High-throughput Gene Expression Analysis Research Articles

Spatially resolved transcriptomic analysis of the germinating barley grain.

Seeds are a vital source of calories for humans and a unique stage in the life cycle of flowering plants. During seed germination, the embryo undergoes major developmental transitions to become a seedling. Studying gene expression in individual seed cell types has been challenging due to the lack of spatial information or low throughput of existing methods. To overcome these limitations, a spatial transcriptomics workflow was developed for germinating barley grain. This approach enabled high-throughput analysis of spatial gene expression, revealing specific spatial expression patterns of various functional gene categories at a sub-tissue level. This study revealed over 14000 genes differentially regulated during the first 24 hafter imbibition. Individual genes, such as the aquaporin gene family, starch degradation, cell wall modification, transport processes, ribosomal proteins and transcription factors, were found to have specific spatial expression patterns over time. Using spatial autocorrelation algorithms, we identified auxin transport genes that had increasingly focused expression within subdomains of the embryo over time, suggesting their role in establishing the embryo axis. Overall, our study provides an unprecedented spatially resolved cellular map for barley germination and identifies specific functional genomics targets to better understand cellular restricted processes during germination. The data can be viewed at https://spatial.latrobe.edu.au/.

Investigation into the immune microenvironment of gastroenteropancreatic high-grade neuroendocrine carcinoma.

e16244 Background: Gastroenteropancreatic high-grade neuroendocrine carcinomas (GEP HG-NEC) are aggressive cancers with poor survival and limited therapies. Using high-throughput gene expression analysis, we report the tumor-immune system interactions within the tumor microenvironment (TME), differentially expressed genes based on age, tumor location, survival, and objective response rate (ORR) to systemic therapy with the aim to drive future effective therapy research. Methods: We evaluated patients diagnosed with GEP HG-NEC from 2010-2021 for a pilot study and included those with adequate tumor samples. RNA was analyzed using the NanoString nCounter PanCancer IO 360 panel. Logistic regression modeling was used for hypothesis testing associated with best overall response. Cox model was used for testing overall survival (OS). One-sided P values were calculated per the hypothesized positive association between immune signatures and improved clinical outcomes. Results: 21 patients were identified. Mean age 64 years (yrs) with a 2:1 gender ratio (M=14; F=7). Most common primary locations - pancreas (PNEC = 8) and esophagus (3). ORR = 78.6%. TME trends were dampened anti-cancer immune response in patients >60 yrs old and <6-month OS on treatment. TME gene signatures of age >60 yrs (vs. <60 yrs), were indicative of fewer neutrophils, myeloid cells, CD8+ T-cells and CD45+ cells. Downregulated genes in the >60yr old population associated with dampened immune response - ICAM1, TNFAIP6, TWIST1, and PTGER4. A smaller natural killer (NK) cell gene signature was the only notable association with OS <6 months (vs. >6 month). Downregulated genes in >6-month population were HK2 and REN while upregulated genes included CX3CR1, ZAP70, KLRK1, XCL1/2, and MMP7 (immunostimulatory). Increased immune infiltration was associated with prolonged OS, with elevated gene signature of T-cells, lymphoid cells, mast cells, and cytotoxic cells. Downregulated genes related to poor OS were HNF1A and ESR1 (immunosuppressive). A greater potential for a tumor adaptive immune resistance/response were noted; age <60 yrs and prolonged OS having elevated TME PD-L1 and PD-1/TIGIT gene signatures respectively. PNEC was associated with elevated gene signatures of TME MHCII vs. non-PNEC. Upregulated genes in non-PNEC include CXCL2/3 while downregulated genes include TMEM173, IFI16 and RELN (diminished adaptive immune response). Conclusions: This pilot study identified trends in gene expression associated with clinical outcomes. While statistical significance was precluded by limited sample size, our results suggest trends toward increased TME immune cell infiltration in age <60yrs and prolonged OS, increased potential for adaptive immune responses in PNEC, and elevated NK cell infiltration in patients with >6 month OS. Rational drug development for affected patients should target these specific abnormalities.

