shawanda

Saturday, June 17, 2006

 

Scientists published the first complete genome sequence

Proteome analysis

                Michael Dunn explains how analysing the total protein content of              organisms is helping chemists to decipher the mechanisms controlling                                           gene expression.

           Scientists published the first complete genome sequence � of the bacterium Haemophilus            influenzae � less than three years ago. Since that time, researchers have completed the            genome sequences of 11 more microorganisms and many others are in progress (Table 1            and http://www.tigr.org/tdb/mdb/mdb.html). The! y have completed the sequence of only one            eukaryotic organism to date � the yeast Saccharomyces cerevisiae � but are making            significant progress for several other species, with a current target date for completing the            human genome by 2005. This wealth of information represents an invaluable resource in            terms of understanding how an organism functions and its evolutionary relationships with other            forms of life.

            Table 1. Some sequenced and partially sequenced genomes             Organism                                            Size/million base         &nbs! p;                   &nbs p;               pairs of DNA                                                              ORFs

Year completed             Microorganisms

            Mycoplasma genitalium                                                0.58                                                               470

1995             Ureaplasma urealyticum                         &n! bsp;                      0.75                                                               640

            Mycoplasma pneumoniae                                                0.81                                                               679

1996             Treponema pallidum                                          ! ;      1.14                                                               1000

            Borrelia burgdorferi                                                1.44                                                               843

1997             Aquifex aeolicus                                                1.50                              !                                 1512

1998             Helicobacter pylori                                                1.66                                                               1590

1997             Methanococcus jannaschii                                                1.66                                           &nbs! p;                   1738

1996             M. thermoautotrophicum                                                1.75                                                               1855

1997             Haemophilus influenzae                                                1.83                                                               1743

1995           &! nbsp; Streptococcus pyogenes                                                1.98                                                               1900

            Archaeoglobus fulgidis                                                2.18                                                               2436

1997             Nisseria gonorrhoreae       &n! bsp;                   &n bsp;                    2.20                                                               2100

            Pyrobaculum aerophilum                                                2.22                                                               1900

            Synechocystis PCC6803                                            !    3.57                                                               3168

1996             Bacillus subtilis                                                4.20                                                               4100

1997             Escherichia coli                                                4.60           &n! bsp;                   &n bsp;                               4288

1997             Eukaryotes

            Saccharomyces cerevisiae (yeast)                                                13.0                                                               5885

1996             Dictyostelium doscoideum (slime mould)                                                 70                     &n! bsp;                                        12 500

            Arabidopsis thalania (cress)                                                 70                                                              14 000

            Caenorhabditis elegans (nematode             worm)                                                 80                   &n! bsp;                   &n bsp;                      17 800

            Drosophila melanogaster (fruit fly)                                                170                                                              30 000

            Homo sapiens (human)                                                2900                                                     !          50 000

           However, it is becoming clear from these genome programmes that it is usually impossible to            attribute even putative functions to as many as 40 per cent of the structural genes within a            particular organism. In addition, as many as 30 per cent of the open reading frames (ORFs)            are assigned functions only on the basis of homology to genes encoding proteins of known            function. Although the genomics approach provides information on all of the possible ways            that an organism may express its genes, it does not provide insights into the ways in which an            organism may modify its pattern of gene expression in response to particular conditions.

!            Direct answers

  &nb sp;        Scientists can solve these problems only by investigating gene expression directly, by studies            at either the messenger RNA (mRNA) or protein level. They have also developed powerful            techniques such as DNA micro-arrays and serial analysis of gene expression (Sage), which            make it possible to undertake mass screening of mRNA expression and obtain information on            which mRNAs are expressed in an organism at any particular time. However, it is becoming            increasingly apparent that there is often a poor correlation between mRNA abundance and            the amount of the corresponding functional molecule � the protein � present in the cell. The            other major problem is tha! t studies at the mRNA level provide no information on processes of            co- and post-translational modification (Fig 1) that result in polypeptides being modified by            the addition of other groups. These modifications include phosphorylation, sulphation,            glycosylation, hydroxylation, N-methylation, carboxymethylation, acylation, prenylation, and            N-myristoylation. Such modifications usually have a profound influence on the functional            properties of proteins, so that knowledge of these processes is fundamental to understanding            gene expression.

                          Fig 1. Transcription, translation and post translational           &! nbsp;                 processe s resulting in the production of a mature                                  protein product from a particular gene.

