Individuals carrying the derived T alleles have higher IQGAP1 expression in the brain as compared to the ancestral A allele carriers. We observed a significant and male-specific association between rs1042538 and tactile performances in two independent cohorts. Males with the derived allele displayed higher tactual performances as compared to those with the ancestral allele. Furthermore, we found a highly diverged allele-frequency distribution of rs1042538 among world human populations, likely caused by natural selection and/or recent population expansion. These results suggest that current human populations still carry sequence variations that affect cognitive performances and that these genetic variants may likely have been subject to comparatively recent natural selection.As a product of the unique evolution of the human brain, human cognitive performance is largely a collection of heritable traits. Rather surprisingly, to date there have been no reported cases to highlight genes that underwent adaptive evolution in humans and which carry polymorphisms that have a marked effect on cognitive performance. IQ motif containing GTPase activating protein 1 (IQGAP1), a scaffold protein, affects learning and memory in a dose-dependent manner. Its expression is regulated by miR-124 through the binding sites in the 3′UTR, where a SNP (rs1042538) exists in the core-binding motif. Here we showed that this SNP can influence the miR-target interaction both  Hence, it may affect the binding affinity of miR-124, and eventually lead to possible functional consequences.MicroRNAs (miRNAs) are endogenous ∼21 nt RNAs that play important roles in a variety of biological processes in vitro experiment showed that the reporter gene bearing the 3′UTR of IQGAP1 could be down-regulated by miR-124 MiR-124 is one of the most conserved and abundantly expressed neuron specific miRNAs. It plays a critical role in neuronal differentiation and proper nervous system development in vitro and in vivo. Results of our analysis showed that this was indeed the case, so we opted to further see if there was a connection between this SNP and cognitive performance. An analysis of two independent Chinese cohorts showed a significant association between this SNP and cognitive performance in males, indicating that rs1042538 does have some functional role to play in cognitive ability. Finally, we examined the evolutionary history of rs1042538, we found a high level population differentiation of allele frequency, and we demonstrated that the genomic region containing rs1042538 is likely subject to recent positive selection.Based on these previous observations, we hypothesized that the presence of the SNP rs1042538 might alter miR-124's regulation of IQGAP1, and in doing so, exert some effect on cognitive performance across human populations. To test this supposition, we first tested whether this SNP affects miR-124 IQGAP1 interaction We cloned IQGAP1 3′UTR fragment of 975 bp covering three putative miR-124 binding sites and inserted it into the downstream of firefly luciferase reporter gene. In brief, we amplified the 3′UTR fragment from the human genomic DNA by PCR. The PCR product, which contained the primer-introduced Bgl Π and Xba Ι sites, was digested, purified, and cloned into pGL 3 firefly luciferase reporter plasmid. Finally, we created three reporter gene constructs: (1) IQGAP1 3′UTR with the ancestral allele (rs1042538/A), (2) IQGAP1 3′UTR with the derived allele (rs1042538/T), (3) IQGAP1 3′UTR with the site-directed A to T mutation at the rs1042538 site. The sequences of the constructs were confirmed by Sanger sequencing.The miR-124 and control miRNA duplexes were synthesized in Shanghai GenePharma. The duplexes sequences were as follows:miR-124 . When cells were grown to a confluence of 40–60% in 24-well plates, they were transfected with 100 ng pGL3 firefly luciferase report plasmid, 200 ng pRL-TK renilla luciferase plasmid and 20 pmol miRNA using Lipofectamine 2000 . All experiments were performed in quadruplicate. The activities of the two luciferases were measured 36 h after transfection using the Dual-Luciferase Reporter Assay System . The firefly activity has been normalized to renilla.−ΔCt method.DNA was extracted from 60 frozen human parietal cortex tissues with proteinase-K-chloroform method. Next, rs1042538 was genotyped using the SNaPshot method . Total RNA was extracted using TRIzol . Reverse transcription was performed using the miScript PCR Starter Kit . Real-time quantitative PCR was performed using gene specific primers, and the fold change of gene expression levels was calculated using the Double standard curve method. The GAPDH was used as the internal control. Mature miRNA expression was quantified using SYBR Green master mix  and miR Reverse Primer Kit . Small nuclear RNA U6 snRNA was used as internal control. The relative quantification was calculated using the 2Total proteins were extracted using RIPA lysis buffer, and quantified using a Pierce bicinchoninic acid protein assay. Proteins were analyzed by western blot with antibodies against IQGAP1  or actin . Immunoreactivity was detected with a chemiluminescence system. The band intensity was analyzed using ImageJ analyzer software.We recruited 195  healthy undergraduate students from Qujing Normal University to participate in three sub-tests of Chinese Wechsler Memory Scale-revised (WMS-CR). The mean age of the participants was 20.88±1.53 y (range from 18 to 25). Most participants (96%) are Han Chinese and few participants (4%) are Chinese ethnic minority (CEM), all self-reported as having no neurological or psychiatric history. For replication test, we recruited an independent cohort from Liaoning Normal University, including 265  individuals, with a mean age of 19±0.96 y (range from 16 to 23). All DNA samples were extracted from blood. Genotyping of rs1042538 was conducted using the SNaPshot method And the Hardy-Weinberg equilibrium of this SNP was assessed using Haploview (version 4.2) http://cbbc.scuec.edu.cn, Wuhan, China). According to the protocol of CBBC, written informed consent for brain autopsy and use of the brain tissue for research was obtained from either the donors or their relatives. These donors did not have neurological disease. The sample information is given in Human brain tissues were provided by Chinese Brain Bank Center .We used WMS-CR to measure memory functions http://hgdp.uchicago.edu). For 1000 Human Genome data analyses, we obtained the resequencing data of 460 individuals for the surrounding regions of rs1042538 (chr15:91044408) from the 1000-Human-Genome Project website (http://www.1000genomes.org). Individuals from three population groups were analyzed: Europeans (CEU); East Asians (ESA)—which includes Han Chinese in Beijing (CHB), Southern Han Chinese (CHS) and Japanese in Tokyo (JPT)—and Yoruba in Ibadan (YRI). Neutrality test was conducted with DnaSP 5.10 Global distributions of rs1042538 in major world populations were extracted from the HGDP Selection Browser , we measured the mature miR-124 expression and IQGAP1 expression at both mRNA and protein levels. We found that miR-124 was equally expressed in both genotypes  from Qujing Normal University in southwestern China. We genotyped these individuals for the rs1042538 SNP, and we identified 60 AA homozygotes, 91 AT heterozygotes and 44 TT homozygotes . The genAs such a small sample can often lead to confounding results or false positives, to replicate and verify the initial findings, we recruited an independent cohort of 265 college students  from Liaoning Normal University of northeastern China. In this sample, we identified 80 AA homozygotes, 127 A/T heterozygotes and 58 TT homozygotes , leavingIn order to further understand the evolutionary history of rs1042538, we first examined the allele frequency distribution of rs1042538 among global populations. We found large allelic differences among 53 different populations . GeneralPreviously, several SNPs such as rs363039 and rs17070145, which are located at introns, were shown to have some association with human cognition There is one puzzling factor that deserves mention. The observed gender dependent association of tactual performance is rather unusual, because our findings would seem to imply that the manifestation of variations for cognitive performances such as spatial abilities may differ between males and females. One possible explanation may be that numerous studies have confirmed that hormone levels have a strong impact on learning and memory The diverged allele frequency distribution of rs1042538 is intriguing. We observed an ESA specific haplotype, which suggests a recent expansion of this haplotype containing the derived T allele of rs1042538 among East Asian populations. We also observed a higher EHH value for the derived T allele in multiple populations including those from ESA, a signature of recent positive selection on this sequence variation. The observed higher tactual performance by those with the derived T allele provides a possible driving force if Darwinian positive selection has been acting on this SNP in East Asians. Interestingly, another report showed that the derived T allele of this SNP was also associated with a lower risk of developing breast cancer In conclusion, our work showed that a SNP residing in the IQGAP1 3′UTR miRNA binding site can alter the affinity of miRNA binding. This SNP is likely a target of positive selection in East Asian populations, and it is associated with cognition performance at least among Chinese populations. Given the abundant SNPs that are capable of either creating or destroying putative miRNA target sites Figure S1Comparison of IQGAP1 expression at protein level between AA and TT genotype in human brain parietal cortex tissues.(DOCX)Click here for additional data file.Figure S2The score distributions of three sub-tests.(DOCX)Click here for additional data file.Table S1Information of human brain tissues.(DOCX)Click here for additional data file.Table S2Details of genotype and phenotype data.(XLSX)Click here for additional data file.Table S3Nucleotide diversity and neutrality tests for IQGAP1 (covering rs1042538) in human populations.(DOCX)Click here for additional data file.


