus vesiculosus [Sargassum macrocarpum, a brown alga, is a rich source of anti-inflammatory compounds [S. macrocarpum (MES) using macrophages, human umbilical vein endothelial cells, and collagen-induced rheumatoid arthritis mice [Seaweed has been utilized as food, medicines, fertilizer, and animal feed for centuries . Seaweedjaponica , a minerllioides , and fuciculosus . Sargassompounds ,20,21,22tis mice ,24. It atis mice . These ttis mice .Dextran sulfate sodium(DSS)-induced colitis is a widely used animal model of colonic inflammation that resemble several features of UC. Therefore, in this study, we investigated the effects of MES supplementation on intestine condition, inflammatory cytokines, inflammation regulation pathways, using DSS-treated mice.Primary and secondary antibodies were obtained from Santa Cruz Biotechnology  and Abcam . Enhanced chemiluminescence (ECL) detection kit was purchase from GE Healthcare Bio-Sciences . Enzyme-linked immunosorbent assay (ELISA) kits and Proteome profiler array kit (Mouse XL Cytokine Array Kit) were obtained from R&D System . Dextran sulfate sodium  was obtained from MP Biomedicals Inc. .S. macrocarpum was harvested along the coast of Busan, South Korea, in May 2015. The specimen was identified by an algal taxonomist (C.G. Choi), at the Department of Ecological Engineering, Pukyong National University, South Korea. Voucher specimen was deposited in Dr. Choi’s laboratory (CCG51814). The fresh material of S. macrocarpum was air dried and stored in a deep-freezer until subsequent extraction. The extract preparation and active component analysis have been described previously [v/v) ethyl alcohol (5 L each) for 3 h each at 70 °C. The ethanol extract was filtered through an ultrafiltration system  and evaporated ethanol with vacuum evaporator  until the lipid compound was separated from the water fraction. The separated lipophilic fraction was washed with distilled water twice and concentrated by a vacuum evaporator at 45 °C until water content was less than 5% (w/w). The combined extracts were concentrated and lyophilized by a vacuum evaporator at 45 °C to obtain the MES (80 g). The isolated compounds from MES were identified as sargahydroquinoic acid (SHQA) (37.6%), sargachromeol (SCM) (6.23%), and sargaquinoic acid (SQA) (1.89%), according to our previous study [eviously . In brieus study .n = 8 per group) were randomly assigned to four groups: (1) control, (2) DSS, (3) DSS + MES (12 mg/kg body weight), and (4) DSS + celecoxib (10 mg/kg body weight) (w/v) DSS. The mice received either regular drinking water (control group) or 4% DSS drinking water (the other three groups) for 7 days and thereafter all mice were provided with regular drinking water for 3 days. Celecoxib, a cyclooxygenase-2 (COX-2) selective inhibitor, significantly ameliorated colitis in various animal models, and therefore was used as a positive control [All mouse studies were accomplished with the guidelines of the Korean National Institute of Health Guide for the Care and Use of Laboratory Animals, and were approved by the Animal Ethics Committee of Pukyong National University. Six week-old BALB/c male mice were purchased from Central Lab Animal Inc. . After one week of acclimation, mice ( weight) . Colitis control ,29,30,31 control . The difThe human equivalent dose (HED) is determined by the following equation: HED (mg/kg) = Animal dose (mg/kg) × Km ratio . Km ratiThe mice were checked daily for colitis based on their body weight, stool consistency, and gross rectal bleeding. The disease activity index (DAI) score was determined by combining scores of body weight, stool consistency, and gross rectal bleeding, as previously described . Each scOne-third of each colon was fixed with 4% paraformaldehyde. After dehydration and paraffin-embedding, colons were cut into 7 μm sections and stained with hematoxylin and eosin. The images of stained colon tissues were taken with a Moticam photomicroscope . Histological score was evaluated as described earlier ,36. The 2O2 for 10 min to inhibit endogenous peroxidase. The sections were then rinsed with PBS, and blocked with 1% bovine serum albumin for 30 min at room temperature. Then, sections were incubated with the inducible nitric oxide synthase (iNOS) antibody  at 4 °C overnight. After washing three times in PBS for 5 min each time, sections were incubated with secondary antibody (1:100) for 1 h at room temperature. The sections were stained by DAB chromogen kit and counterstained with hematoxylin.Paraffin-embedded colon tissues were sectioned to 5 μm, then the sections were deparaffinized with xylene and rehydrated with ethanol. The sections were incubated in PBS containing 3% Hg for 2 min at 4 °C. Fifty microliters of the supernatant were added to a black 96-well microplate with clear bottom and 50 μL of MPO reaction mixture was added. Fluorescence intensity was measured on a microplate reader at Ex/Em = 485/525 nm. All experiments were performed in triplicate. MPO activity was indicated as units/mg of protein.MPO activity was determined according to the manufacturer’s instructions for MPO activity assay kit . Briefly, colon samples (20 mg) were thawed and homogenized with cold assay buffer and then centrifuged at 20,000× The levels of cytokines and chemokines in serum were determined using a Mouse XL Cytokine Array Kit  following the manufacturer’s instructions. Briefly, membranes were blocked with blocking buffer for 1 h, serum samples were subsequently added and incubated overnight at 4 °C. Membranes were then incubated at room temperature for 1 h after mixing with a detection antibody cocktail. After washing, membranes were incubated for 30 min with streptavidin-horseradish peroxidase conjugate working solution. After washing, membranes were incubated for 1 min using a Chemi Reagent Mix, then exposed to an X-ray film for 5 min. Quantitative analysis of cytokine or chemokine spots were performed using a CS analyzer ver. 3.00 software .Colon tissues were homogenized with RIPA buffer containing a protease inhibitor and phosphatase inhibitor cocktail on ice. The procedure for Western blot has been described before . The prop < 0.05 were considered statistically significant. All analyses were performed using SPSS for Windows, version 10.07 .Data were expressed as means ± standard deviations (SDs) of at least three independent experiments unless otherwise indicated. Data were analyzed using one-way analysis of variance (ANOVA), flowed by Tukey’s post hoc analysis. Differences with a value of The protective effect of MES against colitis was evaluated by body weight, DAI, and colon length. As shown in DSS-treated mice exhibited pronounced histological changes, such as disruption of the epithelial barrier, destruction of cryptal glands structure, and infiltration of inflammatory cells a. MES anTo examine the infiltration of inflammatory cells into the colon, MPO activity of colon tissue was also measured. As shown in DSS markedly elevated the level of pro-inflammatory cytokines such as TNF-α, IL-1β, IL-17, and IFN-γ in colon . MeanwhiThe overexpression of inflammatory-related proteins, MMP-2, MMP-9 and MMP-13 has been reported to be involved in colon damage during colitis . DSS expAdhesion molecules, such as ICAM-1 and VCAM-1, suppress the circulation of lymphocytes and propagate the inflammatory process by stimulating their migration into inflamed bowel tissue. DSS induced the expression of ICAM-1 and VCAM-1 in colon, which was strongly inhibited by MES b. BesideBesides the inflammatory status of the colon, the level of pro-inflammatory cytokines and chemokines in serum was also assessed using a Proteome Profiler Array assay kit. As shown in NF-κB regulates the expression of pro-inflammatory cytokines and mediators in inflammatory responses . The actMAPKs  and Akt have been implicated in the regulation and release of pro-inflammatory cytokines in the course of UC ,39. DSS These results indicated that MES inhibited the production of pro-inflammatory cytokines through blocking of the phosphorylation of Akt, JNK and NF-kB signaling pathways in DSS-induced colitis.The majority of colitis patients suffer from a chronic disease course with intensive pain, rapid