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Dopamine-β-hydroxylase (DBH), an enzyme that converts dopamine into norepinephrine, is a drug target in cardiovascular and neuropsychiatric disorders. We aimed to identify functional variants in this gene by deep sequencing and enzyme phenotyping in an Indian cohort.
MATERIALS AND METHODS:
Targeted resequencing of 12 exons and 10 kb upstream sequences of DBH in healthy volunteers (n=50) was performed using the Ion Personal Genome Machine System. Enzyme quantity and activity in their sera samples were determined by ELISA and ultra performance liquid chromatography, respectively. The association of markers with phenotypes was determined using Matrix eQTL. Global P-values for haplotypes generated using UNPHASED 3.1.5 were graphed using GrASP v.082 beta.
RESULTS:
Of the 49 variants identified, nine were novel (minor allele frequency≥0.01). Though individual markers associated with enzyme quantity did not withstand multiple corrections, a novel distal promoter block driven by rs113249250 (global P=1.5×10) was associated. Of the nine single nucleotide polymorphisms (SNPs) associated with enzyme activity, rs3025369, rs1076151 and rs1611115, all from the upstream region, withstood false discovery rate correction (false discovery rate=0.03, 0.03 and 2.9×10, respectively). Conditioning for rs1611115 identified rs1989787 also to affect activity. Importantly, we report an association of a novel haplotype block distal to rs1076151 driven by rs3025369 (global P=8.9×10) with enzyme activity. This regulatory SNP explained 4.9% of the total 46.1% of variance in DBH activity caused by associated SNPs.
CONCLUSION:
This first study combining deep sequencing and enzyme phenotyping identified yet another regulatory SNP suggesting that regulatory variants may be central in the physiological or metabolic role of this gene of therapeutic and pharmacological relevance.
Correlation of plasma dopamine beta-hydroxylase activity with polymorphisms in DBH gene: a study on Eastern Indian population.
Plasma dopamine beta-hydroxylase activity (plDbetaH) is tightly regulated by the DBH gene and several genetic polymorphisms have been found to independently exert their influence. In the present investigation, association of four DBH polymorphisms, DBH-STR, rs1611115, rs1108580, and rs2519152 with plDbetaH was examined in blood samples from 100 unrelated individuals belonging to the state of West Bengal, Eastern India. Genotypes obtained after PCR amplification and restriction digestion were used for statistical analyses. plDbetaH was measured using a photometric assay and its correlation with the genetic polymorphisms was analyzed using analysis of variance and linear regression. Moderate linkage disequilibrium (LD) was observed between DBH-STR and rs1611115, while rs1108580 and rs2519152 were in strong LD. ‘T’ allele of rs1611115 showed strong negative correlation with plDbetaH, whereas DBH-STR, rs1108580 and rs2519152 had no major effect. Four haplotypes showed significant influence on plDbetaH. This is the first report on the effect of genetic polymorphisms on plDbetaH from the Indian sub-continent. rs1611115 was the only polymorphism that showed substantial control over plDbetaH. Other polymorphisms which did not show individual effects could possibly be part of larger haplotype blocks that carry the functional polymorphisms controlling plDbetaH.
Polymorphisms and low plasma activity of dopamine-beta-hydroxylase in ADHD children.
Attention-deficit Hyperactivity disorder (ADHD) is a multifactorial disorder clinically characterized by inattentiveness, impulsivity and hyperactivity. The occurrence of this disorder is between 3 and 6% of the children population, with boys predominating over girls at a ratio of 3:1 or more. The research of some candidate genes (DRD4, DAT, DRD5, DBH, 5HTT, HTR1B and SNAP25) brought consistent results confirming the heredity of ADHD syndromes. Dopamine-beta-hydroxylase (DBH) is an enzyme responsible for the conversion of dopamine into noradrenaline. Alteration of the dopamine/noradrenaline levels can result in hyperactivity. The DBH protein is released in response to stimulation. DBH activity, derived largely from sympathetic nerves, can be measured in human plasma. Patients with ADHD showed decreased activities of DBH in serum and urine. Low DBH levels correlate indirectly with the seriousness of the hyperkinetic syndrome in children [19,20]. In the DBH gene, the G444A, G910T, C1603T, C1912T, C-1021T, 5 -ins/del and TaqI polymorphisms occur frequently and may affect the function of gene products or modify gene expression and thus influence the progression of ADHD. This article reviews the DBH itself and polymorphisms in the DBH gene that influence the DBH activity in the serum and the CSF level of DBH. All those are evaluated in connection with ADHD.
Candidate gene studies of attention-deficit/hyperactivity disorder.
A growing body of behavioral and molecular genetics literature has indicated that the development of attention-deficit/hyperactivity disorder (ADHD) may be attributed to both genetic and environmental factors. Family, twin, and adoption studies provide compelling evidence that genes play a strong role in mediating susceptibility to ADHD. Molecular genetic studies suggest that the genetic architecture of ADHD is complex, while the handful of genome-wide scans conducted thus far is not conclusive. In contrast, the many candidate gene studies of ADHD have produced substantial evidence implicating several genes in the etiology of the disorder. For the 8 genes for which the same variant has been studied in 3 or more case-control or family-based studies, 7 show statistically significant evidence of association with ADHD based on pooled odds ratios across studies: the dopamine D4 receptor gene (DRD4), the dopamine D5 receptor gene (DRD5), the dopamine transporter gene (DAT), the dopamine beta-hydroxylase gene (DBH), the serotonin transporter gene (5-HTT), the serotonin receptor 1B gene (HTR1B), and the synaptosomal-associated protein 25 gene (SNAP25). Recent pharmacogenetic studies have correlated treatment nonresponse with particular gene markers, while preclinical studies have increased our understanding of gene expression paradigms and potential analogs for human trials. This literature review discusses the relevance and implications of genetic associations with ADHD for clinical practice and future research
Lack of significant association between -1021C–>T polymorphism in the dopamine beta hydroxylase gene and attention deficit hyperactivity disorder.
Recent trends in medications for attention deficit hyperactivity disorder (ADHD) suggest that norepinephrine (NE) deficiency may contribute to the disease etiology. Dopamine beta hydroxylase (DBH) is the key enzyme which converts dopamine to NE and since DBH gene is considered a major quantitative trait locus for plasma DBH activity, genetic polymorphism may lead to altered NE neurotransmission. Several polymorphisms including a 5′ flanking -1021C–>T polymorphism, was reported to be associated with changed DBH activity and an association between -1021C–>T polymorphism with ADHD was observed in Han Chinese children. We have carried out family-based studies with three polymorphisms in the DBH gene, -1021C–>T polymorphism, exon 2*444g/a and intron 5 TaqI RFLP, to explore their association with Indian ADHD cases. Allele and genotype frequency of these polymorphisms in ADHD cases were compared with that of their parents and a control group. Haplotypes obtained were analyzed for linkage disequilibrium (LD). Haplotype-based haplotype relative risk analysis and transmission disequilibrium test showed lack of significant association between transmission of the polymorphisms and ADHD. A haplotype comprising of allele 1 of all polymorphisms showed a slight positive trend towards transmission from parents to ADHD probands. Strong LD was observed between *444g/a and TaqI RFLP in all the groups. However, low D’ values and corresponding log of odds scores in the control group as compared to the ADHD families indicated that, the incidence of the two polymorphisms being transmitted together could be higher in ADHD families.
Association of the dopamine beta hydroxylase gene with attention deficit hyperactivity disorder: genetic analysis of the Milwaukee longitudinal study.
Attention deficit hyperactivity disorder (ADHD) is a highly heritable and common disorder that partly reflects disturbed dopaminergic function in the brain. Recent genetic studies have shown that candidate genes involved in dopamine signaling and metabolism contribute to ADHD susceptibility. We have initiated genetic studies in a unique cohort of 158 ADHD and 81 control adult subjects who have been followed longitudinally since childhood in the Milwaukee study of ADHD. From this cohort, genetic analysis was performed in 105 Caucasian subjects with ADHD and 68 age and ethnicity-matched controls for the DRD4 exon 3 VNTR, the SLC6A3 (DAT1) 3′ UTR VNTR, dopamine beta hydroxylase (DBH) TaqI A polymorphism, and the DBH GT microsatellite repeat polymorphism that has been quantitatively associated with serum levels of DBH activity, but not previously studied in ADHD. Results indicate a significant association between the DBH TaqI A1 allele and ADHD (P = 0.018) with a relative risk of 1.33. The DBH GT repeat 4 allele, which is associated with high serum levels of DBH, occurred more frequently in the ADHD group than controls, but the difference did not reach statistical significance. Associations were not found with the SLC6A3 10 repeat or DRD4 7 repeat alleles. These results indicate that the DBH TaqI A allele, or another polymorphism in linkage disequilibrium with this allele, may confer increased susceptibility towards ADHD.
