Genome-Wide Profiling of Pluripotent Cells Reveals a Unique Molecular Signature of Human Embryonic Germ Cells

Human embryonic germ cells (EGCs) provide a powerful model for identifying molecules involved in the pluripotent state when compared to their progenitors, primordial germ cells (PGCs), and other pluripotent stem cells. Microarray and Principal Component Analysis (PCA) reveals for the first time that human EGCs possess a transcription profile distinct from PGCs and other pluripotent stem cells. Validation with qRT-PCR confirms that human EGCs and PGCs express many pluripotency-associated genes but with quantifiable differences compared to pluripotent embryonic stem cells (ESCs), induced pluripotent stem cells (IPSCs), and embryonal carcinoma cells (ECCs). Analyses also identified a number of target genes that may be potentially associated with their unique pluripotent states. These include IPO7, MED7, RBM26, HSPD1, and KRAS which were upregulated in EGCs along with other pluripotent stem cells when compared to PGCs. Other potential target genes were also found which may contribute toward a primed ESC-like state. These genes were exclusively up-regulated in ESCs, IPSCs and ECCs including PARP1, CCNE1, CDK6, AURKA, MAD2L1, CCNG1, and CCNB1 which are involved in cell cycle regulation, cellular metabolism and DNA repair and replication. Gene classification analysis also confirmed that the distinguishing feature of EGCs compared to ESCs, ECCs, and IPSCs lies primarily in their genetic contribution to cellular metabolism, cell cycle, and cell adhesion. In contrast, several genes were found upregulated in PGCs which may help distinguish their unipotent state including HBA1, DMRT1, SPANXA1, and EHD2. Together, these findings provide the first glimpse into a unique genomic signature of human germ cells and pluripotent stem cells and provide genes potentially involved in defining different states of germ-line pluripotency

Temporal Profiling of the Secretome during Adipogenesis in Humans

Adipose tissue plays a key role as a fat-storage depot and as an endocrine organ. Although mouse adipogenesis has been studied extensively, limited studies have been conducted to characterize this process in humans. We carried out a temporal proteomic analysis to interrogate the dynamic changes in the secretome of primary human preadipocytes as they differentiate into mature adipocytes. Using iTRAQ-based quantitative proteomics, we identified and quantified 420 proteins from the secretome of differentiated human adipocytes. Our results revealed that the majority of proteins showed differential expression during the course of differentiation. In addition to adipokines known to be differentially secreted in the course of adipocyte differentiation, we identified a number of proteins whose dynamic expression in this process has not been previously documented. They include collagen triple helix repeat containing 1, cytokine receptor-like factor 1, glypican-1, hepatoma-derived growth factor, SPARC related modular calcium binding protein 1, SPOCK 1, and sushi repeat-containing protein. A bioinformatics analysis using Human Protein Reference Database and Human Proteinpedia revealed that of the 420 proteins identified, 164 proteins possess signal peptides and 148 proteins are localized to the extracellular compartment. Additionally, we employed antibody arrays to quantify changes in the levels of 182 adipokines during human adipogenesis. This is the first large-scale quantitative proteomic stud

Multiomics links global surfactant dysregulation with airflow obstruction and emphysema in COPD

RATIONALE: Pulmonary surfactant is vital for lung homeostasis as it reduces surface tension to prevent alveolar collapse and provides essential immune-regulatory and antipathogenic functions. Previous studies demonstrated dysregulation of some individual surfactant components in COPD. We investigated relationships between COPD disease measures and dysregulation of surfactant components to gain new insights into potential disease mechanisms. METHODS: Bronchoalveolar lavage proteome and lipidome were characterised in ex-smoking mild/moderate COPD subjects (n=26) and healthy ex-smoking (n=20) and never-smoking (n=16) controls using mass spectrometry. Serum surfactant protein analysis was performed. RESULTS: Total phosphatidylcholine, phosphatidylglycerol, phosphatidylinositol, surfactant protein (SP)-B, SP-A and SP-D concentrations were lower in COPD versus controls (log2 fold change (log2FC) -2.0, -2.2, -1.5, -0.5, -0.7 and -0.5 (adjusted p<0.02), respectively) and correlated with lung function. Total phosphatidylcholine, phosphatidylglycerol, phosphatidylinositol, SP-A, SP-B, SP-D, napsin A and CD44 inversely correlated with computed tomography small airways disease measures (expiratory to inspiratory mean lung density) (r= -0.56, r= -0.58, r= -0.45, r= -0.36, r= -0.44, r= -0.37, r= -0.40 and r= -0.39 (adjusted p<0.05)). Total phosphatidylcholine, phosphatidylglycerol, phosphatidylinositol, SP-A, SP-B, SP-D and NAPSA inversely correlated with emphysema (% low-attenuation areas): r= -0.55, r= -0.61, r= -0.48, r= -0.51, r= -0.41, r= -0.31 and r= -0.34, respectively (adjusted p<0.05). Neutrophil elastase, known to degrade SP-A and SP-D, was elevated in COPD versus controls (log2FC 0.40, adjusted p=0.0390), and inversely correlated with SP-A and SP-D. Serum SP-D was increased in COPD versus healthy ex-smoking volunteers, and predicted COPD status (area under the curve 0.85). CONCLUSIONS: Using a multiomics approach, we demonstrate, for the first time, global surfactant dysregulation in COPD that was associated with emphysema, giving new insights into potential mechanisms underlying the cause or consequence of disease