weight loss, swelling of the colon tissue, and rectal bleeding . TreatmeS. macrocarpum, exhibited a strong anti-inflammatory activity, in multiple cell and animal models [MES, a meroterpeniod rich extract of brown alga l models ,33,42. Il models ,43,44,45DSS-fed mice present distinct symptoms of colitis, including body weight loss, colon shortening, bloody diarrhea, disruption of epithelial barrier, destruction of crypt, and infiltration of inflammatory cells . Our resDefects of epithelial barrier and cryptal glands are strongly implicated in the pathogenesis of colitis, since disruption of barrier integrity facilitates the translocation of lumen bacteria into the mucosa ,48. InfiPro-inflammatory cytokines produced by hyperactivated immune and stromal cells are pivotal in the initiation and development of colitis. The imbalance between pro-inflammatory and anti-inflammatory cytokines in IBD leads to disease progression and tissue destruction . For insMatrix metalloproteinases (MMPs) comprise a large group of zinc- and calcium-dependent endopeptidases, which are involved in the degradation of extracellular matrix components, including collagen, glycoproteins and proteoglycans, and cleavage of bioactive proteins . MMP expThe expression of adhesion molecules such as ICAM-1 and VCAM-1 are upregulated by cytokines and they function to stop the circulation of lymphocytes and allow their migration into inflamed bowel tissue and propagate the inflammatory process ,61. AntiBesides pro-inflammatory cytokines, inducible iNOS is another inflammatory marker whose expression is predominantly at the site of inflammation . OverproSargassum species exert immune response regulation function through NF-κB signaling pathway in vivo and in vitro [One major pro-inflammatory transcription factor, NF-κB, is markedly activated in IBD patients and strongly influences the course of mucosal inflammation . In unstin vitro ,66,67,68in vitro ,21,24,25Akt and JNK signaling pathways are also implicated in the regulation and release of pro-inflammatory cytokines, and promote the progress of colitis ,39. The This study also has its limitations. For example, functional evaluation of intestinal permeability was not performed; BALB/c mice were used in inducing acute colitis, instead of strains that could develop chronic colitis after induction, such as C57BL/6; whether the beneficial effects was due to the treatment effect of MES or due to its interference of induction of colitis was not investigated in this study; IBD is a chronic inflammatory condition, while an acute colitis model was used in current study, the effect of MES on human UC needs to be further studied.In conclusion, our study showed the administration of MES at 12 mg/kg for 10 days significantly alleviated symptoms of colitis induced by DSS, and suppressed the corresponding infiltration of inflammatory cells, production of pro-inflammatory cytokines, expression of adhesion molecules and inflammatory enzymes. Mechanism exploration suggests that MES may exert those functions through inhibiting NF-κB, Akt, and JNK signaling pathways.


Nephotettix cincticeps Uhler) is one of the most important insect pests causing serious damage to rice production and yield loss in East Asia. Prior to performing RNA-Seq analysis, we conducted an electrical penetration graph (EPG) test to investigate the feeding behavior of GRH on Ilpum , a near-isogenic line (NIL carrying Grh1) compared to the Grh1 donor parent (Shingwang). Then, we conducted a transcriptome-wide analysis of GRH-responsive genes in Ilpum and NIL, which was followed by the validation of RNA-Seq data by qPCR. On the one hand, EPG results showed differential feeding behaviors of GRH between Ilpum and NIL. The phloem-like feeding pattern was detected in Ilpum, whereas the EPG test indicated a xylem-like feeding habit of GRH on NIL. In addition, we observed a high death rate of GRH on NIL (92%) compared to Ilpum (28%) 72 h post infestation, attributed to GRH failure to suck the phloem sap of NIL. On the other hand, RNA-Seq data revealed that Ilpum and NIL GRH-treated plants generated 1,766,347 and 3,676,765 counts per million mapped (CPM) reads, respectively. The alignment of reads indicated that more than 75% of reads were mapped to the reference genome, and 8859 genes and 15,815,400 transcripts were obtained. Of this number, 3424 differentially expressed genes  were identified. According to the quantile normalization of the fragments per kilobase of transcript per million mapped reads (FPKM) values, followed by the Student’s t-test (p < 0.05), we identified 3283 DEGs in Ilpum (1935 upregulated and 1348 downregulated) and 2599 DEGs in NIL (1621 upregulated and 978 downregulated) with at least a log2 (logarithm base 2) twofold change (Log2FC ≥2) in the expression level upon GRH infestation. Upregulated genes in NIL exceeded by 13.3% those recorded in Ilpum. The majority of genes associated with the metabolism of carbohydrates, amino acids, lipids, nucleotides, the activity of coenzymes, the action of phytohormones, protein modification, homeostasis, the transport of solutes, and the uptake of nutrients, among others, were abundantly upregulated in NIL (carrying Grh1). However, a high number of upregulated genes involved in photosynthesis, cellular respiration, secondary metabolism, redox homeostasis, protein biosynthesis, protein translocation, and external stimuli response related genes were found in Ilpum. Therefore, all data suggest that Grh1-mediated resistance against GRH in rice would involve a transcriptome-wide reprogramming, resulting in the activation of bZIP, MYB, NAC, bHLH, WRKY, and GRAS transcription factors, coupled with the induction of the pathogen-pattern triggered immunity (PTI), systemic acquired resistance (SAR), symbiotic signaling pathway, and the activation of genes associated with the response mechanisms against viruses. This comprehensive transcriptome profile of GRH-responsive genes gives new insights into the molecular response mechanisms underlying GRH (insect pest)–rice (plant) interaction.The green rice leafhopper (GRH,  During their life cycle, plants are constantly confronted by different sorts of environmental stimuli (abiotic stress) ,2 or attOryza sativa L.) is recognized as the staple food for nearly half of the global population, which is projected to reach about 9.8 billion people by 2050 [Nilaparvata lugens Stal, small brown planthopper (SBPH): Laodelphax striatellus Fallen, green leafhopper (GLH): Nephotettix virescens Distant, green rice leafhopper (GRH): Nephotettix cincticeps Uhler, whitebacked planthopper (WBPH): Sogatella furcifera Horvath, and zigzag leafhopper (ZLH): Recilia dorsalis Motschulsky), stem borers, and gall midges, which are considered as the most serious pests of rice [Rice  and phytohormone signaling cascades are activated . Among tFor several decades, many plant breeding research programs have shown a growing interest in developing crop varieties with improved resistance against economically important insect pests, including GRH. In recent years, the use of molecular breeding techniques such as marker-assisted selection (MAS) or marker-assisted backcrossing (MABC), as well as gene pyramiding on various types of breeding populations, such as near-isogenic lines (NILs), recombinant inbred lines (RILs), doubled haploid (DH) lines, and pyramiding lines, have proven beneficial for developing rice varieties carrying a single gene or multiple GRH resistance genes ,24.Grh1, chromosome 5 [Grh2, chromosome 11; Grh3, chromosome 6; Grh4, chromosome 3; Grh5, chromosome 8 [Grh6, chromosome 4; Grh9 [So far, studies aimed at investigating quantitative trait loci (QTLs) associated with GRH resistance in rice have employed forward genetics, in addition to linkage mapping and QTL analysis or genome-wide association studies (GWAS) approaches. These studies have proposed a number of QTLs mapped to different chromosomes of rice, and, in some cases, fine mapping of major QTLs has been performed, resulting in the identification of putative candidate genes . Of Recent advances in molecular breeding research and the emergence of genome sequencing technologies have introduced a wide range of