MicroRNA Biogenesis in Cell Senescence Induced by Chronic Endoplasmic Reticulum Stress

MicroRNAs are small noncoding RNAs that regulate gene expression; stabilize the cell phenotype; and play an important role in cell differentiation, development, and apoptosis. A canonical microRNA biogenesis pathway includes several posttranscriptional steps of processing and transport and ends with cytoplasmic cleavage of pre-miRNA by type III ribonuclease DICER to form a mature duplex, which is included in RISC. MicroRNA biogenesis and role in cell stress are still poorly understood. Using flow cytometry and high-throughput analysis of gene expression, we have shown that chronic endoplasmic reticulum (ER) stress, which is associated with improper protein folding in the ER, induce a cellular senescence phenotype in fibroblast-like FRSN cells. While acute ER stress can reduce miRNA biogenesis, chronic stress does not cause a significant drop in global microRNA expression and is accompanied by only a slight decrease in DICER1 mRNA expression. Heterogeneity with respect to lysosomal β-galactosidase activity was found to increase in the cell population exposed to ER stress. We do not exclude induced cell heterogeneity regarding expression of components of the microRNA biogenesis pathway.

A comprehensive survey on computational learning methods for analysis of gene expression data.

Computational analysis methods including machine learning have a significant impact in the fields of genomics and medicine. High-throughput gene expression analysis methods such as microarray technology and RNA sequencing produce enormous amounts of data. Traditionally, statistical methods are used for comparative analysis of gene expression data. However, more complex analysis for classification of sample observations, or discovery of feature genes requires sophisticated computational approaches. In this review, we compile various statistical and computational tools used in analysis of expression microarray data. Even though the methods are discussed in the context of expression microarrays, they can also be applied for the analysis of RNA sequencing and quantitative proteomics datasets. We discuss the types of missing values, and the methods and approaches usually employed in their imputation. We also discuss methods of data normalization, feature selection, and feature extraction. Lastly, methods of classification and class discovery along with their evaluation parameters are described in detail. We believe that this detailed review will help the users to select appropriate methods for preprocessing and analysis of their data based on the expected outcome.

Mildly dysplastic oral lesions with optically-detectable abnormalities share genetic similarities with severely dysplastic lesions

ObjectiveOptical imaging studies of oral premalignant lesions have shown that optical markers, including loss of autofluorescence and altered morphology of epithelial cell nuclei, are predictive of high-grade pathology. While these optical markers are consistently positive in lesions with moderate/severe dysplasia or cancer, they are positive only in a subset of lesions with mild dysplasia. This study compared the gene expression profiles of lesions with mild dysplasia (stratified by optical marker status) to lesions with severe dysplasia and without dysplasia. Materials and methodsForty oral lesions imaged in patients undergoing oral surgery were analyzed: nine without dysplasia, nine with severe dysplasia, and 22 with mild dysplasia. Samples were submitted for high throughput gene expression analysis. ResultsThe analysis revealed 116 genes differentially expressed among sites without dysplasia and sites with severe dysplasia; 50 were correlated with an optical marker quantifying altered nuclear morphology. Ten of 11 sites with mild dysplasia and positive optical markers (91%) had gene expression similar to sites with severe dysplasia. Nine of 11 sites with mild dysplasia and negative optical markers (82%) had similar gene expression as sites without dysplasia. ConclusionThis study suggests that optical imaging may help identify patients with mild dysplasia who require more intensive clinical follow-up. If validated, this would represent a significant advance in patient care for patients with oral premalignant lesions.

Extra virgin olive oil extract rich in secoiridoids induces an anti-inflammatory profile in peripheral blood mononuclear cells from obese children

