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Background Aims: Age-related macular degeneration (AMD) is the most common cause of blindness in elderly patients within developed countries, affecting more than 190 million worldwide. In AMD, the retinal pigment epithelial (RPE) cell layer progressively degenerates, resulting in subsequent loss of photoreceptors and ultimately vision. There is currently no cure for AMD, but therapeutic strategies targeting the complement system are being developed to slow the progression of the disease., Methods: Replacement therapy with pluripotent stem cell-derived (hPSC) RPEs is an alternative treatment strategy. A cell therapy product must be produced in accordance with Good Manufacturing Practices at a sufficient scale to facilitate extensive pre-clinical and clinical testing. Cryopreservation of the final cell product is therefore highly beneficial, as the manufacturing, pre-clinical and clinical testing can be separated in time and location., Results: We found that mature hPSC-RPE cells do not survive conventional cryopreservation techniques. However, replating the cells 2-5 days before cryopreservation facilitates freezing. The replated and cryopreserved hPSC-RPE cells maintained their identity, purity and functionality as characteristic RPEs, shown by cobblestone morphology, pigmentation, transcriptional profile, RPE markers, transepithelial resistance and pigment epithelium-derived factor secretion. Finally, we showed that the optimal replating time window can be tracked noninvasively by following the change in cobblestone morphology., Conclusions: The possibility of cryopreserving the hPSC-RPE product has been instrumental in our efforts in manufacturing and performing pre-clinical testing with the aim for clinical translation., Competing Interests: Declaration of Competing Interest The authors have no commercial, proprietary or financial interest in the products or companies described in this article., (Copyright © 2024 International Society for Cell & Gene Therapy. Published by Elsevier Inc. All rights reserved.)

Background: An activated, proinflammatory endothelium is a key feature in the development of complications of obesity and type 2 diabetes and can be caused by insulin resistance in endothelial cells., Methods: We analyzed primary human endothelial cells by RNA sequencing to discover novel insulin-regulated genes and used endothelial cell culture and animal models to characterize signaling through CXCR4 (C-X-C motif chemokine receptor 4) in endothelial cells., Results: CXCR4 was one of the genes most potently regulated by insulin, and this was mediated by PI3K (phosphatidylinositol 3-kinase), likely through FoxO1, which bound to the CXCR4 promoter. CXCR4 mRNA in CD31+ cells was 77% higher in mice with diet-induced obesity compared with lean controls and 37% higher in db/db mice than db/+ controls, consistent with upregulation of CXCR4 in endothelial cell insulin resistance. SDF-1 (stromal cell-derived factor-1)-the ligand for CXCR4-increased leukocyte adhesion to cultured endothelial cells. This effect was lost after deletion of CXCR4 by gene editing while 80% of the increase was prevented by treatment of endothelial cells with insulin. In vivo microscopy of mesenteric venules showed an increase in leukocyte rolling after intravenous injection of SDF-1, but most of this response was prevented in transgenic mice with endothelial overexpression of IRS-1 (insulin receptor substrate-1)., Conclusions: Endothelial cell insulin signaling limits leukocyte/endothelial cell interaction induced by SDF-1 through downregulation of CXCR4. Improving insulin signaling in endothelial cells or inhibiting endothelial CXCR4 may reduce immune cell recruitment to the vascular wall or tissue parenchyma in insulin resistance and thereby help prevent several vascular complications.

Human embryonic stem cell-derived retinal pigment epithelial cells (hESC-RPE) are a promising cell source to treat age-related macular degeneration (AMD). Despite several ongoing clinical studies, a detailed mapping of transient cellular states during in vitro differentiation has not been performed. Here, we conduct single-cell transcriptomic profiling of an hESC-RPE differentiation protocol that has been developed for clinical use. Differentiation progressed through a culture diversification recapitulating early embryonic development, whereby cells rapidly acquired a rostral embryo patterning signature before converging toward the RPE lineage. At intermediate steps, we identified and examined the potency of an NCAM1 + retinal progenitor population and showed the ability of the protocol to suppress non-RPE fates. We demonstrated that the method produces a pure RPE pool capable of maturing further after subretinal transplantation in a large-eyed animal model. Our evaluation of hESC-RPE differentiation supports the development of safe and efficient pluripotent stem cell-based therapies for AMD., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