opportunities and possibilities for exploring the molecular basis underlying the defense mechanisms of plants in response to pathogens or attack of pests. As sequencing technology has improved and costs have decreased, an exponential increase in the use of transcriptome studies has been observed, and RNA sequencing (herein referred to as RNA-Seq) has been employed to explore the molecular mechanisms of various biological phenotypes ,30,31,32Green rice leafhopper resistance 1 (Grh1) locus, which has been fine mapped to chromosome 5 and located in a region covered by 670 kbp) and the rice cultivar Ilpum (GRH-susceptible) exposed to GRH infestation. Then, we performed a transcriptome study to identify novel GRH-responsive genes between the NIL GRH-resistant line and Ilpum. In addition, we monitored the feeding behavior of GRH, over time, on GRH-resistant and -susceptible rice lines, using the electrical penetration graph (EPG) technique to investigate the molecular mechanisms underlying Grh1-mediated resistance against GRH, and we elucidated the molecular basis for the GRH (insect pest)–rice (plant) interaction, which would explain the differential transcriptome profile between GRH-susceptible and -resistant rice lines, as well as the activation or suppression of diverse regulatory pathways, coupled with reprogramming of physiological and biochemical processes. This study aimed to investigate the transcriptome-wide profile, as well as the defense mechanisms and signaling pathways activated, when rice plants are infested with green rice leafhopper (GRH). To achieve that, we used a rice near-isogenic line (NIL) reported by Park et al.  (carryinGrh1) showing zero (0) in the cumulative Nc6 column  technology has long been employed to observing the stylet probing behavior of waveforms in each process, from host detection to insect feeding, and it helps examine the phloem feeding activity of the insect on the host plant . Waveforlumn see . The accGrh1 resistance locus. The death rate increased with time and reached 92%  at the final count (72 h after infestation)  .p < 0.05. We observed a 13.3% increase in the number of upregulated genes in the NIL compared to Ilpum  per tube, and leaf samples were collected 48 h post infestation, in duplicate, for RNA-Seq analysis of Ilpum (recurrent parent) and NIL. Another set of leaf samples were collected from seedlings grown without GRH. Data in to Ilpum C,D. In tto Ilpum A,B, whict-test, p < 0.05), we identified 3283 DEGs in Ilpum (1935 upregulated and 1348 downregulated) and 2599 DEGs in NIL (1621 upregulated and 978 downregulated) with at least log2 (logarithm base 2) twofold change (Log2FC ≥2) in the expression, in response to GRH. Up to 75% of these reads successfully mapped to the rice reference genome database  values  to Ilpum (recurrent parent). This is reflected in the heat map (2FC) in their transcriptional level in response to GRH infestation led to 2250 DEGs being identified in Ilpum, of which 1410 genes were upregulated and 840 were downregulated. Similarly, 1834 DEGs were identified (1237 upregulated and 597 downregulated genes). The gene expression and raw sequence data were submitted to the Gene Expression Omnibus (GEO) and Short Read Archive (SRA) at NCBI (https://www.ncbi.nlm.nih.gov/geo/submitter/), accessed on 25 August 2021, with accession numbers GSE176497 and SRP323419, respectively, using FileZilla 3.54.1 software , accessed on 25 August 2021. Lists of the 10 most upregulated and 10 most downregulated genes in Ilpum and NIL are given in The major characteristic of near-isogenic lines (NILs), also known as inbred lines, is the identical genetic makeups with their recurrent parent except for a few specific locations or genetic loci as a result of an introgression of a desirable character or trait (gene) from a donor parent into an otherwise agronomically acceptable cultivar (recurrent parent) . Here, Iheat map D, which 2FC) but downregulated in NIL (–1.6 to –9.9 log2FC) (2FC). In the same way, the top 10 upregulated genes showed an increase in their expression levels by 8.1–15.4 log2FC in NIL, while having lower expression levels in Ilpum under the same conditions (upregulated by 0.2–2.7 log2FC)  . Meanwhi log2FC) .In the perspective of identifying the classes to which the identified GRH-responsive genes belong, a Gene Ontology (GO) classification was done, according to the molecular function, biological process, and cellular response. The GO enrichment revealed that a broad range of molecular functions and biological processes were involved, among which the binding activity, transport activity, and catalytic activity predominated. The majority of the identified genes were proposed to be involved in the macromolecule catabolic process, organic acid biosynthetic process, carboxylic acid biosynthesis, protein catabolic process, or cofactor metabolism . In the 2 sensing and signaling: two), and gravity sensing and signaling (four). Among the 34 genes, 18 were differentially regulated between Ilpum and NIL (seven genes were downregulated in Ilpum (log2FC: −0.12 to −1.24) but upregulated in NIL (Log2FC: 0.03–1.46), while six other genes were upregulated in Ilpum (Log2FC: 0.04–2.53) but downregulated in NIL (Log2FC: −0.1 to −4.87)). Some of the DEGs (downregulated in Ilpum and upregulated in NIL), which are associated with the abiotic stress response, include EID1 (a regulator component encoding the CUL4–DDB1 ubiquitination complex), PIF transcription factor, PKS , ARG1 , SCaBP8/CBL10 , and DELLA transcription factor .Fifty-eight DEGs were proposed to be associated with the response to external stimuli. Of this number, 34 were associated with abiotic stress response, and 24 were associated with biotic stress response G. The se2FC: 0.6–2.5) but downregulated in NIL (Log2FC: −0.09 to −0.5) , PEPR (pep-elicitor peptide receptor involved in damage repair), and three genes  associated with the pattern-triggered immunity (PTI) network and bacterial elicitor response. Furthermore, as shown in GRH infestation is primarily considered as a biotic stress, because the stress is induced by a living organism (insect pest), which is also a vector for various plant’s viruses. Here, DEGs associated with biotic stress response included the damage-elicitor peptide precursor (three), pathogen-pattern triggered immunity (PTI) network (eight), pathogen defense mechanisms , symbiotic signaling pathway (two), and virus response mechanism (five). It was interesting to see that five genes associated with pathogen response mechanism exhibited a differential transcriptional regulation between Ilpum and NIL (upregulated in Ilpum (Logto −0.5) . These gUpon stress induction, from living organisms (biotic stress) or environmental factors (abiotic stress), plants activate various signaling cascades that are sent as an alert to activate the required defense system. In plants, phytohormones, in addition to being essential for growth and development of plants, serve as signaling molecules under stress. After being perceived, signals are transduced at a whole-plant level and allow the activation of various antioxidant systems, followed by a transcriptional reprogramming within the cell. Here, upon GRH infestation, the RNA-Seq results revealed that 168 DEGs associated with phytohormone biosynthesis or signaling (abscisic acid (ABA) biosynthesis: nine, perception and signaling: 11, and conjugation and degradation: two; auxin biosynthesis: three, perception and signal transduction: five, conjugation and degradation: two, and transport: five; brassinosteroid (BR) biosynthesis: four, and perception and signal transduction: 17; cytokinin (CK) biosynthesis: three, perception and signal transduction: 15, and conjugation and degradation: five; ethylene (ET) biosynthesis: six, and perception and signal transduction: 16; gibberellin (GA) biosynthesis: two, perception and signal transduction: one, modification and degradation: two, and transport: one; jasmonic acid (JA) biosynthesis: 15, and perception and signal transduction: eight; salicylic acid (SA) perception and signal transduction: one; strigolactone (SL) biosynthesis: one, and perception and signal transduction: eight) were induced or suppressed. Another