Polymorphisms of the dopamine transporter gene: influence on response to methylphenidate in attention deficit-hyperactivity disorder.
Attention deficit-hyperactivity disorder (ADHD) is a very common and heterogeneous childhood-onset psychiatric disorder, affecting between 3% and 5% of school age children worldwide. Although the neurobiology of ADHD is not completely understood, imbalances in both dopaminergic and noradrenergic systems have been implicated in the origin and persistence of core symptoms, which include inattention, hyperactivity, and impulsivity. The role of a genetic component in its etiology is strongly supported by genetic studies, and several investigations have suggested that the dopamine transporter gene (DAT1; SLC6A3 locus) may be a small-effect susceptibility gene for ADHD. Stimulant medication has a well-documented efficacy in reducing ADHD symptoms. Methylphenidate, the most prescribed stimulant, seems to act mainly by inhibiting the dopamine transporter protein and dopamine reuptake. In fact, its effect is probably related to an increase in extracellular levels of dopamine, especially in brain regions enriched in this protein (i.e. striatum). It is also important to note that dopamine transporter densities seem to be particularly elevated in the brain of ADHD patients, decreasing after treatment with methylphenidate. Altogether, these observations suggest that the dopamine transporter does play a major role in ADHD. Among the several polymorphisms already described in the SLC6A3 locus, a 40 bp variable number of tandem repeats (VNTR) polymorphism has been extensively investigated in association studies with ADHD. Although there are some negative results, the findings from these reports indicate the allele with ten copies of the 40 bp sequence (10-repeat allele) as the risk allele for ADHD. Some investigations have suggested that this polymorphism can be implicated in dopamine transporter gene expression in vitro and dopamine transporter density in vivo, even though it is located in a non-coding region of the SLC6A3 locus. Despite all these data, few studies have addressed the relationship between genetic markers (specifically the VNTR) at the SLC6A3 locus and response to methylphenidate in ADHD patients. A significant effect of the 40 bp VNTR on response to methylphenidate has been detected in most of these reports. However, the findings are inconsistent regarding both the allele (or genotype) involved and the direction of this influence (better or worse response). Thus, further investigations are required to determine if genetic variation due to the VNTR in the dopamine transporter gene is able to predict different levels of clinical response and palatability to methylphenidate in patients with ADHD, and how this information would be useful in clinical practice.
Pharmacogenomics in psychiatry: the relevance of receptor and transporter polymorphisms.
The treatment of severe mental illness, and of psychiatric disorders in general, is limited in its efficacy and tolerability. There appear to be substantial interindividual differences in response to psychiatric drug treatments that are generally far greater than the differences between individual drugs; likewise, the occurrence of adverse effects also varies profoundly between individuals. These differences are thought to reflect, at least in part, genetic variability. The action of psychiatric drugs primarily involves effects on synaptic neurotransmission; the genes for neurotransmitter receptors and transporters have provided strong candidates in pharmacogenetic research in psychiatry. This paper reviews some aspects of the pharmacogenetics of neurotransmitter receptors and transporters in the treatment of psychiatric disorders. A focus on serotonin, catecholamines and amino acid transmitter systems reflects the direction of research efforts, while relevant results from some genome-wide association studies are also presented. There are many inconsistencies, particularly between candidate gene and genome-wide association studies. However, some consistency is seen in candidate gene studies supporting established pharmacological mechanisms of antipsychotic and antidepressant response with associations of functional genetic polymorphisms in, respectively, the dopamine D2 receptor and serotonin transporter and receptors. More recently identified effects of genes related to amino acid neurotransmission on the outcome of treatment of schizophrenia, bipolar illness or depression reflect the growing understanding of the roles of glutamate and γ-aminobutyric acid dysfunction in severe mental illness. A complete understanding of psychiatric pharmacogenomics will also need to take into account epigenetic factors, such as DNA methylation, that influence individual responses to drugs.
Molecular genetic approaches provide a novel method of dissecting the heterogeneity of psychotropic drug response. These pharmacogenetic strategies offer the prospect of identifying biological predictors of psychotropic drug response and could provide the means of determining the molecular substrates of drug efficacy and drug-induced adverse events.
METHOD:
The authors discuss methods issues in executing pharmacogenetic studies, review the first generation of pharmacogenetic studies of psychotropic drug response, and consider future directions for this rapidly evolving field.
RESULTS:
Pharmacogenetics has been most commonly used in studies of antipsychotic drug efficacy, antidepressant drug response, and drug-induced adverse effects. Data from antipsychotic drug studies indicate that polymorphisms within the serotonin 2A and dopamine receptor 2 genes may influence drug efficacy in schizophrenia. Moreover, a growing body of data suggests a relationship between the serotonin transporter gene and clinical effects of the selective serotonin reuptake inhibitors used to treat depression. A significant relationship between genetic variation in the cytochrome P450 system and drug-induced adverse effects may exist for certain medications. Finally, a number of independent studies point to a significant effect of a dopamine D(3) receptor polymorphism on susceptibility to tardive dyskinesia.
CONCLUSIONS:
Initial research into the pharmacogenetics of psychotropic drug response suggests that specific genes may influence phenotypes associated with psychotropic drug administration. These results remain preliminary and will require further replication and validation. New developments in molecular biology, human genomic information, statistical methods, and bioinformatics are ongoing and could pave the way for the next generation of pharmacogenetic studies in psychiatry.
OBJECTIVE: Molecular genetic approaches provide a novel method of dissecting the heterogeneity of psychotropic drug response. These pharmacogenetic strategies offer the prospect of identifying biological predictors of psychotropic drug response and could provide the means of determining the molecular substrates of drug efficacy and drug-induced adverse events. METHOD: The authors discuss methods issues in executing pharmacogenetic studies, review the first generation of pharmacogenetic studies of psychotropic drug response, and consider future directions for this rapidly evolving field. RESULTS: Pharmacogenetics has been most commonly used in studies of antipsychotic drug efficacy, antidepressant drug response, and drug-induced adverse effects. Data from antipsychotic drug studies indicate that polymorphisms within the serotonin 2A and dopamine receptor 2 genes may influence drug efficacy in schizophrenia. Moreover, a growing body of data suggests a relationship between the serotonin transporter gene and clinical effects of the selective serotonin reuptake inhibitors used to treat depression. A significant relationship between genetic variation in the cytochrome P450 system and drug-induced adverse effects may exist for certain medications. Finally, a number of independent studies point to a significant effect of a dopamine D3 receptor polymorphism on susceptibility to tardive dyskinesia. CONCLUSIONS: Initial research into the pharmacogenetics of psychotropic drug response suggests that specific genes may influence phenotypes associated with psychotropic drug administration. These results remain preliminary and will require further replication and validation. New developments in molecular biology, human genomic information, statistical methods, and bioinformatics are ongoing and could pave the way for the next generation of pharmacogenetic studies in psychiatry.
We have completed a series of discussions on proteomics, a scientific endeavor that is essentially 15 years old. It is quite remarkable what has been accomplished in that time. The interest is abetted by the understanding of the limitations of the genomic venture that has preceded it. The thorough, yet incomplete knowledge of the genome, has led to the clarification of its limits. It is the coding for all that lives, but all that lives has evolved to meet a demanding and changing environment with respect to
availability of nutrients
salinity
temperature
radiation exposure
toxicities in the air, water, and food
stresses – both internal and external
We have seen how both transcription and translation of the code results in a protein, lipoprotein, or other complex than the initial transcript that was modeled from tRNA. What you see in the DNA is not what you get in the functioning cell, organ, or organism. There are comparabilities as well as significant differences between plants, prokaryotes, and eukaryotes. There is extensive variation. The variation goes beyond genomic expression, and includes the functioning cell, organ type, and species.
Here, I return to the introductory discussion. Proteomics is a goal directed, sophisticated science that uses a combination of methods to find the answers to biological questions. Graves PR and Haystead TAJ. Molecular Biologist’s Guide to Proteomics. Microbiol Mol Biol Rev. Mar 2002; 66(1): 39–63. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC120780/
Peptide mass tag searching
Peptide mass tag searching. Shown is a schematic of how information from an unknown peptide (top) is matched to a peptide sequence in a database (bottom) for protein identification. The partial amino acid sequence or “tag” obtained by MS/MS is combined with the peptide mass (parent mass), the mass of the peptide at the start of the sequence (mass tag 1), and the mass of the peptide at the end of the sequence (mass tag 2). The specificity of the protease used (trypsin is shown) can also be included in the search.