Human thermogenic adipose tissue mitigates metabolic disease, raising much interest in understanding its development and function. Here, we show that human thermogenic adipocytes specifically express a primate-specific long non-coding RNA, LINC00473 which is highly correlated with UCP1 expression and decreased in obesity and type-2 diabetes. LINC00473 is detected in progenitor cells, and increases upon differentiation and in response to cAMP. In contrast to other known adipocyte LincRNAs, LINC00473 shuttles out of the nucleus, colocalizes and can be crosslinked to mitochondrial and lipid droplet proteins. Up- or down- regulation of LINC00473 results in reciprocal alterations in lipolysis, respiration and transcription of genes associated with mitochondrial oxidative metabolism. Depletion of PLIN1 results in impaired cAMP-responsive LINC00473 expression and lipolysis, indicating bidirectional interactions between PLIN1, LINC00473 and mitochondrial oxidative functions. Thus, we suggest that LINC00473 is a key regulator of human thermogenic adipocyte function, and reveals a role for a LincRNA in inter-organelle communication and human energy metabolism., Competing Interests: Competing Interests Statement The authors declare no competing interests.

Semaglutide, a glucagon-like peptide 1 (GLP-1) analog, induces weight loss, lowers glucose levels, and reduces cardiovascular risk in patients with diabetes. Mechanistic preclinical studies suggest weight loss is mediated through GLP-1 receptors (GLP-1Rs) in the brain. The findings presented here show that semaglutide modulated food preference, reduced food intake, and caused weight loss without decreasing energy expenditure. Semaglutide directly accessed the brainstem, septal nucleus, and hypothalamus but did not cross the blood-brain barrier; it interacted with the brain through the circumventricular organs and several select sites adjacent to the ventricles. Semaglutide induced central c-Fos activation in 10 brain areas, including hindbrain areas directly targeted by semaglutide, and secondary areas without direct GLP-1R interaction, such as the lateral parabrachial nucleus. Automated analysis of semaglutide access, c-Fos activity, GLP-1R distribution, and brain connectivity revealed that activation may involve meal termination controlled by neurons in the lateral parabrachial nucleus. Transcriptomic analysis of microdissected brain areas from semaglutide-treated rats showed upregulation of prolactin-releasing hormone and tyrosine hydroxylase in the area postrema. We suggest semaglutide lowers body weight by direct interaction with diverse GLP-1R populations and by directly and indirectly affecting the activity of neural pathways involved in food intake, reward, and energy expenditure.

Objective: To characterize the EndoC-βH1 cell line as a model for human beta cells and evaluate its beta cell functionality, focusing on insulin secretion, proliferation, apoptosis and ER stress, with the objective to assess its potential as a screening platform for identification of novel anti-diabetic drug candidates., Methods: EndoC-βH1 was transplanted into mice for validation of in vivo functionality. Insulin secretion was evaluated in cells cultured as monolayer and as pseudoislets, as well as in diabetic mice. Cytokine induced apoptosis, glucolipotoxicity, and ER stress responses were assessed. Beta cell relevant mRNA and protein expression were investigated by qPCR and antibody staining. Hundreds of proteins or peptides were tested for their effect on insulin secretion and proliferation., Results: Transplantation of EndoC-βH1 cells restored normoglycemia in streptozotocin induced diabetic mice. Both in vitro and in vivo, we observed a clear insulin response to glucose, and, in vitro, we found a significant increase in insulin secretion from EndoC-βH1 pseudoislets compared to monolayer cultures for both glucose and incretins. Apoptosis and ER stress were inducible in the cells and caspase 3/7 activity was elevated in response to cytokines, but not affected by the saturated fatty acid palmitate. By screening of various proteins and peptides, we found Bombesin (BB) receptor agonists and Pituitary Adenylate Cyclase-Activating Polypeptides (PACAP) to significantly induce insulin secretion and the proteins SerpinA6, STC1, and APOH to significantly stimulate proliferation. ER stress was readily induced by Tunicamycin and resulted in a reduction of insulin mRNA. Somatostatin (SST) was found to be expressed by 1% of the cells and manipulation of the SST receptors was found to significantly affect insulin secretion., Conclusions: Overall, the EndoC-βH1 cells strongly resemble human islet beta cells in terms of glucose and incretin stimulated insulin secretion capabilities. The cell line has an active cytokine induced caspase 3/7 apoptotic pathway and is responsive to ER stress initiation factors. The cells' ability to proliferate can be further increased by already known compounds as well as by novel peptides and proteins. Based on its robust performance during the functionality assessment assays, the EndoC-βH1 cell line was successfully used as a screening platform for identification of novel anti-diabetic drug candidates., (Copyright © 2017 Novo Nordisk A/S. Published by Elsevier GmbH.. All rights reserved.)