Mitochondrial reactive oxygen species (ROS) production and detoxification are tightly balanced. Shifting this balance enables ROS to activate intracellular signaling and/or induce cellular damage and cell death. Increased mitochondrial ROS production is observed in a number of pathological conditions characterized by mitochondrial dysfunction. One important hallmark of these diseases is enhanced glycolytic activity and low or impaired oxidative phosphorylation. This suggests that ROS is involved in glycolysis (dys)regulation and vice versa. Here we focus on the bidirectional link between ROS and the regulation of glucose metabolism. To this end, we provide a basic introduction into mitochondrial energy metabolism, ROS generation and redox homeostasis. Next, we discuss the interactions between cellular glucose metabolism and ROS. ROS-stimulated cellular glucose uptake can stimulate both ROS production and scavenging. When glucose-stimulated ROS production, leading to further glucose uptake, is not adequately counterbalanced by (glucose-stimulated) ROS scavenging systems, a toxic cycle is triggered, ultimately leading to cell death. Here we inventoried the various cellular regulatory mechanisms and negative feedback loops that prevent this cycle from occurring. It is concluded that more insight in these processes is required to understand why they are (un)able to prevent excessive ROS production during various pathological conditions in humans. These two molecules serve as electron donors for mitochondrial complex I (CI or NADH:ubiquinone oxidoreductase) and complex II (CII or succinate:ubiquinone oxidoreductase) of the electron transport chain (ETC). The electrons are subsequently transported by ubiquinone to complex III (CIII or ubiquinol:cytochrome-c oxidoreductase) and by cytochrome-c to complex IV (CIV or cytochrome-c oxidase) where they react with oxygen to form water. At CI, CIII and CIV protons are expelled from the mitochondrial matrix across the mitochondrial inner membrane (MIM). This results in establishment of an inward-directed proton motive force (PMF) that consists of a chemical (ΔpH) and electrical (Δψ) component (Mitchell 1Fo-ATP synthase), protons are allowed to flow back into the matrix to fuel generation of ATP from ADP and inorganic phosphate (Pi). Together with the ETC, CV constitutes the mitochondrial oxidative phosphorylation (OXPHOS) system.Mitochondria are among the prime ATP-generating organelles, which are necessary for cellular functioning  site  ROS production appears to be much lower , an enzyme that is localized in the mitochondrial matrix and rapidly converts superoxide to hydrogen peroxide. This conversion is also catalyzed by the copper/zinc-dependent superoxide dismutase (Cu/ZnSOD or SOD1), which is localized in the cytosol, nucleus and mitochondrial intermembrane space Murphy . In turn−, known as S-oxidation or sulfenylation)  to sulfinic acid (–SO2H) and sulfonic acid (–SO3H). In case of CI, such over-oxidation is associated with irreversible deactivation of CI . In principle, superoxide can react with protein iron–sulfur (Fe–S) clusters  of HIF-1α are hydroxylated by prolyl-4-hydroxylases  appears to be involved in HIF-1α stabilization by mitochondrial ROS in Hep3B cells Fig. . CompatiThe cellular capacity for glucose uptake is co-determined by the abundance of functional GLUTs at the plasma membrane. This means that glucose uptake can be regulated by GLUT trafficking between the cytosol and the plasma membrane. During exercise, muscle contraction is associated with increased ROS levels, believed to represent a fast adaptive response to an increase in energy demand  can be modulated by activation or deactivation of GLUTs at the plasma membrane. A number of metabolic inhibitors and AMPK activators acutely stimulate glucose uptake without increasing the amount of GLUT molecules at the plasma membrane  and represents a relatively fast mechanism that allows the cells to cope with metabolic stress Fig. . In addiThe above evidence supports the conclusion that increased ROS levels stimulate cellular glucose uptake both at slow and fast time scales. However, inhibition of GLUT1 activity in myoblasts was paralleled by increased ROS levels  displayed GLUT1 up-regulation and increased NADPH and GSH levels  conditions favor activation of a self-amplifying cycle of glucose uptake and glucose-stimulated ROS production, ultimately leading to cell death. Glucose-stimulated ROS production might be counterbalanced by the combined action of endogenous antioxidant systems Sect.  and glucIn principle, ETC electron input can be reduced by lowering cellular glucose uptake. A high extracellular glucose concentration triggers a rapid reduction in GLUT1 levels at the plasma membrane, without affecting their total cellular levels  enhanced oxidative stress and cell death in tumor cells  can play a role. Therefore, every mechanism that reduces proton influx or increases proton efflux into the MIM, when not counterbalanced, stimulates  Δψ depolarization. In this sense, Δψ depolarization can be induced by ETC inhibition, CV stimulation (increased coupling efficiency) and/or increased trans-MIM proton leak (uncoupling). The latter is mediated by mitochondrial uncoupling proteins (UCPs) 1-3  Fig. . More re187, Cys206, Cys425) and 75-kDa (NDUFS1) subunit (Cys367 Cys531 Cys704 Cys226 Cys727), which can be glutathionylated and thereby diminish the activity of CI  has also been described as a mechanism to depolarize Δψ and lower ROS production Fig. . RecruitROS are produced as a consequence of normal mitochondrial energy metabolism. When transiently and/or moderately increased, ROS can activate signaling pathways involved in cellular adaptation to various types of (metabolic) stress. One of these pathways is the stimulation of glucose uptake. When ROS levels are too high and/or remain increased during a prolonged period of time, a vicious circle of ROS-stimulated glucose uptake and glucose-stimulated ROS production can be triggered. This pathological cycle can be broken by restoring mitochondrial ROS production to normal levels. We presented three major mechanisms that, in principle, can lower mitochondrial ROS production: (1) reducing glucose uptake, (2) increasing lactate secretion and (3) depolarization of Δψ. Unfortunately, these mechanisms have also been associated with increases in ROS and/or appear to be not effective in all experimental models. Undesirable side effects include reduced NADPH production during reduced glucose uptake, a high rate of lactate secretion potentially inducing lactic acidosis and induction of mitochondrial dysfunction and apoptosis by (high-magnitude) and/or prolonged Δψ depolarization. We conclude that cellular glucose metabolism and mitochondrial ROS production are coupled by various signaling mechanisms, which need to be controlled by the cell to avoid oxidative stress. A more detailed understanding of how these pathways interact with mitochondrial ROS production, endogenous antioxidant systems and mitochondrial/cellular function is required to explain why oxidative stress induction still appears to contribute to pathology induction in humans .


Ultra-conserved genes or elements (UCGs/UCEs) in the human genome are extreme examples of conservation. We characterized natural variations in 2884 UCEs and UCGs in two distinct populations; Singaporean Chinese (n = 280) and Italian (n = 501) by using a pooled sample, targeted capture, sequencing approach. We identify, with high confidence, in these regions the abundance of rare SNVs (MAF<0.5%) of which 75% is not present in dbSNP137. UCEs association studies for complex human traits can use this information to model expected background variation and thus necessary power for association studies. By combining our data with 1000 Genome Project data, we show in three independent datasets that prevalent UCE variants (MAF>5%) are more often found in relatively less-conserved nucleotides within UCEs, compared to rare variants. Moreover, prevalent variants are less likely to overlap transcription factor binding site. Using SNPfold we found no significant influence of RNA secondary structure on UCE conservation. All together, these results suggest UCEs are not under selective pressure as a stretch of DNA but are under differential evolutionary pressure on the single nucleotide level. Evolutionary conservation has been a good measure to identify potentially important regions in DNA and protein primary sequences in cis in clusters spanning hundreds of kb's The extreme conservation of UCEs reflects a strong negative selective pressure on these regions Indeed, a different line of evidence suggests that UCEs produce functional non-coding RNAs UCEs have been shown to be under negative selection in the human population, since they are relatively devoid of common SNPs, and are depleted among segmental duplications and copy number variations We used 280 DNA samples from ethnic Chinese  from the Singapore Prospective Study Program (SP2) Our UCEs selection combined the regions from three different studies- From the Singapore Chinese samples we created 18 pools. Each pool contained 14–16 samples. From the Italian female samples we created 48 total pools, 10–11 samples per pool. The DNA concentration of each individual sample was determined by qPCR (Singapore Chinese samples) or by NanoDrop instrument . Samples were added in equal molar concentrations of DNA in pools to obtain a final pool DNA amount of 1 µg per pool. Pools were then carried through the standard Illumina library preparation process. Briefly, the genomic DNA in the pools was sheared using Covaris S2, followed by end repair, A-tailing and ligation of unique Illumina indexes for each pool (New England Biolabs enzymes were used).Prepared libraries were combined in equal amounts (as determined by qPCR with adapter primers) and captured using Roche NimbleGen custom designed SeqCap EZ Library solution-based capture reactions and the recommended protocol. The total captured genomic region was ∼1.39 Mb. http://picard.sourceforge.net). Thereafter base quality score recalibration and realignment of the reads around the indels was performed using tools BaseRecalibrator and IndelRealigner form the GATK package Reads from the pools were aligned to the UCSC human reference genome (hg19) using BWA aligner (version 0.5.6) with default parameters http://hgdownload.cse.ucsc.edu/goldenPath/hg19/phyloP46way/) through UCSC public MySQL server using hgWiggle.The 46-way placental alignment phyloP conservation scores were retrieved from the UCSC Genome archive .Super-enhancer regions were obtained from the study by Whyte et.al http://rth.dk/resources/rnasnp/).RNA secondary structure predictions were made by RNAsnp perl script which allows large-scale analysis All statistical calculations and figures were produced using R and its packages.We analyzed single nucleotide variations (SNVs) within 2884 UCE regions that span ∼1.39 Mb of the human genome . In ordeFor variant calling, we used two independent variant calling programs, namely CRISP Within the targeted regions from the SG-CHN and ITA cohorts, we detected about 15.1 and 12.4 SNVs per one Mb of targeted region per sample, respectively . In ordeInitial sets of UCEs were discovered by using the program PhastCons that finds conserved elements in multiple genome alignments Boundaries of UCEs are defined as a decline in the PhastCons conservation score. We excluded the possibility that prevalent SNVs are clustered closer to UCE boundaries by plotting the distance of each variant from its host UCEs start position . This anInterestingly, rare SNVs also seem to occur in slightly less conserved positions compared to the random UCEs positions . UCEs inTo determine whether the pattern of conservation of the rare and prevalent SNVs were unique to that position, or reflected a selective pressure on the local nucleotide composition, we determined the PhyloP score for the nucleotides immediately upstream or downstream of the identified SNVs. The neighboring nucleotides of prevalent SNVs are clearly more constrained . Taken tPrevalent variations within UCEs may be tolerated because they have lower functional impact and hence these variations may spread in the population. UCEs are described to act as enhancers Next, we were curious to see whether the conservation score of SNVs within the non-constraint regulatory elements follows the same pattern as we have noticed for the UCEs. Super-Enhancers (SE) are densely occupied by TF and the Mediator co-activator A recent study showed that UCE are proposed to act as transcription factor binding “hubs” that contain multiple overlapping TFBS and this may count for the UCEs conservation As enhancers, UCEs can also be transcribed to produce ncRNA The most striking feature of UCEs is the presence of so many consecutive conserved nucleotides. We can speculate that different positions in the UCEs are under different levels of selection. Thus, some positions may be neutral and with no or little effect on fitness. Indeed, we noticed that prevalent SNVs in the UCEs have in general lower phyloP score  compared to the rare SNVs. Importantly, the same trend was true regardless of the analyzed population . This inDoes the conservation reflect the functional importance of each particular nucleotide? First of all, we noticed that UCEs contain an abundance of rare SNVs, 63–74% of all called variants have MAF less then 0.5% . One expet. al that shows overlapping TFBS within their tested UCEs are more stringently conserved Our findings that prevalent SNVs are depleted for TFBS  support Our study is the first that has specifically characterized natural variations in UCEs at this scale. There is emerging evidence that the non-coding genome, including regulatory regions, contribute to complex traits Why are UCEs so ultra conserved? We show a clear selective pressure that correlates with phyloP score, indicating that the pressures that were present during evolution of vertebrates were still relevant, at least until very recently, in the human population, with regard to UCEs. Although there is a clear signal indicating the importance of TF binding in UCEs, the density of in vivo validated TFBS in UCEs or the selection against higher conserved sites in prevalent SNVs, do not explain their conservation. Although production of functional RNA from UCEs is an attractive model for additional selection pressure parallel or synergistic with pressure to bind TF, we could not confirm a role of secondary RNA structure in our data. Better RNA prediction algorithms and/or in vivo structure studies of nuclear noncoding, low abundant RNAs are required to thoroughly address this question.Figure S1Comparison of SNVs called by CRISP and GATK. SNVs from the (A) SG-CHN and (B) ITA populations were called by programs CRISP and GATK (and GATK . The ove(EPS)Click here for additional data file.Figure S2Prevalent and rare SNVs are randomly distributed across the UCE sequence. Black dots represent the distance (y-axis) of each UCE nucleotide and its corresponding phyloP score (x-axis) as the percentage from the start point of the UCE. UCE start is defined as 0% and end as 100%. UCE flanks  represent upstream (100–200%) and downstream (−100–0%) regions from the UCE end and start, respectively. Location of prevalent and rare SNVs and their corresponding phyloP scores from the (A) 1 KG, (B) SG-CHN and (C) ITA populations are shown as green and red dots, respectively. UCE start and end coordinates are shown in the (EPS)Click here for additional data file.Figure S3Neighboring positions of prevalent SNVs are more constraint. Cumulative fraction of phyloP scores of prevalent (MAF>5%) and rare (MAF<0.5%) SNVs from the (A) ITA, (B) SG-CHN and (C) 1 KG populations are shown as black and green lines, respectively. Upstream and downstream regions are defined as the three bp windows from the corresponding SNVs. Brown and red lines represent the cumulative faction of phyloP scores of the prevalent SNVs upstream and downstream regions, respectively. Orange and purple lines represent the cumulative faction of phyloP scores of the rare SNVs upstream and downstream regions, respectively. Shaded grey area represents 95% confidence interval (obtained by bootstrapping) of random UCE positions (blue line).(EPS)Click here for additional data file.Figure S4Prediction of SNVs effects on the local RNA secondary structure.(A) Analysis of prevalent and rare variants from all three data sets. (B) Analysis of rare most conserved (phyloP score>2) and least conserved (phyoP score <2) SNVs. y-axis represents RNAsnp (EPS)Click here for additional data file.Table S1Genomic coordinates (hg19) of analysed UCEs. Excel sheet containing genomic coordinates of analysed UCEs, including information about overlap with UCSC Genes 5′UTR, 3′UTR and exons.(XLSX)Click here for additional data file.Table S2General characteristics of sequenced sample pools. This excel sheet contains following information for each sequenced pool: mapped reads on target, average sequencing depth, average depth per allele, % of alleles covered> = 5X.(XLSX)Click here for additional data file.


