Oligonucleotide Analyzer

The quantity of an oligonucleotide usually is given as its total optical density (OD value), as amount of substance (nmol) or as its available mass (μg). The OD value is measured experimentally, then the other values are calculated.

OD Value

The OD value of a sample at a wavelength of 260 nm is defined as the extinction that occurs in measuring absorption of the sample in 1 ml aqueous solution in a 1 cm cuvette at the respective wavelength.

In practice, OD values are often outside of the linear measurement range of an UV spectrometer; therefore diluted samples have to be quantified and to be extrapolated to the total OD value.

The dried oligonucleotide is dissolved in 400 μl of sterile water. From this stock solution an aliquot of 10 μl is taken and filled up with sterile water to 1 ml. Now the extinction value of this diluted solution is measured in a photometer in a 1 cm quartz cuvette at a wavelength of 260 nm. The obtained extinction (e.g. 0,25) is multiplied with the aliquotation factor (400 μl / 10 μl = 40). The result is the OD value (10 in our example).

Amount of oligonucleotide in nmol

According to the law of Lambert and Beer (E = Epsilon * C * d) one can convert from the extinction E (OD value) to the concentration C and therefore to the amount of substance of the oligonucleotide. Strictly speaking, the extinction coefficient Epsilon is different for each oligonucleotide sequence and would have to be ascertained empirically. Using so-called nearest-neighbour methods the extinction coefficient of an oligo can also be obtained computationally with acceptable precision. In a good approximation it correspondents to the sum of the extinction coefficients of the individual nucleotides in the sequence.Using the oligo's sequence data and the OD value one can calculate the amount of material as

follows:

n [OD]: OD value
n [nmol]: Amount in nmol
A,G,C,T: Number of the respective bases in the oligonucleotide

For mixed sequences the following values for the amount of material (nmol) result depending on oligo length:

Thus, for a rough estimate applies for a mixed 20mer oligonucleotide :

1 OD approximates 5 nmol (5000 pmol).

Amount of oligonucleotide in μg

Using the amount of substance in nmol and the oligo's molecular weight, one can calculate the amount of oligonucleotide in μg:

n [μg]: Amount in μg
n [nmol]: Amount in nmol
MW: Molecular weight

Also, for rough estimates applies:

1 OD approximates 30 μg DNA oligonucleotide

Calculating concentrations

A dried oligonucleotide is to be dissolved to obtain a concentation of x pmol/μl.

n [nmol]: Amount in nmol
c [pmol/μl]: Concentration
v [μl]: Volume of the oligo

An oligonucleotide (54 nmol) is to be dissolved with a target concentration of 50 pmol/μl in the resulting solution: v[μl] = 1000 * 54 nmol / 50 pmol/μl = 1080 μl

The following concentrations are identical:

100 pmol/μl = 100 nmol/ml = 100 μmol/l = 100 μM

A dried oligonucleotide is to be dissolved in a defined volume of water. Which concentration results ?

n [nmol]: Amount of substance in nmol
c [pmol/μl]: Concentration
v [μl]: Volumen of the oligos

An oligonucleotide (54 nmol) is to be dissolved in 200 μl water. Which concentation will result ? c[pmol/μl] = 1000 * 54 nmol / 200 μl = 270 pmol/μl

The molecular weight of an oligonucleotide is calculated from the number of individual nucleotides in the oligonucleotide and from possible modifications of the oligonucleotide:

MW_oligo=313,2*A + 329,2*G + 289,2*C + 304,2*T + MWmod -61 * [g/mol]

A,G,C,T: Number of bases in the oligo

MW_mod: Molecular weight of a modification, if present

5’-CCA GGC AGT CTT ATT TTG ACT-3’

MW = 313,2 *4 +329,2 *4 + 289,2 * 5 + 304,2 * 8 –61 = 6388,2 g/mol

The melting temperature Tm of a DNA double strand is defined as the temperature at which 50% of the double strand have been denaturated, thus being present in single stranded form. Length of the oligo, base composition and concentration of an oligonucleotide as well as the salt concentration in the solution have a key influences on the Tm value. There are different more or less exact methods of predicting the melting temperature:

This rule which is valid for very short oligonucleotides (up to about 15 bases) assumes a contribution of 2 °C for each AT-pair and of 4°C for each GC-pair to the melting temperature of a double strand:

The rule was established for hybridizations to membrane-bound oligonucleotides and assumes a salt concentration of 1 M. For solution-based experiments one should add 8°C to the calculated temperature.

The following formula based on Howly et al. [2][3] takes mostly into account the GC content of the oligo and is valid for long oligonucleotides:

Tm = 81,5 + 0,41 (%GC) + 16,6 log c(M+) – 500/n –0,61 (%F) –1,2 D

with

%GC = Percentage of GC-pairs
c(M+) = Concentration of mono-valent cations
n = Number of nucleotides
%F = Percentage of formamide in the buffer
D = Percentage of mismatches

The so-called Nearest-Neighbor-Method also takes into account sequence-dependent stacking effects for Tm calculation and is based on thermodynamic properties of neighbouring nucleotide pairs. This method is reliable for oligonucleotides of medium length (20 – 60 bases).

Tm = [(1000 x dH) /(A + dS + R x ln (C/4))] – 273.15 + 16,6 x log c(K+)

with

dH = Sum of the enthalpies of all pairs
dS = Sum of the entropies of all pairs
A = -10.8 cal, Entropy of helix formation
R = 1.984 cal/grad x mol, Gas constant
C = Oligonucleotide concentration (250 pmol/l)
c(K+) = Concentration of potassic ions in the oligo solution (50 mmol/l)

Oligo: 5'-GTC GAA CCG GAA ACC ACC CCT-3'

dH = -6.5 –5.6 –11.9 –5.6 –9.1 –6.5 –11.0 –11.9 –11.0 –5.6 –9.1 –9.1 – 6.5 –11.0 -5.8 -6.5 –11.0 –11.0 –11.0 –7.8 = -173.5 dS = -17.3 –13.5 –27.8 –13.5 –24.0 –17.3 –26.6 –27.8 –26.6 –13.5 –24.0 –24.0 –17.3 –26.6 –12.9 –17.3 -26.6 –26.6 –26.6 – 20.8 = -430.6

Tm = (1000 x (–173.5))/ ((-10.8 –430.6 + 1.984 x ln (6.25 x 10-11)) – 273.15 + 16.6 log 50x10-3 = 60.7

All methods for the calculation of melting temperatures given above do not take into account modifications of the oligonucleotide (e.g. dyes, linkers).

1. R.B. Wallace, J. Schaffer, R.F. Murphy, J. Bonner, K.Itakura; Nuc. Acids Res. 1979, 6, 3543
2. P.M. Howley, M.F. Israel, M-F. Law, M.A. Martin, M.A. J. Biological Chemistry 1979, 254, 4876
3. R. Teoule, H.Bazin, B.Fouqué, A.Roget, S.Sauvaigo; Nucleosides & Nucleotides 1991, 10, 129
4. W. Rychlik, W.J. Spencer, R.E. Rhoads; Nuc. Acids Res. 1990, 18, 6409-6413
5. K.J. Breslauer, R. Frank, H. Blöcker, L.A. Marky; Proc. Natl. Acad. Sci 1986, 83, 3736-3750
6. P.N. Borer, B. Dengler, I.J. Tinoco, O.C. Uhlenbeck; J. Mol.Biol. 1983, 86, 843-853

10/13

Template optimization using In Vitro Transcription

Bio-Synthesis provides enzymatic long RNA synthesis using transcription from DNA template. In vitro transcribed RNA can be used as control template for Taqman SNP genotyping assays, drug metabolism genotyping assays or as positive control template for basic clinical research.