Obesity represents an important public health challenge of the twenty first century reaching epidemic proportions worldwide; this is especially true for the pediatric population. In this context, bioactive compounds from foods are crucial to counteract chronic inflammation as a typical feature of obesity. In particular, extra virgin olive oil (EVOO) is one of the most important functional foods exerting, among others, an anti-inflammatory activity not only due to its major (monounsaturated fatty acids) but also to its minor (phenolics) components, as reported in the last years. However, only a limited number of studies were performed on pediatric population, and even fewer are those focusing on EVOO phenolics that investigate the correlation of the chemical characterization with the biological function. Thus, starting from our in vitro data identifying an EVOO chemical profile characterized by a high content of secoiridoids correlating with an anti-inflammatory effect, we studied the ability of an EVOO extract with the same chemical profile to retain this function ex vivo. Specifically, peripheral blood mononuclear cells (PBMCs) collected from obese children were treated with EVOO and olive oil extracts, characterized by a low polyphenol content, to study the ability of secoiridoids to dampen the inflammatory response. A reduction of pro-inflammatory CD14+CD16+ monocytes was detected by cytofluorimetric analysis when PBMCs were treated with EVOO as compared to olive oil extracts. According to this, a down modulation of CCL2 and CCL4 chemokines involved in the recruitment of inflammatory cells, was reported in the supernatants of EVOO relative to olive oil extracts treated PBMCs. Moreover, a high-throughput gene expression analysis revealed that PBMCs molecular profile from obese children is greatly modulated after the treatment with EVOO extract in terms of metabolic and inflammatory pathways. Importantly, some of the significantly modulated genes were involved in the pathways promoting the development of severe obesity. Overall, our ex vivo data demonstrated the ability of EVOO to reduce the inflammatory milieu of PBMCs from obese children both at protein and molecular levels. Of note, a good correlation between the EVOO chemical profile and the biological modulations in terms of anti-inflammatory activity was reported.

Application of GeneCloudOmics: Transcriptomic Data Analytics for Synthetic Biology.

Research in synthetic biology and metabolic engineering require a deep understanding on the function and regulation of complex pathway genes. This can be achieved through gene expression profiling which quantifies the transcriptome-wide expression under any condition, such as a cell development stage, mutant, disease, or treatment with a drug. The expression profiling is usually done using high-throughput techniques such as RNA sequencing (RNA-Seq) or microarray. Although both methods are based on different technical approaches, they provide quantitative measures of the expression levels of thousands of genes. The expression levels of the genes are compared under different conditions to identify the differentially expressed genes (DEGs), the genes with different expression levels under different conditions. DEGs, usually involving thousands in number, are then investigated using bioinformatics and data analytic tools to infer and compare their functional roles between conditions. Dealing with such large datasets, therefore, requires intensive data processing and analyses to ensure its quality and produce results that are statistically sound. Thus, there is a need for deep statistical and bioinformatics knowledge to deal with high-throughput gene expression data. This represents a barrier for wet biologists with limited computational, programming, and data analytic skills that prevent them from getting the full potential of the data. In this chapter, we present a step-by-step protocol to perform transcriptome analysis using GeneCloudOmics, a cloud-based web server that provides an end-to-end platform for high-throughput gene expression analysis.

Angiotensin-converting Enzyme-2 (ACE2) Expression in Pediatric Liver Disease.

The membrane protein angiotensin-converting enzyme-2 (ACE2) has gained notoriety as the receptor for severe acute respiratory syndrome coronavirus 2. Prior evidence has shown ACE2 is expressed within the liver but its function has not been fully discerned. Here, we utilized novel methodology to assess ACE2 expression in pediatric immune-mediated liver disease to better understand its presence in liver diseases and its role during infections such as COVID-19. We stained liver tissue with ACE2-specific immunofluorescent antibodies, analyzed via confocal microscopy. Computational deep learning-based segmentation models identified nuclei and cells, allowing the quantification of mean cellular and cytosolic immunofluorescent. Spatial transcriptomics provided high-throughput gene expression analysis in tissue to determine cellular composition for ACE2 expression. ACE2 plasma expression was quantified via enzyme-linked immunosorbent assay. High ACE2 expression was seen at the apical surface of cholangiocytes, with lower expression within hepatocyte cytosol and nonparenchymal cells ( P <0.001). Children with liver disease had higher ACE2 hepatic expression than pediatric control tissue ( P <0.001). Adult control tissue had higher expression than pediatric control ( P <0.001). Plasma ACE2 was not found to be statistically different between samples. Spatial transcriptomics identified cell composition of ACE2-expressing spots containing antibody-secreting cells. Our results show ACE2 expression throughout the liver, with strongest localization to cholangiocyte membranes. Machine learning can be used to rapidly identify hepatic cellular components for histologic analysis. ACE2 expression in the liver may be increased in pediatric liver disease. Future work is needed to better understand the role of ACE2 in chronic disease and acute infections.

Preparation of Intact Nuclei for Single-Nucleus Omics Using Frozen Cell Suspensions from Mutant Embryos of Xenopus tropicalis.