To understand cardiac and skeletal muscle function, it is important to define and explore their molecular constituents and also to identify similarities and differences in the gene expression in these two different striated muscle tissues. Here, we have investigated the genes and proteins with elevated expression in cardiac and skeletal muscle in relation to all other major human tissues and organs using a global transcriptomics analysis complemented with antibody-based profiling to localize the corresponding proteins on a single cell level.Our study identified a comprehensive list of genes expressed in cardiac and skeletal muscle. The genes with elevated expression were further stratified according to their global expression pattern across the human body as well as their precise localization in the muscle tissues. The functions of the proteins encoded by the elevated genes are well in line with the physiological functions of cardiac and skeletal muscle, such as contraction, ion transport, regulation of membrane potential and actomyosin structure organization. A large fraction of the transcripts in both cardiac and skeletal muscle correspond to mitochondrial proteins involved in energy metabolism, which demonstrates the extreme specialization of these muscle tissues to provide energy for contraction.Our results provide a comprehensive list of genes and proteins elevated in striated muscles. A number of proteins not previously characterized in cardiac and skeletal muscle were identified and localized to specific cellular subcompartments. These proteins represent an interesting starting point for further functional analysis of their role in muscle biology and disease.The online version of this article (doi:10.1186/s12864-015-1686-y) contains supplementary material, which is available to authorized users. Cardiac and skeletal muscles are both striated muscles composed of repeated units called sarcomeres, crossed with a regular pattern of fine red and white lines giving the muscles their distinctive striated appearance and their name. The cells are rich in mitochondria and contain to a large extent myosin and actin proteins, signifying different regions of the sarcomeres. While skeletal muscle consists of parallel linear fibers, the cardiac muscle cells (cardiomyocytes) are arranged in fibers exhibiting cross-striations formed by alternating segments of thick and thin protein filaments. For rhythmical and synchronized contraction, cardiomyocytes form a functional syncytium via intercalated discs, where the membranes of adjacent cells are situated closely together. Intercalated discs are unique for the heart and visible as clearly distinguishable bands between cardiomyocytes. In addition to muscle fibers and vasculature, the heart also includes streaks of connective tissue and cuffs of adipose tissue surrounding the smaller vessels. Skeletal muscles consist of large multinucleated myocytes called syncytia, formed during development via fusion of myotubes. There are two main muscle fiber types (slow type I and fast type II) depending on the dominant type of myosin present. Skeletal muscles are attached to bone and contract voluntarily (via nerve stimulation) as opposed to cardiac muscle and smooth muscle. In addition to the muscle fibers, skeletal muscle samples also contain streaks of adipose tissue and connective tissue with fibroblasts. Skeletal muscle is highly vascularized with a fine network of capillary endothelial cells running in between the fibers.Detailed knowledge of the molecular constituents of striated muscles under normal conditions is essential to understand the cellular interactions in health and disease. Thus far, several transcriptomics signatures on diseased hearts have been performed, primarily using animal models or human serum –3. TheseHere, we generated next generation sequencing (RNA-seq) data for skeletal muscle tissue and performed an extended analysis based on the RNA-seq data of 28 different tissues involving 100 samples, including four and five individual samples from cardiac and skeletal muscle, respectively. This approach has been used for identifying a comprehensive list of several hundred genes elevated in striated muscles as compared to other analyzed tissues, representing all major organs in the human body. Subsequently, an antibody-based approach using tissue microarrays and immunohistochemistry was used to localize the elevated proteins to different subcompartments of heart and skeletal muscle on a single cell level.A transcriptomic analysis was performed using deep sequencing (RNA-seq) on five skeletal muscle samples. These were compared with our previously reported transcriptomic analysis on 27 fresh frozen tissue types including four heart muscle samples . This reThe variance between muscle samples from different individuals was analyzed by pairwise correlations of the expression level of all protein coding genes Fig. –d. A Spen = 20,314) into various classes of tissue-specific expression. Figure n = 8760) representing “housekeeping genes” expressed in all tissues, out of which 641 genes encoded mitochondrial proteins. Only 283 genes were defined as elevated in heart as compared to the other tissues  portal cross-referenced with the Cardiac Organellar Protein Atlas Knowledge base (www.heartproteome.org) [The proteins elevated in heart or skeletal muscle identified by the transcriptomics analysis were further studied by antibody-based profiling using the publicly available resource of TMA data within the Human Protein Atlas (ome.org)  in orderAn interesting analysis is to investigate proteins elevated in heart, particularly in relation to skeletal muscle. Examples of eight proteins related to contraction and with highest expression in heart muscle are displayed in Fig. A large number of proteins identified as highly expressed in heart were implicated in homeostasis and regeneration/repair, and some of these are displayed in Fig. Intercalated discs are defined as the connections between two adjacent cardiomyocytes, aiding in contraction of multiple cardiomyocytes simultaneously as a unit, which is necessary for proper heart function. Examples of eight proteins distinctly expressed in intercalated discs are displayed in Fig. Interestingly, two proteins previously not characterized in heart (SBK2 and SHD) were at the mRNA level selectively expressed in both samples from the atrium and not in the ventricular wall or in any of the other analyzed tissues. Immunohistochemically stained images of SBK2 and SHD are displayed in Fig. Similar to heart muscle, the main function of skeletal muscle is contraction. Four proteins related to contraction with exclusive expression in skeletal muscle are displayed in Fig. In both heart and skeletal muscle, contraction is dependent on the level of intracellular calcium. However, in contrast to cardiomyocytes, where calcium release is regulated via binding of external calcium ions to voltage gated calcium channels, skeletal myocytes store calcium in the sarcoplasmic reticulum until a neuronal impulse triggers calcium influx along the myofilaments. In Fig. Contraction is an energy demanding process and it is acknowledged that skeletal muscle is a tissue with high metabolic activity. Skeletal muscle is one of the body’s major sites for glucose disposal and is implicated in metabolic diseases such as type II diabetes. Thus, enzymatic activity is an important function in skeletal muscle, relating to various processes such as glucose metabolism, glycogen storage and regeneration. Indeed, a large number (72 out of 371) of the elevated proteins in skeletal muscle are related to different metabolic processes, i.e. present in the HMR2.0 metabolic reaction library , 20. GenFour examples of proteins selectively expressed, but with unknown function in skeletal muscle are displayed in Fig. Although heart and skeletal muscles differ in arrangement of cells and response to signals, the two muscle types have many similarities. Several proteins related to contraction are shared between the two organs, as displayed in Fig. In Fig. Examples of proteins involved in metabolism and myofibrillar organization with expression shared between heart and skeletal muscle are displayed in Fig. Four proteins with selective expression but unknown function in heart and skeletal muscle are displayed in Fig. in situ protein expression, by thorough visual examination of the immunohistochemical images provided by an antibody-based profiling approach. In this way, the muscle specific genes could be further stratified into different subcompartments present within the striated muscles. This allowed us to identify proteins with previously unknown patterns of expression, such as FILIP1 and POPDC2 distinctly expressed in intercalated discs of cardiac muscle. Using this approach, we were also able to identify novel proteins specifically expressed in myocytes and not present in other cell types in the samples, such as adipocytes, fibroblasts or endothelial cells, which suggests a role of these proteins in striated muscle physiology and function.To our knowledge, this is the first study utilizing an integrative omics approach comparing heart and skeletal muscle specific gene expression providing a detailed genome-wide transcriptomics overview characterizing normal striated muscles in relation to a broad range of other tissues. The tissue specific RNA levels were compared to corresponding www.proteinatlas.org, which allows for further interpretation and analysis of the genes and proteins presented here.The immunohistochemistry-based profiling was performed within the infrastructure of the Human Protein Atlas program, a multidisciplinary research initiative which systematically generates and validates representative antibodies towards all non-redundant human proteins , 36. In The analysis of the heart muscle elevated proteins is well in line with the function of the heart. The list includes well-known proteins of the myosin, actin and troponin families, as well as the natriuretic peptides A and B, extensively studied as markers for heart failure . In addiIt is important to point out that the heart samples used in the present investigation are taken from patients with various cardiovascular diseases and that the sample size is rather small. Although it cannot be ruled out that an underlying disease alters transcription of individual genes, the global expression profiles were shown to be highly similar between samples despite different disease background of the patients. Given that a large number of the genes identified as most abundant in heart represented genes associated with a well-known function and no overrepresentation of genes associated with other pathological conditions was observed, a good estimate of a normal mRNA profile can be anticipated.From a medical point of view, the identification of the molecular constituents of the cardiac and skeletal muscle is important. Despite the high prevalence of myocardial infarction, the diagnosis remains a challenge as routine signs and symptoms have low specificity and sensitivity. Myocardial infarction may occur without symptoms, stressing the need for other diagnostic methods such as cardiac imaging or biomarker alterations. Research on serum-based biomarkers has identified several proteins that may serve as markers of cardiomyocyte injury, such as troponins, CKMB and MYL1 , 38. MorIn summary, our work presents a comprehensive resource of proteins elevated in cardiac and skeletal