The development of an organism depends upon accurate and finely-tuned control of mRNA transcription. The round worm Caenorhabditis elegans (C. elegans) is a transparent nematode about 1 mm in length. This organism has been studied intensively in recent decades and has become a model organism for molecular biologists. Already various biological processes that involve direct regulation or specific functions of general transcription machinery components such as “Mediator”, or transcription co-factors that function in multiple discrete regulator systems, such as chromatin modification proteins, have been identified. For example, the multiprotein complex termed Mediator functions as a transcriptional coactivator in all eukaryotes. This protein complex was discovered by Roger D. Kornberg who was awarded the 2006 Nobel Prize in Chemistry for “his studies of the molecular basis of eukaryotic transcription". This multiprotein complex sometimes is also referred to as the Vitamin D Receptor Interacting Protein (DRIP) coactivator complex or the Thyroid Hormone Receptor-associated Proteins (TRAP). However, all genes have to be expressed in order to function in a cell. The first step in expression is transcription of the gene into a complementary RNA strand. For genes that code for transfer RNA (tRNA) and ribosomal RNA (rRNA) moleculs the transcript itself is the functionally important molecule. For other genes however, the transcript is translated into a protein.

The Central Dogma in molecular biology for prokaryotic in comparison to eukaryotic cells is outlined as follows: In prokaryotic cells, which have no nuclear membrane, DNA replication and transcription and RNA translation occurs in one compartment. Furthermore, the three processes can occur simultaneously. However, in eukaryotic cells, which have a nuclear membrane, DNA replication and transcription occurs in the nucleus, and proteins are synthesized in the cytoplasm. RNA molecules therefore have to travel across the nuclear membrane before translation can happen. In these cells transcription and translation are physically separated. In addition, the primary transcript, heterogeneous nuclear RNA (hnRNA), is post-transcriptional processed to generate a messenger RNA (mRNA) molecule that can migrate through the nuclear membrane. The following figure illustrates this.

Advancements made in recent years in manual and automated oligonucleotide synthesis technologies allow now to routinely synthesize DNA, RNA and/or artificial oligonucleotides that can be modified or unmodified with high purity. Artificial oligonucleotides can act as RNA and DNA mimics but may have different sets of properties, such as higher affinities to their targets. These technologies have already enabled the use of synthetic oligonucleotides to construct synthetic biochemical circuits from simple components useful for the study of in-vitro transcriptional circuits. For example the use of two essential enzymes, bacteriophage T7 RNA polymerase and Escherichia coli ribonuclease H, together with synthetic oligonucleotides allowed the systematic construction of arbitrary circuits for the study of synthetic in-vitro transciption. In addition, scientists in recent years have shown that mathematical modeling can be used to guide the design process of this type of systems. Some of these experimental conditions yielded oscillating biochemical circuits. The notion here is that synthetic transcriptional oscillators could prove valuable for systematic exploration of biochemical circuit design principles. The understanding of these principles could allow scientist to design artificial cells and control nanoscale devices. Future studies will surely identify additional examples of direct communications between regulatory and general transcription factors and reveal how promoter groups and gene networks are regulated through these interactions. Finally, new insights into the specific biological processes in which they are involved will be gained.

Transcription refers to the transfer of genetic code information from one kind of nucleic acid to another. It refers to the process by which a base sequence of messenger RNA is synthesized by an RNA polymerase on a template of complementary DNA. On the other hand, the reversal of this process or flow of information is called “reverse transcription.” In reverse transcription the normal pattern is reversed, for example by a viral enzyme called “reverse transcriptase.” Furthermore, a polymerase associated with the process of transcription is called a “transcriptase”. The DNA-dependent RNA polymerase is an example for a transcriptase. The template is defined as “a single-stranded polynucleotide or the region of a polynucleotide that directs the synthesis of a complementary polynucleotide”. Experiments that aim to find out which portion of a DNA molecule is transcribed into RNA are called “transcript analysis”. Furthermore, the entire mRNA content of a cell or tissue is now called the “transcriptome”.

In bacteria, or prokaryotes, transcription is catalyzed by a single RNA polymerase. In e.coli the RNA polymerase is a large enzyme of almost 500 kilodaltons. The holoenzyme has five subunits, α2ββ’ω, and the core enzyme lacks the σ factor. An essential step in bacterial transcription is the binding of one of a number of dissociable accessory proteins, called the σ factor, to a core RNA polymerase to form a holoenzyme. In e. coli the core enzyme, α2ββ’ω with a mass of 379 kDa binds the σ⁷⁰ factor to form the holoenzyme α2ββ’ω σ⁷⁰, with a mass of 449 kDa. Only as a holoenzyme can RNA polymerase initiate transcription and it is thought that the holoenzyme binds weakly to the DNA and explores the DNA double helix until with the help of the σ factor it recognizes a promoter sequence to which it finely binds tightly. Finn et al. in 2000 determined the structures of the core RNA polymerase and the σ⁷⁰ holoenzyme using cryo-electron microscopy and angular reconstruction.

Escherichia coli RNA polymerase (RNAP) is the most studied bacterial RNA polymerase and has been used as the model RNAP for screening and evaluating potential RNAP-targeting antibiotics. Murakami in 2013 reported the X-ray structure of the E. coli RNAP σ(70) holoenzyme which showed the σ region 1.1 (σ1.1) and the α subunit C-terminal domain in the context of an intact RNAP. The structure revealed that σ1.1 is positioned at the RNAP DNA-binding channel and completely blocks DNA entry to the RNAP active site. Furthermore, the σ1.1 contains a basic patch on its surface. It is thought that this batch may play an important role in DNA interaction to facilitate open promoter complex formation. In this structure the α-subunit C-terminal domain is positioned next to σ domain 4 with a fully stretched linker between the N- and C-terminal domains. The X-ray based model is depicted in the next figure.

Transcription involves RNA polymerases binding, initiation,elongation and termination. During the initiation of the transcription cycle an RNA polymerase searches for a promoter site and binds to DNA, unwinds and separates the two strands. The separation occurs in such a way that one strand, the template strand, is copied, but not the other. Next, a base pair forms between a base in the template strand and a ribonucleotide triphosphate. The first nucleotide retains its three phosphate groups at the 5’ end as the RNA chain grows on the OH group attached to its 3’ carbon. During elongation the RNA strand grows from its 5’-end to its 3’ end, as the polymerase copies the template DNA strand from its 3’-end to its 5’-end. The RNA polymerase catalyzes the formation of a phosphodiester bond. The DNA duplex unwinds and a newly duplex is formed made of the newly synthesized RNA and DNA template strand, which extends for 10 to 12 bases behind the most recent DNA. Next, the growing RNA molecule detaches from the template and the DNA helix forms again. The new RNA strand has exactly the same sequence as the nontemplate strand of DNA, however, wherever DNA has a thymidine (T), the RNA has a uridine (U). During termination, the ending of chain growth, the RNA polymerase detaches from the DNA template and the growing RNA chain. Termination sites or sequences in the DNA signal the end of transcription. Many prokaryotic genes contain self-complementary sequences that can fold back on itself and form hairpin duplexes or stretches of U’s.

However, termination in eukaryotes is more complex and the elucidation of the exact mechanism or mechanisms is still under investigation. Termination can also occur at termination sites that do not have these features, in additon, for this to occur protein factors are needed. One of these termination assisting proteins is called rho (ρ). In addition, so called antiterminating proteins can allow elongation to continue through DNA sequences that otherwise can serve as termination sites.