Single-cell omics such as single-cell RNA-sequencing (RNA-seq) have been used extensively to obtain single-cell genome-wide expression data. This technique can be used to compare mutant and wild-type embryos at predifferentiation stages when individual tissues are not yet formed (therefore requiring genotyping to distinguish among embryos), for example, to determine effects of mutations on developmental trajectories or congenital disease phenotypes. It is, however, hard to use single cells for this technique, because such embryos or cells would need to be frozen until genotyping is complete to capture a given developmental stage precisely, but intact cells cannot be isolated from frozen samples. We developed a protocol in which high-quality nuclei are isolated from frozen cell suspensions, allowing for genotyping individual embryos based on a small fraction of a single embryo suspension. The remaining suspension is frozen. After genotyping is complete, nuclei are isolated from embryo suspensions with the desired genotype and encapsulated in 10× Genomics barcoded gel beads for single-nucleus RNA-seq. We provide a step-by-step protocol that can be used for single transcriptomic analysis as well as single-nucleus chromatin accessibility assays such as ATAC-seq. This technique allows for high-quality high-throughput single-nucleus analysis of gene expression in genotyped embryos. This approach may also be valuable for collection of wild-type embryonic material, for example, when collecting tissue from a particular developmental stage. In addition, freezing of tissue suspensions allows precise staging of collected embryos or tissue that may be difficult to manage when collecting and processing cells from living embryos for single-cell RNA-seq.

Probing Carboxylate Anolytes for Photo-Biofuel Cells through Combination of Bioinformatics and Electrochemistry

Photoheterotrophic purple bacterium Rhodobacter capsulatus has recently gained attention for its high halotolerance and its photo-enhanced extracellular electron transfer via exogenous quinone redox mediators, opening opportunity for self-powered decontamination of saline wastewater. Biodegradation of malate and succinate in R. capsulatus electrochemical systems has undergone prior examination, although a consistent bioelectrochemical system to comparatively study multiple carbon sources has not previously been developed. In this study, electrochemical techniques, biological assays, and computational tools were combined to evaluate malate, succinate, propionate, and lactate as oxidizable fuels in photo-enhanced microbial electrochemical systems. Specifically, cyclic voltammetry and amperometry data demonstrated that R. capsulatus generates distinctive photo-enhanced current densities dependent on both fuel identity and concentration. Bacterial growth curve studies were in agreement with the electrochemical data, indicating that lactate, which yielded the greatest bio-anodic current density (9.5 ± 1.9 µA cm-2), allowed the bacteria to grow more rapidly than the other substrates, suggesting its effectiveness as a fuel. Moreover, propionate appeared to be the fuel least efficiently utilized by R. capsulatus, having the slowest growth curve and the lowest current density generation (1.3 ± 0.2 µA cm-2). Finally, high-throughput differential gene expression analysis allowed for illuminating the physiological underpinnings of the observed differences between substrates. Most remarkably, cells grown in lactate were found to overexpress light harvesting complex II proteins and to underexpress flagellar motility proteins, which both correspond to the high photo-enhanced current density in lactate bioanodes compared to malate and propionate.

UBE2S promotes the development of ovarian cancer by promoting PI3K/AKT/mTOR signaling pathway to regulate cell cycle and apoptosis