           These problems can be resolved by protein biochemistry techniques, and this interface            between protein biochemistry and molecular biology has become known as 'proteome            analysis'. The term 'proteome' was first coined by a collaborative team at Macquarie and            Sydney Universities, Australia, in 1995, and they defined it as the protein complement of the            genome of an organism. Currently, researchers are undertaking proteome analysis for simple            organisms such as the mycoplasmas (the smallest free living organisms known), bacteri! a and            yeast. Characterising the proteome of eukaryotic organisms will obviously require an            enormous effort because of the size of the genome and the co- and post-translational            modifications, which result in protein diversity far exceeding the complexity of the genome.            The complexity of eukaryotic proteomes means that we can use proteomics in a narrower            context, to define patterns of quantitative gene expression in particular cells and tissues.            Researchers can then exploit this information to characterise biological processes, such as            those involved in development, during the cell cycle, during cell death, in disease, and in            response to p! harmaceutical intervention, extracellular stimuli and toxic agents. U ltimately, our            goal is to decipher the mechanisms controlling gene expression.

           Separating proteins

           The first requirement for proteome analysis is that we must be able to separate the complex            mixture of proteins obtained from whole cells, tissues or organisms. Currently, the best            method for separating complex protein mixtures simultaneously is two-dimensional            polyacrylamide gel electrophoresis (2-DE), in which sample proteins are separated according            to different properties in each dimension. The first 2-DE experiments reported in 1956 used a            combination of paper and starch gel electrophoresis for separating serum proteins, and since !            that time researchers have described a variety of improved methods. However, the most            commonly used approach for 2-DE is the combination of a first dimension separation by            isoelectric focusing (IEF) under denaturing conditions with a second dimension separation by            sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-Page). The first            separation is according to charge (different proteins are focused at their respective            isoelectric points, pI - the pH at which the net charge is zero); this is followed by a size-based            separation (molecular weight, Mr). This orthogonal combination of two separations carried out            at right angles to e! ach other results in the sample proteins being distributed across the            two-dimensional (2-D) gel profile (Fig 2).

                         Fig 2. A 2-DE separation of 100 ug bovine heart proteins                            using a non-linear pH 3.5 to 10 IPG IEF gel in the first                            dimension and 12 per cent SDS-Page in the second                                               dimension.

           For effective use in proteome analysis, 2-DE must be capable of reproducible high resolution            protein separation. In the early days of 2-DE this proved to be a problem largely because of!            the nature of the synthetic carrier ampholytes (SCA) used to generate the pH gradients            required for IEF. The electroendosmotic flow of water (migration of H3O+ towards the cathode            during electrophoresis) occurring during IEF results in migration of these small SCA            molecules towards the cathode. This process, known as cathodic drift, results in pH gradient            instability and loss of the more basic proteins from the gel. This problem was overcome, at            least in theory, when Amersham Pharmacia Biotech developed the Immobiline reagents for            generating immobilised pH gradients (IPG) for IEF in the early 1980s. The Immobiline            reagents are a series ! of eight acrylamide derivatives with the structure CH2=CH-CO-NH-R, & nbsp;          where R contains either a carboxyl or tertiary amino group, giving a series of buffers with            different pK values distributed throughout the pH 3 to 10 range. One can add the appropriate            IPG reagents, calculated according to published recipes, to the mixture used for gel            polymerisation. During polymerisation, the buffering groups that will form the pH gradient are            covalently attached via vinyl bonds to the polyacrylamide backbone. IPG generated in this way            are immune to the effects of electroendosmosis, so that they give us the opportunity to carry            out IEF separations that are extremely stable, allowing the true equilibrium state to be            attain! ed.

           Scientists encountered several problems during initial attempts to implement the IPG            technology to 2-D separations, but these were solved largely by Angelika G�rg and her            colleagues at the Technical University in Munich, and we now prefer to use IPG IEF for the first            dimension separation of 2-DE. Researchers perform IPG IEF in individual IPG gel strips, 3 to            5mm wide, cast on a plastic support. After steady-state IEF, strips are equilibrated and the            separated proteins then applied either to the surface of a horizontal or to the top of a vertical            SDS-containing gel. Inter-laboratory studies of heart, barley and yeast proteins show the           &n! bsp;excellent reproducibility of both protein spot position and quant itation attained by this 2-DE            method.