Transcription of two genes. RNA polymerase moves from the 3’ end of the template strand and creates an RNA strand that grows in a 5’ to 3’ direction because it must be antiparallel to the template strand. Some genes are transcribed from one strand of the DNA double helix whereas other genes are transcribed from the other as the template. Furthermore, a uracil is being added to the 3’ end of the transcript for gene 1. Querying the Pubmed structure data base revealed that many solved structures are available for polymerase complexes indicating the importance of these protein complexes.

Zhang et al. in 2012 have determined crystal structures at 2.9 and 3.0 Å resolution of functional transcription initiation complexes comprising Thermus thermophilus RNA polymerase, sigma factor A (σ), and a promoter DNA fragment corresponding to the transcription bubble and downstream double-stranded DNA of the RNAP-promoter open complex. The structures showed that σ recognizes the –10 element and discriminator element through interactions that include the unstacking and insertion into pockets of three DNA bases and that RNA polymerase recognizes the –4/+2 region through interactions that include the unstacking and insertion into a pocket of the +2 base. Furthermore the structures also revealed that interactions between σ and template-strand single-stranded DNA (ssDNA) preorganize the template-strand ssDNA to engage the active center of RNA polymerase. The model of the crystal structure of the bacterial RNA polymerase (RNAP)-promoter complex (RPo) in complex with a ribonucleotide primer (RPo-GpA) is shown below.

Model of the bacterial RNA polymerase (RNAP)-promoter complex (RPo) in complex with a ribonucleotide primer (RPo-GpA).

The crystal structure of a bacterial RNA polymerase (RNAP)-promoter complex (RPo) in complex with a ribonucleotide primer (RPo-GpA) is illustrated at the left part of the panel. The interactions of RNAP and the σ factor with the transcription-bubble non-template strand, transcription-bubble template strand, and the downstream dsDNA is shown at the right part of the panel. (Source: Zhang et al. 2012). The sigma factor (σ factor) is a protein needed for the initiation of RNA synthesis. This bacterial transcription initiation factor enables specific binding of RNA polymerase to gene promoters. However, each specific sigma factor used to initiate transcription of a given gene will vary depending on the gene and on the environmental signals needed to initiate transcription of that gene. In addition, every molecule of RNA polymerase holoenzyme contains exactly one sigma factor subunit.

Bye 1 is a transcription factor that links histones to post-translational modification events.

Kinkelin et al. in 2013 reported crystal structures of the nuclear protein bypass of Ess1 (Bye1) TFIIS-like domain (TLD) bound to Pol II and three different polymerase II-nucleic acid complexes. The researchers could show that like TFIIS, Bye1 binds with its TLD to the polymerase II jaw and funnel. Furthermore, it was demonstrated that Bye1 is recruited in vivo to chromatin via its TLD and occupies the 5'-region of active genes. The paper showed that a plant homeo domain (PHD) in Bye1 binds histone H3 tails with trimethylated lysine 4. This interaction is enhanced by the presence of neighboring posttranslational modifications (PTMs) that mark active transcription and is impaired by repressive PTMs. The scientists identified putative human homologs of Bye1, the proteins PHD finger protein 3 and death-inducer obliterator. Both proteins are implicated in cancer. These results establish Bye1 as a chromatin transcription factor that links histones with active PTMs to transcribing Polymerase II. Bypass of Ess1 (Bye1) is a nuclear protein with a domain resembling the central domain in the transcription elongation factor TFIIS.

The researchers used purified cloned proteins together with Surface Plasmon Resonance, crystallization of the complexes followed by determining the X-ray structure, chromatin fractionation, histone peptide microarrays, synthetic lethality screening, in vitro transcription assays, RNA extension assays, chromatin immune precipitation (ChIP) and gene averaged profiling. A model of this complex is shown next.

Model of a polymerase II-Bye 1-nucleosome complex. This model shows that Bye associates with active genes in front of the +2 nucleosome. The model is based on crystal structures and ChIP occupancy peak positions (Source: Kinkelin et al., 2013).

The central dogma of molecular biology first stated by Francis Crick in 1958 and re-stated in a Nature paper published in 1970 describes the “information flow in biological systems”. It deals with the detailed residue-by-residue transfer of sequential information. It states that such information cannot be transferred back from protein to either protein or nucleic acid and has been also described as "DNA makes RNA makes protein." Furthermore, since it is a simplification it does not make it clear that the sequence hypothesis as stated by Crick does not preclude the reverse flow of information from RNA to DNA, but only the reverse flow from protein to RNA or DNA.

This graphics (left) illustrates the central dogma and its expansion as new knowledge about the nature of different types of RNAs became available. The flow of information and substances in a cell is even more complex. This is illustrated in more detail next. Regulatory feedback loops are depicted as well.

The exponential increase in RNA research has in recent years tremendously increased our knowledge about their function. This has led to our expanded understanding of complex regulatory pathways implied by the central dogma. The next graphic shows the current view how RNA processing is thought to occur in a cell.

Eukaryotes express many functional non-protein-coding RNAs (ncRNAs) that used to be thought of as “junk DNA’ or the “dark matter” of the DNA. These RNAs participate in the processing and regulation of other RNA molecules common patterns have emerged that form a network-like RNA infrastructure. For more details see Collins & Penny in Trend in Genetics, 2009.

Over the years scientists have devised a variety of techniques to study RNA transcripts. Some of them detect the presence of a transcript and give some information of its length whereas others enable the start and end of the transcript to be mapped and the position of introns to be located. The following is a list of these methods:

1. Northern hybridization: RNA molecules present in RNA extracts are separated by electrophoresis, for example, in an agarose gel, using denaturing buffers to ensure that the RNAs do not form inter- or intramolecular base pairs. After electrophoresis, the gel is blotted onto a nylon, a nitrocellulose or a polyvinylidene fluoride (PVDF) membrane followed by hybridization with a labeled probe. If the probe is a cloned gene, the band that appears on the color or radioactively developed membrane is the transcript of the gene. The size can be determined from its position within the gel in relation to RNA marker molecules or RNA isolated from different tissues that are run in different lanes of the gel. This allows to find out if the gene is differentially expressed.
2. Transcript mapping by hybridization between gene and RNA: DNA-mRNA hybridization can be used to investigate if incomplete or complete cDNA synthesis occurred. If a hybrid is formed between a DNA strand that contains a gene and its mRNA the boundaries between double- and single-stranded regions will mark the start and end points of the mRNA. Introns that are present in the DNA but not in the mRNA will “loop out” as additional single-stranded regions. S1 nuclease degrades single-stranded DNA or RNA polynucleotides including the single-stranded ends of predominantly double-stranded molecules. However S1 nuclease has no effect on double-stranded DNA or on DNA-RNA hybrids. Singel-stranded DNA fragments protected from S1 nuclease digestion can be recovered by treatment with alkali. S1 nuclease mapping allows the localization of the starting-point and end-point of a transcript.
3. Transcript analysis by primer extension: Primer extension can only be used if at least part of the sequence of a transcript is known. In this technique a short oligonucleotide primer must be annealed to the RNA at a known position. Usually the primer anneals within 100-200 nucleotides of the 5’ end of the transcript and is extended by reverse transcriptase which is a cDNA reaction. The 3’ end of the newly synthesized strand of DNA corresponds with the 5’ terminal end of the transcript. Determination of the length of the single-stranded DNA molecule and correlating this information with the annealing position of the primers allows location of the position of this terminus.
4. Transcript analysis by PCR: A modified method of a standard reverse trancriptase PCR procedure called rapid amplification of cDNA ends (RACE) can be used to identify the 5’ and 3’ termini of RNA molecules and allow to map the ends of a transcript. Several RACE methods have been developed over the years.
5. Digital PCR can be used to determine the number of transcripts: Farago et al. in 2003 have shown that digital PCR can be used to determine the number of transcripts from single neurons after patch-clamp recoding.