BackgroundOvarian cancer is one of the important factors that seriously threaten women's health and its morbidity and mortality ranks eighth among female cancers in the world. It is critical to identify potential and promising biomarkers for prognostic evaluation and molecular therapy of OV. Ubiquitin-conjugating enzyme E2S (UBE2S), a potential oncogene, regulates the malignant progression of various tumors; however, its role in OV is still unclear.MethodsThe expression and prognostic significance of UBE2S at the pan-cancer level were investigated through high-throughput gene expression analysis and clinical prognostic data from TCGA, GEPIA, and GEO databases. 181 patients with OV were included in this study. Cell culture and cell transfection were performed on OV cell lines (SKOV3 and A2780) and a normal ovarian cell line (IOSE80). The expression level and prognostic significance of UBE2S in OV were verified by western blot, immunohistochemistry, and Kaplan–Meier survival analysis. Through cell transfection, CCK-8, Ki-67 immunofluorescence, wound healing, Transwell, clonogenic, and flow cytometry assays, the effect and detailed mechanism of UBE2S knockdown on the malignant biological behavior of OV cells were explored.ResultsUBE2S exhibited abnormally high expression at the pan-cancer level. The results of RT-qPCR and Western blotting indicated that UBE2S was significantly overexpressed in ovarian cancer cell lines compared with normal cell lines (P < 0.05). Kaplan–Meier survival analysis and Immunohistochemistry indicated that overexpression of UBE2S was related to poor prognosis of OV (HR > 1, P < 0.05). Results of in vitro experiments indicated that UBE2S gene knockdown might inhibit the proliferation, invasion, and prognosis of OV cells by inhibiting the PI3K/AKT/mTOR signaling pathway, thereby blocking the cell cycle and promoting apoptosis (P < 0.05).ConclusionUBE2S is a potential oncogene strongly associated with a poor prognosis of OV patients. Knockdown of UBE2S could block the cell cycle and promote apoptosis by inhibiting the PI3K/AKT/mTOR pathway and ultimately inhibit the proliferation, migration and prognosis of ovarian cancer, which suggested that UBE2S might be used for molecular therapy and prognostic evaluation of ovarian cancer.

Spatial and Transcriptomic Analysis of Perineural Invasion in Oral Cancer.

Perineural invasion (PNI), a common occurrence in oral squamous cell carcinomas, is associated with poor survival. Consequently, these tumors are treated aggressively. However, diagnostic criteria of PNI vary and its role as an independent predictor of prognosis has not been established. To address these knowledge gaps, we investigated spatial and transcriptomic profiles of PNI-positive and PNI-negative nerves. Tissue sections from 142 patients were stained with S100 and cytokeratin antibodies. Nerves were identified in two distinct areas: tumor bulk and margin. Nerve diameter and nerve-to-tumor distance were assessed; survival analyses were performed. Spatial transcriptomic analysis of nerves at varying distances from tumor was performed with NanoString GeoMx Digital Spatial Profiler Transcriptomic Atlas. PNI is an independent predictor of poor prognosis among patients with metastasis-free lymph nodes. Patients with close nerve-tumor distance have poor outcomes even if diagnosed as PNI negative using current criteria. Patients with large nerve(s) in the tumor bulk survive poorly, suggesting that even PNI-negative nerves facilitate tumor progression. Diagnostic criteria were supported by spatial transcriptomic analyses of >18,000 genes; nerves in proximity to cancer exhibit stress and growth response changes that diminish with increasing nerve-tumor distance. These findings were validated in vitro and in human tissue. This is the first study in human cancer with high-throughput gene expression analysis in nerves with striking correlations between transcriptomic profile and clinical outcomes. Our work illuminates nerve-cancer interactions suggesting that cancer-induced injury modulates neuritogenesis, and supports reclassification of PNI based on nerve-tumor distance rather than current subjective criteria.

Macrophage functional diversity in NAFLD - more than inflammation.

Macrophages have diverse phenotypes and functions due to differences in their origin, location and pathophysiological context. Although their main role in the liver has been described as immunoregulatory and detoxifying, changes in macrophage phenotypes, diversity, dynamics and function have been reported during obesity-related complications such as non-alcoholic fatty liver disease (NAFLD). NAFLD encompasses multiple disease states from hepatic steatosis to non-alcoholic steatohepatitis (NASH), fibrosis, cirrhosis and hepatocarcinoma. Obesity and insulin resistance are prominent risk factors for NASH, a disease with a high worldwide prevalence and no approved treatment. In this Review, we discuss the turnover and function of liver-resident macrophages (Kupffer cells) and monocyte-derived hepatic macrophages. We examine these populations in both steady state and during NAFLD, with an emphasis on NASH. The explosion in high-throughput gene expression analysis using single-cell RNA sequencing (scRNA-seq) within the last 5 years has revolutionized the study of macrophage heterogeneity, substantially increasing our understanding of the composition and diversity of tissue macrophages, including in the liver. Here, we highlight scRNA-seq findings from the last 5 years on the diversity of liver macrophages in homeostasis and metabolic disease, and reveal hepatic macrophage function beyond their classically described inflammatory role in the progression of NAFLD and NASH pathogenesis.