MicroRNAs have potential as diagnostic cancer biomarkers. The aim of this study was (1) to define microRNA expression patterns in formalin-fixed parafin-embedded tissue from pancreatic ductal adenocarcinoma, ampullary adenocarcinoma, normal pancreas and chronic pancreatitis without using micro-dissection and (2) to discover new diagnostic microRNAs and combinations of microRNAs in cancer tissue. The expression of 664 microRNAs in tissue from 170 pancreatic adenocarcinomas and 107 ampullary adenocarcinomas were analyzed using a commercial microRNA assay. Results were compared with chronic pancreatitis, normal pancreas and duodenal adenocarcinoma. In all, 43 microRNAs had higher and 41 microRNAs reduced expression in pancreatic cancer compared with normal pancreas. In all, 32 microRNAs were differently expressed in pancreatic adenocarcinoma compared with chronic pancreatitis (17 higher; 15 reduced). Several of these microRNAs have not before been related to diagnosis of pancreatic cancer (eg, miR-492, miR-614, miR-622). MiR-614, miR-492, miR-622, miR-135b and miR-196 were most differently expressed. MicroRNA profiles of pancreatic and ampullary adenocarcinomas were correlated (0.990). MicroRNA expression profiles for pancreatic cancer described in the literature were consistent with our findings, and the microRNA profile for pancreatic adenocarcinoma (miR-196b-miR-217) was validated. We identified a more significant expression profile, the difference between miR-411 and miR-198 (P=2.06 × 10(-54)) and a diagnostic LASSO classifier using 19 microRNAs (sensitivity 98.5%; positive predictive value 97.8%; accuracy 97.0%). We also identified microRNA profiles to subclassify ampullary adenocarcinomas into pancreatobiliary or intestinal type. In conclusion, we found that combinations of two microRNAs could roughly separate neoplastic from non-neoplastic samples. A diagnostic 19 microRNA classifier was constructed which without micro-dissection could discriminate pancreatic and ampullary adenocarcinomas from chronic pancreatitis and normal pancreas with high sensitivity and accuracy. Ongoing prospective studies will evaluate if these microRNA profiles are useful on fine-needle biopsies for early diagnosis of pancreatic cancer.