muscle that have been identified and localized to specific muscle segments. This resource can be used for further molecular studies on striated muscle biology as well as for research studies comparing normal and pathological tissues.Tissues used for RNA extraction was based on biopsies from four heart muscle samples and five skeletal muscle samples. The heart material was composed of two samples from the left ventricle  and two samples from the left auricles . One left ventricle sample was obtained by surgery for asymmetrical hypertrophy, with the sample showing slight fibrosis, but not diagnostic for hypertrophic cardiomyopathy. The other left ventricle sample was obtained from an individual diagnosed with post partum cardiomyopathy, with the material taken in connection with temporary use of left ventricle device (heart mate). The sample had some dilation and slight endocardial increased thickness. The histology of the sample was mainly normal, but also showed areas with increased fibrotic tissue and compensatory hypertrophy, as well as a slight probably unspecific inflammation. Both auricle samples were obtained from individuals operated for atrial fibrillation, with normal histological picture without amyloid depositions. The five skeletal muscle samples  were derived from the vastus lateralis muscle in adult healthy volunteers . In addiThe use of human tissue samples was approved by the Uppsala Ethical Review Board (Reference #2011/473). Tissues samples were embedded in Optimal Cutting Temperature (O.C.T.) compound and stored at −80 °C. A hematoxylin-eosin (HE) stained frozen section (4 μm) was prepared from each sample using a cryostat and each slide was examined by a pathologist to ensure proper tissue morphology and sampling of representative normal tissue. Three sections (10 μm) were cut from each frozen tissue block and collected into a tube for subsequent RNA extraction. The tissue was homogenized mechanically using a 3 mm steel grinding ball (VWR). Total RNA was extracted from cell lines and tissue samples using the RNeasy Mini Kit  according to the manufacturer’s instructions. For the skeletal muscle samples, RNA was extracted using the Trizol® method . The extracted RNA samples were analyzed using either an Experion automated electrophoresis system  with the standard-sensitivity RNA chip or an Agilent 2100 Bioanalyzer system  with the RNA 6000 Nano Labchip Kit. Only samples of high-quality RNA (RNA Integrity Number ≥7.5) were used in the following mRNA sample preparation for sequencing. mRNA sequencing was performed on Illumina HiSeq2000 and 2500 machines  using the standard Illumina RNA-seq protocol with a read length of 2 × 100 bases. The samples were sequenced multiplexed 15 per lane, producing an average of 18 million mappable read pairs per sample.The raw reads obtained from the sequencing system were trimmed for low quality ends with the software Sickle (3), using a phred quality threshold of 20. All reads shorter than 54 bp after the trimming were discarded. The processed reads were mapped to the GRCh37 version of the human genome with Tophat v2.0.3 (4). Potential PCR duplicates were eliminated using the MarkDuplicates module of Picard 1.77 (5). To obtain quantification scores for all human genes and transcripts, FPKM (fragments per kilobase of exon model per million mapped reads) values were calculated using Cufflinks v2.0.2 (6), which corrects for transcript length and the total number of mapped reads from the library to compensate for different read depths for different samples. The gene models from Ensembl build 69 (7) were used in Cufflinks. Data was analyzed using R Statistical Environment (8) with the addition of package ‘gplots’ (9). A network analysis was performed using Cytoscape 3.0 (10). For analyses where a log2-scale of the data was used, pseudo-counts of +1 were added to the values.The average FPKM value of all individual samples for each tissue was used to estimate the gene expression level and classify the 20,314 genes into one of six categories: (1) “Not detected”, <1 FPKM in tissue; (2) “Tissue enriched”, at least five-fold higher FPKM level in tissue compared to all other 27 tissues; (3) “Group enriched”, at least five-fold higher FPKM level in a group of 2–7 tissues compared to all other tissues; (4) “Expressed in all”, detected in all 28 tissues; (5) “Tissue enhanced”, at least five-fold higher FPKM level in tissue compared to the average FPKM value of all 28 tissues and (6) “Mixed”, genes expressed in 1–27 tissues and in none of the above categories. A tissue-specific score .A gene ontology (GO)  analysisTissue microarrays (TMAs) were generated as previously described , containFour-micrometer sections were cut from the TMA blocks, mounted on adhesive slides and baked at 60 °C for 45 min. TMA slides were then deparaffinised in Neo-Clear® , followed by hydration in graded alcohols and blocking for endogenous peroxidase in 0.3 % hydrogen peroxide. For antigen retrieval, slides were immersed and boiled in Citrate buffer®, pH6  for 4 min at 125 °C and then allowed to cool to 90 °C. Automated IHC was performed essentially as previously described , using aThe IDs of all antibodies used in the immunohistochemically stained images are summarized here. All antibodies are from the Human Protein Atlas project, unless otherwise stated. Proteins elevated in cardiac muscle: MYH6 (HPA001239), MYL4 (HPA051884), MYL7 (HPA013331), ACTC1 , TNNI3 (HPA063258), TNNT2 (HPA015774), MYBPC3 (HPA040147), CACNA1C (HPA039796), NPPA (HPA058269), AKAP6 , NES (HPA026111), BVES (HPA014788), ATP1A3 (HPA045367), CDH2 , MYZAP (HPA039827), PKP2 (HPA014314), ART3 (HPA011268), FILIP1 (HPA055754), POPDC2 (HPA024255), RAB9B (HPA061932), SBK2 (HPA030631), SHD (HPA017955). Proteins elevated in skeletal muscle: MYH2 , TNNT1 (HPA058448), MYBPC1 (HPA021004), MYOT (HPA037733), RYR1 (HPA056416), CASQ1 (HPA026823), CAPN3 (HPA040052), JPH1 (HPA009413), AMPD1 (HPA028080), PYGM (HPA056003), CA3 , ENO3 (HPA000793), FAM166B (HPA045540), OR10AB1P (HPA044992), PHKG1 (HPA012057). Proteins elevated in both cardiac and skeletal muscle: MYH7 , MYL3 , TNNC1 , TPM3 (HPA047089), CAMK2B (HPA026307), CASQ2 (HPA027285), HRC (HPA004833), SRL (HPA041535), CKM (HPA047859), PGAM2 (HPA060173), LDB3 (HPA048955), MURC (HPA020973), ADSSL1 (HPA052621), HHATL (HPA018174), C1ORF170 (HPA031712), SPTB (HPA003398).www.proteinatlas.org/about/download). The skeletal muscle data will be added to the next release of the Human Protein Atlas. The primary data (reads) are available through the Array Express Archive (www.ebi.ac.uk/arrayexpress/) under accession number E-MTAB-1733, as well as at Gene Expression Omnibus under the accession numbers GSE58387 and GSE58608. Transcript profiling data for each gene in each tissue type, as well as the original immunohistochemically stained images are also available on the Human Protein Atlas (www.proteinatlas.org).FPKM values for samples from all analyzed tissues except skeletal muscle are available for download without any restrictions (


Numerous studies have reported the existence of tumor-promoting cells (TPC) with self-renewal potential and a relevant role in drug resistance. However, pathways and modifications involved in the maintenance of such tumor subpopulations are still only partially understood. Sequencing-based approaches offer the opportunity for a detailed study of TPC including their transcriptome modulation. Using microarrays and RNA sequencing approaches, we compared the transcriptional profiles of parental MCF7 breast cancer cells with MCF7-derived TPC (i.e. MCFS). Data were explored using different bioinformatic approaches, and major findings were experimentally validated. The different analytical pipelines (Lifescope and Cufflinks based) yielded similar although not identical results. RNA sequencing data partially overlapped microarray results and displayed a higher dynamic range, although overall the two approaches concordantly predicted pathway modifications. Several biological functions were altered in TPC, ranging from production of inflammatory cytokines  to proliferation and response to steroid hormones. More than 300 non-coding RNAs were defined as differentially expressed, and 2,471 potential splicing events were identified. A consensus signature of genes up-regulated in TPC was derived and was found to be significantly associated with insensitivity to fulvestrant in a public breast cancer patient dataset. Overall, we obtained a detailed portrait of the transcriptome of a breast cancer TPC line, highlighted the role of non-coding RNAs and differential splicing, and identified a gene signature with a potential as a context-specific biomarker in patients receiving endocrine treatment. There is substantial evidence to support the presence of a subpopulation of tumor-promoting cells (TPC) in both hematologic and solid tumors with self-renewal and asymmetric division capabilities. The proposed model looks at TPC as responsible for treatment failure due to their resistance to anticancer drugs and due to the inability of the presently employed drugs to specifically target the TPC subpopulation –4.in vitro functional approach  [Identification and enumeration of such cells is difficult, their phenotypes are poorly defined and no specific biomarker allows a clear distinction of TPC, although several markers have been proposed . The assrmation) .In breast and other tumor types, much effort has been made to identify the pathways involved in maintenance of the TPC phenotype and to tackle possible TPC-specific targets with therapeutic potential. Among others, Notch , 9 and HAccumulating evidence in other malignancies suggests that also poorly characterized non-coding RNAs (ncRNAs) could have a role in cancer  and in tin vitro propagation of highly tumorigenic mammospheres isolated from the MCF7 breast cancer cell line (commonly defined as MCFS) [in vitro. Finally, the significance of the TPC gene signature derived from our model was confirmed in a cohort of endocrine therapy-treated breast cancer patients.We previously reported the isolation and as MCFS) . In the Transcriptome analysis of tumor-promoting mammospheres (MCFS) and of the parental breast cancer cell line MCF7 was run in triplicate on microarrays and as a single experiment using RNA-seq after linear isothermal DNA amplification. In microarray data, 9,283 probes, corresponding to the same number of genes, were retained after normalization and filtering.Since using only one method for the analysis of RNA-seq datasets can result in a suboptimal analysis, especially when working with a cancer transcriptome, we decided to apply two different methods for the absolute quantification of gene expression after the genome mapping step, i.e., Lifetech Lifescope 2.5.1 pipeline and the TopHat/Cufflinks method (version 1.0.2), using as a common reference gene annotation the UCSC RefSeq dataset. We next correlated fold changes (FC) between MCFS and MCF7 cells obtained with the two analytical pipelines. As for RPKM and FPKM values, a good correlation was found, but the correlation coefficient (R = 0.89) was affected by large expression differences present between the two cell lines (up to 1000-fold changes). Usually, fold changes higher than 2 are already considered to be biologically relevant, but, as can be seen in Figure Fold changes obtained from RNA-seq were then correlated with the results elaborated from microarray data for common genes. As expected, lower correlations were