ICAT method for measuring differential protein expression
The ICAT method for measuring differential protein expression. (A) Structure of the ICAT reagent. ICAT consists of a biotin affinity group, a linker region that can incorporate heavy (deuterium) or light (hydrogen) atoms, and a thiol-reactive end group for linkage to cysteines. (B) ICAT strategy. Proteins are harvested from two different cell states and labeled on cysteine residues with either the light or heavy form of the ICAT reagent. Following labeling, the two protein samples are mixed and digested with a protease such as trypsin. Peptides labeled with the ICAT reagent can be purified by virtue of the biotin tag by using avidin chromatography. Following purification, ICAT-labeled peptides can be analyzed by MS to quantitate the peak ratios and proteins can be identified by sequencing the peptides with MS/MS.
Strategies for determination of phosphorylation sites in proteins
Strategies for determination of phosphorylation sites in proteins. Proteins phosphorylated in vitro or in vivo can be isolated by protein electrophoresis and analyzed by MS. (A) Identification of phosphopeptides by peptide mass fingerprinting. In this method, phosphopeptides are identified by comparing the mass spectrum of an untreated sample to that of a sample treated with phosphatase. In the phosphatase-treated sample, potential phosphopeptides are identified by a decrease in mass due to loss of a phosphate group (80 Da). (B) Phosphorylation sites can be identified by peptide sequencing using MS/MS. (C) Edman degradation can be used to monitor the release of inorganic 32P to provide information about phosphorylation sites in peptides.
protein mining strategy
Proteome-mining strategy. Proteins are isolated on affinity column arrays from a cell line, organ, or animal source and purified to remove nonspecific adherents. Then, compound libraries are passed over the array and the proteins eluted are analyzed by protein electrophoresis. Protein information obtained by MS or Edman degradation is then used to search DNA and protein databases. If a relevant target is identified, a sublibrary of compounds can be evaluated to refine the lead. From this method a protein target and a drug lead can be simultaneously identified.
Although the technology for the analysis of proteins is rapidly progressing, it is still not feasible to study proteins on a scale equivalent to that of the nucleic acids. Most of proteomics relies on methods, such as protein purification or PAGE, that are not high-throughput methods. Even performing MS can require considerable time in either data acquisition or analysis. Although hundreds of proteins can be analyzed quickly and in an automated fashion by a MALDI-TOF mass spectrometer, the quality of data is sacrificed and many proteins cannot be identified. Much higher quality data can be obtained for protein identification by MS/MS, but this method requires considerable time in data interpretation. In our opinion, new computer algorithms are needed to allow more accurate interpretation of mass spectra without operator intervention. In addition, to access unannotated DNA databases across species, these algorithms should be error tolerant to allow for sequencing errors, polymorphisms, and conservative substitutions. New technologies will have to emerge before protein analysis on a large-scale (such as mapping the human proteome) becomes a reality.
Another major challenge for proteomics is the study of low-abundance proteins. In some eukaryotic cells, the amounts of the most abundant proteins can be 106-fold greater than those of the low-abundance proteins. Many important classes of proteins (that may be important drug targets) such as transcription factors, protein kinases, and regulatory proteins are low-copy proteins. These low-copy proteins will not be observed in the analysis of crude cell lysates without some purification. Therefore, new methods must be devised for subproteome isolation.
Tissue Proteomics for the Next Decade? Towards a Molecular Dimension in Histology
R Longuespe´e, M Fle´ron, C Pottier, F Quesada-Calvo, Marie-Alice Meuwis, et al.
OMICS A Journal of Integrative Biology 2014; 18: 9. http://dx.doi.org:/10.1089/omi.2014.0033
The concept of tissues appeared more than 200 years ago, since textures and attendant differences were described within the whole organism components. Instrumental developments in optics and biochemistry subsequently paved the way to transition from classical to molecular histology in order to decipher the molecular contexts associated with physiological or pathological development or function of a tissue. In 1941, Coons and colleagues performed the first systematic integrated examination of classical histology and biochemistry when his team localized pneumonia antigens in infected tissue sections. Most recently, in the early 21st century, mass spectrometry (MS) has progressively become one of the most valuable tools to analyze biomolecular compounds. Currently, sampling methods, biochemical procedures, and MS instrumentations
allow scientists to perform ‘‘in depth’’ analysis of the protein content of any type of tissue of interest. This article reviews the salient issues in proteomics analysis of tissues. We first outline technical and analytical considerations for sampling and biochemical processing of tissues and subsequently the instrumental possibilities for proteomics analysis such as shotgun proteomics in an anatomical context. Specific attention concerns formalin fixed and paraffin embedded (FFPE) tissues that are potential ‘‘gold mines’’ for histopathological investigations. In all, the matrix assisted laser desorption/ionization (MALDI) MS imaging, which allows for differential mapping of hundreds of compounds on a tissue section, is currently the most striking evidence of linkage and transition between ‘‘classical’’ and ‘‘molecular’’ histology. Tissue proteomics represents a veritable field of research and investment activity for modern biomarker discovery and development for the next decade.
Progressively, tissue analyses evolved towards the description of the whole molecular content of a given sample. Currently, mass spectrometry (MS) is the most versatile
analytical tool for protein identification and has proven its great potential for biological and clinical applications. ‘‘Omics’’ fields, and especially proteomics, are of particular
interest since they allow the analysis of a biomolecular picture associated with a given physiological or pathological state. Biochemical techniques were then adapted for an optimal extraction of several biocompounds classes from tissues of different natures.
Laser capture microdissection (LCM) is used to select and isolate tissue areas of interest for further analysis. The developments of MS instrumentations have then definitively transformed the scientific scene, pushing back more and more detection and identification limits. Since a few decades, new approaches of analyses appeared, involving the use of tissue sections dropped on glass slides as starting material. Two types of analyses can then be applied on tissue sections: shotgun proteomics and the very promising MS imaging (MSI) using Matrix Assisted Laser Desorption/Ionization (MALDI) sources. Also known as ‘‘molecular histology,’’ MSI is the most striking hyphen between histology and molecular analysis. In practice, this method allows visualization of the spatial distribution of proteins, peptides, drugs, or others analytes directly on tissue sections. This technique paved new ways of research, especially in the field of histopathology, since this approach appeared to be complementary to conventional histology.
Tissue processing workflows for molecular analyses
Tissue processing workflows for molecular analyses. Tissues can either be processed in solution or directly on tissue sections. In solution, processing involves protein
extraction from tissue pieces in order to perform 2D gel separation and identification of proteins, shotgun proteomics, or MALDI analyses. Extracts can also be obtained from
tissues area selection and protein extraction after laser micro dissection or on-tissue processing. Imaging techniques are dedicated to the morphological characterization or molecular mapping of tissue sections. Histology can either be conducted by hematoxylin/eosin staining or by molecular mapping using antibodies with IHC. Finally, mass spectrometry imaging allows the cartography of numerous compounds in a single analysis. This approach is a modern form of ‘‘molecular histology’’ as it grafts, with the use of mathematical calculations, a molecular dimension to classical histology. (AR, antigen retrieval; FFPE, formalin fixed and paraffin embedded; fr/fr, fresh frozen; IHC, immunohistochemistry; LCM, laser capture microdissection; MALDI, matrix assisted laser desorption/ionization; MSI, mass spectrometry imaging; PTM, post translational modification.)
Analysis of tissue proteomes has greatly evolved with separation methods and mass spectrometry instrumentation. The choice of the workflow strongly depends on whether a bottom-up or a top-down analysis has to be performed downstream. In-gel or off-gel proteomics principally differentiates proteomic workflows. The almost simultaneous discoveries of the MS ionization sources (Nobel Prize awarded) MALDI (Hillenkamp and Karas, 1990; Tanaka et al., 1988) and electrospray ionization (ESI) (Fenn et al., 1989) have paved the way for analysis of intact proteins and peptides. Separation methods such as two-dimension electrophoresis (2DE) (Fey and Larsen, 2001) and nanoscale reverse phase liquid chromatography (nanoRP-LC) (Deterding et al., 1991) lead to efficient preparation of proteins for respectively topdown and bottom-up strategies. A huge panel of developments was then achieved mostly for LC-MS based proteomics in order to improve ion fragmentation approaches and peptide
identification throughput relying on database interrogation. Moreover, approaches were developed to analyze post translational modifications (PTM) such as phosphorylations (Ficarro et al., 2002; Oda et al., 2001; Zhou et al., 2001) or glycosylations (Zhang et al., 2003), proposing as well different quantification procedures. Regarding instrumentation, the most cutting edge improvements are the gain of mass accuracy for an optimal detection of the eluted peptides during LC-MS runs (Mann and Kelleher, 2008; Michalski et al., 2011) and the increase in scanning speed, for example with the use of Orbitrap analyzers (Hardman and Makarov, 2003; Makarov et al., 2006; Makarov et al., 2009; Olsen et al., 2009). Ion transfer efficiency was also drastically improved with the conception of ion funnels that homogenize the ion transmission
capacities through m/z ranges (Kelly et al., 2010; Kim et al., 2000; Page et al., 2006; Shaffer et al., 1998) or by performing electrospray ionization within low vacuum (Marginean et al., 2010; Page et al., 2008; Tang et al., 2011). Beside collision induced dissociation (CID) that is proposed for many applications (Li et al., 2009; Wells and McLuckey, 2005), new fragmentation methods were investigated, such as higher-energy collisional dissociation (HCD) especially for phosphoproteomic
applications (Nagaraj et al., 2010), and electron transfer dissociation (ETD) and electron capture dissociation (ECD) that are suited for phospho- and glycoproteomics (An
et al., 2009; Boersema et al., 2009; Wiesner et al., 2008). Methods for data-independent MS2 analysis based on peptide fragmentation in given m/z windows without precursor selection neither information knowledge, also improves identification throughput (Panchaud et al., 2009; Venable et al., 2004), especially with the use of MS instruments with high resolution and high mass accuracy specifications (Panchaud et al., 2011). Gas fractionation methods such as ion mobility (IM) can also be used as a supplementary separation dimension which enable more efficient peptide identifications (Masselon et al., 2000; Shvartsburg et al., 2013; Shvartsburg et al., 2011).