Background: The aim of the present study was to identify a panel of microRNAs (miRNAs) that can predict overall survival (OS) in non micro-dissected cancer tissues from patients operated for pancreatic cancer (PC)., Methods: MiRNAs were purified from formalin-fixed paraffin embedded (FFPE) cancer tissue from 225 patients operated for PC. Only a few of those patients received adjuvant chemotherapy. Expressions of miRNAs were determined with the TaqMan MicroRNA Array v2.0. Two statistical methods, univariate selection and the Lasso (Least Absolute Shrinkage and Selection Operator) method, were applied in conjunction with the Cox proportional hazard model to relate miRNAs to OS., Results: High expression of miR-212 and miR-675 and low expression of miR-148a, miR-187, and let-7g predicted short OS independent of age, gender, calendar year of operation, KRAS mutation status, tumor stage, American Society of Anesthesiologists (ASA) score, localization (not miR-148a), and differentiation of tumor. A prognostic index (PI) based on these five miRNAs was calculated for each patient. The median survival was 1.09 years (Confidence Interval [CI] 0.98-1.43) for PI > median PI compared to 2.23 years (CI 1.84-4.36) for PI < median. MiR-212, miR-675, miR-187, miR-205, miR-944, miR-431, miR-194, miR-148a, and miR-769-5p showed the strongest prediction ability by the Lasso method. Thus miR-212, miR-675, miR-187, and miR-148a were predictors for OS in both statistical methods., Conclusions: The combination of five miRNAs expression in non micro-dissected FFPE PC tissue can identify patients with short OS after radical surgery. The results are independent of chemotherapy treatment. Patients with a prognostic index > median had a very short median OS of only 1 year.

Recently, next-generation sequencing has been introduced as a promising, new platform for assessing the copy number of transcripts, while the existing microarray technology is considered less reliable for absolute, quantitative expression measurements. Nonetheless, so far, results from the two technologies have only been compared based on biological data, leading to the conclusion that, although they are somewhat correlated, expression values differ significantly. Here, we use synthetic RNA samples, resembling human microRNA samples, to find that microarray expression measures actually correlate better with sample RNA content than expression measures obtained from sequencing data. In addition, microarrays appear highly sensitive and perform equivalently to next-generation sequencing in terms of reproducibility and relative ratio quantification.

The global feature of the completely sequenced Alcanivorax borkumensis SK2 type strain chromosome is its symmetry and homogeneity. The origin and terminus of replication are located opposite to each other in the chromosome and are discerned with high signal to noise ratios by maximal oligonucleotide usage biases on the leading and lagging strand. Genomic DNA structure is rather uniform throughout the chromosome with respect to intrinsic curvature, position preference or base stacking energy. The orthologs and paralogs of A. borkumensis genes with the highest sequence homology were found in most cases among gamma-Proteobacteria, with Acinetobacter and P. aeruginosa as closest relatives. A. borkumensis shares a similar oligonucleotide usage and promoter structure with the Pseudomonadales. A comparatively low number of only 18 genome islands with atypical oligonucleotide usage was detected in the A. borkumensis chromosome. The gene clusters that confer the assimilation of aliphatic hydrocarbons, are localized in two genome islands which were probably acquired from an ancestor of the Yersinia lineage, whereas the alk genes of Pseudomonas putida still exhibit the typical Alcanivorax oligonucleotide signature indicating a complex evolution of this major hydrocarbonoclastic trait.

The systematic comparison of transcriptional responses of organisms is a powerful tool in functional genomics. For example, mutants may be characterized by comparing their transcript profiles to those obtained in other experiments querying the effects on gene expression of many experimental factors including treatments, mutations and pathogen infections. Similarly, drugs may be discovered by the relationship between the transcript profiles effectuated or impacted by a candidate drug and by the target disease. The integration of such data enables systems biology to predict the interplay between experimental factors affecting a biological system. Unfortunately, direct comparisons of gene expression profiles obtained in independent, publicly available microarray experiments are typically compromised by substantial, experiment-specific biases. Here we suggest a novel yet conceptually simple approach for deriving 'Functional Association(s) by Response Overlap' (FARO) between microarray gene expression studies. The transcriptional response is defined by the set of differentially expressed genes independent from the magnitude or direction of the change. This approach overcomes the limited comparability between studies that is typical for methods that rely on correlation in gene expression. We apply FARO to a compendium of 242 diverse Arabidopsis microarray experimental factors, including phyto-hormones, stresses and pathogens, growth conditions/stages, tissue types and mutants. We also use FARO to confirm and further delineate the functions of Arabidopsis MAP kinase 4 in disease and stress responses. Furthermore, we find that a large, well-defined set of genes responds in opposing directions to different stress conditions and predict the effects of different stress combinations. This demonstrates the usefulness of our approach for exploiting public microarray data to derive biologically meaningful associations between experimental factors. Finally, our results indicate that FARO is more powerful in associating mutants in common pathways than existing methods such as co-expression analysis.