How can the yields of full-length RNA from an in-vitro transcription reaction be maximized?

The quality and quantity of RNA produced in an in-vitro transcription reaction is dependent upon several factors. The size of the RNA transcript, template concentration, reaction time and temperature, all influence the yield of the final full-length transcript. During an individual application, the starting template and the resulting transcript determine how a reaction needs to be modified to increase the final yields. In general, T7, T3, or SP6 RNA polymerase are used for in-vitro transcription reactions. Each polymerase recognizes a short, well-defined, phage promoter sequence with a high degree of specificity that has a minimal length of 20 nucleotide bases. In-vitro transcription reactions usually include ribonucleoside tri-phosphates (rNTPs) at concentrations of 0.5 mM per each nucleotide, reaction buffer, a linear DNA template, amounts of 1 to 2 µg, and the appropriate bacteriophage RNA polymerase. On average, these reactions produce 10 to 40 µg of RNA. However, since increasingly techniques such as gene expression profiling using microarrays, RNA interference (RNAi) gene-silencing, in-vitro translation, ribozymes, and RNA structure studies require larger quantities of RNA commercial in-vitro transcription kits have been developed to address this need. Starting with 1 µg of template up to 100 or 200 µg of RNA may be produced. Even though reaction conditions in commercial kits have been optimized to maximize the RNA yield from control templates which typically can produce 1 to 2 kB transcripts, each unique transcript may need adjustments to the protocol to maximize yields.

Template preparation: The DNA template used should be linear, double-stranded, and relatively clean. Typically templates used include linearized plasmids that contain blunt or 5’-protruding ends, PCR products or cDNAs. The templates should be free of RNase and other contaminations such as phenol, trace metals and sodium dodecyl sulfate (SDS). The treatment of the DNA with proteinase K, followed by phenol-chloroform extraction and ethanol precipitation usually allows producing a sufficiently clean template. The analysis of the template with the help of an agarose or polyacrylamide gel and staining with ethidium bromide or syber green allows verifying that the template is pure enough.

Template concentration and reaction time: For the production of a long-transcript a higher concentration of template DNA is less critical. Sometimes increasing the amount of template reduces the total reaction time to yield the RNA transcript.

Optimizing long transcripts from limited amounts of template: If the amounts of template DNA is limited to less than 1 µg the reaction time and/or temperature may need to be increased, or the reaction may need to be scaled up, to maximize yields. Reaction incubation times may need to be increased to 2 to 3 hours.

Reaction temperature for a long transcript: Increasing the reaction temperature from 37 °C to 42 °C will increase the rate at which the RNA is produced and also increases the maximal yield that can be attained. This temperature effect is more significant for lower template concentrations. A limited amount of template may demand that the reaction is incubated at 42 °C for 3 to 4 hours.

Scale-up for long transcripts: To achieve even higher yields all components of the reaction mixture including the template may need to be scaled up by 6 to 10 fold. Because the initiation of the reaction is the rate-limiting step in a transcription reaction, the reaction dynamics in a short-transcript reaction differ from those in long-transcript reaction. The best way to optimize transcription of short RNAs is to maximize the number of possible transcription initiations. This can be achieved by increasing template concentration or reaction times.

Template size and concentration for a short transcript: The increase of the template concentration in an in-vitro transcription reaction will result in an increase of the yield of a short RNA transcript. Usually in-vitro transcription reactions use 1 µg of template. However, if a 75 base pair (bp) double-stranded oligonucleotide template is used 20 picomoles of DNA will be used. On the other hand, if 1 µg of a 4.2 kilo base (kb) linear plasmid is used only 360 femtomoles of DNA is present. Therefore, 1 µg of an oligonucleotide template produces more short RNA than 1 µg of a plasmid template if all other parameters are equal in the reaction.

Reaction time for a short transcript: Increasing the reaction time will increase the number of transcription initiation events and significantly increase the yield of the RNA. However, after a reaction time of 3 to 4 hours the yield in general will plateau.

Reaction temperature for a short transcript: Typically in-vitro transcription reactions are performed at 37^o°C. The increase of the temperature to 42 °C can increase the yields and shorten reaction times.

To conclude, RNA yields for both long and short transcripts from in-vitro transcription reactions can be maximized by adjusting the template DNA concentration, the reaction time, and the reaction temperature.

Transcription templates can either be synthetic DNA, PCR products, or linearized vectors. Synthetic templates can be purified using reversed phase HPLC, ion exchange chromatography, an oligonucleotide purification cartridge, desalted by butanol precipitation or ethanol precipitation, or purified by Urea-PAGE. Furthermore, synthetic templates can be used for the antisense strand (cDNA).

Brown, T.A.; Gene cloning and DNA analysis. An introduction. Sixth edition. Wiley-Blackwell. 2010.

Crick, F.H.C. (1958): On Protein Synthesis. Symp. Soc. Exp. Biol. XII, 139-163.

Crick, F (August 1970). "Central dogma of molecular biology". Nature 227 (5258): 561–3. Bibcode:1970 Nature.227..561C. doi:10.1038/227561a0. PMID 4913914.}

Collins LJ, Penny D.;The RNA infrastructure: dark matter of the eukaryotic cell? Trends Genet. 2009 Mar;25(3):120-8. doi: 10.1016/j.tig.2008.12.003. Epub 2009 Jan 24.

Nóra Faragó, Ágnes K. Kocsis, Sándor Lovas, Gábor Molnár, Eszter Boldog, Márton Rózsa, Viktor Szemenyei, Enikő Vámos, Lajos I. Nagy, Gábor Tamás, and László G. Puskás; Digital PCR to determine the number of transcripts from single neurons after patch-clamp recording. BioTechniques 54:327-336 ( June 2013) doi 10.2144/000114029.

Robert D. Finn, Elena V. Orlova, Brent Gowen, Martin Buck, and Marin van Heel; Escherichia coli RNA polymerase core and holoenzyme structures. The EMBO Journal vol. 19 No. 24 pp. 6833-6844, 2000.

Magali Frugier, Catherine Florentz, Mir Wais Hosseini, Jean-Marie Lehn and Richard Giegd; Synthetic polyamines stimulate in-vitro transcription by T7 RNA polymerase2784-2790 Nucleic Acids Research, 1994, Vol. 22, No. 14.

Kinkelin, K., Wozniak, G.G., Rothbart, S.B., Lidschreiber, M., Strahl, B.D., Cramer, P.; Structures of RNA polymerase II complexes with Bye1, a chromatin-binding PHF3/DIDO homologue. (2013) Proc.Natl.Acad.Sci.USA 110: 15277.

Jongmin Kim and Erik Winfree; Synthetic in-vitro transcriptional oscillators. Molecular Systems Biology 7:465

Lewin’s Genes I to XI. Oxford University Press.

Lodish, Harvey; Molecular Cell Biology – 2^nd to 7^th edition. Scientific American Books.

Craig T. Martin, Daniel K. Muller, and Joseph E. Coleman; Processivity in Early Stages of Transcription by T7 RNA Polymerase. Biochemistry 1988, 27, 3966-3974.