Preprint Highlight: Adult fibroblasts retain organ-specific transcriptomic identity.

Even with recent advances in lineage tracing and multiomics analyses, it is difficult to specifically identify and target heterogeneous fibroblast populations in an organ-specific manner. This study combined robust multi-organ in vitro, in vivo, and high-throughput gene expression analyses of mouse fibroblast populations derived from various organs to define organ-specific transcriptional signatures. The analyses revealed that fibroblasts derived from different organs retain transcriptional embryonic gene signatures as organ-of-origin identifiers in adulthood. Moreover, organ-specific transcriptome identities of fibroblast populations were maintained in fibroblast co-cultures in vitro and ectopic transplants in vivo. These studies advance our current understanding of the heterogeneity of fibroblast populations and suggest opportunities for their exploitation and targetability in an organ-specific manner.

Cytotoxicity, crosslinking and biological activity of three mitomycins

While interstrand crosslinks (ICLs) have been considered as one type of DNA damage in the past, there is mounting evidence suggesting that these highly cytotoxic lesions are processed differently by the cellular machinery depending upon the ICL structure. In this study, we examined the crosslinking ability of three mitomycins, the structure of the ICLs they produce and the cytotoxicity of the drugs toward three different cell lines. The drugs are: mitomycin C (1), decarbamoylmitomycin C (2), and a mitomycin-conjugate (3) whose mitosane moiety is linked to a N-methylpyrrole carboxamide. We found that, overall, both MC and compound 3 show strong similarities regarding their alkylation of DNA, while DMC alkylating behavior is markedly different. To gain further insight into the mode of action of these drugs, we performed high throughput gene expression and gene ontology analysis to identify gene expression and cellular pathways most impacted by each drug treatment in MCF-7 cell lines. We observed that the novel mitomycin derivative (3) specifically causes changes in the expression of genes encoding proteins involved in cell integrity and tissue structure. Further analysis using bioinformatics (IPA) indicated that the new derivative (3) displays a stronger downregulation of major signaling networks that regulate the cell cycle, DNA damage response and cell proliferation when compared to MC and DMC. Collectively, these findings demonstrate that cytotoxic mechanisms of all three drugs are complex and are not solely related to their crosslinking abilities or the structure of the ICLs they produce.

GeneCloudOmics: A Data Analytic Cloud Platform for High-Throughput Gene Expression Analysis.

Gene expression profiling techniques, such as DNA microarray and RNA-Sequencing, have provided significant impact on our understanding of biological systems. They contribute to almost all aspects of biomedical research, including studying developmental biology, host-parasite relationships, disease progression and drug effects. However, the high-throughput data generations present challenges for many wet experimentalists to analyze and take full advantage of such rich and complex data. Here we present GeneCloudOmics, an easy-to-use web server for high-throughput gene expression analysis that extends the functionality of our previous ABioTrans with several new tools, including protein datasets analysis, and a web interface. GeneCloudOmics allows both microarray and RNA-Seq data analysis with a comprehensive range of data analytics tools in one package that no other current standalone software or web-based tool can do. In total, GeneCloudOmics provides the user access to 23 different data analytical and bioinformatics tasks including reads normalization, scatter plots, linear/non-linear correlations, PCA, clustering (hierarchical, k-means, t-SNE, SOM), differential expression analyses, pathway enrichments, evolutionary analyses, pathological analyses, and protein-protein interaction (PPI) identifications. Furthermore, GeneCloudOmics allows the direct import of gene expression data from the NCBI Gene Expression Omnibus database. The user can perform all tasks rapidly through an intuitive graphical user interface that overcomes the hassle of coding, installing tools/packages/libraries and dealing with operating systems compatibility and version issues, complications that make data analysis tasks challenging for biologists. Thus, GeneCloudOmics is a one-stop open-source tool for gene expression data analysis and visualization. It is freely available at http://combio-sifbi.org/GeneCloudOmics.