Background: It is well known that gene expression is dependent on chromatin structure in eukaryotes and it is likely that chromatin can play a role in bacterial gene expression as well. Here, we use a nucleosomal position preference measure of anisotropic DNA flexibility to predict highly expressed genes in microbial genomes. We compare these predictions with those based on codon adaptation index (CAI) values, and also with experimental data for 6 different microbial genomes, with a particular interest in experimental data from Escherichia coli. Moreover, position preference is examined further in 328 sequenced microbial genomes., Results: We find that absolute gene expression levels are correlated with the position preference in many microbial genomes. It is postulated that in these regions, the DNA may be more accessible to the transcriptional machinery. Moreover, ribosomal proteins and ribosomal RNA are encoded by DNA having significantly lower position preference values than other genes in fast-replicating microbes., Conclusion: This insight into DNA structure-dependent gene expression in microbes may be exploited for predicting the expression of non-translated genes such as non-coding RNAs that may not be predicted by any of the conventional codon usage bias approaches.

Signals from different oligonucleotide probes against the same target show great variation in intensities. However, detection of differences along a sequence e.g. to reveal intron/exon architecture, transcription boundary as well as simple absent/present calls depends on comparisons between different probes. It is therefore of great interest to correct for the variation between probes. Much of this variation is sequence dependent. We demonstrate that a thermodynamic model for hybridization of either DNA or RNA to a DNA microarray, which takes the sequence-dependent probe affinities into account significantly reduces the signal fluctuation between probes targeting the same gene transcript. For a test set of tightly tiled yeast genes, the model reduces the variance by up to a factor approximately 1/3. As a consequence of this reduction, the model is shown to yield a more accurate determination of transcription start sites for a subset of yeast genes. In another application, we identify present/absent calls for probes hybridized to the sequenced Escherichia coli strain O157:H7 EDL933. The model improves the correct calls from 85 to 95% relative to raw intensity measures. The model thus makes applications which depend on comparisons between probes aimed at different sections of the same target more reliable.

Background: Microarrays have recently emerged as a novel procedure to evaluate the genetic content of bacterial species. So far, microarrays have mostly covered single or few strains from the same species. However, with cheaper high-throughput sequencing techniques emerging, multiple strains of the same species are rapidly becoming available, allowing for the definition and characterization of a whole species as a population of genomes--the 'pan-genome'., Results: Using 32 Escherichia coli and Shigella genome sequences we estimate the pan- and core genome of the species. We designed a high-density microarray in order to provide a tool for characterization of the E. coli pan-genome. Technical performance of this pan-genome microarray based on control strain samples (E. coli K-12 and O157:H7) demonstrated a high sensitivity and relatively low false positive rate. A single-channel analysis approach is robust while allowing the possibility for deriving presence/absence predictions for any gene included on our pan-genome microarray. Moreover, the array was highly sufficient to investigate the gene content of non-pathogenic isolates, despite the strong bias towards pathogenic E. coli strains that have been sequenced so far., Conclusion: This high-density microarray provides an excellent tool for characterizing the genetic makeup of unknown E. coli strains and can also deliver insights into phylogenetic relationships. Its design poses a considerably larger challenge and involves different considerations than the design of single strain microarrays. Here, lessons learned and future directions will be discussed in order to optimize design of microarrays targeting entire pan-genomes.