obtained with RNA-seq data, independently of the pipeline used, clearly showing a higher dynamic range, in fold change terms, than microarrays Figure . A similMicroarray as well as RNA-seq expression data were subjected to a Gene Set Enrichment Analysis (GSEA) in order to provide a robust way to compare elaborated gene expression data sets obtained with different platforms and to highlight biologically meaningful pathways modulated in MCFS compared to MCF7 cells. For RNA-seq data, both data analysis procedures were considered in order to investigate their reliability by comparison with array data. For all data, genes were ordered according to fold changes and array data were ordered according to GSEA statistics. Data analyzed with Cufflinks, besides fold changes, were ordered according to the ranking suggested by the Cuffdiff statistics. Enrichment for functionally related genes was tested across a collection of 4,850 curated gene sets (C2 collection), and a summary of obtained results is reported in To obtain a meaningful interpretation of the findings, our approach was to distribute the gene sets in different categories, linking them to a possible biological function. Such biofunctions, which were differentially modulated in MCFS compared with MCF7 cells are listed in Table As expected, based on the growth kinetics of the two cell types, genes associated to cell cycle progression, DNA replication and proliferation were expressed at lower levels in MCFS cells. Whereas the low proliferative potential of TPC is well known, no enrichments in proliferation related –genes has been reported in other studies comparing gene expression profiles of CD44+/CD24– breast cancer stem cells with the remaining bulk tumor cells [−8 M 17β-estradiol for 6 days caused almost a doubling in the MCF7 cell growth rate compared to untreated cells (P = 0.033), whereas as expected based on gene expression data, estradiol had no significant effect on MCFS cell growth , increases in response to estradiol treatment due to paracrine stimulation by non-TPC ER-positive cells mainly through EGFR [It is also worth to mention that paradoxically the TPC population , confirming the gene expression data  response in the maintenance of “stemness”. Finally, several gene sets supported the undifferentiated state of MCFS cells Table .To identify differentially expressed IncRNAs, we compared transcripts derived from Cufflinks analysis with ncRNAs represented in the RefSeq database (June 2013 release) and with those annotated in the ENCODE/GENCODE v.7 lncRNA catalog (June 2013) dataset. This way a total of 331 and 398 noncoding transcripts were respectively identified and were manually annotated in subclasses Table .Five ncRNAs were selected for experimental validation: four of them were down-regulated in MCFS compared to MCF7 cells , whereas the remaining one (LINC01278) was up-regulated. In addition, we chose to validate the differential expression of the long ncRNA MALAT1, previously reported to be highly expressed also in breast cancer tissue , as it sAlternatively spliced genes were identified using a reciprocal junction analysis as implemented in the AltAnalyze software , startinTo verify the predictions, a specific measurement of the relative abundance of transcripts including or excluding the MYOF/SRSF10 candidate exon was obtained by fluorescent competitive RT-PCR (see We confirmed that inclusion of the in-frame 39-base pair (bp) exon 18 was reduced in MCFS compared to MCF7 cells (from 42% to 21%), thus generating an imbalance in the levels of the two alternatively spliced isoforms  Figure . Structuin vivo, which is likely dependent on their binding location within the pre-mRNA. Using this strategy, the RNA-binding protein regulates splicing in the cell [We also validated a significant reduction of SRSF10 expression in MCFS and a concomitant imbalance in the inclusion of the in-frame 363-bp exon 3, which decreased from 41% to 16% Figure . Splicinthe cell , 38.In parallel, to better characterize the predicted RPS6KB1-VMP1 fusion events, we performed RT-PCR using a reverse primer in VMP1 exon 12 and a forward primer located either in RPS6KB1 exon 1 or in exon 4. Using the forward primer in RPS6KB1 exon 4, we obtained a unique amplification product of about 150 bp, whereas using the forward primer in exon 1 we amplified two different products of about 430 and 340 bp, respectively. The direct sequencing of individual RT-PCR products allowed us to identify two different fusion transcripts, one including RPS6KB1 exons 1 to 4 and VMP1 exon 12 (fusion A), and the other connecting RPS6KB1 exons 1 and 2 to VMP1 exon 11 (fusion B)Figure –5B. The RPS6KB1 is a serine/threonine-protein kinase, an important regulator of cell size control, protein translation, and cell proliferation  and it iVacuole membrane protein 1 (VMP1) is a plasma membrane protein and an essential component of initial cell–cell contacts and tight junction formation. It has been described as a cancer-relevant cell cycle modulator, but the function of the protein and its mode of action in tumor progression are still unknown. Its high expression is correlated with noninvasive breast cancer cell lines .Our RT-PCR data suggest that the fusion transcript (RPS6KB1-VMP1) is expressed more in MCF7 cells than in MCFS, as suggested by the AltAnalyze analysis.Interestingly, Inaki et al.  found thin vitro findings, are clinically relevant since fulvestrant has been approved as a second-line therapy for patients experiencing recurrence after a tamoxifen regimen, as it lacks cross-resistance with other antiestrogens, has no agonistic activity and accelerates degradation of ERα. Our results question the utility of fulvestrant as second-line endocrine therapy and suggest that treatment with this pure antiestrogen might fail due to the outgrowth of TPC cell subpopulations.One of the hypotheses suggested by the interpretation of differentially modulated coding genes was a reduced sensitivity to endocrine treatment of MCFS. To evaluate whether the gene expression modulation observed in this model could also be traced in clinical samples of breast cancer, a consensus list of 77 genes  overexprFinally we asked whether the particular condition for MCFS isolation could have influenced the gene expression pattern. In fact, most studies trying to tackle transcriptome variations in TPCs compared to parental cells have employed enrichments based on the expression of selected markers , 27, 31,We also would like to emphasize that the lack of growth of MCFS cells upon stimulation with 10–8 M E2 is not a simple result of culture conditions since in the presence of a serum –free medium supplement , estradiol was still stimulatory for MCF7 . This isin vitro as spherogenic cultures that initiate tumors in mice and their transcriptomes were compared to more differentiated cells expanded as adherent monolayers in serum (i.e. exactly our approach). The derived stemness consensus signature when applied to the single cell transcriptional profiles, revealed a gradient of stemness among the single cells, suggesting that in vitro models do in fact give important clues, although limiting to the phenotypic extremes of cellular states. We have not yet proven such a concept in breast, but results on bulk tumors go in this direction.In an interesting paper on primary glioblastoma , single-The MCF7 breast cancer cell line was purchased from the American Type Culture Collection  and cultured in DMEM/F-12  medium supplemented with 10% fetal bovine serum (Lonza). MCFS were derived from the MCF7 cell line  and prop® Reagent (Life Technologies); lysates were stored at −80°C for not more than 2 weeks. Total RNA was extracted following the manufacturer's instructions. Contaminating DNA was digested using recombinant DNase I (Life Technologies), and RNA samples were purified using the RNeasy MinElute Cleanup Kit . Total RNA was quantified by a NanoDrop spectrophotometer and assessed for quality by the Agilent RNA 6000 Nano kit  using the Agilent 2100 Bioanalyzer (Agilent Technologies).Cell pellets (∼106 cells) were immediately put on ice and homogenized in 1 ml of TRIzol® RNAdvance® Cell v2  protocol using Agencourt's patented SPRI® paramagnetic bead available in the kit. After Proteinase K cell lysis and protein digestions, total RNA was separated from contaminants exploiting its binding to the magnetic particles. Manufacturer instructions were followed with the exception of the DNase treatment step, which was carried on with the Ambion® TURBO DNA-free™ (Life Technologies). Fifty μl of a solution containing 1 μl of TURBO DNase (2 Units/μl), 5 μl of 10X TURBO DNase Buffer, and 44 μl of nuclease-free water was prepared, added directly to the bead-linked RNA and incubated at 37°C for 30 min. The addition of aqueous DNase released DNA and RNA from the beads; while DNA was digested, RNA was re-bound to the beads by adding 250 μl of Agencourt Wash Buffer. Thereafter, as in the original Agencourt protocol, RNA was eluted in 40 μl of nuclease-free water and quantified using Qubit™ RNA Assay Kits (Life Technologies); its quality was checked using the Agilent® RNA 6000 Pico kit .For RNA-seq experiments, total RNA from 5000 MCF7 cells and MCFS were extracted following AgencourtArray experiments with the Illumina platform were run by the Functional Genomics Core Facility at the Fondazione IRCCS Istituto Nazionale Tumori, as previously described . Brieflylumi package [P < 0.01 in at least 2 of 6 samples were selected (11406 probes). When multiple probes per gene were present, only the probe with the highest detection rate or highest interquartile range was retained . Raw and processed data were deposited at the Gene Expression Omnibus data repository (GSE58383).Three replicates were profiled for both cell types. Microarray raw data where generated using the Illumina BeadStudio 3.8 software and processed using the  package  of Bioco® technology developed by NuGEN following Ovation RNA-seq . Briefly, first-strand cDNA was prepared from total RNA using unique primers that hybridize either to the 5′ portion of the poly(A) sequence or randomly across the transcript. The resulting mRNA within the cDNA/mRNA complex was fragmented, and DNA was amplified using a linear isothermal DNA process developed by NuGEN named SPIA®. The post-SPIA modification process completed the amplification step, producing targets appropriate for SOLiD library preparation. The amplified cDNA was purified prior to subsequent processing for library construction using RNA clean purification magnetic beads (Beckman Coulter Genomics), as suggested in the protocol. Double-stranded DNA was quantified with Qubit™ DNA BR Assay Kits (Life Technologies), and its size distribution was checked using the Agilent® RNA Nano kit (Agilent) following the manufacturer's instructions.Total RNA (90 ng) was amplified, prior to transcriptome sequencing, using Ribo-SPIA® iBase™ system: the 150–200 bp region was collected.DNA libraries, one for each sample, were constructed following the SOLiD™ 3 Plus System Library Preparation Guide (Life Technologies) manufacturer's instructions. One μg of cDNA was diluted in 100 μl in 1X low TE buffer and transferred in a Covaris™ microTUBE. DNA was sheared using the following Covaris S2 System conditions : 10 cycles 60 s each, 10% duty cycle, 5 intensity and 100 cycles/burst. Sheared samples were first end-repaired, columns purified and ligated to specific Solid adaptors containing P1 and P2 sequences. DNA