Author: joseph@dnasoftware.com

Not too many people believe this myth, and yet their actions are somewhat irrational as they proceed to immediately use that approach to try to experimentally optimize a multiplex PCR. It is true that well-designed single-target PCRs are useful for developing a multiplex reaction, but for a variety of reasons, this approach alone is too simplistic. The most common experimental approach to optimizing a multiplex PCR design is shown in Fig. 11, as suggested by Henegariu et al. (30). This is a laborious procedure that has a high incidence of failure even after extensive experimentation. The core of this approach is to first optimize the single-target amplifications and then to iteratively combine primer sets to determine which primer sets are incompatible and also to try to adjust the thermocycling or buffer conditions. With such an approach, the optimization of a 10-plex PCR typically takes a PhD level scientist 3–6 months (or more), with a significant chance of failure anyway.

Myth 6: At the End of PCR, Amplification Efficiency Is Not Exponential Because the Primers or NTPs Are Exhausted or the Polymerase Looses Activity

PCR amplification occurs with a characteristic “S” shape. During the early cycles of PCR, the amplification is exponential. During the later stages of PCR, saturation behavior is observed, and the amplification efficiency of PCR decreases with each successive cycle. What is the physical origin of the saturation and why is the explanation important for PCR design? Most practitioners of PCR believe that saturation is observed because either the primers or the NTPs are exhausted or the polymerase looses activity.

The idea of lost polymerase activity is historical. In the early days of PCR, polymerase enzymes did loose activity with numerous cycles of PCR. Modern thermostable engineered polymerases, however, are quite robust and exhibit nearly full activity at the end of a typical PCR. The idea of one or more of the NTPs or primers being limiting reagents is perfectly logical and consistent with chemical principles but is not correct for the concentrations that are usually used in PCR. Chemical analysis of the PCR mixture reveals that at the end of PCR there is usually plenty of primers and NTPs so that PCR should continue for further cycles before saturation is observed due to consumption of a limiting reagent. Experimentally, if you double the concentration of the primers, you do not observe twice the PCR product. Thus, the amplicon yield of PCR is usually less than predicted based on the primer concentrations.

What is causing the PCR to saturate prematurely? The answer is that double-stranded DNA is an excellent inhibitor of DNA polymerase. This can be demonstrated experimentally by adding a large quantity of non-extensible “decoy” duplex DNA to a PCR and comparing the result to a PCR without the added duplex. The result clearly shows that the reaction with added duplex DNA shows little or no amplification while the control amplifies normally. The reason why duplex DNA inhibits DNA polymerase is that the polymerase binds to the duplex rather than binding to the small quantity of duplex arising from the primers binding to target strands during the early cycles of PCR.

To minimize mispriming, several PCR texts suggest performing a BLAST search, and such capability is a part of some primer design packages such as GCG and Vector NTI and Visual-OMP. However, a BLAST search is not the appropriate screen for mispriming because sequence identity is not a good approximation to duplex thermodynamics, which is the proper quantity that controls primer binding. For example, BLAST scores a GC and an AT pair identically (as matches), whereas it is well known that base pairing in fact depends on both the G+C content and the sequence, which is why the NN model is most appropriate. In addition, different mismatches contribute differently to duplex stability.

For example, a G−G mismatch contributes as much as −22kcal/mol to duplex stability at 37C, whereas a C−C mismatch can destabilize a duplex by as much as +25 kcal/mol. Thus, mismatches can contribute G over a range of 4.7 kcal/mol, which corresponds to factor of 2000 in equilibrium constant.

In addition, the thermodynamics of DNA–DNA duplex formation are quite different than that of DNA–RNA hybridization. Clearly, thermodynamic parameters will provide better prediction of mispriming than sequence similarity. BLAST also uses a minimum 8nt “word length,” which must be a perfect match; this is used to make the BLAST algorithm fast, but it also means that BLAST will miss structures that have fewer than eight consecutive matches. As GT, GG, and GA mismatches are stable and occur commonly when a primer is scanned against an entire genome, such a short word length can result in BLAST missing thermodynamically important hybridization events.

BLAST also does not properly score the gaps that result in bulges in the duplexes. DNA Software, Inc. is developing a new algorithm called ThermoBLAST that retains the computational efficiency of BLAST so that searches genomic can be accomplished rapidly but uses thermody- namic scoring for base pairs, dangling end, single mismatches, bulges, tandem mismatches, and other motifs. Figure 10 gives some examples of strong hybridization that would be missed by BLAST but detected by ThermoBLAST. The computational efficiency of ThermoBLAST is accomplished using a variant of the bimolecular dynamic programming algorithm that was invented at DNA Software, Inc.

A common artifact in PCR is the amplification of “primer dimers.” The most common conception of the origin of primer dimers is that two primers hybridize at their 3′-ends (see Fig. 8). DNA polymerase can bind to such species and extend the primers in both directions to produce an undesired product with a length that is slightly less than the sum of the lengths of the forward and reverse primers. This mechanism of primer dimerization is certainly feasible and can be experimentally demonstrated by performing thermocycling in the absence of target DNA. This mechanism can also occur when the desired ampli- fication of the target is inefficient (e.g., when one of the primers is designed to bind to a region of the target that is folded into a stable secondary structure). Therefore, most PCR design software packages check candidate primers for 3′-complementarity and redesign one or both of them if the thermodynamic

Myth 3: Designing Forward and Reverse Primers to Have Matching Tm’s Is the Best Strategy to Optimize for PCR

Nearly all “experts” in PCR design would claim to believe in myth 3. Most current software packages base their design strategy on this myth. Some careful thought, however, quickly reveals the deficiencies of that approach. The Tm is the temperature at which half the primer strands are bound to target. This provides intuitive insight for very simple reactions, but it does not reveal the behavior (i.e., the amount of primer bound to target) at the annealing temperature. The PCR annealing temperature is typically chosen to be 10 C below the Tm . However, different primers have different H of binding, which results in different slopes at the Tm of the melting transition. Thus, the hybridization behavior at the Tm is not the same as the behavior at the annealing temperature. The quantity that is important for PCR design is the amount of primer bound to target at the annealing temperature. Obtaining equal primer binding requires that the solution of the equilibrium equations as discussed in Subheading 2.1. If the primers have an equal concentration of binding, then they will be equally extended by DNA polymerase, resulting in efficient amplification. This principle is illustrated in Fig. 5. The differences in primer binding are amplified with each cycle of PCR, thereby reducing the amplification efficiency and providing opportunity for artifacts to develop. The myth of designing forward and reverse primers with matched Tm’s is thus flawed. Nonetheless, as single-target PCR is fairly robust, such inaccuracies are somewhat tolerated, particularly if one allows for experimental optimization of the temperature cycling protocol for each PCR. In multiplex and other complex assays, however, the design flaws from matched Tm’s become crucial and lead to failure.

Myth 2: Best Methods for Predicting Hybridization Tm

Best methods for predicting hybridization Tm are essentially equivalent in accuracy. The melting temperature, Tm, of duplex formation is usually defined as the temperature at which half the available strands are in the double-stranded state (or folded state for unimolecular transitions) and half the strands are in the “random coil” state. We will see later (i.e., myth 3) that this definition is not general and that the Tm itself is not particularly useful for PCR design. Over the past 45 years (1960–2005), there have been a large number of alternative methods for predicting DNA duplex Tm that have been published. The simplest equation based on base content is the “Wallace rule” (19):