Murakami KS; X-ray crystal structure of escherichia coli RNA polymerase sigma70 holoenzyme. J.Biol.Chem. (2013) 288 p.9126.

Patrushev LI, Bocharova TN, Khesin RB.;The effect of various templates and oligonucleotide primers on RNA and poly (A) synthesis by E. coli and T7 RNA polymerases. FEBS Lett. 1978 Feb 1;86(1):108-12.

Yu Zhang, Yu Feng, Sujoy Chatterjee, Steve Tuske, Mary X. Ho, Eddy Arnold, Richard H. Ebright; Structural Basis of Transcription Initiation. Science 338, 1076 (2012).

10/28/2013

EXTINCTION COEFFICIENTS AND FLUORESCENCE DATA

Calculate extinction coefficient of an oligo by either summing up the extinction coefficients of the individual bases times their number of occurrences. Or use a formula that takes into account nearest neighbor effects. An algorithm for this calculation can be found on the web. Just type in the sequence and the program will calculate the concentration of a l A260/ml solution.

To calculate the MW of the aminomodified oligo just add 179.16 to the calculated MW of the unmodified oligo.

Note: Biotin and Cholesterol have no absorbance at 260nm.

*With an extinction coefficient of approximately 10,500 M-1 and a quantum yield of fluorescence of 0.2, AP-dC is 2-3 times as bright as our popular Pyrrolo-dC analog. In addition, AP-dC exhibits a Stokes’ shift greater than 100 nm. As with most fluorescent base analogs, it is substantially quenched upon forming a duplex. The quantum yield drops to 0.1 while gaining significant structure in the emission spectrum (Figure 4), making it an ideal probe of DNA structure.

FLUORESCENCE DATA

PHYSICAL PROPERTIES OF BLACK HOLE QUENCHERS

Amino Acid Analysis / Testing refers to the quantitative analysis of either free amino acids or amino acids released from proteins via hydrolysis present in biological samples such as blood, plasma, urine, foods, dietary or health supplements, nutraceuticals, beverages, tablets, supplement capsules, plant extracts and any other samples or matrices that contain amino acids.

Proteins, peptides and amino acids are found in a great variety of food sources including animals, fungi, vegetables, cereals and many others. It has been shown by many authors that due to their complexity the identification of these compounds require the use of advanced analytical techniques. Many techniques including high-performance liquid chromatography, sometimes referred to as high-pressure liquid chromatography (HPLC), gas chromatography (GC), capillary electrophoresis (CE), nuclear magnetic resonance (NMR), Fourier transform infrared spectroscopy (FTIR), inductively coupled plasma mass spectrometry (ICP-MS), inmunosensors, and others have been used or were investigated for their use to analyze amino acids in different matrices in the past. Furthermore, amino acids have been identified and quantified in different natural matrices using micellar electrokinetic chromatography (MEKC), micro chip electrophoresis or HPLC. The US Pharmacopeia Dietary Supplement Chapter lists detailed test methods for each individual amino acid ingredient as follows: the identification of amino acids is perform by FTIR, analysis of chromatographic impurities is performed by a TLC–ninhydrin based method and the determination of the potency of raw materials is done by using titration assays. However, these are classical or older methods. The newer, more recent methods that were developed during the last decades utilize automated instruments called “amino acid analyzers.” Most amino acid analysis or testing labs are now capable of routinely testing amino acids as either the free amino acids or those released from protein hydrolysates.

Amino acid analysis enables the precise determination of protein quantities and provides detailed information regarding the relative amino acid composition of proteins and free amino acids present in physiological samples. The resulting amino acid composition is a characteristic profile for a protein. In some cases this profile allows to identify a protein via database searches. A typical amino acid analysis includes a hydrolysis step followed by separation, and detection and quantification of the released and labeled amino acids. Briefly, samples that contain proteins are subjected to acid hydrolysis and are broken down into individual amino acids. Next, the released amino acids are reacted with a derivatizing reagent, converted to stable chromophore modified amino acids and are separated and analyzed by HPLC.

Amino acids present in finished goods such as tablets, capsules, powders, and in liquid syrups can all be analyzed using automated amino acid analysis. The analysis of single and/or multiple amino acid preparations can be performed and the results are documented according to the specific guidelines.

What are amino acids?

Amino acids are the "building blocks" of proteins and are found in every human tissue as well as all mammalian tissues. Amino acids play major roles in nearly every chemical process in the human body. Amino acids are vital molecules that affect both physical and mental functions in mammals and humans.

Proteins are found in the brain, the nervous system, ligaments, tendons, bones, as well as in antibodies, and are vital for the regulation of enzymes and blood transport proteins. Only twenty amino acids of the naturally occurring amino acids are found in proteins because they are the only ones that are coded for by the genetic code.

Chemically, an amino acid is an organic acid in which one of the hydrogen atoms on a carbon atom has been replaced by an ammonia group (NH₂). The term amino acid usually refers to an aminocarboxylic acid. One particular type of amino acids called α-amino acids are of the general formula R-CHNH₂-COOH with the NH₂ group in the alpha position. All amino acids, except the amino acid glycine, are stereoisomers and only the L-form or L-enantiomer, which is one mirror image, of the possible two amino acids, is biologically active in an organism. The L refers to L-stereoisomers or left-handed isomers of the amino acids. These L-forms are the result of the hydrolysis products of proteins. All proteins consist of groups of different types and percentages of L-amino acids. Sometimes, in rare instances, these classes of molecules also include α–amino phosphoric acids and α–aminosulfonic acids. The following structures illustrate the nature of stereoisomers.

Stereoisomers of alanine

The models of D- and L-alanine are used here as an example to describe the nature of stereo isomers. The four bonds of the central alpha carbon of an amino acid point towards the four corners of a tetrahedron. Alanine has a methyl group (CH₃) as a side chain group. If we imagine holding the model of the structure with the carboxyl group (COOH) at the top and the amino group (NH₂) at the bottom, the CH₃ group in the D form will be on the right, and in the mirror image L form will be on the left.

Amino acids are important for the function of an organism and are part of its metabolism. The misregulation of biochemical processes that involve amino acids in the human body can lead to metabolic diseases. An example is the presence of excessive amounts of specific amino acids in the blood called “aminoacidemia.” Another example is the excessive excretion of amino acids in the urine called“aminoaciduria.” In addition, an inherited disorder called hyperbasic aminoaciduria is associated with a deficiency of a dibasic amino acid transport. Individuals with this disorder do not display protein intolerance. Because of the great number of metabolic disorders that involve amino acids and the wide range of affected systems, nearly every "presented complaint" to a doctor may have a congenital metabolic disease as a possible cause. This is especially true in childhood. Therefore, it is safe to reason that amino acid analysis or testing is an important technique for the analysis of metabolites that contain primary and secondary amino groups in their structure, which are present in humans or mammals as well as in food stuff, nutraceuticals and health supplements. This type of analysis is also quite important in clinical chemistry.