was size-selected using a SOLiD™ Library Size Selection gel run in the E-Gel® DNA 1000 Kit (Agilent Technologies). Four PCR emulsions, two for each library, were manually performed following the Applied Biosystems SOLiD™ 3 Plus System Templated Bead Preparation Guide, according to the manufacturer's instructions (Life Technologies).The nick-translated adaptor-ligated DNA was amplified using Library PCR Primer P1 and P2 with 6 cycles, and after SOLiD™ Library Column purification, the yield and size distribution of the libraries were checked using the AgilentThe library and emulsion qualities were checked in a workflow analysis run following the SOLiD™ 3 Plus System Instrument Operation Guide (Life Technologies).Sequencing was done using standard fragment settings on the SOLiD™ Systems V3 plus according to SOLiD™ 3 Plus System Instrument Operation Guide protocol (Life Technologies). At least 150 M of tags for each library, 50 bp long, distributed in 2 quad each, were sequenced.Sequence reads in SOLiD Color Space format were mapped to the UCSC repeat-masked hg19 reference genome and analyzed for transcript representation in RPKM and splice site-fusion representation with the Whole Transcriptome Analysis module of the Lifetech Lifescope 2.5.1 analysis software and ad hoc created perl scripts. The resulting genome alignment files in .bam format were used to originate the fastq files corresponding to the aligned sequence reads and for further analysis with the TopHat/Cufflink/Cuffdiff whole transcriptome analysis pipeline.Enrichment analysis in mRNA expression data was performed using GSEA (v. 2.0) . The C2 To identify splicing events in MCFS compared with the parental MCF7 cells, AltAnalyze software  was usedFirst of all, we selected events occurring in genes expressed at relatively high levels, i.e., RPKM > 5 in MCFS and MCF7 cells. Then, we distinguished between events with positive or negative ASPIRE values. In exon junctions, positive ASPIRE values correspond to a down-regulation of junction 1 and up-regulation of junction 2, and vice versa for ASPIRE negative values. The subsequent criterion was to have a value higher than 15 in the sample were the junction was up-regulated. For events in unchanging genes, we also selected events where fold change value was higher than 3.See We performed a detailed study of TPC transcriptome using microarrays and RNA-seq. Informative RNA-seq data were derived starting from small input RNA, making the approach applicable to various scenarios where a limited amount of material is available. Some of our findings were already reported as being crucial in TPC, although using different approaches to isolate such a tumor subpopulation, therefore supporting the validity of our model. Of note was the up-regulation of the NF-κB pathway, IL-8 and other inflammatory cytokines. Our TPC also showed less responsiveness to endocrine treatment, and, interestingly, genes over-expressed in MCFS cells were found to be up-regulated also in clinical tumors resistant to fulvestrant treatment, suggesting that they might represent a new putative predictive marker of hormone-treatment resistance. Finally, RNA-seq analysis suggested an involvement of several ncRNAs and differential splicing events in maintenance of the TPC phenotype.in vitro validation of the hypothesis generated by the data and iii) the successful identification of a gene signature predicting response to fulvestrant obtained in this study, give additional strength to other still to validate findings and to the model itself.We are aware that it is not yet clear if the putative stem cell components derived from established cell lines is a valid model for TPC and that experimental conditions might be very critical, however, i) the confirmation of some earlier literature data , 31, ii)


Drosophila Klf15  was restricted to the only two nephrocyte populations in Drosophila, the garland cells and pericardial nephrocytes. Loss of dKlf15 function led to attrition of both nephrocyte populations and sensitised larvae to the xenotoxin silver nitrate. Although pericardial nephrocytes in dKlf15 loss of function mutants were specified during embryogenesis, they failed to express the slit diaphragm gene sticks and stones and did not form slit diaphragms. Conditional silencing of dKlf15 in adults led to reduced surface expression of the endocytic receptor Amnionless and loss of in vivo scavenger function. Over-expression of dKlf15 increased nephrocyte numbers and rescued age-dependent decline in nephrocyte function. The data place dKlf15 upstream of sns and Amnionless in a nephrocyte-restricted differentiation pathway and suggest dKlf15 expression is both necessary and sufficient to sustain nephrocyte differentiation. These findings explain the physiological relevance of dKlf15 in Drosophila and imply that the role of KLF15 in human podocytes is evolutionarily conserved.Insect nephrocytes are highly endocytic scavenger cells that represent the only invertebrate model for the study of human kidney podocytes. Despite their importance, nephrocyte development is largely uncharacterised. This work tested whether the insect ortholog of mammalian Kidney Krüppel-Like Factor (Klf15), a transcription factor required for mammalian podocyte differentiation, was required for insect nephrocyte development. It was found that expression of  Drosophila the non-phagocytic system is comprised primarily of nephrocytes, highly endocytic cells that exists close to the heart  and oesophagus (garland cells). Nephrocytes have long been regarded as analogous to mammalian reticuloendothelial cells [sticks and stones, an ortholog of mammalian Nphs1, which is critical for slit diaphragm formation) [Amnionless and Cubulin, genes critical for protein reabsorption and endocytosis in invertebrates and mammals)[Drosophila is important because they may provide important insights into genetic pathways relevant to human physiology and stem cell differentiation.Invertebrates, like mammals, have both phagocytic and non-phagocytic scavenger systems for the clearance from circulation of effete cells, foreign material and macromolecules –3. In Dral cells , and recrmation) , 6 and r mammals), 8. As sKLF15 exists on the X-chromosome in Drosophila but this gene was originally regarded as an ortholog of mammalian Bteb2/Klf5, hence it was named Bteb2. However, this gene shares greater amino acid sequence similarity with the more recently identified mammalian Klf15 [Drosophila gene as dKlf15 to reflect this. Embryonic and adult gene expression data indicate that dKlf15 has a highly restricted expression pattern limited to the embryonic garland cells [The Krüppel-like family (KLF) of transcription factors mediate the development, differentiation and function of multiple cell types from invertebrates to mammals . KLF genan Klf15   localised to the nucleus of pericardial nephrocytes that co-expressed the nephrocyte marker Amnionless in adults ED6727; i.e. they had no wild type copy of dKlf15) had no nephrocytes  had no nephrocytes  and dKlf15NN mutant flies was identical  and dKlf15NN mutants were crossed into a Hand-GFP background to mark cardiomyocytes and pericardial nephrocytes with green fluorescent protein [dKlf15NN mutants was indistinguishable from that in controls. After L1, the pericardial nephrocytes in controls grew considerably in size, whereas this failed to occur in dKlf15NN mutants and by the L3 stage, very few pericardial nephrocytes remained in the mutant . In controls there was no sns signal in L1 pericardial cells but strong expression in L2s  nor the function of the nephrocytes in young (1-week-old) flies  flies . All nepd) flies , howeverd) flies . In star , a gene required for human renal podocyte differentiation, acts upstream of Amnionless and the slit diaphragm gene sticks and stones, to drive and maintain the differentiation of Drosophila nephrocytes.Multicellular organisms contain circulating fluids which must be filtered to remove toxins, effete cells and endogenous macromolecules. Whether this is mammalian blood or invertebrate hemolymph, elaborate filtration systems have evolved which maintain organ homeostasis. In insects the principal filtration cell is the nephrocyte. Nephrocytes have long been regarded as functionally analogous to highly endocytic scavenger cells within the mammalian reticuloendothelial system , 27, 28.dKlf15 expression in Drosophila, mammalian Klf15 is expressed in a variety of tissues, suggesting diversification of the ortholog’s role during evolution. Although transcriptional activity of dKlf15 has been demonstrated in two independent, in vitro studies [NPHS1 and NPHS2 [dKlf15 is restricted to nephrocytes, the only insect cell type known to form filtration slits, it is plausible the role of mammalian Klf15 in podocyte biology has been evolutionarily conserved and that dKlf15 may directly activate sns, the Drosophila ortholog of human NPHS1. This hypothesis is consistent with the observed loss of sns expression and lack of slit diaphragms in the pericardial nephrocytes of dKlf15NN mutants. Garland cells are known to develop as mononuclear cells which then fuse to form binucleate, mature nephrocytes. This fusion process is dependent on sns and modulation of fusion can lead to multi-nucleate garland cells [neph genes as well as hyperactivation of Src64B, a kinase that regulates the slit-diaphragm protein encoded by Dumbfounded, can lead to multinucleate garland cells through agglutination, a phenotype reminiscent of the poly-nucleate morphology seen in dKlf15NN mutants [dKlf15 function leads to a phenotype similar to that seen in gain-of-function experiments is unclear.In contrast to the restricted pattern of  studies , 32 the nd NPHS2 , which end cells , 30. Ove mutants , 30. HowRedStinger) driven by the presumed cis acting enhancer element of dKlf15 was limited to garland cells and pericardial nephrocytes. This corroborated high throughput datasets and anti-dKlf15 immuno-staining results, suggesting the enhancer element used to drive RedStinger provided faithful representation of the dKlf15 expression pattern. Attempts to perform in situs on larval tissue were unsuccessful, reflecting the possibly that dKlf15 expression is too low to be detected, so it is not known with certainty when dKlf15 expression is switched-on in pericardial nephrocytes. However, the timing of nephrocyte attrition and RedStinger reporter gene expression, from the L2 stage onwards, would strongly suggest that dKlf15 expression is initiated in pericardial nephrocytes soon after the L1 stage. No attempt to study the timing of dKlf15 expression in embryonic garland cells was made but high throughput data indicates dKlf15 is expressed in garland cells after embryonic stage 10 [dKlf15 was required for the differentiation and sustained function of pericardial nephrocytes it will be interesting to examine how dKlf15 affects the development and function of the garland cells.Expression of a fluorescent reporter gene  controlling dKlf15 expression in order to identify both upstream regulators of Klf15 expression and the gene’s downstream effectors as these may provide insights into human KLF15 function.Garland cells and pericardial nephrocytes develop in different anatomical locations, at different times, suggesting that at least two independent signalling pathways initiate oic acid  and glucoic acid . Retinoiosophila , 35. InsDrosophila larvae that ingest silver nitrate [dKlf15NN mutants, the observed sensitivity