Microdissection relies on a laser ablation principle. The tissue section is dropped on a plastic membrane covering a glass slide. The preparation is then placed into a microscope
equipped with a laser. A highly focused beam will then be guided by the user at the external limit of the area of interest. This area composed by the plastic membrane, and the tissue section will then be ejected from the glass slide and collected into a tube cap for further processing. This mode of microdissection is the most widely used due to its ease of handling and the large panels of devices proposed by constructors. Indeed, Leica microsystem proposed the Leica LMD system (Kolble, 2000), Molecular Machine and Industries, the MMI laser microdissection system Microcut, which was used in combination with IHC (Buckanovich et al., 2006), Applied Biosystems developed the Arcturus
microdissection System, and Carl Zeiss patented P.A.L.M. MicroBeam technology (Braakman et al., 2011; Espina et al., 2006a; Espina et al., 2006b; Liu et al., 2012; Micke
et al., 2005). LCM represents a very adequate link between classical histology and sampling methods for molecular analyses as it is a simple customized microscope. Indeed,
optical lenses of different magnification can be used and the method is compatible with classical IHC (Buckanovich et al., 2006). Only the laser and the tube holder need to be
added to the instrumentation.
After microdissection, the tissue pieces can be processed for analyses using different available MS devices and strategies. The simplest one consists in the direct analysis of the
protein profiles by MALDI-TOF-MS (MALDI-time of flight-MS). The microdissected tissues are dropped on a MALDI target and directly covered by the MALDI matrix (Palmer-Toy et al., 2000; Xu et al., 2002). This approach was already used in order to classify breast cancer tumor types (Sanders et al., 2008), identify intestinal neoplasia protein biomarkers (Xu et al., 2009), and to determine differential profiles in glomerulosclerosis (Xu et al., 2005).
Currently the most common proteomic approach for LCM tissue analysis is LC-MS/MS. Label free LC-MS approaches have been used to study several cancers like head and neck squamous cell carcinomas (Baker et al., 2005), esophageal cancer (Hatakeyama et al., 2006), dysplasic cervical cells (Gu et al., 2007), breast carcinoma tumors (Hill et al., 2011; Johann et al., 2009), tamoxifen-resistant breast cancer cells (Umar et al., 2009), ER + / – breast cancer cells (Rezaul et al., 2010), Barretts esophagus (Stingl et al., 2011), and ovarian endometrioid cancer (Alkhas et al., 2011). Different isotope labeling methods have been used in order to compare proteins expression. ICAT was first used to investigate proteomes of hepatocellular carcinoma (Li et al., 2004; 2008). The O16/O18 isotopic labeling was then used for proteomic analysis of ductal carcinoma of the breast (Zang et al., 2004).
Currently, the lowest amount of collected cells for a relevant single analysis using fr/fr breast cancer tissues was 3000–4000 (Braakman et al., 2012; Liu et al., 2012; Umar et al., 2007). With a Q-Exactive (Thermo, Waltham) mass spectrometer coupled to LC, Braakman was able to identify up to 1800 proteins from 4000 cells. Processing
of FFPE microdissected tissues of limited sizes still remains an issue which is being addressed by our team.
Among direct tissue analyses modes, two categories of investigations can be done. MALDI profiling consists in the study of molecular localization of compounds and can be
combined with parallel shotgun proteomic methods. Imaging methods give less detailed molecular information, but is more focused on the accurate mapping of the detected compounds through tissue area. In 2007, a concept of direct tissue proteomics (DTP) was proposed for high-throughput examination of tissue microarray samples. However, contrary to the classical workflow, tissue section chemical treatment involved a first step of scrapping each FFPE tissue spot with a razor blade from the glass slide. The tissues were then transferred into a tube and processed with RIPA buffer and finally submitted to boiling as an AR step (Hwang et al., 2007). Afterward, several teams proved that it was possible to perform the AR directly on tissue sections. These applications were mainly dedicated to MALDI imaging analyses (Bonnel et al., 2011; Casadonte and Caprioli, 2011; Gustafsson et al., 2010). However, more recently, Longuespe´e used citric acid antigen retrieval (CAAR) before shotgun proteomics associated to global profiling proteomics (Longuespee et al., 2013).
MALDI imaging workflow
MALDI imaging workflow. For MALDI imaging experiments, tissue sections are dropped on conductive glass slides. Sample preparations are then adapted depending on the nature of the tissue sample (FFPE or fr/fr). Then, matrix is uniformly deposited on the tissue section using dedicated devices. A laser beam subsequently irradiates the preparation following a given step length and a MALDI spectrum is acquired for each position. Using adapted software, the different detected ions are then mapped through the tissue section, in function of their differential intensities. The ‘‘molecular maps’’ are called images. (FFPE, formalin fixed and paraffin embedded; fr/fr, fresh frozen; MALDI, matrix assisted laser desorption ionization.)
Proteomics instrumentations, specific biochemical preparations, and sampling methods such as LCM altogether allow for the deep exploration and comparison of different proteomes between regions of interest in tissues with up to 104 detected proteins. MALDI MS imaging that allows for differential mapping of hundreds of compounds on a tissue section is currently the most striking illustration of association between ‘‘classical’’ and ‘‘molecular’’ histology.
Novel serum protein biomarker panel revealed by mass spectrometry and its prognostic value in breast cancer
Introduction: Serum profiling using proteomic techniques has great potential to detect biomarkers that might improve diagnosis and predict outcome for breast cancer patients (BC). This study used surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry (MS) to identify differentially expressed proteins in sera from BC and healthy volunteers (HV), with the goal of developing a new prognostic biomarker panel.
Methods: Training set serum samples from 99 BC and 51 HV subjects were applied to four adsorptive chip surfaces (anion-exchange, cation-exchange, hydrophobic, and metal affinity) and analyzed by time-of-flight MS. For validation, 100 independent BC serum samples and 70 HV samples were analyzed similarly. Cluster analysis of protein spectra was performed to identify protein patterns related to BC and HV groups. Univariate and multivariate statistical analyses were used to develop a protein panel to distinguish breast cancer sera from healthy sera, and its prognostic potential was evaluated.
Results: From 51 protein peaks that were significantly up- or downregulated in BC patients by univariate analysis, binary logistic regression yielded five protein peaks that together classified BC and HV with a receiver operating characteristic (ROC) area-under-the-curve value of 0.961. Validation on an independent patient cohort confirmed
the five-protein parameter (ROC value 0.939). The five-protein parameter showed positive association with large tumor size (P = 0.018) and lymph node involvement (P = 0.016). By matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS, immunoprecipitation and western blotting the proteins were identified as a fragment
of apolipoprotein H (ApoH), ApoCI, complement C3a, transthyretin, and ApoAI. Kaplan-Meier analysis on 181 subjects after median follow-up of >5 years demonstrated that the panel significantly predicted disease-free survival (P = 0.005), its efficacy apparently greater in women with estrogen receptor (ER)-negative tumors (n = 50, P = 0.003) compared to ER-positive (n = 131, P = 0.161), although the influence of ER status needs to be confirmed after longer follow-up.
Conclusions: Protein mass profiling by MS has revealed five serum proteins which, in combination, can distinguish between serum from women with breast cancer and healthy control subjects with high sensitivity and specificity. The five-protein panel significantly predicts recurrence-free survival in women with ER-negative tumors and may have value in the management of these patients.