We describe the design and evaluate the use of a high-density oligonucleotide microarray covering seven sequenced Escherichia coli genomes in addition to several sequenced E. coli plasmids, bacteriophages, pathogenicity islands, and virulence genes. Its utility is demonstrated for comparative genomic profiling of two unsequenced strains, O175:H16 D1 and O157:H7 3538 (Deltastx(2)::cat) as well as two well-known control strains, K-12 W3110 and O157:H7 EDL933. By using fluorescently labeled genomic DNA to query the microarrays and subsequently analyze common virulence genes and phage elements and perform whole-genome comparisons, we observed that O175:H16 D1 is a K-12-like strain and confirmed that its phi3538 (Deltastx(2)::cat) phage element originated from the E. coli 3538 (Deltastx(2)::cat) strain, with which it shares a substantial proportion of phage elements. Moreover, a number of genes involved in DNA transfer and recombination was identified in both new strains, providing a likely explanation for their capability to transfer phi3538 (Deltastx(2)::cat) between them. Analyses of control samples demonstrated that results using our custom-designed microarray were representative of the true biology, e.g., by confirming the presence of all known chromosomal phage elements as well as 98.8 and 97.7% of queried chromosomal genes for the two control strains. Finally, we demonstrate that use of spatial information, in terms of the physical chromosomal locations of probes, improves the analysis.

Background: Codon adaptation indices (CAIs) represent an evolutionary strategy to modulate gene expression and have widely been used to predict potentially highly expressed genes within microbial genomes. Here, we evaluate and compare two very different methods for estimating CAI values, one corresponding to translational codon usage bias and the second obtained mathematically by searching for the most dominant codon bias., Results: The level of correlation between these two CAI methods is a simple and intuitive measure of the degree of translational bias in an organism, and from this we confirm that fast replicating bacteria are more likely to have a dominant translational codon usage bias than are slow replicating bacteria, and that this translational codon usage bias may be used for prediction of highly expressed genes. By analyzing more than 300 bacterial genomes, as well as five fungal genomes, we show that codon usage preference provides an environmental signature by which it is possible to group bacteria according to their lifestyle, for instance soil bacteria and soil symbionts, spore formers, enteric bacteria, aquatic bacteria, and intercellular and extracellular pathogens., Conclusion: The results and the approach described here may be used to acquire new knowledge regarding species lifestyle and to elucidate relationships between organisms that are far apart evolutionarily.

Motivation: Array comparative genomic hybridization (CGH) allows detection and mapping of copy number of DNA segments. A challenge is to make inferences about the copy number structure of the genome. Several statistical methods have been proposed to determine genomic segments with different copy number levels. However, to date, no comprehensive comparison of various characteristics of these methods exists. Moreover, the segmentation results have not been utilized in downstream analyses., Results: We describe a comparison of three popular and publicly available methods for the analysis of array CGH data and we demonstrate how segmentation results may be utilized in the downstream analyses such as testing and classification, yielding higher power and prediction accuracy. Since the methods operate on individual chromosomes, we also propose a novel procedure for merging segments across the genome, which results in an interpretable set of copy number levels, and thus facilitate identification of copy number alterations in each genome., Availability: http://www.bioconductor.org

Two recent genome-scale analyses underscore the importance of DNA topology and chromatin structure in regulating transcription in Escherichia coli.

A method to predict lipoprotein signal peptides in Gram-negative Eubacteria, LipoP, has been developed. The hidden Markov model (HMM) was able to distinguish between lipoproteins (SPaseII-cleaved proteins), SPaseI-cleaved proteins, cytoplasmic proteins, and transmembrane proteins. This predictor was able to predict 96.8% of the lipoproteins correctly with only 0.3% false positives in a set of SPaseI-cleaved, cytoplasmic, and transmembrane proteins. The results obtained were significantly better than those of previously developed methods. Even though Gram-positive lipoprotein signal peptides differ from Gram-negatives, the HMM was able to identify 92.9% of the lipoproteins included in a Gram-positive test set. A genome search was carried out for 12 Gram-negative genomes and one Gram-positive genome. The results for Escherichia coli K12 were compared with new experimental data, and the predictions by the HMM agree well with the experimentally verified lipoproteins. A neural network-based predictor was developed for comparison, and it gave very similar results. LipoP is available as a Web server at www.cbs.dtu.dk/services/LipoP/.