Total HIV-1 DNA decays rapidly with suppression of virus replication in vivo. Clearance of HIV-1 DNA during the first 6 months of therapy reflects a disproportionate loss of nonintegrated HIV-1 DNA genomes, suggesting that levels of total HIV-1 DNA in PBMCs after prolonged virus suppression largely represent integrated HIV-1 genomes.

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Amplification of RNA by the polymerase chain reaction (PCR) is normally a two-step process requiring separate enzymes and buffer conditions. We describe a combined reverse transcription-PCR (RT-PCR) assay for hepatitis C virus (HCV) RNA amplification in which a single enzyme and buffer condition are used. In this assay, both the RT and PCR steps are carried out with the thermoactive DNA polymerase of Thermus thermophilus. A transcription vector containing HCV sequences has also been constructed to generate quantifiable HCV RNA templates that can be used to optimize reaction conditions and to assess the efficiency of amplification. Amplification from < or = 100 copies of RNA was detected reproducibly by gel electrophoresis. The assay sensitivity was increased to 10 RNA copies by hybridization to a probe. The patterns of viremia in three individuals infected with HCV were examined by amplification of HCV RNA from plasma samples collected serially over a period of 1 year. These results were correlated with the times of seroconversion and the onset of rise in levels of alanine aminotransferase in serum. In all three subjects, HCV RNA was detected prior to seroconversion and the initial rise in levels of alanine aminotransferase in serum. Upon seroconversion, HCV RNA fell to a level below the detection limit of the assay. This pattern of transient viremia appears to be characteristic of acute, resolving HCV infections. The combined RT-PCR assay is a sensitive method which circumvents the problems associated with PCR amplification of RNA. Using this assay, we demonstrated that three donors infected by the same index case all have similar patterns of viremia.

In exponentially growing bacteria, expression of heterologous protein impedes cellular growth rates. Quantitative understanding of the relationship between expression and growth rate will advance our ability to forward engineer bacteria, important for metabolic engineering and synthetic biology applications. Recently, a work described a scaling model based on optimal allocation of ribosomes for protein translation. This model quantitatively predicts a linear relationship between microbial growth rate and heterologous protein expression with no free parameters. With the aim of validating this model, we have rigorously quantified the fitness cost of gene expression by using a library of synthetic constitutive promoters to drive expression of two separate proteins (eGFP and amiE) in E. coli in different strains and growth media. In all cases, we demonstrate that the fitness cost is consistent with the previous findings. We expand upon the previous theory by introducing a simple promoter activity model to quantitatively predict how basal promoter strength relates to growth rate and protein expression. We then estimate the amount of protein expression needed to support high flux through a heterologous metabolic pathway and predict the sizable fitness cost associated with enzyme production. This work has broad implications across applied biological sciences because it allows for prediction of the interplay between promoter strength, protein expression, and the resulting cost to microbial growth rates.