           Size matters

           The separation capacity of 2-DE is critically dependent on gel size. The current standard            combination of 18cm IPG strips for IEF with 20cm long SDS-Page gels is capable of routinely            separating 2000 proteins from tissue and cell extracts. Very large format gels of about 30cm            in each dimension are capable of separating up to 10,000 proteins, but this is achieved at the            expense of the ease of gel handling and processing. Only a few hundred proteins can be            separated using mini-gel formats, but these are quick to run and are useful for rapid screening           &! nbsp;purposes. One can also choose the range of the pH gradient for IPG IEF to maximise protein            separation. Wide pH gradients covering pH 3-10 allow us to analyse the protein diversity in a            particular sample, while narrower pH gradients improve the resolution in particular regions of            the protein profile. Very basic pH gradients, up to pH 12, are now available for 2-DE and we            can use these to separate very basic proteins, such as nuclear and ribosomal proteins. A            further and very important advantage of IPG IEF is that it has a very high capacity for            micro-preparative 2-DE protein separations, particularly using a recently described method in            which dry IPG strips are reswollen dir! ectly in a solution containing up to several mg of the            protein sample to be analysed.

           Detective work

           The next critical issue in proteome analysis is to detect the separated proteins at high            sensitivity. Traditional methods of protein staining following gel electrophoresis based on the            use of the dye Coomassie brilliant blue have limited sensitivity. Researchers can achieve            higher detection sensitivity � 0.1ng protein per spot � by silver staining, but there can be            problems using this method as a quantitative procedure because it is known to be            non-stoichiometric and prone to saturation and negative staining effects, where regions of            very high protein concentra! tion do not stain and appear as 'holes' in the pattern of stained            spots. Detection methods based on using fluorescent compounds, which scientists are            developing for use with 2-DE separations, promise to overcome these problems because of            their excellent linearity and high dynamic range (ie they can be used over a wide range of            protein concentrations). We can also achieve very sensitive protein detection in situations            where metabolic labelling of proteins with a radiolabelled amino acid can be used before their            2-DE separation, for example in cell culture systems.

           We need automated computer analysis systems for the rigorous qualitative and quantitative       &n! bsp;    analysis of the complex patterns of protein expressi on visualised by 2-DE. The first step in this            process is to obtain a digitised image of the 2-D protein separation. A flat-bed scanning laser            densitometer providing high resolution � down to 50�m � combined with a high dynamic            range � up to 4OD (optical density) � is the best option for stained gels. The current            generation of desktop scanners can also achieve high resolution (600dpi is equivalent to            42�m) and a high dynamic range (12bits), but care must be taken to ensure the linearity of            such devices. We can also prepare film images of radiolabelled 2-D separations using such            devices, but accurate quantitation is complicated both by the limited dynamic range and the   &nb! sp;        non-linearity of film response.

           We can overcome this problem by using phosphorimaging screens, the surface of which            contain a thin layer of BaFbr:Eu2+ in a plastic support. We place the dried 2-D gel in contact            with the screen; during this exposure step the b-particles emitted by the radiolabelled proteins            pass through the layer, converting Eu2+ to Eu3+. After a suitable exposure time, we transfer            the screen to a 'phosphorimaging' scanner where light from a high intensity HeNe laser            (633nm) is absorbed, causing the excited state Eu3+ ions to decay to the Eu2+ ground state            by the emission of blue (390nm) luminescence proportional to the amount of! radiation incident            on the s creen. The major advantages of this approach compared with conventional            autoradiography is that relatively short exposure times are required, it has a high dynamic            range and good linearity of response is achieved. The only disadvantage is the high capital            cost of the phosphorimaging screens and the dedicated imaging device that is required.            Similarly, a dedicated densitometer is required for the imaging of 2-D gel profiles of            fluorescently labelled proteins

           .

           In the early days of 2-DE scientists needed large, dedicated computer systems for analysing            2-DE protein separation profiles. The rapid progress made in microcomputer technolog! y has            changed this situation, so that we can run the current generation of commercial 2-DE analysis            software systems � Melanie II, Bio-Rad Laboratories; BioImage, BioImage Systems;            Phoretix, Phoretix International; Kepler, LSB � on desktop workstations, such as Unix, PC or            Mac. These systems mean that we can derive qualitative and quantitative information from            individual 2-D gels, to match the protein separation profiles from large numbers of 2-D gels            and construct comprehensive databases of quantitative protein expression for cells, tissues            and whole organisms.