group of 25 DEGs were categorized as signaling peptides F.2FC: −0.01 to −7.3) but were upregulated in NIL (Log2FC: 0.03–8.1), whereas 19 genes were upregulated in Ilpum (Log2FC: 0.24–3.5) but downregulated in NIL (Log2FC: −0.01 to −4.9) under the same conditions. However, 112 had similar expression patterns in Ilpum and NIL. The DEGs included auxin , brassinosteroids , cytokinin , ethylene , gibberellin , jasmonic acid , salicylic acid , strigolactone , and other signaling peptide-related genes.We were interested to see the differential transcriptional level of phytohormone signaling pathway genes in response to GRH. As shown in 2O2) removal: 13, chloroplast redox homeostasis: eight, and cytosol/mitochondrion/nucleus redox homeostasis: nine).Secondary metabolites, also known as secondary  or natural products, are organic compounds derived from primary metabolites generated by living organisms, including plants, which are not required for the growth, development, or reproduction of the organism but are produced to confer a selective advantage to the organism. For instance, they may be involved in plants defense or act as regulators in various plant metabolic processes, among other factors . In this2FC: −0.02 to −3.78) but upregulated in NIL, and the other 12 were upregulated in Ilpum (Log2FC: 0.04–1.6), while being downregulated in NIL (Log2FC: −0.2 to −2.7). However, the remaining 40 genes had similar expression patterns between Ilpum and NIL. Regarding the transcriptional regulation of genes associated with redox homeostasis, 27 were differentially expressed between Ilpum and NIL, where 12 genes were downregulated in Ilpum (Log2FC: −0.4 to −4.9) but upregulated in NIL (Log2FC: 0.01–1.6). Under the same conditions, 15 genes exhibited an upregulation pattern in Ilpum (Log2FC: 0.02–5.04), while being downregulated in NIL (Log2FC: −0.04 to −2.1)  .2FC −0.286 to −2.372) but upregulated in NIL (Log2FC 0.08–6.67), whereas 40 were upregulated in Ilpum (Log2FC: 0.002–6.69) but downregulated in NIL (Log2FC: −0.21 to −11.3). In the same way, 95 and 122 DEGs were associated with cellular respiration  cycle: 17) and carbohydrate metabolism , respectively. A comparative transcriptome analysis revealed that, among the genes controlling cellular respiration, 34 were differentially regulated (10 downregulated in Ilpum (Log2FC: −0.71 to −5.75) but upregulated in NIL (Log2FC: 0.48–5.17), and 24 upregulated in Ilpum (Log2FC: 0.099–4.49) but downregulated in NIL (Log2FC: −0.15 to −4.19)), and 61 genes showed a similar expression pattern (upregulated or downregulated) in both Ilpum and NIL. Likewise, out of the 122 DEGs involved in the carbohydrate metabolism, 55 genes were differentially regulated (31 downregulated in Ilpum (Log2FC: −0.06 to −13.71) but upregulated in NIL (Log2FC: 0.16–11.54), and 24 genes were upregulated in Ilpum (Log2FC: 0.28–4.36) but downregulated in NIL (Log2FC: −0.03 to −3.99)), while 75 genes had similar transcript accumulation patterns in both Ilpum and NIL  A. Among  and NIL .S-glutathionylation: 26, S-nitrosylation: one, lipidation: 12, and phosphorylation: 365) (2FC: −0.11 to −3.12) but upregulated in NIL (Log2FC: 0.03–2.8), and 19 genes were upregulated in Ilpum (Log2FC: 0.01–2.71) but downregulated in NIL (Log2FC: −0.09 to −2.86), whereas 45 genes recorded a similar transcriptional level , circadian clock system: 14, organelle machinery: 12, target of rapamycin (TOR) signaling: eight, G-protein signaling: one, phosphoinositide lipid regulatory system: 27, and Rop-GTPase regulatory system: five) , proteinon: 365) , cell-cyon: 365) . In the on: 365)  and proton: 365) . From a al level .2FC: 6.24–9.98) and top 10 downregulated (Log2FC: −3.07 to −7.78) TF-encoding genes belonged to the Homeobox, GRAS, Alfin, B3, RNA polymerase II, and C2H2-ZF TF families, and the Homeobox, mitochondrial transcription termination factor (mTERF), auxin-responsive factor (ARF), plastid-encoded bacterial-type RNA polymerase (PEP), C2H2F, myeloblastosis (MYB), NAC , ATAF12, and cup-shaped cotyledon (CUC2)), polymerase complexes, and nuclear factor Y (NF-Y) TF families, for upregulated and downregulated, respectively.The regulation of gene expression occurs at different levels of the metabolism of the cell. This important event involves many factors, including proteins, which act alone or in complex with other cellular compounds to regulate gene expression under specific conditions. Our RNA-Seq data show that, upon GRH infestation, 599 DEGs (356 upregulated and 243 downregulated) belonging to 53 transcription regulation complexes and transcription factor (TF) families were either induced or suppressed. Of this number, we can mention the basal transcription regulators such as RNA polymerase I (two) and II (59)-dependent transcription complexes, TIFY (13), and Sigma factor (two), as well as the commonly reported TF families such as C2C2 (32), bZIP (basic leucine zipper: 32), MYB (myeloblastosis: 59), Homeobox (33), and AP2/ERF (ethylene-responsive factor: 31) TF superfamilies, and the GRAS (GIBBERELILIN-INSENSITIVE (GAI), REPRESSOR of GA1-3 (RGA), and SCARECROW (SCR): 15), C2H2-ZF (31), C3H-ZF (19), NAC (27), and WRKY (27), basic helix–loop–helix (bHLH: 28) TF families H. Other 2FC: −0.03 to −7.21) but upregulated in NIL (Log2FC: 0.01–9.99), and 81 genes were upregulated in Ilpum (Log2FC: 0.01–8.42) but downregulated in NIL (Log2FC: −0.1 to −5.99)). However, 375 genes exhibited similar expression patterns between Ilpum and NIL , vesicle trafficking (179), protein translocation (87), solute transport (434), amino-acid metabolism, lipid metabolism (191), nucleotide metabolism (41), coenzyme metabolism (127), chromatin organization (117), and RNA processing (219) were differentially regulated between Ilpum and NIL in response to GRH. To this number, we can add genes involved in cytoskeleton organization (93), protein biosynthesis (233), and DNA damage response (22). We observed that GRH-induced biotic stress provoked changes in various plant metabolisms, in addition to what has been described in the previous paragraphs. As shown in panels F–O of With the purpose of validating the RNA-Seq data, the expression of 12 genes selected from RNA-Seq data , Os04g43800 , Os05g35290  and downregulated by GRH: Os03g03360 , Os06g40640 , Os09g16910 ; NIL upregulated genes: Os01g62020 (NAD dependent epimerase/dehydratase family domain-containing protein), Os04g43800 , Os12g37260  and downregulated by GRH: Os01g62244 (ubiquitin-conjugating enzyme), Os07g04840 , Os12g17600  among the most upregulated and downregulated were validated by qPCR A–D.Ghr1 locus) compared to Ilpum or exhibiting differential expression patterns between the two genetic materials under study. It was interesting to see that the expression level of Os07g34520 , and that of Os10g37340  significantly increased in NIL  and 1.42 (48 h) for OsADF3 and RNA-Seq: 1.22 Log2FC, qPCR: 0.99 and 0.94 Log2FC, at 24 h and 48 h for cystathionine) carrying the resistance QTL Grh1 compared to Ilpum  and 0.78 (48 h) Log2FC for OsADF3 and RNA-Seq: 0.11 Log2FC, qPCR: 0.13 (24 h) and 0.42 (48 h) Log2FC) in response to GRH infestation , Os03g60580 , Os01g74450 (Aquaporin), and Os01g06740  exhibited differential expression patterns (downregulated in Ilpum but upregulated in NIL) under the same conditions  and PCRK: LOC_Os10g30600, the bacterial elicitor response protein kinase, which were upregulated in Ilpum and NIL by Log2FC 0.9 and 2.3, respectively. In addition, the NPR1 , a key regulator of salicylic acid (SA)-mediated resistance and systemic acquired resistance (SAR) [2FC 0.87 in Ilpum and 2.61 in NIL. Furthermore, the TGA  proteins [NRP1 homologs NH1 and NH3, and three OsWRKY33 TF-dependent plant immunity (similarly upregulated in Ilpum and NIL) and Virus tobamovirus multiplication were the most abundant  ,42, was proteins  similarlabundant G. These SOS2, LOC_Os01g35184) signaling pathway genes, earlier suggested to positively regulate the salt stress response in plants [OsGAI TF  was differentially regulated between Ilpum (downregulated) and NIL (upregulated). This applies also to COLD1 , which was upregulated in Ilpum, while being downregulated in NIL. Another group of abiotic