Except for the nine so called "essential amino acids," the human body can synthesize all of the amino acids necessary for the biochemical synthesis of proteins. Plants and micro-organisms can synthesize all amino acids from small precursor molecules. These nine amino acids must be included in the human diet or taken as supplements to be available in adequate amounts. The failure to obtain enough of even one of these essential amino acids can result in serious health implications and the degradation of the body's proteins. These phenomena can lead to the destruction of muscle and other protein structures to obtain the amino acids that the body needs to survive. Because of this, amino acids are classified into two main groups: essential and non-essential amino acids. There are nine essential amino acids in the group: phenylalanine, valine, threonine, tryptophan, isoleucine, methionine, leucine, lysine, and histidine. In some biochemical and molecular biology books, arginine and histidine are sometimes also listed as essential amino acids. Non-essential amino acids are amino acids that can be produced by the human body. These include: alanine, aspartic acid, arginine, cysteine, cystine, glutamine, glycine, serine, tyrosine, hydroxyproline, asparagine, and proline. However, non-essential amino acids are also used as a supplement for cell culture medium to increase cell growth and cell viability. Furthermore, protein sources that have the full complement of essential amino acids are sometimes called complete proteins. Whereas proteins that are devoid or deficient in one or more essential amino acid are called incomplete proteins. Arginine is essential during times of rapid growth. It is particularly needed during childhood or when muscle growth is initiated during weight training sessions. Furthermore, the amounts of each essential amino acid required depends on the overall amino acid composition of the proteins that are consumed. For example, human cells can synthesize cysteine from methionine if needed. However, if the intake of cysteine is low extra methionine is needed in the diet not only to meet the needed methionine levels but also to synthesize cysteine.

For nutritional purposes, the protein quality can be estimated and a chemical score can be defined. Usually this is done by assigning a chemical score of one hundred (100) to whole egg protein and by comparing the proteins of interest to this protein. This score implies that the whole egg protein is completely utilized. The amino acid that gives the lowest score in relation to the reference protein will dictate the final chemical score. This amino acid is called the first limiting amino acid. The following formula is used to calculate the chemical score:

Proteinogenic amino acids are amino acids that are used by the cellular machinery of an organism to synthesize proteins. These amino acids are encoded for in the genetic code. There are 22 standard amino acids, but only 21 are found in eukaryotes. Selenocysteine and pyrrolysine are incorporated into proteins by different biosynthetic mechanisms. The other 20 are directly encoded by the universal genetic code.

Branched-chain amino acids, a term used by the food and supplement industry, are amino acids that contain branched aliphatic side-chains. The side chains contain a carbon atom that is connected to more than two other carbon atoms. There are three branched-chain amino acids: leucine, isoleucine and valine. The structures of these amino acids are shown below.

Leucine	Isoleucine	Valine

In muscle proteins these three branched-chain amino acids account for circa 35% of the essential amino acids and 40% of the preformed amino acids required by mammals.

Amino acid profiles that determine the presence or absence and the quantities of the twenty amino acids in plasma can illuminate problems in amino acid status of a human patient. This is done by determining essential amino acid imbalances. Amino acid profiles containing up to 45 compounds can be even more informative. These evaluation types allow identifying the status of essential, branched chain, and other non-essential amino acids. Together, with the analysis of vitamins and minerals, this analysis allows identification of neuroendocrine, vascular, detoxification, and functional vitamin and mineral deficiencies.

Fasting plasma amino acid levels represent a homeostatic balance between supply and utilization of amino acids, making amino acid analysis of plasma amino acids ideal for repeated assessments by monitoring the progress of treatment. Collecting a fasting plasma specimen from a patient removes recent dietary intake effects. The following factors can reflect changes over time in plasma: chronic dietary intake, digestive efficiency, hepatic uptake and skeletal muscle's ability to maintain transamination. Amino acid analysis or testing helps monitoring amino acid levels involved in nutritional function, including gastrointestinal function, cellular energy production, detoxification, neurotransmitter metabolism, muscle catabolism, collagen synthesis and maintenance, as nutritional markers, and can be indicators of vascular function. Furthermore, amino acid analysis or testing of amino acid levels in plasma is useful for the design of supplement formulas. For example, to manufacture customized amino acid blends based on a patient's specific test results. The notion here is that these customized amino acid formulations will provide appropriate amounts of essential and conditionally essential amino acids that can be delivered in a balanced ratio to offset the risk of imbalance, sometimes observed when single amino acid supplements are used. Known conditions associated with amino acid changes in plasma include cardiovascular disease, depression, anxiety, insomnia, chronic fatigue syndrome, multiple sclerosis, rheumatoid arthritis, epilepsy, congestive heart failure, impotence and erectile pain syndromes, multiple chemical sensitivities, detoxification disorders, autism spectrum disorders, Alzheimer's disease, hypothyroidism, arrhythmias, hypertension, ADD/ADHD, and infertility.   10/31/2013

Amino acid analysis of plasma metabolites.

Amino acid analysis is an important tool for the analysis of free amino acids and other similar biomolecules that contain primary and secondary amino groups within their structure and which are present in blood serum, plasma, and other body fluids such as urine and cerebrospinal fluid (CSF). CSF is a clear, colorless bodily fluid found in the brain and spine. During the last decades, it has become clear that amino acids play a crucial role as metabolites and as regulators of metabolic pathways in mammals, including humans. Since the blood serves as a common medium that links all organs in the body together, plasma amino acid concentrations could be affected by metabolic disturbances in a particular organ system. Therefore, amino acid profiling of blood plasma samples can be used to study the levels of amino acid metabolites.

Metabolite profiling usually refers to a set of metabolites, along with their concentrations, detected in a biological sample. Metabolite profiles can be very specific for certain classes of chemical compounds, such as lipids or amino acids. Similar to the genome, the full complement of genes of an organism, the metabolome, is described as the full complement of metabolites of an organism. The terms"metabolite" and"metabolome" have become established in the scientific literature since the year 2000. A Pubmed search for "metabolomics" showed that, as of Fall 2013, over 6,100 papers on this subject have already been published thus far. The combination of next-generation deep-sequencing technologies with mass spectrometry and other technologies such as amino acid analysis will surely provide more accurate data as a result of the extensive study of the metabolome in the near future.

Abnormal profiles in amino acid concentrations are observed in various diseases such as liver disease, end-stage renal disease, hepatocellular carcinoma, and others. In addition, several plasma peptides have also been identified as hormones important in metabolic physiology and diseases. One important peptide class includes the family of cardiac natriuretic peptides. These types of peptides have emerged as potent metabolic hormones that exhibit a wide range of biological actions and are involved in the control of metabolic homeostasis. Homeostasis is the ability or tendency of an organism or cell to maintain internal equilibrium.  A mammalian body achieves this by adjusting all physiological processes to coordinate responses of its parts to any situation or stimulus that tends to disturb the normal conditions or functions in order to maintain internal stability. Therefore, changes in plasma amino acid levels can reflect the metabolic status of a patient. For example, patients with severe hepatic disease have an amino acid imbalance in which low levels of branched chain amino acids and high levels of aromatic amino acids are observed in their systemic blood when analyzed.  Further, it is known that the increase in aromatic amino acids levels in the brain can lead to a decrease in the normal neurotransmitters and an increase in the neurologically inactive phenylethanolamine and octopamine. The intake of branched chain amino acids improves the plasma amino acid balance. Peptides with high levels of branched chain amino acids and low levels of aromatic amino acids are called high-Fischer-ratio oligopeptides. The Fischer ratio is the ratio between branched-chain amino acids (BCAA) and aromatic amino acids (AAA) which can be defined by the formula Fr = (Leu + Val + Ile)/(Tyr + Phe). This ratio has been used for the diagnosis of hepatic encephalopathy and its drug treatment efficacy. High Fischer ratio oligopeptides can be derived from various food proteins and their resulting amino acid content can be determined by amino acid analysis.

Kimura T, Noguchi Y, Shikata N, Takahashi M Plasma amino acid analysis for diagnosis and amino acid-based metabolic networks. Curr Opin Clin Nutr Metab Care. 2009 Jan;12(1):49-53. doi: 10.1097/MCO.0b013e3283169242.