           Identity parade

           Next, we need! to be able to identify and characterise the separated proteins. The 2-DE            separation provides us with information on the apparent Mr, pI and relative abundance of the            proteins, but gives us no direct clues to their identities or functions. We can search the            sequence databases for proteins of matching Mr and pI, for example using the TagIdent tool in            Expasy ( http://www.expasy.ch/www/guess-prot.html) but this approach is unlikely on its own to            result in unequivocal protein identification. This problem is exacerbated by the uncertainty of            mass values � around �10 per cent � derived from protein mobility during SDS-Page.            However, we can now determine directly the abs! olute mass of proteins by mass spectrometry            (Fig 3). The best approach is to transfer the separated proteins by Western blotting onto the            surface of a nitrocellulose or polyvinylidene difluoride membrane. We then treat the blot with            the matrix required for MS, cut out the protein of interest, and mount it directly into a            matrix-assisted laser desorption (Maldi)-MS and measure the mass of the intact protein. This            method is very accurate, usually within 1 per cent of the predicted mass, but requires a            Maldi-MS instrument fitted with an infrared laser and works best if the proteins are not stained.            This approach can also be extended to two-dimensional 'scanning' of the sample targ! et,            thereby generating mass contour images.

               Fig 3. Methods for identifying and characterising proteins separated by 2-DE.

           Western method

           Until recently we only had available laborious and time-consuming methods, such as specific            staining methods, co-electrophoresis with purified proteins, cellular subfractionation and            over-expression of genes introduced via plasmid or viral constructs, to identify proteins from            2-D gels. The first major advance was developing methods for Western blotting, which            allowed us to probe gel-separated proteins with a variety of ligands, particularly poly- and            monoclonal antibodies, after their transfer to the surface ! of an inert support such as            nitrocellulose. Biochemists use this approach extensively for identifying proteins separated by            2-DE, but it is still a time-consuming method that depends on the availability of a suitable            panel of specific antibodies reactive with the denatured proteins in 2-DE gels.

           Amino acid sequence, even if this is only a few residues in length, is the most specific method            of identifying proteins. The preferred method for chemically sequencing proteins is still based            on the Edman degradation method. Edman degradation was first described in 1949, although            it did not become a practical method until the first automated protein sequenator was     &nbs! p;      developed in 1967. A commercial version became available in 1971, which had a sensitivity            limit of 10 nanomole (equivalent to 500�g for a 50kDa protein). Since 1971, progress in            sequenator technology and the optimisation of Edman degradation chemistry has resulted in            the current generation of gas-liquid and solid-phase sequenators, which we can use to            determine N-terminal sequences from low picomole quantities of protein (5 picomole is            equivalent to 0.25�g for a 50kDa protein). This level of sensitivity is compatible with the            amount of protein present in many of the spots present in micro-preparative 2-D gels, and this            is our preferred method if extended runs of N-terminal protein sequences are required.

    &n! bsp;      A major problem with N-terminal sequencing by Edman degradation is that many proteins are            'blocked', that is they lack a free a-amino group. This results from processes of co- and            post-translational modification, such as those involving the addition of formyl, acetyl or acyl            groups. In the case of eukaryotic organisms, we usually find that 50 per cent of all cellular            proteins are modified in this way. The best approach to this problem is to cleave the blocked            protein with either a chemical reagent such as CNBr or an enzyme such as trypsin, to            generate shorter, 'internal' peptides that can be isolated by HPLC and sequenced. We can            carry out the cleavage s! tep either in situ within the 2-D gel or after Western blot transfer of the            protein onto a nitrocellulose or PVDF membrane. While this procedure is effective, it requires            considerably more protein than direct N-terminal sequencing, so that normally we have to use            multiple spots collected from a series of replicate 2-D gels.

           An alternative approach to sequence determination of peptides is to use mass spectrometry.            This can be effected either by peptide fragmentation within the spectrometer or by a            technique known as ladder sequencing. In the latter method, we use either chemical (Edman            degradation) or enzymic (aminopeptidase, carboxypeptidase) degradation under limiting            conditions to generate a series of ! truncated peptides that differ in size according to the            number of amino acids that have been removed from their N- or C-terminus. We can then            measure the masses of these peptides, usually by Maldi-MS, to deduce the sequence. We            require very high mass accuracy to generate unambiguous sequence and cannot distinguish            between the amino acids leucine and isoleucine because these have an identical mass.

           Increased throughput

           Although chemical protein sequencing is a sensitive and highly discriminating method of            protein identification, sample throughput using an automated sequenator is low, t! ypically one            or two samples per day. We therefore need techniques that are capable of high-throughput            sensitive screening of proteins separated by 2-DE, so that only those proteins that cannot be            identified unequivocally or appear to be novel need further characterisation by protein            sequencing.