stress-responsive genes included stomata closure (drought), heat response transcriptional regulator and temperature sensing and signaling, and CAS  among others. A study conducted by Rolly et al. [MAX1–4 , gibberellin biosynthesis genes (GA20ox1 and 2), and cytokinin biosynthesis  could be involved in the adaptive response towards drought tolerance in Arabidopsis.It was interesting to see that, in addition to biotic stress-related genes, GRH triggered significant changes in the expression of genes previously associated with abiotic stress response in plants. These include the salt overly sensitive  recorded the highest number of downregulated genes , it appears that Ilpum experienced a high level of stress caused by GRH compared to NIL. The NIL (GRH resistant) might have activated other defense systems providing the required cellular response towards GRH resistance. We could then propose that, during insect pest feeding on host plants, the photosynthesis rate increased to provide enough energy as part of the primary metabolism, which contributed to the adaptive response mechanisms towards insect pest resistance and helped maintain balanced growth and development of plants. It is well established that photosynthesis and respiration are two fundamental physiological processes required for the survival of plants during stress . In thisIn the biological system, biological processes such as photosynthesis and cellular respiration have evolved multiple biochemical steps, which occur simultaneously within the cells and share common molecular components . Here, wMaintaining genome integrity is recognized as crucial for all living organisms, especially under stress conditions where plants experience changes in their metabolism and increased accumulation of bioactive molecules such as reactive oxygen species (ROS) that may cause DNA damage and cell death . Our datFurthermore, the transcription profile of genes related to amino-acid metabolism (BIN 4), lipid metabolism (BIN 5), coenzyme metabolism (BIN 7), polyamine metabolism (BIN 8), protein modification (BIN 18), and protein homeostasis (BIN 19) indicated that the number of downregulated genes by GRH in these categories was much higher in Ilpum compared to the GRH-resistant rice line (NIL), whereby some of the downregulated genes in Ilpum were differentially regulated under the same conditions. Grh1), pooled from the GRH-mediated transcriptome data  but downregulated in NIL (−0.44 Log2FC)), OsAIP1 or OsBAT1  but downregulated in NIL (−4.6 Log2FC)), and OsFtsH2 (LOC_Os06g45820) identified as cell division protease, homolog of AtFtsH2/8 [2FC) but downregulated in NIL (−0.92 Log2FC). In contrast, genes such as OsBIHD1  [OsRLI  sub-family E member 1 [OsFNR  [2FC −0.63 (OsBIHD1), −024 (OsRLI), and −0.13 (OsFNR)), while being highly induced in NIL (Log2FC 9.99 (OsBIHD1), 8.79 (OsRLI), and 8.39 (OsFNR)) under the same conditions. Generally, genes whose expression is highly induced upon stress induction (abiotic or biotic stress) are considered as having a high potential to be involved in the adaptive response or resistance mechanisms towards that particular stress. In addition, most upregulated and downregulated genes are thought to have differential contributions acting as positive or negative regulators of plant defense. In this study, among the top 20 DEGs between Ilpum (GRH susceptible) and NIL  ,56,57, Oecursor) ), previoThe molecular mechanisms against the attack of insect pests, including GRH, involve a wide range of complex signaling networks, predominantly mediated by but not limited to jasmonic acid (JA) ,61. Othe2FC), while being either downregulated or not affected in NIL (0.08 to –2.05 Log2FC), coupled with the differential transcript accumulation of ROS scavenger-related genes , LOC_Os06g51150 (CAT-B), LOC_Os03g03910 (CAT isozyme 2), LOC_Os07g46990 ) and hydrogen peroxide removal-related genes (ascorbate peroxidase (LOC_Os04g35520) and ascorbate free radical reductase (LOC_Os02g47800)), among others, gives insights into the observed enhanced resistance of NIL plants to GRH and a low level of ROS accumulation compared to Ilpum, while suggesting a possible interaction with Ghr1.Respiratory burst oxidase homologs (RBOHs) are recognized as being crucial for defense signaling events and are key players in plant immunity ,71,72,73Nephotettix cincticeps Uhler) found that, when leafhoppers were reared on resistant plants, their development was slowed down, followed by a rapid death, especially first nymphs. The author also indicated that the sugar content of the excreta was roughly below 0.1% in GRHs reared on resistant rice varieties, contrasting with nearly 0.8–1.6% of sugar content of the excreta of GRHs reared on susceptible rice varieties. In a converse approach, Reddy et al. [Grh1) compared to the 72% survival rate recorded in Ilpum 72 h after infestation would imply that GRHs reared on the resistant NIL seedlings starved to death due to a failure to suck the phloem sap of NIL  is a result of a complex and a combinational action of transcriptome-wide interactions, coupled with biochemical reactions and physiological processes across the plant, rather than gene–gene action. In addition, RNA-Seq and ManMan data associated with the EPG results propose that the feeding behavior of GRHs on rice plants determines the kind of defense mechanism and physiological processes that will be activated, as well as the biochemical reactions that will take place, in order to provide a proper response towards the stress, while tending to maintain balanced plant growth and development.Therefore, considering the transcriptome profile of GRH-responsive genes in Ilpum and NIL, and the differential expression patterns displayed in the two rice genetic materials, coupled with the interesting functions of genes with a logPrior to infestation, second nymph GRHs were grown and maintained as described previously . BrieflyGrh1 (a gene conferring resistance towards GRH) derived from a cross between Shingwang  and Ilpum  [Grh1 donor parent Shingwang was included in the study solely to monitor the feeding behavior of GRH during the electrical penetration graph (EPG) test. Prior to germination, rice seeds were surface-sterilized using nitric acid   overnight to break the dormancy [Two rice lines, Ilpum (the GRH-susceptible cultivar) and a near-isogenic line (NIL) carrying the ica, P2) , were usdormancy , followedormancy . Leaf saWe monitored the feeding behavior of GRH on selected plant materials using an electrical penetration graph (EPG) technology as described previously . In esse2), and a gold line electroductive silver conductive paint  was attached to GRH wings. The gold lines were connected to the GIGA-4 DC EPG amplifier . EPG waveforms were analyzed using PROBE 3.4 software . The substrate voltage was adjusted in the range of +5 V to −5 V [Nephotettix cincticeps Uhler). The mean waveform duration (Nc1–Nc6), mean duration per waveform event, and mean number of waveform events per insect were calculated  initially infested—number of dead insects over time)/ × 100, and the data were expressed as a percentage.Total RNA was isolated from leaf samples using a Takara MiniBEST RNA extraction kit , and DNA contamination was eliminated using DNase. An mRNA purification kit was used to prepare the library according to the manufacturer’s protocol ; protocol: TruSeq Stranded Total RNA Sample Prep Guide, Part #15031048 Rev.E; Reagent: TruSeq 3000 4000 SBS Kit v3). RNA fragments were randomly purified for short-read sequencing, followed by reverse transcription of fragmented RNA into cDNA. The adapters were ligated onto both ends of the cDNA fragments. After amplifying fragments using PCR, fragments with insert sizes between 200 and 400 bp were selected, and both ends of the cDNA were sequenced by read length (paired-end sequencing)  using Illumina’s HiSeq™ 4000 Sequencing System facilitated by HCS 3.3.52 software  according to the manufactures’ instructions (Sequencing protocol: HiSeq 3000 4000 System User Guide Document#15066496 v05 HCS 3.3.52). edgeR package in R  for all samples were compared with each other and merged into one file prior to performing the transcriptome assembly. Merged