to silver nitrate was expected. In contrast, survivorship of adult mutants given silver nitrate was not different to that of controls fed the same diet, despite both genotypes showing sensitivity to the xenotoxin. This argues that nephrocytes are the primary system for mitigating xenotoxin insults in larvae but that other cells compensate for the loss in adults. It has been reported that the ablation of post-embryonic pericardial nephrocytes shortens adult lifespan [It is well established that mutations affecting nephrocyte function reduce survivorship of  nitrate , 21. Givlifespan , geneticdKlf15 loss of function. This is an important area to follow-up using this model because mechanisms affecting cardiac function in Drosophila can be of direct relevance to human cardiovascular physiology [dKlf15-loss of function, offers an attractive alternative for such studies.Pericardial nephrocytes are thought to modulate cardiac function , and preysiology . It is aysiology . Beyond dKlf15, is defined as a nephrocyte-restricted transcription factor critically required for the differentiation and sustained function of insect nephrocytes. As nephrocytes are important model of human renal podocytes the model has great potential to guide and support research into podocytopathies [In summary opathies , an impoCanton Special (CaS), w1118 (used as wild-type strains in this study), Bteb2f06447 , Dorothy-Gal4 , Tub-Gal80ts, Dp122, Dp120, Dp473 and Df(1)ED6727 lines were all from the Bloomington Stock Centre . The HandC-Gal4  line was described in [Hand-GFP line was from Dr. Zhe Han  and Bloomington . All genetic combinations were generated by standard crosses. The sns-mCherryNLS line was kindly provided by Susan Abmayr and is described in [Hand-Gal4; Tub-Gal80ts) was achieved by standard crossing techniques [The ribed in , UAS-mChribed in ). The twribed in . Generatchniques .dKlf15NN mutant was backcrossed onto the w1118 for >20 generations. Fur establishing survivorship of larvae on silver nitrate, 20 eggs from control or dKlf15NN mutants were placed onto agar with yeast paste containing different concentrations of silver nitrate. Survivorship was calculated as the percentage of adults eclosing. For the determination of lifespan, male or female flies were collected within 1–3 days of eclosion and housed in vials with free access to food  in groups of 15. Flies were tipped to fresh food twice a week and the number of dead flies recorded until all flies were dead.Flies were propagated routinely on a standard cornmeal-yeast diet at 25°C under a 12hr:12hr light-dark schedule. For TARGET experiments flies were reared at 18°C and then transferred to 29°C within 1–5 days of eclosing. Flies remained at 29°C for one to two weeks. Prior to analysis of heart function flies were transferred to 25°C for 24 hours. To reduce the effect of genetic background the dKlf15. Anti-Amnionless antisera were used at 1:100.Antisera were prepared by GenoSphere Biotechnologies . The immunogen chosen for dKlf15 was the peptide CPPDLSDWEQRLLDN, whereas the peptide for dAmnionless was DPRLWRWRHLGLRLR. Antisera to the peptides were generated in rabbits (dKlf15) and guinea pigs (dAmnionless). Antisera were affinity purified to yield the total IgG fraction. Antibodies were verified for specificity by ELISA using the peptide as target antigen. Pre-incubating antibodies with a 10-fold excess of peptide blocked all immunoreactivity in adult flies. Anti-dKlf15 antisera was used at 1:10 to detect protein in wild-type flies and 1:100 in flies over-expressing dKlf15-Gal4 line, a 2131bp fragment of DNA containing sequence upstream of the predicted 5’ translation initiation site of the dKlf15 gene was cloned into pPTGAL4 and transgenic flies generated by a commercial company .To generate the dKlf15 gene expression were as follows: (left) GGAGGAGAGCAACAGCAATC; (right) CATCGTGTCCTTGGAATGTG. This amplified a 538bp amplicon, between base pairs 420 and 957 of the 962bp dKlf15 transcript. In the dKlf15NN mutant this region is downstream of the P-element insertion  for 30 minutes, placed dorsal side up, on a microscope slide and then cover-slipped so as to partially flatten but not burst the larvae. Adult were dissected and hearts stained as described previously . For somEggs were collected from agar plates every 24h. Embryos were dechorionized in 50% bleach and fixed as described before . PrimaryPericardial nephrocytes in third instar larvae were analysed by transmission electron microscopy (TEM) in semi-dissected animals. Therefore, larvae were collected, dissected in cold PBS and fixed in 3.7% formaldehyde for 1h at room temperature. Further fixation and preparation for TEM imaging was essentially done as described in . Samples2 and then dissected as for heart analysis (see above). The semi-intact preparation was then incubated in a solution of Alexa488 fluorescently labelled 10kDa dextran  containing 2mM CaCl2), at 25°C for 0–30 minutes. Endocytosis was then inhibited by placing the preparation on ice, washing with ice-cold HBSS and fixing samples for 15 minutes with 4% formaldehyde in HBSS. Some samples were co-incubated with wheat-germ agglutinin (WGA) conjugated to the Alexa594 fluorochrome.Adult flies were anaesthetised by brief exposure to COFluoresce microscopy of flies was performed with a Zeiss Axioskop MOT II microscope  illuminated with mercury or halogen light sources for fluorescence or differential interference contrast (DIC) imaging using a 40x objective. Images were captured with an ORCA-ER CCD camera  coupled to Openlab 4.1 . Confocal images were collected with a Zeiss LSM 780 coupled to Zen imaging software. Images were coloured, contrast enhanced and overlaid using Photoshop CS3. All micrographs from an experiment were collected using the same microscope settings and image alterations. For quantification of fluorescence, micrographs were opened in ImageJ and converted to 8-bit greyscale format. The line tool was then used to draw across a region of interest and the maximum pixel intensity recorded.P values between control and the different genotypes. If only two genotypes or treatments were used an unpaired two-tailed student’s t-Test was applied to establish the P-value. For endocytosis experiments a 2-way ANOVA was used to examine if there was an interaction between the fluorescence signal, time and genotype.When more than two genotypes or treatments were used in an experiment one-way ANOVA was used to test the hypothesis that genotype may have affected heart function and post hoc test (Tukey’s HSD) was used to establish S1 Fig(DOCX)Click here for additional data file.S2 Fig(DOCX)Click here for additional data file.S3 Fig(DOCX)Click here for additional data file.S4 Fig(DOCX)Click here for additional data file.S5 Fig(DOCX)Click here for additional data file.S6 Fig(DOCX)Click here for additional data file.S7 Fig(DOCX)Click here for additional data file.


Immune tolerance induced by regulatory mechanisms is an integral and fundamental part of immunity. In therapeutic settings, however, tolerance may significantly limit efficacy. Here, we summarize possible strategies to enhance therapeutic antibody dependent cellular cytotoxicity by overcoming NK cell tolerance. Along with their potential for strong cytotoxic responses without previous priming, the common expression of the low-affinity immunoglobulin gamma Fc region receptor III-A (FcγR3A) makes natural killer (NK) cells potent effectors of therapeutic antibody dependent cellular cytotoxicity (ADCC). Nevertheless, ADCC efficacy is limited by NK cell intrinsic and extrinsic regulatory mechanisms. In particular, the interaction between inhibitory killer-cell immunoglobulin-like receptors (KIR) and their HLA Class I ligands is fundamental to NK cell development and tolerance. In a process called “licensing”, only NK cells expressing inhibitory receptors able to interact with self-HLA molecules gain full functional capacity. Potentially autoreactive NK cells carrying KIR that lack a cognate HLA ligand stay hypo-functional.1 We recently addressed the question of how KIR/HLA interactions influence rituximab-induced ADCC, and showed that the advantage of the full functional potential of licensed NK cells is compensated by the inhibitory KIR signal, if target cells express cognate HLA , the benefit of anti-CD20 therapy in such patients may be strongly limited by NK cell tolerance. Our in vitro data were recently confirmed by the analysis of follicular lymphoma patients treated with rituximab, which showed that progression-free survival (PFS) decreases with the number of viable KIR/HLA interactions.3 These data indicate a need for strategies to overcome the negative impact of KIR/HLA interactions in order to enhance the efficacy of therapeutic antibodies.Rituximab – a chimeric anti-CD20 antibody – is a standard component of regimens used to treat B-cell lymphoma. How NK cell function in rituximab-induced ADCC is affected by regulatory mechanisms has not yet been completely defined.4 led to the development of new anti-CD20 antibodies with modified Fc regions aiming to strengthen Fc/FcR interactions. One such antibody is obinutuzumab carrying an afucosylated glycoengineered Fc part, which increases the affinity to the FcγR3A receptor, and thereby enhances NK cell activation and killing efficiency.5,6 Based on increased response rates and prolonged PFS as compared to rituximab when given in combination with chlorambucil to patients with chronic lymphocytic leukemia, obinutuzumab was recently approved for this indication and is undergoing evaluation in other types of B-cell lymphoma.7The observation that rituximab had greater clinical efficacy in patients carrying the high-affinity FcγR3AIn vitro, obinutuzumab recruited more NK cells for ADCC and activated them more strongly than rituximab. Most notably, licensed and unlicensed cells practically did not differ in their level of activation and the activation was hardly influenced by the presence of cognate HLA KIR ligand on target cells. Importantly, multiple KIR/HLA interactions were necessary to decrease obinutuzumab-induced ADCC to the level achieved by rituximab.2 In line with these observations, target depletion was unaffected by both the percentage of unlicensed effector cells in the repertoire, and by the number of KIR ligands expressed on target cells. In summary, obinutuzumab can induce comparable percentage and quality of activation in all NK cells subpopulations, independent from the licensing status and the KIR/HLA interactions  in patients with multiple myeloma (NCT02252263).Another strategy to overcome the suppressive KIR/HLA interaction is based on antibody blockade. To this end, an antagonistic, non-depleting anti-KIRD2 antibody (lirilumab) has been developed. Lirilumab can block the KIR/HLA interaction in approximately half of NK cells (those expressing KIR2D receptors), increasing the number of activated immune effector cells The differences between the 2 presented strategies are too great to determine which one could be more beneficial. The advantage of the strategy represented by obinutuzumab is maximal percentage and level of activation of all FcγR3A-positive NK cells independently from their licensing status and the KIR/HLA interaction mediated by a single agent therapy. Fc enhancement can easily be incorporated into the development of new therapeutic antibodies. In contrast, lirilumab can be added to existing therapies in which the KIR/HLA interaction limits therapeutic benefits.