Cellular prion protein is required for neuritogenesis: fine-tuning of multiple signaling pathways involved in focal adhesions and actin cytoskeleton dynamics
Aurélie Alleaume-Butaux, et al. Cell Health and Cytoskeleton 2013:5 1–12
Neuritogenesis is a dynamic phenomenon associated with neuronal differentiation that allows a rather spherical neuronal stem cell to develop dendrites and axon, a prerequisite for the integration and transmission of signals. The acquisition of neuronal polarity occurs in three steps:
(1) neurite sprouting, which consists of the formation of buds emerging from the postmitotic neuronal soma;
(2) neurite outgrowth, which represents the conversion of buds into neurites, their elongation and evolution into axon or dendrites; and
(3) the stability and plasticity of neuronal polarity.
In neuronal stem cells, remodeling and activation of focal adhesions (FAs)
associated with deep modifications of the actin cytoskeleton is
a prerequisite for neurite sprouting and subsequent neurite outgrowth.
A multiple set of growth factors and interactors located in
the extracellular matrix and the plasma membrane orchestrate neuritogenesis
by acting on intracellular signaling effectors, notably small G proteins such as RhoA, Rac, and Cdc42,
which are involved in actin turnover and the dynamics of FAs.
The cellular prion protein (PrPC), a glycosylphosphatidylinositol (GPI)-anchored membrane protein
mainly known for its role in a group of fatal neurodegenerative diseases,
has emerged as a central player in neuritogenesis.
Here, we review the contribution of PrPC to neuronal polarization and
detail the current knowledge on the signaling pathways fine-tuned
by PrPC to promote neurite sprouting, outgrowth, and maintenance.
We emphasize that PrPC-dependent neurite sprouting is a process in which
PrPC governs the dynamics of FAs and the actin cytoskeleton via β1 integrin signaling.
The presence of PrPC is necessary to render neuronal stem cells
competent to respond to neuronal inducers and to develop neurites.
In differentiating neurons, PrPC exerts a facilitator role towards neurite elongation.
This function relies on the interaction of PrPC with a set of diverse partners such as
elements of the extracellular matrix,
plasma membrane receptors,
adhesion molecules, and
soluble factors that control actin cytoskeleton turnover
through Rho-GTPase signaling.
Once neurons have reached their terminal stage of differentiation and
acquired their polarized morphology,
PrPC also takes part in the maintenance of neurites.
By acting on tissue nonspecific alkaline phosphatase, or matrix metalloproteinase type 9,
PrPC stabilizes interactions between neurites and the extracellular matrix.
Fusion-pore expansion during syncytium formation is restricted by an actin network
Background: Role of uncoupling proteins (UCP) in the brain is unclear.
Results: UCP, present in astrocytes, mediate the intra-mitochondrial acidification leading to a decrease in mitochondrial ATP production.
Conclusion: Astrocyte pH regulation promotes ATP synthesis by glycolysis whose final product, lactate, increases neuronal survival.
Significance: We describe a new role for a brain uncoupling protein.
Brain activity is energetically costly and requires a steady and
highly regulated flow of energy equivalents between neural cells.
It is believed that a substantial share of cerebral glucose, the major source of energy of the brain,
will preferentially be metabolized in astrocytes via aerobic glycolysis.
The aim of this study was to evaluate whether uncoupling proteins (UCPs),
located in the inner membrane of mitochondria,
play a role in setting up the metabolic response pattern of astrocytes.
UCPs are believed to mediate the transmembrane transfer of protons
resulting in the uncoupling of oxidative phosphorylation from ATP production.
UCPs are therefore potentially important regulators of energy fluxes. The main UCP isoforms
expressed in the brain are UCP2, UCP4, and UCP5.
We examined in particular the role of UCP4 in neuron-astrocyte metabolic coupling
and measured a range of functional metabolic parameters
including mitochondrial electrical potential and pH,
reactive oxygen species production,
NAD/NADH ratio,
ATP/ADP ratio,
CO2 and lactate production, and
oxygen consumption rate (OCR).
In brief, we found that UCP4 regulates the intra-mitochondrial pH of astrocytes
which acidifies as a consequence of glutamate uptake,
with the main consequence of reducing efficiency of mitochondrial ATP production.
the diminished ATP production is effectively compensated by enhancement of glycolysis.
this non-oxidative production of energy is not associated with deleterious H2O2 production.
We show that astrocytes expressing more UCP4 produced more lactate,
used as energy source by neurons, and had the ability to enhance neuronal survival.
Jose Eduardo des Salles Roselino
The problem with genomics was it was set as explanation for everything. In fact, when something is genetic in nature the genomic reasoning works fine. However, this means whenever an inborn error is found and only in this case the genomic knowledge afterwards may indicate what is wrong and not the completely way to put biology upside down by reading everything in the DNA genetic as well as non-genetic problems.
Metabolomics is about Metabolic Systems Integration
Author and Curator: Larry H Bernstein, MD, FCAP
This is an exploration of biological thoughts in the series on metabolomics, putting enzymatic reactions, proteins and protein conformation, and subanatomic structure into a more complete perspective in order to realize normal and dysfunctional states
of eukaryoticcells and organ systems and prokaryotic organisms. There are structures and functions that have evolved in evolution that have concordance, even
if we find variation on themes. Moreover, these have to be understood in a systems oriented view to have any clarity, which is currently an ongoing proposal.
It is perhaps relevant to quote Radoslav Bosov on his observation:
“After finishing her portion of the work on DNA, Franklin led pioneering work on the tobacco mosaic virus and the polio virus. She died in 1958 at the age of 37 of ovarian cancer.” My job is to illuminate what is cancer, but serving structural identity issues.
DNA is not DNA, as RNA is not RNA as proteins are not Proteins, there is only time – interference of particles/strings/waves within ever emerging discrete relative spaces where energy transforms from one absolute form into another!
He adds the following: “A 2005 study showed methionine restriction without energy restriction extends mouse lifespan.” BUT balancing energy is not as same as balancing matter due quantum electrodynamics interference and transfromability – http://en.wikipedia.org/wiki/Methionine
I have made the following calculations!
1 – methyl groups = i Ln (1 – Lactate )/Ln (Oxygen) – K (O) =
i Ln (1/(Sqrt (1 – Acetate^2)) /Ln(Oxygen) – K(O) = i Ln (Glyoxylate)/Ln (Oxygen) – K(O)
where K(O) – mechanical electro magnetics pressure, with increase of T, increase of S (entropy), and 1-S = negative entropy
But don’t try to realize the path of derivation, it would get you in dark matter issues – water!
The problem seems to be:
Methionine is necessary to provide S for acetyl CoA
Insufficiency of this amino acid has consequences, which leads to increased homocysteine
This imbalance is also associated with a decrease in lewan body mass
Of course, the reality is that geographic location, proximity to volcanic ash, and temperate zone have relevance, as does food source, and they are relevant variables
JEDS Rosalino has referred to the important conclusion in Erwin Schroedinger’s “What is Life?”, and Schroedinger’s cat. It is impossible to come up with a predictive equation to explain life.
It had to come from a founder of “Quantum Mechanics” because, unlike economics, physics is a science based on experimental validation. In entering biology from Physics to make it more rigorous, as was the case for Max Delbruck, who was preceded by the Cori’s, Beadle and Tatum, Herschey, Luria, Dubecco, Kornberg and Ochoa, Lipmann, Watson and Crick, a discipline called “Molecular Biology and Biochemistry” emerged that would open the secrets of life. Beadle and Tatum gave us “one gene – one enzyme”, a formulation that led in medical teaching from William Osler’s edict to “Inherited Metabolic Disorders” – gene related disruption of the chemical reactions taking place in the body to convert or use energy. Physiological chemistry taught:
Breaking down the carbohydrates, proteins, and fats in food to release energy.
Transforming excess nitrogen into waste products excreted in urine.
Breaking down or converting chemicals into other substances and transporting them inside cells.
Metabolism is an organized but chaotic chemical assembly line. Raw materials, half-finished products, and waste materials are constantly being used, produced, transported, and excreted. The “workers” on the assembly line are enzymes and other proteins that make chemical reactions happen. – http://www.webmd.com/a-to-z-guides/inherited-metabolic-disorder-types-and-treatments
The original cause of most genetic metabolic disorders is a gene mutation that occurred many, many generations ago. Each inherited metabolic disorder is quite rare in the general population, affecting about 1 in 1,000 to 2,500 newborns. But the developments now refocused an emphasis on HOW – a gene mutation occurs that is passed on through generations. This had to be derived initially from methods developed in prokaryotes in order to relieve the complexity. However, complexity came from evolutionary events over a long time span.
Yeast cells display synchronized oscillation between
phases of high and low oxygen consumption
accompanied by a program of cyclical gene expression.