data were assembled using Trinity (http://trinityrnaseq.github.io), accessed on 25 August 2021, to form contigs (longer fragments without N gaps). The quality control of the sequenced raw reads was done via a computational method using the FastQ Screen program   to ensurFor assembled genes, the longest of the assembled contigs were filtered and clustered into nonredundant transcripts using CD-HIT-EST ,93. We dThe total number of bases, reads, GC (%), Q20 (%), and Q30 (%) were calculated for four samples. The Trimmomatic program  was used−5. Classification of GO terms was subsequently performed using and in-house script. The GO terms belonging to biological processes (BPs), cellular components (CCs), and molecular function (MFs) were listed  database was applied to classify the annotated unigenes using BLASTX of DIAMOND with an E-value cutoff of 1.0 × 10e listed . −5 in the EggNOG  database. The annotated unigenes were mapped to the annotation of the corresponding orthologous groups in the EggNOG database.To identify the proteins distributed in eukaryotic orthologous groups (KOG), clusters of orthologous groups (COGs), and non-supervised orthologous groups (NOGs), we carried out BLASTX of DIAMOND with an E-value cutoff of 1.0 × 10−5 in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Bidirectional best hit (BBH), which is a widely used method to infer orthology, was used to search against the KEGG database to obtain the KO (reference pathway) number of the KEGG annotation. The KO number of the transcriptome was also obtained according to KEGG annotation (Oryza sativa Japonica RAPDB (RAPDB_IRGSP-1.0) genome database, https://www.genome.jp/kegg-bin/show_organism?org=dosa), accessed on 25 August 2021.For functional annotation of the unigenes, we carried out BLASTX of DIAMOND with an E-value cutoff of 1.0 × 10E-value cut-off of 1.0 × 10−5 in the UniProt  database. In addition to capturing the core data mandatory for each UniProtKB entry , as much annotation information as possible was added.For functional annotation of the unigenes, we carried out BLASTX of DIAMOND with an −5 in the Pfam database. The Pfam database is a large collection of protein families, each represented by multiple sequence alignments and hidden Markov models (HMMs). Proteins are generally composed of one or more functional regions, commonly termed domains. The identification of domains that occur within proteins can, therefore, provide insights into their function.For functional annotation of the unigenes, we carried out BLASTX of DIAMOND with an E-value cut-off of 1.0 × 10TM by Zeeberg et al. [Big data with several genes and transcripts often challenge efficient data analysis. Common Gene Ontology (GO) enrichment analysis relying on a database search, although useful for functional characterization of specific gene sets, happens to be less informative if detailed analysis is required at the level of studying genes involved in particular pathways or physiological functions. In this regard, various tools have been developed and used with variable success, e.g., the TM4 suit by Saeed et al. , and GoMg et al. .http://mapman.gabipd.org), accessed on 25 August 2021, has been widely used for visualization of omics data at the process or pathway level. The software is designed and optimized to map transcriptomic data in existing databases for different plant species, including rice. MapMan employs a hierarchical BIN-based ontology system , where specific bins are allocated to biological processes or molecular functions and sub-bins are allocated to individual steps or nodes in that particular biological process. For instance, BIN number 26 is related to stress, and BIN numbers 26.1–6 refer to abiotic stress, while BIN numbers 26.8–10 indicate biotic stress. In the same way, sub-bins associated with abiotic stress include 26.1 (light stress), 26.2 , 26.3 , 26.4 , 26.5 (drought stress), and 26.6 . Similarly, sub-bins 26.8.1, 26.8.3, 26.9.1, and 26.10.1.2 are associated with pathogen pattern-triggered immunity (PTI), defense mechanisms, symbiont-symbiosis signaling, virus movement, and tobamovirus multiplication, respectively. This approach helps to minimize the redundancy usually found in GO enrichment analysis. Furthermore, MapMan uses expression values of genes and displays the analyzed data in the form of diagrams, which allows a better understanding of the significance of the data, where genes with increased or decreased expression levels are indicated as color-coded square blocks. In the perspective of obtaining meaningful information, 8859 DEGs were analyzed using MapMan 3.6.0RC1. To achieve that, all gene expression data with significant DEGs (p < 0.05) were formatted in Microsoft Excel using their unique locus identifiers and expression values expressed as Log2FC and saved as a tab-delimited file. The file was further mapped against the rice genome database (X4.2 oryza_sativa) in MapMan. Then, the analyzed data were classified into different metabolic pathways.In addition, the MapMan omics data analysis program  was used to extract the total RNA from leaf samples, following the manufacturer’s instructions. Briefly, frozen leaf samples with liquid nitrogen were crushed to fine powder, and 450 μL of buffer RL ) was added and pipetted up and down for a few seconds until the lysate showed no precipitate. The mixture was then centrifuged at 12,000 rpm for 5 min (top bench centrifuge), and the supernatant was transferred to fresh 1.5 mL Eppendorf tubes (e-tubes) (Step 1). Then, one volume of ethanol (100%) was added to the mixture from Step 1, followed by mixing by pipetting up and down, and 600 μL was transferred to a pin column with a 2 mL collection tube. The tubes were centrifuged for 1 min at 12,000 rpm, and the flowthrough was discarded, followed by the addition of 500 μL of buffer RWA and centrifugation for 30 s at 12,000 rpm. Immediately after discarding the flowthrough, 600 μL of buffer RWB was added to the spin column and centrifuged for 30 s at 12,000 rpm (this step was repeated twice). Empty spin columns with collection tubes were centrifuged for 2 min at 12,000 rpm, and the spin column were placed on fresh 1.5 e-tubes; then, 100 μL of RNase free water was added. Finally, samples were incubated for 5 min at room temperature, followed by centrifugation for 2 min at 12,000 rpm (the elution step was repeated twice).®II First Strand cDNA Synthesis Kit  was employed according to the manufacturer’s instructions. The newly synthesized cDNA was then used as a template for qPCR  to validate the transcript accumulation of the six upregulated (three in Ilpum and three in NIL) and six downregulated (three in Ilpum and three in NIL) genes.To synthesize the cDNA (complementary DNA) , 1 μg ofTM Design and Analysis Software v.1.3, Applied Biosystems, Thermo Fisher Scientific, Seoul, Korea), with a total of 40 reaction cycles, and the data were normalized to the relative expression of rice Actin1. The list of primers used to validate RNA-Seq results by qPCR can be found in To validate the expression patterns of differentially expressed genes (DEGs) selected from the RNA-Seq dataset, a reaction mixture was prepared comprising 10 μL of Prime Q-Master Mix (with SYBR green I), 0.1× ROX (0.1 μL/50×) , 1 μL of template DNA, and 10 pM of each forward and reverse primers in a total reaction volume of 20 μL, including a no-template control (NTC). A three-step reaction including polymerase activation at 95 °C for 10 min, denaturation at 95 °C for 20 s, annealing at 60 °C for 30 s, and extension at 72 °C for 30 s was performed in a real-time PCR machine (QuantStudioGrh1 locus). In addition, genes associated with basal defense and systemic acquired resistance (SAR), as well as major transcription factors encoding genes belonging to GRAS, NAC, bHLH, MYB, bZIP, WRKY, and C2H2-F families, were differentially regulated between NIL and Ilpum. Furthermore, the electrical penetration graph revealed that GRHs reared on NIL failed to suck phloem sap and starved to death. However, genes involved in cellular respiration, as well as genes related to photosynthesis, redox homeostasis, secondary metabolism, and external stimulus response, were abundantly induced in the GRH-susceptible rice cultivar Ilpum. Therefore, all data suggest that Grh1-mediated activation of multiple regulatory and signaling pathways in response to GRH may involve an interactome with a large number of defense systems towards GRH resistance in rice, rather than gene–gene actions. Advanced functional analyses would help to elucidate the mechanism underlying GRH resistance in rice on a genome-wide scale.Green rice leafhopper (GRH) is a permanent threat to rice cultivation and food security, especially in East Asia. The use of GRH resistance rice lines is the most effective way to overcome crop failure caused by GRH and viral diseases conveyed by this insect pest. This study performed a comparative transcriptome-wide analysis of GRH-responsive genes in GRH-susceptible and -resistant rice genotypes. The RNA-Seq results revealed that phytohormone signaling pathways, carbohydrate metabolism, protein modification and homeostasis, nutrient uptake, and solute transport-related genes, among others, were predominantly upregulated in the GRH-resistant near-isogenic line (NIL, carrying