Necrotizing enterocolitis (NEC) is a devastating condition of premature infants that results from the gut microbiome invading immature intestinal tissues. This results in a life-threatening disease that is frequently treated with the surgical removal of diseased and dead tissues. Epidermal growth factor (EGF), typically found in bodily fluids, such as amniotic fluid, salvia and mother’s breast milk, is an intestinotrophic growth factor and may reduce the onset of NEC in premature infants. We have produced human EGF in soybean seeds to levels biologically relevant and demonstrated its comparable activity to commercially available EGF. Transgenic soybean seeds expressing a seed-specific codon optimized gene encoding of the human EGF protein with an added ER signal tag at the N’ terminal were produced. Seven independent lines were grown to homozygous and found to accumulate a range of 6.7 +/- 3.1 to 129.0 +/- 36.7 μg EGF/g of dry soybean seed. Proteomic and immunoblot analysis indicates that the inserted EGF is the same as the human EGF protein. Phosphorylation and immunohistochemical assays on the EGF receptor in HeLa cells indicate the EGF protein produced in soybean seed is bioactive and comparable to commercially available human EGF. This work demonstrates the feasibility of using soybean seeds as a biofactory to produce therapeutic agents in a soymilk delivery platform. Experl growth ,17. The l growth . Transgel growth . Conversl growth .A prospective, multi-center trial demonstrated that infants fed regular formula (not containing growth factors) were 6 to 10 times more likely to develop NEC than infants fed breast milk . While aIf the proactive EGF feeding strategy is effective to induce the maturation of the neonate intestinal tract then this simple approach may mitigate the development of NEC with its resulting high costs in medical resources, pain and possible life-long debilitation and for the 40% infants with NEC that proves fatal –27. To aArabidopsis chitinase gene [-2/s.Epidermal growth factor protein from humans was produced in soybean seeds by constructing a plant gene expression cassette that involved a synthetic codon optimized EGF nucleotide sequence (protein sequence from Genbank accession CCQ43157). This 162 bp open reading frame was placed in-frame behind a 20-amino acid endoplasmic reticulum (ER) signal sequence from the ase gene ,31. The ase gene . The resase gene . EmbryosTotal soluble protein was extracted from dry seeds of two homozygous EGF lines and a nontransgenic control by repeated acetone washes followed by acetone precipitation with the protein pellet dissolved in water. Proteins with molecular weight 10 kDa and under were isolated by separately passing each extract through an Amicon Ultra centrifugal filter . The samples were each suspended in sample buffer , 0.7 M β-mercaptoethanol, 0.1% (w/v) bromphenol blue and 10% (v/v) glycerol) and then denaturated 5 min 95°C. Protein content was determined by Bradford assay . A 15% STotal soluble protein was extracted from dry soybean seeds as described previously ,32 from Total soluble proteins were extracted, quantitated and suspended in sample loading buffer as previously described , 32. AppGlycine max was downloaded on August 5, 2015 from NCBI RefSeq with the addition of the EGF amino acid sequence. A randomized version of the Glycine max fasta was concatenated to the original as a way to assess dataset quality. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Constortium  via the PRIDE partner repository [Total soluble protein was extracted from 3 biological EGF transgenic soybean dry seed samples, lines 4, 5 and 6. As described above, proteins with molecular weights lowers than 10 kDa were concentrated using an Amicon Ultra centrifugal filter . Non-transgenic seeds were used as a negative control and 5 μg commercially available EGF (as above in immunoblot section) was the positive control. Protein was precipitated by adjusting the solution to 20% (v/v) trichloroacetic acid and allowed to sit at 4°C overnight. Precipitated proteins were pelleted using centrifugation, washed twice with acetone and then dried using vacuum centrifugation. The commercial EGF was not filtered or precipitated, only dried. Dried pellets were rehydrated with the addition of 10 μl 100 mM dithiothreitol in 100 mM ammonium bicarbonate and placed at 85°C for 5 minutes to reduce disulphide bonds. Samples were then alkylated with addition of 10 μl iodacetamide in 100 mM ammonium bromide and placed at room temperature in the dark for 30 minutes. Two μg trypsin in 200 μl 100 mM ammonium bromide was added to each samples and placed in 37°C overnight for enzymatic digestion. Post trypsin digest samples were desalted using a peptide reverse phase microtrap , dried and ultimately resuspended in 2 μl of 2% (v/v) acetonitrile, 0.1% (v/v) formic acid. Separation of peptides was performed using a Dionex U3000 splitless nanoflow HPLC system operated at 333 nl minute using a gradient from 2–50% acetonitrile over 60 minutes, followed by a 15 minute wash with 95% acetonitrile and a 15 minute equilibration with 2% acetonitrile. The C18 column, an in-house prepared 75 μm by 15 cm reverse phase column packed with Halo 2.7 μm, 90Å C18 material  was located in the ion source just before a silica emitter. A potential of 2100 volts was applied using a liquid junction between the column and emitter. A Thermo LTQ Velos Pro mass spectrometer using a nanospray Flex ion source was used to analyze the eluate from the U3000. Scan parameters for the LTQ Velos Pro were one MS scan followed by 10 MS/MS scans of the 5 most intense peaks. MS/MS scans were performed in pairs, a CID fragmentation scan followed a HCD fragmentation scan of the same precursor m/z. Dynamic exclusion was enabled with a mass exclusion time of 3 min and a repeat count of 1 within 30 sec of initial m/z measurement. Spectra were collected over the entirety of each 90 minute chromatography run. Raw mass spectra were converted to MGF format using MSConvert, part of the ProteoWizard software library  X!tandempository  with theHela cells (obtained from American Tissue Culture Collection) were cultured in Minimum Essential Media (MEM) complemented with 10% Fetal Bovine Serum (FBS), 100 units/ml penicillin, and 100 μg/ml streptomycin. For western blotting assay, cells grown in 6-well plate were kept in serum free MEM media for 24 hours. Cells were then either kept in serum free medium (control) or stimulated with soy milk alone, soy EGF or commercial recombined human EGF for different time period as indicated. Cells were lysed by directly adding 1× SDS sample buffer  to the cells after washing 3 times with 1X PBS. EGF bio-activity was determined via EGFR phosphorylation and downstream AKT phosphorylation. Total EGFR was also measured since EGFR is known to undergo internalization when stimulated with EGF. Antibodies used in western blot are anti-p-EGFR (Tyr1068) , anti-total EGFR , anti-p-AKT  and anti-Lamin B1  [0 generation EGF transgenic plants were grown in the greenhouse and further selected by genomic PCR for an additional 2–3 generations. Additionally, each generation of seeds produced by the selected lines were assayed for hEGF content by ELISA. The hEGF content of each line in seeds representative of the homozygous population is shown in Pichia pastoris clone secreting 49 μg EGF/ml. In both the mouse and human EGF yeast production systems, truncated versions of the EGF were detected.To produce hEGF in soybean a strong soybean seed-specific promoter and terminator was used to regulate gene expression of a synthetic soybean codon optimized hEGF (ShEGF) gene that included an N-terminal 60 nucleotide ER-signal sequence . In the The hEGF soybeans and nontransgenic soybeans were evaluated to determine the biochemical authenticity of the soybean-produced EGF protein. Using 1D SDS/PAGE and parallel immunoblots probed with anti-EGF, the soluble low molecular weight (<10 kDa) seed proteins and the Mr of the soybean-produced hEGF was evaluated. The total protein polypeptide of the hEGF expressing lines appeared to be identical to the standard parental control . ImmunobThe delivery of any biopharma product in the context of compositionally complex food presents the potential that the components of the food may act to modulate bioactivity. Plant-source foods in particular pose problems because plant tissues often possess a wide range of intrinsic biologically active components including proteins and natural products. The natural products of food could mask or enhance the effects of an expressed biopharma product. To evaluate the potential of EGF activity in soymilk delivery commercial recombinant human EGF (rhEGF) was added as a supplement to soymilk and the intrinsic activity of the EGF was tested with a HeLa cell assay. To assess the bioactivity of soybean-produced hEGF, samples were prepared from both ShEGF transgenic soybean lines and nontransgenic controls that were used to stimulate HeLa cells to induce EGFR internalization, degradation and phosphorylation. In results shown in In developing a food-based delivery platform for biopharma it is important to address the question of whether there are significant collateral consequences in seed composition resulting from the genetic modification. Ideally a consumption plant biotechnology platform, such as soymilk, should be fully equivalent to the standard type other than the intended modification. Seeds in general, including soybeans, possess an inventory of bioactive proteins and small molecules that will affect the metabolism of consumers in both advantageous and disadvantageous manner. For soybeans some of the relevant molecules are allergens, anti-metabolite proteins, and small molecules especially isoflavones. To test for potential collateral composition in the hEGF-producing soybeans, the ShEGF transgenic and nontransgenic control soybeans were analyzed by non-targeted proteomics and metabolomics. Among the significant proteins identified include various well-documented allergens and anti-metabolite proteins. A comparison of standard soybeans with hEGF-producing soybean lines showed that there was no significant difference (p = .01) between nontransgenic control and ShEGF transgenic soybeans aside from the targeted production of hEGF for any other proteins of concern. This data is available in PRIDE partner repository with the dataset identifier PXD003326 and 10.6019/PXD003326.Non-targeted small molecule metabolomics was used to conduct a parallel analysis of the nontransgenic and hEGF soybeans. Again there were insignificant differences between nontransgenic soybean seeds and the ShEGF transgenic seeds  with oneSince the inception of plant biotechnology its potential use for biopharma applications has been assessed –50. SeveSoybeans like many other seeds produce an array of intrinsic small globular proteins with secondary disulfide bonds accumulated at relatively high levels . Soybean in particular accumulates the Bowman-Birk trypsin inhibitor that is 8.5 kDa with 3 intra-chain disulfide bonds . This suSoybeans have been used as an expression platform for a wide variety of heterologous proteins with investigative as well potential food/feed and biopharma goals , 62–66. Soybeans could be used to produce biopharma products that might be delivered as milk or formula. As a test of this concept human epidermal growth factor (hEGF) has been produced in soybeans to potentially address the devastating disease of neonatal necrotizing enterocolitis. This is a disease of premature infants of low birth weight. These infants have underdeveloped organs including the intestinal tract. The resulting gangrenous infection is treated by emergency surgery to remove dead portions of the intestinal tract that even under most optimistic situations has a high mortality rate and high cost of treatment. An alternative approach is to proactively treat infants at risk immediately post-partum to attempt to improve the integrity and maturity of the lining epithelial cells. The bioactivity results with model HeLa cells shows that hEGF can be produced and accumulated in soybean seeds and as crude soy-milk lysate is capable of stimulating a response from the EGF receptor (EGFR) that occurs on epidermal surfaces such as the intestinal tract. Soybean-produced hEGF has potential other applications in cosmetics, burn and injury treatment, stimulating improved adaptation of the bowel to massive intestinal loss.S1 Table(XLSX)Click here for additional data file.