A study monitoring
mRNA levels,
histone modifications and
chromatin occupancy of histone modifiers
during the yeast metabolic cycle (YMC) at high temporal resolution reveals both
‘just-in-time’ supply of YMC gene products and
new patterns of chromatin reconfiguration
associated with transcriptional regulation.
Figure 1: The yeast metabolic cycle.
The YMC is divided into metabolic phases that correspond to periods of high and low oxygen concentration in the culture medium. The program of gene (mRNA) expression during the YMC is composed of successive reductive-charging (RC),… http://www.nature.com/nsmb/journal/v21/n10/carousel/nsmb.2898-F1.jpg
Figure 2: Modes of transcriptional regulation during the YMC.
Modes of transcriptional regulation during the YMC
(a) Previous work on cycling cells in batch culture revealed that H3K4me3 is typically limited to the promoter region of active genes (MET16 shown here 9, 10). (b) During the YMC, however, the OX gene RMT2 is marked by H3K4me3 regardles…
Under continuous, glucose-limited conditions, budding yeast exhibit
robust metabolic cycles
associated with major oscillations of gene expression.
We examine the correlated
genome-wide transcription and chromatin states
across the yeast metabolic cycle
at unprecedented temporal resolution,
revealing a ‘just-in-time supply chain’
by which components from specific cellular processes such as ribosome biogenesis become available in a highly coordinated manner. We identify
distinct chromatin and splicing patterns
associated with different gene categories and
determine the relative timing of chromatin modifications
relative to maximal transcription.
There is unexpected variation in the chromatin modification and expression relationship, with
histone acetylation peaks occurring with
varying timing and ‘sharpness’ relative to RNA expression
both within and between cycle phases.
Chromatin-modifier occupancy reveals subtly distinct spatial and temporal patterns compared to those of the modifications themselves.
Figure 1: High-temporal-resolution analysis of gene expression reveals meticulous temporal compartmentalization in yeast.
High-temporal-resolution analysis of gene expression
Oscillation of oxygen (dO2) in the YMC. The 16 time points of one cycle for RNA-seq are labeled. Metabolic phases are color coded throughout figures: magenta, OX phase; green, RB phase; blue, RC phase. (b–d) Subtly distinct tempor…
Figure 2: RNA-seq analysis at introns reveals transient accumulation of pre-mRNAs during OX phase.
RNA-seq analysis at introns reveals transient accumulation of pre-mRNAs
Relative RNA signals at intron-containing genes. Each track represents relative RNA levels at one of 16 time points, ordered sequentially from top to bottom. Signals are displayed as a percentage of the maximum value of the 16 time… http://www.nature.com/nsmb/journal/v21/n10/carousel/nsmb.2881-F2.jpg
Figure 3: Dynamic chromatin states across the YMC.
Dynamic chromatin states across the YMC
(a)Oscillation of oxygen in one YMC. Cycling cells were collected at 16 intentionally uneven time points over one cycle for ChIP-seq. (b,c) Temporal relationship between RNA level and histone modifications at the RMT2 locus. (b) RNA…
We present a quantitative model to demonstrate that
coclustering multiple enzymes into compact agglomerates
accelerates the processing of intermediates,
yielding the same efficiency benefits as direct channeling,
a well-known mechanism in which enzymes are funneled between enzyme active sites through a physical tunnel. The model predicts
the separation and size of coclusters that maximize metabolic efficiency,
and this prediction is in agreement with previously reported spacings between coclusters in mammalian cells.
For direct validation, we study a metabolic branch point in Escherichia coli and experimentally confirm the model prediction that enzyme agglomerates can
accelerate the processing of a shared intermediate by one branch, and thus
regulate steady-state flux division.
Our studies establish a quantitative framework to understand coclustering-mediated metabolic channeling
Figure 1: Different types of intermediate channeling in a two-step metabolic pathway, where a substrate is processed by enzyme E1 and turned into intermediate, which is then processed by enzyme E2 and turned into product.
two-step metabolic pathway
Direct channeling. The intermediate is funneled from enzyme E1 to enzyme E2 by means of a protein tunnel that connects the active sites of E1 and E2, thus preventing the intermediate from diffusing away. (b) Proximity channeling. http://www.nature.com/nbt/journal/v32/n10/carousel/nbt.3018-F1.jpg
Figure 2: Two-step metabolic pathway with an unstable intermediate.
Two-step metabolic pathway with an unstable intermediate
(a) The two-step metabolic pathway. Substrate S0 is processed by enzyme E1 and turned into intermediate S1, which is then processed by enzyme E2 and turned into product P. (b) Enzyme configurations in the two-step metabolic pathway. Le… http://www.nature.com/nbt/journal/v32/n10/carousel/nbt.3018-F2.jpg
Part 3. Antibiotics directed at specific DNA sequences
Sequence-specific antimicrobials using efficiently delivered RNA-guided nucleases
Current antibiotics tend to be broad spectrum, leading to
indiscriminate killing of commensal bacteria and
accelerated evolution of drug resistance.
Here, we use CRISPR-Cas technology to create antimicrobials
whose spectrum of activity is chosen by design.
RNA-guided nucleases (RGNs) targeting specific DNA sequences are delivered efficiently to microbial populations using bacteriophage or bacteria carrying plasmids transmissible by conjugation. The DNA targets of RGNs can be
undesirable genes or polymorphisms,
including antibiotic resistance and virulence determinants in
carbapenem-resistant Enterobacteriaceae and
enterohemorrhagic Escherichia coli.
Delivery of RGNs significantly improves survival in a Galleria mellonella infection model. We also show that
RGNs enable modulation of complex bacterial populations
by selective knockdown of targeted strains
based on genetic signatures.
RGNs constitute a class of highly discriminatory, customizable antimicrobials that enact
selective pressure at the DNA level to
reduce the prevalence of undesired genes,
minimize off-target effects and
enable programmable remodeling of microbiota.
Figure 1: RGN constructs delivered by bacteriophage particles (ΦRGN) exhibit efficient and specific antimicrobial effects against strains harboring plasmid or chromosomal target sequences
RGN constructs delivered by bacteriophage particles
(a) Bacteriophage-delivered RGN constructs differentially affect host cell physiology in a sequence-dependent manner. If the target sequence is: (i) absent, the RGN exerts no effect; (ii) chromosomal, RGN activity is cytotoxic; (iii) e…
Figure 3: ΦRGN particles elicit sequence-specific toxicity against enterohemorrhagic E. coli in vitroand in vivo.
ΦRGN particles elicit sequence-specific toxicity against enterohemorrhagic E. coli in vitro and in vivo.
(a) E. coli EMG2 wild-type (WT) cells or ATCC 43888 F′ (EHEC) cells were treated with SM buffer, ΦRGNndm-1 orΦRGNeae at a multiplicity of infection (MOI) ~100 and plated onto LB agar to enumerate total cell number or LB+kanamycin (Km)… http://www.nature.com/nbt/journal/vaop/ncurrent/carousel/nbt.3011-F3.jpg
Part 4. Structure and Isoform functions
Structures of human constitutive nitric oxide synthases.
H Li, J Jamal, C Plaza, SH Pineda, G Chreifi, Q Jing, MA Cinelli, RB Silverman, TLPoulos, [more]
Acta Crystallographica Section D Biological Crystallography (Impact Factor: 12.67). 10/2014; 70(Pt 10):2667-74. http://dx.doi.org:/10.1107/S1399004714017064
Mammals produce three isoforms of nitric oxide synthase (NOS):
neuronal NOS (nNOS),
inducible NOS (iNOS) and
endothelial NOS (eNOS).
The overproduction of NO by nNOS is associated with a number of neurodegenerative disorders; therefore, a desirable therapeutic goal is
the design of drugs that target nNOS
but not the other isoforms.
Crystallography, coupled with computational approaches and medicinal chemistry, has played a critical role in developing highly
selective nNOS inhibitors that
exhibit exceptional neuroprotective properties.
For historic reasons, crystallography has focused on rat nNOS and bovine eNOS because these were available in high quality; thus, their structures have been used in
structure-activity-relationship studies.
Although these constitutive NOSs share more than 90% sequence identity across mammalian species for each NOS isoform,
inhibitor-binding studies revealed that subtle differences near the heme active site
in the same NOS isoform across species still impact enzyme-inhibitor interactions.
Therefore, structures of the human constitutive NOSs are indispensible. Here, the first structure of human neuronal NOS at 2.03 Å resolution is reported and a different crystal form of human endothelial NOS is reported at 1.73 Å resolution.
“We are learning more about less and less” – PJ Russell. 1973.
Part 5. Global Metabolomics
Global Metabolomics Market (Technique, Application, Indication and Geography) – Size, Application Analysis, Regional Outlook, Competitive Strategies and Forecasts, 2014 – 2020
Metabolomics is
the study of chemical processes which involve metabolites.