Venetoclax is a potent, selective inhibitor of B-cell lymphoma 2 (BCL-2) that is a key regulator of apoptosis and is used for the management of chronic lymphocytic leukemia (CLL) either alone or in combination. Inhibition of BCL-2 induces apoptosis, leading to rapid tumor debulking and high response rates in cases of CLL. The toxicity profile of venetoclax includes manageable hematologic toxicities such as neutropenia, gastrointestinal adverse events, and tumor lysis syndrome (TLS). The risk of TLS can be reduced by a slow dose ramp-up, strict monitoring, and adequate prophylaxis ,2,3.An 86-year-old female patient presented to the hospital with fatigue, weight loss, night sweats, shortness of breath, and weakness. She had been diagnosed with CLL 10 years previously and she subsequently received four lines of chemoimmunotherapy. During the COVID-19 pandemic she did not visit the hospital for CLL follow-up. Her white blood cell count was 925,190/µL with 90% lymphocytes. Hemoglobin level was 5.2 g/dL and platelet count was 128,000/µL. Lymphocytes expressed CD5, CD19, CD23, CD200, and CD20. Other laboratory investigations including urea, electrolytes, and liver function tests were all within normal limits. In computed tomography scans of the neck, thorax, abdomen, and pelvis, she was observed to have splenomegaly (150 mm) and paraaortic, supraclavicular, axillar, and mediastinal multiple, differently sized (32x21 to 22x13 mm) lymphadenopathies. Venetoclax treatment was planned with a 5-week dosing ramp-up  with adequate tumor lysis prophylaxis  and close monitoring. In the third week, COVID-19 infection was detected. The venetoclax treatment was continued without any change and the patient was discharged with no complications. Data obtained from laboratory monitoring are presented in We observed rapid tumor debulking without complications and the disappearance of symptoms probably caused by venetoclax-induced apoptosis. We conclude that venetoclax is an effective and safe treatment option for CLL ,5,6.


Drosophila spermatocytes. Here, we use affinity purification coupled with mass spectrometry (AP-MS) to identify the protein-protein interaction network (interactome) of Drosophila GOLPH3 in testes. Analysis of the GOLPH3 interactome revealed enrichment for proteins involved in vesicle-mediated trafficking, cell proliferation and cytoskeleton dynamics. In particular, we found that dGOLPH3 interacts with the Drosophila orthologs of Fragile X mental retardation protein and Ataxin-2, suggesting a potential role in the pathophysiology of disorders of the nervous system. Our findings suggest novel molecular targets associated with GOLPH3 that might be relevant for therapeutic intervention in cancers and other human diseases.Golgi phosphoprotein 3 (GOLPH3) is a highly conserved peripheral membrane protein localized to the Golgi apparatus and the cytosol. GOLPH3 binding to Golgi membranes depends on phosphatidylinositol 4-phosphate [PI(4)P] and regulates Golgi architecture and vesicle trafficking. GOLPH3 overexpression has been correlated with poor prognosis in several cancers, but the molecular mechanisms that link GOLPH3 to malignant transformation are poorly understood. We recently showed that PI(4)P-GOLPH3 couples membrane trafficking with contractile ring assembly during cytokinesis in dividing  Drosophila GOLPH3 (dGOLPH3) is required for retaining to the Golgi exostosins, a class of glycosyltransferases implicated in O-glycosylation of heparan sulfate proteoglycans [Golgi phosphoprotein 3 (GOLPH3) is a highly conserved phosphatidylinositol 4-phosphate [PI(4)P] binding protein, required for maintenance of Golgi structures and protein trafficking . GOLPH3 oglycans . trans-Golgi network (TGN) and endosome-to-plasma membrane transport  were filtered out. Individual MS/MS spectra were manually inspected for proteins represented by a single tryptic peptide.Protein classes and GO over-representation analyses were performed using the PANTHER database , while GCytological preparations were made using testes from third instar larvae. Images of living spermatocytes expressing dGOLPH3-mRFP and GFP-Cog7 were captured as described in . For immz-axis. Projections were created using the Extended Depth of Focus function of the ZEN2 software and processed in Photoshop. Quantification of the number of PLA signals per cell was obtained using the Analyze Particles tools of the ImageJ software. Number of PLA signals, compared to background signals in the control, was examined for statistical significance using the nonparametric Mann-Whitney test.Larval testes were dissected in PBS and fixed using 4% methanol-free formaldehyde in PBS. Samples were blocked with the blocking solution contained in the kit , following the instructions provided by the manufacturer. After blocking, samples were incubated with primary antibodies diluted in Duolink In Situ Antibody Diluent included in the kit  overnight in a humid chamber at 4 °C. Monoclonal antibodies were used to stain dFmr1 . Polyclonal antibodies were: anti-HA  mouse anti-Rab1  and rabTo identify the in vivo interactome of dGOLPH3, we performed affinity purification from testis extract of flies expressing either dGOLPH3-RFP or RFP alone as control. We first assessed whether dGOLPH3-RFP localized to the Golgi in testes co-expressing dGOLPH3-RFP and GFP-Cog7 by time-lapse imaging. dGOLPH3-RFP co-localized with GFP-Cog7  to the GdGOLPH3-RFP and its associated partners were characterized by RFP affinity purification, coupled with mass spectrometry (AP-MS), and selected interactors were subsequently validated by co-immunoprecipitation (Co-IP) or gluthatione S-transferase (GST) pull-down. Using the MaxQuant searching platform, we identified a list of dGOLPH3-interacting proteins that met a cut-off criterion of confidence greater than 95% and were absent in controls . The prodGOLPH3-RFP pulled down well-established interactors of GOLPH3/Vps74p, which include coat protein complex I (COPI) subunits and the phosphatidylinositol 4-phosphatase Sac1 ,43,44; T.Co-IP and GST pull-down experiments further validated the association of dGOLPH3 with COPI subunits a–d.Drosophila and/or human GOLPH3 in previous studies [trans-Golgi network to the plasma membrane [Drosophila testes , a subunit of the Conserved Oligomeric Golgi (COG) complex, which plays a pivotal role in tethering retrograde vesicles that traffic within the Golgi and between the endosomes and the Golgi. Further evidence of COG-dGOLPH3 association was provided in our previous studies [Drosophila homolog of human Sly1, a Sec1/mammalian Unc-18 (SM) protein which functions at the ER-Golgi to regulate SNARE complex assembly and membrane fusion [We also identified the  studies ,38. Of i studies ,52. Slh e fusion ,54,55,56Drosophila Gilgamesh (Gish), a plasma membrane-associated casein kinase that has been involved in the maintenance of germline stem cell sperm individualization in testes [Drosophila orthologs of dynamin and Sorting nexin 9 (Snx9) , the multimeric ribonucleoprotein machine that, along with its conjugate SRP receptor, controls targeting of secretory