           Current methods for the HPLC analysis of amino acid derivatives are capable of very high            (sub-picomole) sensitivity. We can apply this method directly to proteins separated by 2-DE            and have found it to be an excellent method for their rapid identification. This approach            depends on individual proteins having more or less unique amino acid compositions. We use            the experiment! al amino acid composition determined for the protein of interest to interrogate            databases of amino acid compositions derived in silico from sequences of known proteins or            predicted from translated nucleotide sequences. We have access to a number of search            algorithms via the Internet and can filter the search data by including Mr and pI search            windows, or species specificity of the target protein.

           A major drawback to this approach is that the end-point is a list of protein identities ranked in            order of probability, but the 'correct' protein does not necessarily occur as the first ranked            entry. While scientists find score patterns a useful way of increasing confidence of identi! ty, we            generally prefer to a dopt an orthogonal approach and combine amino acid compositional            analysis with another rapid method of protein identification, such as peptide mass profiling.            Recently, scientists have developed a method in which Edman degradation is used to create            a three or four amino acid N-terminal 'sequence tag', following which the proteins are            subjected to amino acid compositional analysis. The combined amino acid composition and            'sequence tag' data are then used for protein identification.

           A major breakthrough in rapid protein identification came when we realised that the set of            peptide masses obtained by MS analysis of a protein digest provides a characteristic       &! nbsp;    fingerprint of that protein (Fig 4a). We then use this information to interrogate databases of            peptide masses derived from sequences of known proteins or predicted from nucleotide            sequences and a number of algorithms have been implemented to facilitate this process. As            in the case of amino acid compositional analysis, this technique of peptide mass profiling or            fingerprinting is a statistical method with putative protein identities being ranked in order of            probability (Fig 4b). We can improve the reliability of this approach by combining peptide            mass profiling data from two separate digests � eg with trypsin and Lys-C � or by adopting            an orthogonal approach in! combination with amino acid compositional analysis.

    ;          Fig 4. Maldi-MS spectrum of the tryptic digest of the protein spot; the peptide mass                 database search indicates that the protein is the M-chain of creatine kinase.

           Peptide profiling

           Scientists have developed methods for peptide mass profiling based on digests generated            by enzymatic cleavage either while the protein spot is in situ within the gel matrix or after            transfer by electroblotting to a suitable membrane. After recovery, we can analyse the            unfractionated peptides by Maldi-MS (Fig 4). Alternatively, we fractionate the peptide mixture            by reverse-phase HPLC. Systematic screening of HPLC fractions can be done either by &! nbsp;          Maldi-MS or by electrospray ionisation ESI-MS using a quadropole or ion-trap instrument. We            can also couple ESI-MS on-line with the HPLC separation by splitting the column effluent,            allowing simultaneous mass measurement and fraction collection. The peptides present in the            fractions may be useful for other identification strategies such as protein sequencing and            carbohydrate analysis.

           Partial peptide sequence data is an extremely powerful adjunct to identifying proteins by            peptide mass profiling. While we can generate this sequence data by automated Edman            degradation or by MS ladder sequencing, there are also two MS-based approaches tha! t we            can use to identify pro teins. These take advantage of the ability of two-stage mass            spectrometers, either Maldi-MS with post-source decay (PSD) or ESI-MS/MS            triple-quadropole or ion-trap instruments, to induce fragmentation of peptide bonds. The first            of these methods, termed peptide sequence tagging, is based on interpreting a portion of the            ESI-MS/MS or PSD-Maldi-MS fragmentation data to generate a short partial sequence or            'tag', which is used in combination with the mass of the intact parent peptide ion, and provides            a significant amount of additional information for the homology search. An elegant extension            of this approach is a nano-electrospray ion source that allows spraying times of more than!            30min from ca 1�l of sample. Using this method, we can sequence multiple peptides from a            digest mixture without the need for prior separation by HPLC. Biochemists have found this            method to be sensitive in the low femtomole range and have successfully analysed silver            stained 2-DE protein spots containing as little as 5ng protein.