After sequencing the human genome scientists began to realize that just knowing the genetic information of an individual is not sufficient to understand its phenotype. The way a DNA sequence is translated into function does not directly depend on the sequence itself. It has now become clear that the interaction of genes with environmental factors plays a role as well. The new field of epigenetics attempts to integrate the different chemical interactions or languages that genomes and environment use to communicate with each other. Chemically, epigenetics can be described as structural adaptations of chromosomal regions that reflect silenced or activated states of genes in response of the epigenetic signaling network of a genome to environmental factors. DNA methylation, indicating a chemical epigenetic change or imprinting, is the most widely studied modification. The modification is found within CpG dinucleotides. DNA methylation is a biochemical process where a DNA base, usually cytosine, is enzymatically methylated at the 5-carbon position. This epigenetic modification is associated with gene regulation, and is of paramount importance to biological health and disease. Over the years a growing number of chemical modification at different amino-acid residues mostly located at histone tails have been identified as well. Examples are acetylation, methylation, phosphorylation, ubiquitination and sumoylation, and new types of modifications are still waiting to be discovered. Other epigenetically important features are factors like nuclear positioning, noncoding RNAs, and microRNAs, among others, which are also associated with gene regulation and chromatin structure. In biochemical and biological science the speed of discovery of novel findings goes hand in hand with the development of new techniques and/or scientific instrumentation. The past few years have witnessed the introduction of a whole host of new techniques that allow for the characterization of the epigenome. Specifically, the number of studies that attempt to characterize the epigenome of normal or altered genetic states has grown exponentially. The following tables outline a list of techniques and methods as well as current microarray platforms that have been developed for the study of the epigenome and their applications in biology and medicine.

CHROMATIN IMMUNOPRECIPITAION is a technique were intact nuclei are gently fixed to maintain the physical relationship of DNA-binding molecules to genomic DNA. The chromatin (DNA plus bound molecules) is sheared to small fragments and incubated with an antibody that selectively immuno-precipitates one of the bound molecules. The binding sites of the molecule (usually a protein) of interest become apparent from their enrichment in the immune-precipitated fraction of the genome.

Legend:TLC, thin-layer chromatography; RP-HPLC, reverse phase high performance liquid chromatography; Anti-5mC, anti-5-methylcytosine; RLGS, restriction landmark genome scanning; AP-PCR, arbitrarily primed polymerase chain reaction; AIMS, amplification of intermethylated sites.

Legend:MS-PCR, methylation-specific polymerase chain reaction; MS-SNuPE, methylation-specific single nucleotide primer extension; MS-SSCA, methylation- specific single-strand conformation analysis; MS-HRM, methylation-specific high resolution melting; CGI, CpGislandmicroarray; SMRT,submegabase resolution tiling array; MeDIP,methylated DNA immunoprecipitation; MeCIP,methyl-CpG immunoprecipitation; Oligonucleotides, Whole genome oligonucleotide array.

1 Sequencing of immunoprecipitated anti-5mC DNA

2 Methyl-binding protein precipitated sequencing.

3 Methyl-sensitive restriction enzyme sequencing.

4 Modified methylation-specific digital karyotyping.

Harrison & Parle-McDermott published a paper in 2011 describing the speed in the development of new techniques to study DNA methylation. The following figure illustrates this quite nicely.

Time line of DNA methylation analysis. Early techniques used in the 1980s allowed to measure the amount of 5-methylcytosine within a particular genome. Since then a variety of methods have been developed that allow for a more detailed study of the epigenome. These new type of methods or assays include the use of methylation-sensitive restriction enzymes, immunoprecipitation, bisulfite sequencing, usually in combination with the polymer chain reaction (PCR), the use of microarrays, reversed-phase high-performance liquid-chromatography (RP-HPLC), methylation-sensitive single nucleotide primer extension (MS-SnuPe), combined bisulfate restriction analysis (COBRA), arbitrarily primed PCR (APPCR), amplification of inter-methylated sites (AIMS), reduced representation bisulfite sequencing (RRBS), and finally next-generation sequencing, to name a few.

It is expected that next-generation sequencing approaches for DNA methylation analysis will dominate for a while. Newer sequencing technologies, such as single-molecule real-time sequencing (SMRT) are needed to directly detect all known DNA methylation reactions without the need for bisulfate treatment. As pointed out by Harrison and Parle-McDermott the major developments in the methodologies for profiling and fingerprinting the human methylome have followed a clear progression toward innovative sequencing techniques that allow for single-pair resolution. It is expected that as the technologies improve the cost of genome-wide sequencing will decrease. This will result in new waves of data and the need for better bioinformatics tools to allow for the accurate analysis of vast datasets in the coming years.

Weixing Feng, Zengchao Dong, Bo He and Kejun Wang; Analysis method of epigenetic DNA methylation to dynamically investigate the functional activity of transcription factors in gene expression. BMC Genomics 2012, 13:532 doi:10.1186/1471-2164-13-532.

Alan Harrison and Anne Parle-McDermott; DNA Methylation: A Timeline of Methods and Applications Front Genet. 2011; 2: 74.)

Lanlan Shena and Robert A. Waterland; Methods of DNA methylation analysis. Curr Opin Clin Nutr Metab Care 10:576–581. 2007 Lippincott Williams & Wilkins.

A brief history of firsts in nanotechnology: Nanotechnology started in 1959 when Feynman gave an after-dinner talk describing molecular machines built with atomic precision. In 1974, Taniguchi used the term "nano-technology" in a paper on ion-sputter machining. The molecular nanotechnology concept was coined by Drexler at MIT in 1977. The first technical paper on molecular engineering to manufacture with atomic precision was published in 1981, when the scanning tunneling microscope (STM) was invented. The Buckyball was discovered in 1985, and the first book on nanotechnology was published in 1986. During the same year, atomic force microscopy (AFM) was invented, and the first nanotechnology organization was formed. The first protein was engineered in 1987, and many firsts followed in nanotechnology, including the publication of the first textbook about the field in 1992, as well as the first nanomedicine book published in 1999. And it all starts with particles.

Let us find out what a particle is. A particle is a small, localized object that behaves as a whole unit and can be described using physical properties such as volume, size and mass. A nano-particle is "a particle having one or more dimensions of the order of 100 nm or less." Usually, fine particles range in their size between 2,500 and 100 nanometers. However, ultrafine particles, or nanoparticles, range in sizes between 100 and 1 nanometers. During the 1970-80’s, when the first thorough fundamental studies were running with "nanoparticles" in the United States (by Granqvist and Buhrman) and Japan, (within an ERATO Project), they were called "ultrafine particles"(UFP). During the 1990s, before the National Nanotechnology Initiative was launched in the United States, the new name, "nanoparticle" had become fashionable. Nanoclusters have at least one dimension between 1 and 10 nanometers and a narrow size distribution. Nanopowders are agglomerates of ultrafine particles, nanoparticles, or nanoclusters. Nanometer-sized single crystals or single-domain ultrafine particles, are often referred to as nanocrystals. The field of nanotechnology is rapidly developing, and new types of nanomaterials are being developed constantly. It is expected that nanomaterials will be developed at several levels, as part of material devices and systems. Many nanomaterials are now commercially available. The cells of living organisms are typically 10 μm in size. Parts of the cells are even much smaller, in the sub-micron size range.

Figure 1: This figure illustrates the size of a nanoparticle. If a nanoparticle was the size of a football - this image shows how atoms, cells and organisms would compare at a more familiar scale to humans.