P.182 Self-Assembling Peptide Biomaterial to Optimize Human Stem Cell-Based Regeneration of the Injured Spinal Cord

Background: Human induced pluripotent stem cell-derived neural stem cells (hiPS-NSCs) are a promising therapeutic approach to regenerate after spinal cord injury (SCI) as they can differentiate to myelinating oligodendrocytes, synaptically-active neurons, and supportive astrocytes. Unfortunately, most chronically injured patients develop ex vacuo microcystic cavitations which prevent regenerative cell migration and neurite outgrowth. QL6 is a novel, pH-neutral, biomaterial which can self-assembles into a supportive extracellular matrix (ECM)-like matrix in vivo. This work assesses QL6’s ability to support hiPS-NSC-based regeneration. Methods:In Vitro:hiPS-NSCs were extensively characterized by EDTA assay, qPCR, and immunocytochemistry(ICC), electron microscopy(EM) and neurosphere formation assays. In Vivo:Immunodeficient rats received clinically-relevant chronic C6-7 injuries. Animals were randomized: (1)vehicle, (2)hiPS-NSCs, (3)QL6, (4)QL6+hiPS-NSCs. All rats underwent treadmill rehabilitation and behavioural testing. A subset underwent single-cell RNA sequencing(scRNAseq). Results: hiPS-NSCs proliferated robustly on QL6(Ki67+/DAPI+; 29%vs6%; p&lt;0.01). EDTA assay showed hiPS-NSC binding to QL6 to be driven by calcium-independent mechanisms. Importantly, QL6 enhanced adherent neurosphere formation. EM-imaging provided the first images of the hiPS-NSC/QL6 interaction. Behavioural assessments demonstrate synergistic improvements with combinatorial treatment. High-throughput scRNAseq differential gene expression analyses suggest QL6 is altering lineage signalling in the human graft post-transplantation. Conclusions: This work provides key proof-of-concept data that QL6 can support translationally-relevant human iPS-NSCs in traumatic SCI.

Test article with 1 Significance Statement and 1 (Normal) Abstract.

Even with recent advances in lineage tracing and multiomics analyses, it is difficult to specifically identify and target heterogeneous fibroblast populations in an organ-specific manner. This study combined robust multi-organ in vitro, in vivo, and high-throughput gene expression analyses of mouse fibroblast populations derived from various organs to define organ-specific transcriptional signatures. The analyses revealed that fibroblasts derived from different organs retain transcriptional embryonic gene signatures as organ-of-origin identifiers in adulthood. Moreover, organ-specific transcriptome identities of fibroblast populations were maintained in fibroblast co-cultures in vitro and ectopic transplants in vivo. These studies advance our current understanding of the heterogeneity of fibroblast populations and suggest opportunities for their exploitation and targetability in an organ-specific manner.

Preprint Highlight: Adult fibroblasts retain organ-specific transcriptomic identity.

Even with recent advances in lineage tracing and multiomics analyses, it is difficult to specifically identify and target heterogeneous fibroblast populations in an organ-specific manner. This study combined robust multi-organ in vitro, in vivo, and high-throughput gene expression analyses of mouse fibroblast populations derived from various organs to define organ-specific transcriptional signatures. The analyses revealed that fibroblasts derived from different organs retain transcriptional embryonic gene signatures as organ-of-origin identifiers in adulthood. Moreover, organ-specific transcriptome identities of fibroblast populations were maintained in fibroblast co-cultures in vitro and ectopic transplants in vivo. These studies advance our current understanding of the heterogeneity of fibroblast populations and suggest opportunities for their exploitation and targetability in an organ-specific manner.

Gene expression analysis method integration and co-expression module detection applied to rare glucide metabolism disorders using ExpHunterSuite

High-throughput gene expression analysis is widely used. However, analysis is not straightforward. Multiple approaches should be applied and methods to combine their results implemented and investigated. We present methodology for the comprehensive analysis of expression data, including co-expression module detection and result integration via data-fusion, threshold based methods, and a Naïve Bayes classifier trained on simulated data. Application to rare-disease model datasets confirms existing knowledge related to immune cell infiltration and suggest novel hypotheses including the role of calcium channels. Application to simulated and spike-in experiments shows that combining multiple methods using consensus and classifiers leads to optimal results. ExpHunter Suite is implemented as an R/Bioconductor package available from https://bioconductor.org/packages/ExpHunterSuite. It can be applied to model and non-model organisms and can be run modularly in R; it can also be run from the command line, allowing scalability with large datasets. Code and reports for the studies are available from https://github.com/fmjabato/ExpHunterSuiteExamples.