Metabolites are small molecules present in the blood, tissues and urine. Metabolomics pertains to the study of the
unique chemical fingerprints left behind by cellular processes.
These metabolite fingerprints could be used to learn about the health of an organism. It is an upcoming technology in the field of analytical biochemistry. Metabolomics has become an experimental technique that can be applied in medicine, biology and environmental science. The incorporation of computers has enabled
the creation of computational metabolomics that has application in life sciences.
Metabolics finds application in other areas as well; for instance, it is used to identify the quality, taste and nutritional value of food in the food science field.
The metabolomics market is segmented based on its application in different fields such as
biomarkers discovery,
drug discovery,
toxicology testing,
nutrigenomics,
clinical studies etc.
The drug discovery segment holds the dominant share in the metabolomics market due to its crucial role in
drug target identification & validation and
optimization & prioritization of diagnostic approaches for oncology research.
The metabolomics market is expected to grow at a rapid rate due to the rise in the number of
pre clinical & clinical trials,
advancements in toxicological studies and
growing awareness about nutritional products.
The stellar growth of data analysis software & solutions in metabolomics and its use in the biomarker screening of diseases would fuel the growth of the metabolomics market. The metabolomics market is also segmented based on techniques into
gas chromatography,
high performance liquid chromatography (HPLC),
ultra performance liquid chromatography, and
capillary electrophoresis.
HPLC holds the dominant share in the metabolomics market.
KEY BENEFITS
In-depth analysis of various regions would enable a clear understanding of current and future trends so that companies can make region specific plans
Comprehensive analysis of the factors that drive and restrict the growth of the metabolomics market
Key regulatory guidelines in various regions which impact the metabolomics market
Quantitative analysis of the current market
Deep dive analysis of various regions
Value chain analysis enables a clear understanding of the roles of the stakeholders involved in the supply chain of the metabolomics market
Market Segmentation
The metabolomics market is segmented based on techniques, applications, indication and geography
What is the Future for Genomics in Clinical Medicine?
Author and Curator: Larry H Bernstein, MD, FCAP
Introduction
This is the last in a series of articles looking at the past and future of the genome revolution. It is a revolution indeed that has had a beginning with the first phase discovery leading to the Watson-Crick model, the second phase leading to the completion of the Human Genome Project, a third phase in elaboration of ENCODE. But we are entering a fourth phase, not so designated, except that it leads to designing a path to the patient clinical experience.
What is most remarkable on this journey, which has little to show in treatment results at this time, is that the boundary between metabolism and genomics is breaking down. The reality is that we are a magnificent “magical” experience in evolutionary time, functioning in a bioenvironment, put rogether like a truly complex machine, and with interacting parts. What are those parts – organelles, a genetic message that may be constrained and it may be modified based on chemical structure, feedback, crosstalk, and signaling pathways. This brings in diet as a source of essential nutrients, exercise as a method for delay of structural loss (not in excess), stress oxidation, repair mechanisms, and an entirely unexpected impact of this knowledge on pharmacotherapy. I illustrate this with some very new observations.
Gutenberg Redone
The first is a recent talk on how genomic medicine has constructed a novel version of the “printing press”, that led us out of the dark ages.
In our series The Creative Destruction of Medicine, I’m trying to get into critical aspects of how we can Schumpeter or reboot the future of healthcare by leveraging the big innovations that are occurring in the digital world, including digital medicine.
We have this big thing about evidence-based medicine and, of course, the sanctimonious randomized, placebo-controlled clinical trial. Well, that’s great if one can do that, but often we’re talking about needing thousands, if not tens of thousands, of patients for these types of clinical trials. And things are changing so fast with respect to medicine and, for example, genomically guided interventions that it’s going to become increasingly difficult to justify these very large clinical trials.
For example, there was a drug trial for melanoma and the mutation of BRAF, which is the gene that is found in about 60% of people with malignant melanoma. When that trial was done, there was a placebo control, and there was a big ethical charge asking whether it is justifiable to have a body count. This was a matched drug for the biology underpinning metastatic melanoma, which is essentially a fatal condition within 1 year, and researchers were giving some individuals a placebo.
The next observation is a progression of what he have already learned. The genome has a role is cellular regulation that we could not have dreamed of 25 years ago, or less. The role is far more than just the translation of a message from DNA to RNA to construction of proteins, lipoproteins, cellular and organelle structures, and more than a regulation of glycosidic and glycolytic pathways, and under the influence of endocrine and apocrine interactions. Despite what we have learned, the strength of inter-molecular interactions, strong and weak chemical bonds, essential for 3-D folding, we know little about the importance of trace metals that have key roles in catalysis and because of their orbital structures, are essential for organic-inorganic interplay. This will not be coming soon because we know almost nothing about the intracellular, interstitial, and intrvesicular distributions and how they affect the metabolic – truly metabolic events.
I shall however, use some new information that gives real cause for joy.
Reprogramming Alters Cells’ Fate
Kathy Liszewski
Gordon Conference Report: June 21, 2012;32(11)
New and emerging strategies were showcased at Gordon Conference’s recent “Reprogramming Cell Fate” meeting. For example, cutting-edge studies described how only a handful of key transcription factors were needed to entirely reprogram cells.
M. Azim Surani, Ph.D., Marshall-Walton professor at the Gurdon Institute, University of Cambridge, U.K., is examining cellular reprogramming in a mouse model. Epiblast stem cells are derived from the early-stage embryonic stage after implantation of blastocysts, about six days into development, and retain the potential to undergo reversion to embryonic stem cells (ESCs) or to PGCs.” They report two critical steps both of which are needed for exploring epigenetic reprogramming. “Although there are two X chromosomes in females, the inactivation of one is necessary for cell differentiation. Only after epigenetic reprogramming of the X chromosome can pluripotency be acquired. Pluripotent stem cells can generate any fetal or adult cell type but are not capable of developing into a complete organism.”
The second read-out is the activation of Oct4, a key transcription factor involved in ESC development. The expression of Oct4 in epiSCs requires its proximal enhancer. Dr. Surani said that their cell-based system demonstrates how a systematic analysis can be performed to analyze how other key genes contribute to the many-faceted events involved in reprogramming the germline.
Reprogramming Expressway
A number of other recent studies have shown the importance of Oct4 for self-renewal of undifferentiated ESCs. It is sufficient to induce pluripotency in neural tissues and somatic cells, among others. The expression of Oct4 must be tightly regulated to control cellular differentiation. But, Oct4 is much more than a simple regulator of pluripotency, according to Hans R. Schöler, Ph.D., professor in the department of cell and developmental biology at the Max Planck Institute for Molecular Biomedicine.
Oct4 has a critical role in committing pluripotent cells into the somatic cellular pathway. When embryonic stem cells overexpress Oct4, they undergo rapid differentiation and then lose their ability for pluripotency. Other studies have shown that Oct4 expression in somatic cells reprograms them for transformation into a particular germ cell layer and also gives rise to induced pluripotent stem cells (iPSCs) under specific culture conditions.
Oct4 is the gatekeeper into and out of the reprogramming expressway. By modifying experimental conditions, Oct4 plus additional factors can induce formation of iPSCs, epiblast stem cells, neural cells, or cardiac cells. Dr. Schöler suggests that Oct4 a potentially key factor not only for inducing iPSCs but also for transdifferention. “Therapeutic applications might eventually focus less on pluripotency and more on multipotency, especially if one can dedifferentiate cells within the same lineage. Although fibroblasts are from a different germ layer, we recently showed that adding a cocktail of transcription factors induces mouse fibroblasts to directly acquire a neural stem cell identity.
Stem cell diagram illustrates a human fetus stem cell and possible uses on the circulatory, nervous, and immune systems. (Photo credit: Wikipedia)
Transforming growth factor beta (TGF-β) is a secreted protein that controls proliferation, cellular differentiation, and other functions in most cells. http://en.wikipedia.org/wiki/TGFbeta (Photo credit: Wikipedia)
Pioneer Transcription Factors
Pioneer transcription factors take the lead in facilitating cellular reprogramming and responses to environmental cues. Multicellular organisms consist of functionally distinct cellular types produced by differential activation of gene expression. They seek out and bind specific regulatory sequences in DNA. Even though DNA is coated with and condensed into a thick fiber of chromatin. The pioneer factor, discovered by Prof. KS Zaret at UPenn SOM in 1996, he says, endows the competence for gene activity, being among the first transcription factors to engage and pry open the target sites in chromatin.