Proteins that make up the cells nanomachinery are just around 5 nanometers (nm) in size. These are the sizes of the smallest man-made nanoparticles. Their size allows them to be used as probes to study the cells’ biological processes. Typically, for biological applications, nanomaterials are selected for their optical and magnetic properties. However, nanomaterials are also applied for novel electronic, optoelectronis, and memory devices. Figure 1 illustrates the size of nanoparticles.

The fact that nanoparticles exist in the same size domain as proteins allows them to be used to label or tag proteins, either in vivo or in vitro. To allow the interaction of nanoparticles with the biological target, a molecular coating or layer acting as an interface will need to be attached to the particle. Examples of biological coatings include antibodies, biopolymers such as collagen, or monolayers of small biocompatible molecules. Since the use of optical detection techniques are widely used in biological research, nanoparticles should either fluoresce or change their optical properties in response to a biological function. Figure 2 illustrates the sizes and shapes of a few nanoparticles. A list of applications involving nanoparticles follows below.

Figure 2: Sizes and shape of different nanoparticles. This cartoon shows the morphology of nanoparticles that can be used for neuroimaging. Source: Moresco & Masserine 2012.

Some applications of nano-materials in biology and medicine are:

Fluorescent biological labels for fluorescent signaling
Drug and gene delivery
Bio detection of pathogens
Detection of proteins – Antigen detection
Probing of DNA structure
Tissue engineering
Tumor destruction via heating (hyperthermia)
Separation and purification of biological molecules and cells
Linker activated nanoparticles
Biocompatible nanoparticles
MRI contrast enhancement
Molecular imaging such as computed tomography (CT), positron emission computed tomography (PET), single photon emission computed tomography (SPECT), and magnetic resonance (MRI),
Phagokinetic studies

Figure 3: Representation of multifunctional iron oxide nanoparticles showing multiple modes of functionalization.

Figure 4: Representation of multifunctional nanoparticles.

Nanoparticles that usually form the core of nano-biomaterials can be composed of inorganic, polymeric materials or can be in the form of nano-vesicles surrounded by a membrane or a layer. The shapes of these particles can come in different morphologies. Furthermore, nanoparticles can be functionalized in multiple ways. Figures 3 and 4 show the graphical representation of different ways to functionalize nanoparticles. For example, as depicted in figure 3, the particles can be conjugated to different types of molecules, such as antibodies, green fluorescent protein (GFP), avidin, or streptavidin, as well as to DNA/RNA oligomers and gold particles or, as shown in Figure 4, contrast agents useful for CT/MRI imaging, radiotracers useful for PET/SPECT imaging, functionalized with drugs for targeted drug delivery or specific ligands, as well as special surfaces such as hydrophilic surfactants to enhance biocompatibility.

It is thought that nanoparticles will play an increasing role in nanomedicine in the future. Nanomedicine applies nanotechnology with the goal to improve the quality of human lives. Useful medical applications of nanoparticles include improved drug delivery, such as protein, peptide, and oligonucleotide delivery in biological systems, nanoparticles to specific targets in tumors and cancers, and nanoparticles for tissue visualization to enhance surgical techniques or to visualize tumors. It is hoped that it will become possible in the near future to design nanorobots or nanomachines that allow for the repair of damage parts of the cell.

More recently, many companies have begun to use nanotechnologies. The majority of the companies are small recent spinouts of various research institutions. Most of the companies are developing applications for the pharmaceutical industry, mainly to enhance or enable drug delivery. Other companies exploit quantum size effects in semiconductor nanocrystals to tag biomolecules or use gold nanoparticles for the labeling of various cellular parts. Cytodiagnostics, one such company, provides gold, silver, and magnetic nanoparticles with sizes ranging from 5 nm to 400 nm. These particles can be conjugated to biomolecules such as antibodies, BSA, KLH, and many others.

Biosynthesis Inc. in Lewisville, Texas offers custom conjugation of antibodies or other proteins to this type of nanoparticles. To be able to perform custom conjugations, approximately 3 mg of purified and lyophilized antibody (or any other protein) is required. A successful conjugation results in a typical yield of 10 ml of protein-gold nanoparticles conjugated at an optical density of 3 (OD=3). This amount is enough to probe approximately 100 dot blot strips using 15 ml of a 1:100 diluted conjugate per strip.

Services include: 1. antibody or protein sourcing, if needed; 2. conjugation of a customer protein to selected gold nanoparticles; and 3. Purification of the conjugate.

Furthermore, oligonucleotides and other molecules can be conjugated to gold nanoparticles as well. Biosynthesis provides custom conjugation of single-stranded or double-stranded oligonucleotides to gold nanoparticles with sizes ranging from 5 nm to 400 nm. A successful conjugation typically results in a yield of 30 ml of oligonucleotide-gold nanoparticle conjugate at an optical density of 1 (OD=1).

Services include: 1. synthesis of oligonucleotides for conjugation. The customers usually supplies the nucleotide sequence, and decides which terminal (5' or 3') will be attached to the gold surface, and Biosynthesis Inc. does the rest; 2. Conjugation of the oligonucleotide to a gold nanoparticle size of customer’s choice; 3. Purification of the conjugate.

The following table shows a list of nanomedical technologies.

Cytodiagnostics, another company, offers a unique proprietary protocol that produces particles with uniform shapes and a narrow size distribution. The gold nanoparticle surface can be modified to allow for the conjugation to molecules such as biotin and other molecules of choice. Furthermore, particles can be functionalized with carboxyl, amine, and methyl groups, among others.

Silver Nanoparticles are also available with core sizes of 40 nm - 100nm

High-quality monodisperse silver nanoparticles with a narrow size distribution (CV <15%) are available as well. Nanosilver products are ideal for a wide array of applications such as “Conjugate Development,”, “Sensor Development,”, “Molecular Imaging’,’Surface Enhance Raman Spectroscopy (SERS),”, and“Bactericidal applications.”

Superparamagnetic iron nanoparticles, both in the metallic, and oxide forms, can be used for bioconjugation as well and are widely used in the life sciences. Typical applications include but are not limited to the separation and purification of biomolecules, such as proteins and DNA, from complex mixtures, as well as in immunoprecipitation protocols. By using only a magnet for fast pull-down and isolation of magnetic particles, cumbersome and long purification protocols using columns or centrifugation are not needed. Other applications may include medical diagnostics, catalysis, probing agents to indirectly study the structure of mixed self-assembled monolayers (SAMs), solid phase extraction, anode materials for Li-ion batteries, and electromagnetic interference (EMI) shielding materials. Source: http://www.cytodiagnostics.com/magnetic_nanoparticles.php

The company Nanoprobes offers 1.4 nm Nanogold® particles. These are gold compounds that are not just adsorbed to proteins, like colloidal gold, but covalently reacts at specific sites under mild buffer conditions with molecules that are selected for conjugation. A well-defined product can be synthesized that can be purified chromatographically.

 Source: http://www.nanoprobes.com/products/LabRgts.html#feat

Features of Nanogold® Unparalleled penetration of conjugates up to 40 µm. Higher density of immunolabeling than with larger gold probes. Can be conjugated to any molecule with a suitable reactive group. Available with different reactivities. Extremely uniform 1.4 nm gold particle Label at specific sites, which do not obstruct native reactivity. Close to stoichiometric labeling. Reacts under mild, neutral conditions Conjugates are easily isolated by gel filtration. Conjugates are stable to a wide range of pH and ionic strengths. High Representation of multifunctional ironstability: conjugates show unchanged reactivity after storage for a year.