proteins to the rough ER . Among an testes ,59. Gishn testes . In acco9 (Snx9) . GST pul9 (Snx9) a,b.Drosophila orthologs of human alpha-1,2-mannosyltransferase (ALG11) and phosphomannomutase type 2 (PMM2) [Experimental data from both yeast and human cultured cells revealed that GOLPH3 controls COPI-mediated Golgi trafficking of several Golgi glycosyltransferases required for N- and O-glycosylation ,8,12. Ou2 (PMM2) ,68,69,702 (PMM2) . Human P2 (PMM2) ,68,69,70Our results implicate dGOLPH3 in the synthesis of mucin-type O-glycans  and glycosaminoglycan (GAG) chains. Consistent with the previous report from Chang and coauthors , we founDrosophila ortholog of human Acylglycerol kinase (AGK) ceramide kinase which reports to phosphorylates ceramide and acts in Wnt-mediated migration of primordial germ cells [Drosophila encodes a unique PAPLA1 enzyme, while the mammalian PAPLA1 family consists of three members: DDHD1, DDHD2 (or KIAA0725p), and the SEC23 interacting protein (SEC23IP) [Drosophila PAPLA1, by interacting with the COPII proteins Sec23 and Sec31, regulates ER to Golgi transport and glycosylation of Rhodopsin 1, an N-glycosylated G-protein coupled receptor [Along with the phosphatidylinositol 4-phosphatase Sac1, other proteins that bound GOLPH3 have a role in lipid homeostasis . The prorm cells . PAPLA1 rm cells ,75. The SEC23IP) ,77,78. DDrosophila Bond protein is a member of the Elovl family of enzymes that is required for the elongation of very-long-fatty-acids, commonly found in sphingolipids and essential for sphingolipid function [Drosophila spermatogenesis [Drosophila ortholog of mammalian ER-Golgi intermediate compartment-53 (ERGIC-53), also known as p58 and lectin mannose binding 1 (LMAN1), a type I transmembrane protein containing a mannose binding domain that has been established as a marker of the ER-Golgi intermediate compartment (ERGIC or IC) [The function ,80. Simiogenesis ,81. Amonogenesis  and the ogenesis . The intogenesis . Ergic53C or IC) ,86. MammC or IC) ,88 and iConsistent with the role of GOLPH3 in cell division and proliferation, many proteins identified in our AP-MS experiments are master cell-cycle regulators and/or signaling proteins including phosphatases and kinases. Protein phosphatase 2A at 29B (Pp2A-29B) and Twins are, respectively, the structural A subunit and the regulatory subunit of PP2A , a heterDrosophila Alphabet is a metal-dependent serine/threonine phosphatase of the PP2C family, closely related to mammalian PP2Cα/β isoforms, that acts as a negative regulator of RAS/MAPK signaling [ignaling ,102.Drosophila GTP binding proteins, Rac and Cdc42, are also key regulators of actin cytoskeleton organization and have been involved in vesicle trafficking, cell polarization and JNK kinase activation [The Mitogen-activated protein kinase kinase (MAPKK) 4 is predicted to have a Jun kinase kinase activity . In accotivation ,107,108 tivation ,110,111.Drosophila 14-3-3 ζ and translationally controlled tumor protein (Tctp) regulate TOR signaling through Rheb (Ras homolog enriched in brain), [Drosophila LST8 is the ortholog of mammalian Lst8 (MLST8), the only conserved TOR-binding protein that is a common partner for both TORC1 and TORC2 complexes and essential for Drosophila TORC2 activity [Among the proteins identified in our AP-MS experiments, at least three proteins are involved in the TOR signaling pathway.  brain), ,113, a R brain), ,116,117.activity ,119,120.Drosophila CG9313, CG3121, CG31803, and CG10859 encode the Drosophila orthologs of dynein axonemal intermediate chain 1, radial spoke head component 4A, radial spoke head component 9, dynein axonemal intermediate chain 2, that are essential constituents of ciliary and flagellar axonemal structures [Drosophila ortholog of human dynein axonemal assembly factor 1 [Many of the candidate partners of dGOLPH3 have been implicated in motile cilia assembly and/or function, suggesting that GOLPH3 might have a role in this process . Drosophructures . Cut up ructures ,124,125.factor 1 . The kinfactor 1 ,129,130.Drosophila orthologs of human Ataxin 2 (ATX2) and fragile mental retardation protein (FMRP), two RNA binding proteins implicated in synaptic plasticity and neuronal translational control [ATXN2 gene have been linked to type-2 spinocerebellar ataxia  and dFmr1, two proteins that have been involved in nervous system functions and polyglutamine diseases, is particularly noteworthy ,132,133;. dAtx2 a control ,135,136 a P and PIP2 in lipid-binding assays [In this paper, we report the first comprehensive analysis of the interactome of GOLPH3 protein. We have exploited the advantages of ntiation ,25,26,27ntiation ,21,22,27ntiation ,46,147. membrane . Rab8 fumembrane . Moreovemembrane ,149. dGOmembrane . Althougg assays . Moreoveg assays  demonstrDrosophila melanogaster Rab11 is essential for cytokinesis of S2 cells and spermatocytes [Drosophila type III PI 4-kinase four wheel drive (Fwd), localizes to the Golgi of male meiotic cells, recruits Rab11 to the Golgi complex and is required for the accumulation of PI(4)P-vesicles co-localizing with Rab11 at the cell equator of dividing spermatocytes [In the context of the GOLPH3-controlled vesicle trafficking in cytokinesis, a vast amount of literature has discussed the role of endocytosis and endocytic recycling pathways during furrow ingression and the final steps of cytokinesis in model organisms and mammalian cultured cells ,152,153.atocytes ,160,161 atocytes ,163. In atocytes ,22 suggeIn contrast to fly spermatocytes, in mammalian cells, the function of Rab11 is dispensable for cleavage furrow ingression but required for abscission ,156,158.The endocytic trafficking proteins, clathrin and dynamin, have been also involved in cytokinesis in several model organisms ,165,166.Drosophila orthologs of human dynamin and SNX9 proteins [Our findings demonstrate that dGOLPH3 interacts with Shibire and SH3PX1 that are, respectively, the proteins ,173,174.proteins ,176,177,proteins  and actiproteins ,180,181.proteins ,183. Theproteins ,184,185.proteins . The C-tproteins ,188. Simproteins . Importantly, human SNX9 subfamily proteins are required for accumulation of active myosin II at the cleavage site and normal furrow ingression during cytokinesis of HeLa cells . FurtherDrosophila dividing cells [Although most studies on membrane trafficking during cytokinesis have revealed the essential role of the Golgi and endocytic pathways proteins, it has been suggested that the ER might provide an important membrane storage within the dividing cells . Consistng cells ,193. Theng cells , data inIt has been amply demonstrated that GOLPH3 proteins control COPI-mediated Golgi trafficking of specific Golgi glycosyltransferases ,8,10,12.The interactome of dGOLPH3 indicates an important role in lipid metabolism and signaling that correlates with tumorigenesis and a variety of human genetic diseases . In thisC. elegans as well as in Drosophila embryos and cultured neurons suggesting a possible mechanism that involves vesicle trafficking in SCA2 disease [C. elegans embryos requires ATX2 function, which controls a molecular mechanism required to target and maintain the kinesin ZEN-4 to the spindle midzone through the posttranscriptional regulation of PAR-5 [Drosophila neurons by binding the mRNA of the Drosophila profilin homolog chickadee and regulating Profilin protein expression [It has been suggested that human GOLPH3 and Golgi alterations might have a potential role in the pathophysiology of neurological disease . Remarka disease . Mammali disease ,209,210. disease ,214,215. disease . Our res disease . Moreoveof PAR-5 . Consistof PAR-5 ,219. In pression ,221. Morpression . Uncoverpression ,224. ThuThe Co-IP of dGOLPH3 is also enriched with proteins controlling cell cycle progression and cell proliferation including protein kinases and phosphatases. A significant finding in our work is the interaction of dGOLPH3 with proteins that are known to play a role in the TOR kinase signaling pathway. Importantly, in the context of cancer pathogenesis, human GOLPH3 function has been associated with enhanced AKT/mTOR signaling, although the precise biochemical basis for its activity remains to be determined . Importa