Systems biology approaches applied to regenerative medicine

Systems biology is the creation of theoretical and mathematical models for the study of biological systems, as an engine for hypothesis generation and to provide context to experimental data. It is underpinned by the collection and analysis of complex datasets from different biological systems, including global gene, RNA, protein and metabolite profiles. Regenerative medicine seeks to replace or repair tissues with compromised function (for example, through injury, deficiency or pathology), in order to improve their functionality. In this paper, we will address the application of systems biology approaches to the study of regenerative medicine, with a particular focus on approaches to study modifications to the genome, transcripts and small RNAs, proteins and metabolites

Human Protein Reference Database—2009 update

Human Protein Reference Database (HPRD—http://www.hprd.org/), initially described in 2003, is a database of curated proteomic information pertaining to human proteins. We have recently added a number of new features in HPRD. These include PhosphoMotif Finder, which allows users to find the presence of over 320 experimentally verified phosphorylation motifs in proteins of interest. Another new feature is a protein distributed annotation system—Human Proteinpedia (http://www.humanproteinpedia.org/)—through which laboratories can submit their data, which is mapped onto protein entries in HPRD. Over 75 laboratories involved in proteomics research have already participated in this effort by submitting data for over 15 000 human proteins. The submitted data includes mass spectrometry and protein microarray-derived data, among other data types. Finally, HPRD is also linked to a compendium of human signaling pathways developed by our group, NetPath (http://www.netpath.org/), which currently contains annotations for several cancer and immune signaling pathways. Since the last update, more than 5500 new protein sequences have been added, making HPRD a comprehensive resource for studying the human proteome

Quantitative Proteomic Analysis of Human Embryonic Stem Cell Differentiation by 8-Plex iTRAQ Labelling

Analysis of gene expression to define molecular mechanisms and pathways involved in human embryonic stem cells (hESCs) proliferation and differentiations has allowed for further deciphering of the self-renewal and pluripotency characteristics of hESC. Proteins associated with hESCs were discovered through isobaric tags for relative and absolute quantification (iTRAQ). Undifferentiated hESCs and hESCs in different stages of spontaneous differentiation by embryoid body (EB) formation were analyzed. Using the iTRAQ approach, we identified 156 differentially expressed proteins involved in cell proliferation, apoptosis, transcription, translation, mRNA processing, and protein synthesis. Proteins involved in nucleic acid binding, protein synthesis, and integrin signaling were downregulated during differentiation, whereas cytoskeleton proteins were upregulated. The present findings added insight to our understanding of the mechanisms involved in hESC proliferation and differentiation

Addressing statistical biases in nucleotide-derived protein databases for proteogenomic search strategies

[Image: see text] Proteogenomics has the potential to advance genome annotation through high quality peptide identifications derived from mass spectrometry experiments, which demonstrate a given gene or isoform is expressed and translated at the protein level. This can advance our understanding of genome function, discovering novel genes and gene structure that have not yet been identified or validated. Because of the high-throughput shotgun nature of most proteomics experiments, it is essential to carefully control for false positives and prevent any potential misannotation. A number of statistical procedures to deal with this are in wide use in proteomics, calculating false discovery rate (FDR) and posterior error probability (PEP) values for groups and individual peptide spectrum matches (PSMs). These methods control for multiple testing and exploit decoy databases to estimate statistical significance. Here, we show that database choice has a major effect on these confidence estimates leading to significant differences in the number of PSMs reported. We note that standard target:decoy approaches using six-frame translations of nucleotide sequences, such as assembled transcriptome data, apparently underestimate the confidence assigned to the PSMs. The source of this error stems from the inflated and unusual nature of the six-frame database, where for every target sequence there exists five “incorrect” targets that are unlikely to code for protein. The attendant FDR and PEP estimates lead to fewer accepted PSMs at fixed thresholds, and we show that this effect is a product of the database and statistical modeling and not the search engine. A variety of approaches to limit database size and remove noncoding target sequences are examined and discussed in terms of the altered statistical estimates generated and PSMs reported. These results are of importance to groups carrying out proteogenomics, aiming to maximize the validation and discovery of gene structure in sequenced genomes, while still controlling for false positives

Correction: Exome Sequencing in an Admixed Isolated Population IndicatesNFXL1 Variants Confer a Risk for Specific Language Impairment

Children affected by Specific Language Impairment (SLI) fail to acquire age appropriate language skills despite adequate intelligence and opportunity. SLI is highly heritable, but the understanding of underlying genetic mechanisms has proved challenging. In this study, we use molecular genetic techniques to investigate an admixed isolated founder population from the Robinson Crusoe Island (Chile), who are affected by a high incidence of SLI, increasing the power to discover contributory genetic factors. We utilize exome sequencing in selected individuals from this population to identify eight coding variants that are of putative significance. We then apply association analyses across the wider population to highlight a single rare coding variant (rs144169475, Minor Allele Frequency of 4.1% in admixed South American populations) in the NFXL1 gene that confers a nonsynonymous change (N150K) and is significantly associated with language impairment in the Robinson Crusoe population (p = 2.04 × 10–4, 8 variants tested). Subsequent sequencing of NFXL1 in 117 UK SLI cases identified four individuals with heterozygous variants predicted to be of functional consequence. We conclude that coding variants within NFXL1 confer an increased risk of SLI within a complex genetic model