FoxA factors, expressed in the foregut endoderm of the mouse,are necessary for induction of the liver program. They found that nearly one-third of the DNA sites bound by FoxA in the adult liver occur near silent genes
A Nontranscriptional Role for HIF-1α as a Direct Inhibitor of DNA Replication
Many of the cellular responses to reduced O2 availability are mediated through the transcriptional activity of hypoxia-inducible factor 1 (HIF-1). We report a role for the isolated HIF-1α subunit as an inhibitor of DNA replication, and this role was independent of HIF-1β and transcriptional regulation. In response to hypoxia, HIF-1α bound to Cdc6, a protein that is essential for loading of the mini-chromosome maintenance (MCM) complex (which has DNA helicase activity) onto DNA, and promoted the interaction between Cdc6 and the MCM complex. The binding of HIF-1α to the complex decreased phosphorylation and activation of the MCM complex by the kinase Cdc7. As a result, HIF-1α inhibited firing of replication origins, decreased DNA replication, and induced cell cycle arrest in various cell types. To whom correspondence should be addressed. E-mail: gsemenza@jhmi.edu
Citation: M. E. Hubbi, Kshitiz, D. M. Gilkes, S. Rey, C. C. Wong, W. Luo, D.-H. Kim, C. V. Dang, A. Levchenko, G. L. Semenza, A Nontranscriptional Role for HIF-1α as a Direct Inhibitor of DNA Replication. Sci. Signal. 6, ra10 (2013).
Identification of a Candidate Therapeutic Autophagy-inducing Peptide
Beth Levine and colleagues have constructed a cell-permeable peptide derived from part of an autophagy protein called beclin 1. This peptide is a potent inducer of autophagy in mammalian cells and in vivo in mice and was effective in the clearance of several viruses including chikungunya virus, West Nile virus and HIV-1.
Could this small autophagy-inducing peptide may be effective in the prevention and treatment of human diseases?
PR-Set7 Is a Nucleosome-Specific Methyltransferase that Modifies Lysine 20 of
Histone H4 and Is Associated with Silent Chromatin
We have purified a human histone H4 lysine 20methyl-transferase and cloned the encoding gene, PR/SET07. A mutation in Drosophila pr-set7 is lethal: second in-star larval death coincides with the loss of H4 lysine 20 methylation, indicating a fundamental role for PR-Set7 in development. Transcriptionally competent regions lack H4 lysine 20 methylation, but the modification coincided with condensed chromosomal regions polytene chromosomes, including chromocenter euchromatic arms. The Drosophila male X chromosome, which is hyperacetylated at H4 lysine 16, has significantly decreased levels of lysine 20 methylation compared to that of females. In vitro, methylation of lysine 20 and acetylation of lysine 16 on the H4 tail are competitive. Taken together, these results support the hypothesis that methylation of H4 lysine 20 maintains silent chromatin, in part, by precluding neighboring acetylation on the H4 tail.
Next-Generation Sequencing vs. Microarrays
Shawn C. Baker, Ph.D., CSO of BlueSEQ
GEN Feb 2013
With recent advancements and a radical decline in sequencing costs, the popularity of next generation sequencing (NGS) has skyrocketed. As costs become less prohibitive and methods become simpler and more widespread, researchers are choosing NGS over microarrays for more of their genomic applications. The immense number of journal articles citing NGS technologies it looks like NGS is no longer just for the early adopters. Once thought of as cost prohibitive and technically out of reach, NGS has become a mainstream option for many laboratories, allowing researchers to generate more complete and scientifically accurate data than previously possible with microarrays.
Gene Expression
Researchers have been eager to use NGS for gene expression experiments for a detailed look at the transcriptome. Arrays suffer from fundamental ‘design bias’ —they only return results from those regions for which probes have been designed. The various RNA-Seq methods cover all aspects of the transcriptome without any a priori knowledge of it, allowing for the analysis of such things as novel transcripts, splice junctions and noncoding RNAs. Despite NGS advancements, expression arrays are still cheaper and easier when processing large numbers of samples (e.g., hundreds to thousands).
Methylation
While NGS unquestionably provides a more complete picture of the methylome, whole genome methods are still quite expensive. To reduce costs and increase throughput, some researchers are using targeted methods, which only look at a portion of the methylome. Because details of exactly how methylation impacts the genome and transcriptome are still being investigated, many researchers find a combination of NGS for discovery and microarrays for rapid profiling.
Diagnostics
They are interested in ease of use, consistent results, and regulatory approval, which microarrays offer. With NGS, there’s always the possibility of revealing something new and unexpected. Clinicians aren’t prepared for the extra information NGS offers. But the power and potential cost savings of NGS-based diagnostics is alluring, leading to their cautious adoption for certain tests such as non-invasive prenatal testing. Cytogenetics
Perhaps the application that has made the least progress in transitioning to NGS is cytogenetics. Researchers and clinicians, who are used to using older technologies such as karyotyping, are just now starting to embrace microarrays. NGS has the potential to offer even higher resolution and a more comprehensive view of the genome, but it currently comes at a substantially higher price due to the greater sequencing depth. While dropping prices and maturing technology are causing NGS to make headway in becoming the technology of choice for a wide range of applications, the transition away from microarrays is a long and varied one. Different applications have different requirements, so researchers need to carefully weigh their options when making the choice to switch to a new technology or platform. Regardless of which technology they choose, genomic researchers have never had more options.
Sequencing Hones In on Targets
Greg Crowther, Ph.D.
GEN Feb 2013
Cliff Han, PhD, team leader at the Joint Genome Institute in the Los Alamo National Lab, was one of a number of scientists who made presentations regarding target enrichment at the “Sequencing, Finishing, and Analysis in the Future” (SFAF) conference in Santa Fe, which was co-sponsored by the Los Alamos National Laboratory and DOE Joint Genome Institute. One of the main challenges is that of target enrichment: the selective sequencing of genomic or transcriptomic regions. The polymerase chain reaction (PCR) can be considered the original target-enrichment technique and continues to be useful in contexts such as genome finishing. “One target set is the unique gaps—the gaps in the unique sequence regions. Another is to enrich the repetitive sequences…ribosomal RNA regions, which together are about 5 kb or 6 kb.” The unique-sequence gaps targeted for PCR with 40-nucleotide primers complementary to sequences adjacent to the gaps, did not yield the several-hundred-fold enrichment expected based on previously published work. “We got a maximum of 70-fold enrichment and generally in the dozens of fold of enrichment,” noted Dr. Han.
“We enrich the genome, put the enriched fragments onto the Pacific Biosciences sequencer, and sequence the repeats,” continued Dr. Han. “In many parts of the sequence there will be a unique sequence anchored at one or both ends of it, and that will help us to link these scaffolds together.” This work, while promising, will remain unpublished for now, as the Joint Genome Institute has shifted its resources to other projects.
At the SFAF conference Dr. Jones focused on going beyond basic target enrichment and described new tools for more efficient NGS research. “Hybridization methods are flexible and have multiple stop-start sites, and you can capture very large sizes, but they require library prep,” said Jennifer Carter Jones, Ph.D., a genomics field applications scientist at Agilent. “With PCR-based methods, you have to design PCR primers and you’re doing multiplexed PCR, so it’s limited in the size that you can target. But the workflow is quick because there’s no library preparation; you’re just doing PCR.” She discussed Agilent’s recently acquired HaloPlex technology, a hybrid system that includes both a hybridization step and a PCR step. Because no library preparation is required, sequencing results can be obtained in about six hours, making it suitable for clinical uses. However, the hybridization step allows capture of targets of up to 5 megabases—longer than purely PCR-based methods can deliver. The Agilent talk also provided details on the applications of SureSelect, the company’s hybridization technology, to Methyl-Seq and RNA-Seq research. With this technology, 120-mer baits hybridize to targets, then are pulled down with streptavidin-coated magnetic beads.
These are selections from the SFAF conference, which is expected to be a boost to work on the microbiome, and lead to infectious disease therapeutic approaches.
Summary
We have finished a breathtaking ride through the genomic universe in several sessions. This has been a thorough review of genomic structure and function in cellular regulation. The items that have been discussed and can be studied in detail include:
the classical model of the DNA structure
the role of ubiquitinylation in managing cellular function and in autophagy, mitophagy, macrophagy, and protein degradation
the nature of the tight folding of the chromatin in the nucleus
intramolecular bonds and short distance hydrophobic and hydrophilic interactions
trace metals in molecular structure
nuclear to membrane interactions
the importance of the Human Genome Project followed by Encode
the Fractal nature of chromosome structure
the oligomeric formation of short sequences and single nucletide polymorphisms (SNPs)and the potential to identify drug targets
Enzymatic components of gene regulation (ligase, kinases, phosphatases)
Methods of computational analysis in genomics
Methods of sequencing that have become more accurate and are dropping in cost
Chromatin remodeling
Triplex and quadruplex models not possible to construct at the time of Watson-Crick
sequencing errors
propagation of errors
oxidative stress and its expected and unintended effects
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