           Automatic responses

           The second method is based on the automated interpretation of ESI-MS/MS fragmentation            data, which is used to search sequence databases directly. In this method, the program first            identifies all those peptides that can be generated from proteins in the sequence database     &n! bsp;      and whose masses match those of the measured peptide ion. In the second step, the            program predicts the fragment ions expected for each of the candidate peptides if they were            fragmented under the experimental conditions used. The experimentally determined MS/MS            spectrum is then compared with the predicted spectra using cluster analysis algorithms. Each            of the comparisons is allocated a score and the highest scoring peptide sequences are            reported. The method has been adapted for automated identification of peptide digests            analysed by ESI-MS/MS where the ions subjected to fragmentation are automatically selected            during the run and the data automatically analysed. Proteins present in mixtures can be readily     &nbs! p;      identified with a 30-fold difference in molar quantity and sensitivity is at the low femtomole            level.

           Our final requirement for proteomic technology is that we must be able to store all the data that            are generated in databases that we can interrogate effectively in the laboratory and also,            where possible, make it available to other scientists worldwide. Our best approach to this at            present is to use the World Wide Web (WWW). In order to provide optimal interconnectivity            between these 2-D gel protein databases and other databases of related information            available via the WWW, it has been suggested that 2-D gel databases are constructed     &nbs! p;      according to a set of fundamental rules. Databa ses conforming to these rules are said to be            'federated 2-D databases', while many of the other databases conform to at least some of the            rules. You can view a list of these 2-D protein databases at World2Dpage on the WWW (            http://www.expasy.ch/ch2d/2d-index.html).

           New insights

           Proteomics interfaces with and complements genomics to provide information on quantitative            protein expression in biological systems. Such information will provide new insights into            complex cellular processes and improve our understanding of cellular responses to external            stimu! li. Proteomics also promises to yield information on the ways in which cells respond to            disease processes, leading to an understanding of disease at the molecular level and            providing new opportunities for developing diagnostics and therapeutics. For these reasons,            proteomics is generating considerable excitement in the biotechnology and pharmaceutical            industry. Moreover, scientists in this sector believe that proteomics can also be used to            validate new therapeutic agents by providing information about their effects on protein            expression, thereby accelerating the process of drug discovery.

           Michael Dunn is a reader in biochemistry in the department of cardiothoracic surgery, !            National Heart and Lung Insti tute, Imperial College School of Medicine, Heart Science            Centre, Harefield Hospital, Harefield, Middlesex UB9 6JH.

           Further reading

                A. G�rg, G. Boguth, C. Obermaier, A. Posch, W. Weiss, Electrophoresis, 1995, 16,                 1079.                 I. Humphery-Smith, S. J. Cordwell, W. P. Blackstock, Electrophoresis, 1997, 18, 1217.                 A. I. Lamond, M. Mann, Trends Cell Biol., 1997, 7, 139.                 S. D. Patterson, R. Aebersold, Electrophoresis, 1995, 16, 1791.                 S. R. Pennington, M. R. Wilkins, D. F. Hochstrasser, M. J. Dunn, Trends Cell Biol.,             &! nbsp;   1997, 7, 168.                 M. R. Wilkins, K. L. Williams, R. D. Appel, D. F. Hochstrasser (eds), Proteome                 research: new frontiers in functional genomics. Berlin: Springer, 1997.                 J. R. Yates, J. Mass Spectrom., 1998, 33, 1.

           Glossary

           Densitometer                 an instrument that measures the optical transmission or reflecting properties of a                 material, particularly the optical density (OD) of exposed and processed photographic                 images.            Eukaryotes                 organisms � eg anima! ls, plants, fungi, whose cells have a membrane-bound nucleus                 and organelles.            Genome                 All of the DNA sequences in an organism.            Mycoplasma                 the smallest free-living organism known.            N-terminal sequencing                 determination of the sequence of a protein using Edman degradation, resulting in the                 sequential release of amino acids from the N-terminus of the protein.            Open reading frame                 A DNA sequence with the potential to encode a protein.            Prokaryotes                 single-! celled organisms � eg bacteria � that have no defined nucleus and whose                 genetic material is usually a circular duplex of DNA.            Reverse phase HPLC                 separation of peptides by differences in polarity of amino acid side chains. Reversed                 phase systems are so-called because the mobile phase (usually a mixture of water and                 an organic modifier) is less polar than the silica-based stationary phase.            Transcription                 process by which RNA polymerase enzyme produces complementary single-stranded                 messenger RNA.            Translation &nbs! p;               process occurring in cell organelles called ribosomes, to decipher the code in mRNA in                 order to synthesise a specific polypeptide.            Western blotting                 the transfer, usually by electrophoresis, of separated proteins from a gel onto the                 surface of a thin support such as nitrocellulose or polyvinylidene difluoride. The                 immobilised proteins can readily interact with antibodies � a process termed                 immunoprobing.


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