Bioinformatic Analysis and RT-qPCR to Characterize and Assess Knockdown of Axonemal Dynein Light Chain 2 in T. brucei

Ethan Lopez (1), Katherine Wentworth (2), Subash Godar (3,4), Joshua Alper (2,3,4)

(1) Department of Genetics and Biochemistry, (2) Department of Biological Sciences, (3) Department of Physics and Astronomy, (4) Eukaryotic Pathogens Innovation Center


Trypanosoma brucei is a parasitic member of the family of flagellated eukaryotes known as kinetoplastids, which affect 350 million people worldwide. Treatments for kinetoplastid diseases are currently limited, difficult to administer, and low in efficacy; however, flagellar proteins that affect parasite motility are potential novel drug targets. Flagellar motility in kinetoplastids exhibits a unique tip-to-base wave propagation that is thought to be governed by the coordination mechanisms of axonemal dynein motor proteins. We previously found that axonemal dynein light chain 2 (LC2) is integral to parasite motility by knocking it down with an inducible RNA interference (RNAi) construct. However, we need a quantifiable assessment of the knockdown to validate these findings. To accomplish this, we obtained composite cDNA from a total RNA extract of trypanosome cells by reverse transcription. We then PCR amplified LC2, along with several reporter genes, from the cDNA stock to construct a series of reverse transcriptase quantitative PCR (RT-qPCR) standard curves, which allow us to determine reaction efficiency and quantify unknown RT-qPCR samples. These RT-qPCR assays will allow us to rapidly quantify differential LC2 expression between wild type, RNAi induced, and RNAi uninduced cells to confirm the success of the knockdown, as well as knockdowns of other flagellar proteins we plan to perform in the future. This work will ultimately lead to insights into the molecular mechanisms of parasite motility and further efforts to develop pan-kinetoplastid drug treatments for disease.

Figure 1. The representative structure of outer arm dynein in T. brucei, including the LC2 subunit [1].


LC2 is a flagellar protein of T. brucei, one of many to be recently identified as a promising pan-kinetoplastid drug target to treat neglected tropical diseases like African sleeping sickness and Chagas disease [1]. We have identified two putative homologs of LC2 (LC2α and LC2β) in our efforts to knockdown its expression and characterize axonemal dynein. Through construction and transfection of a tetracycline-inducible RNAi plasmid (pZJM-LC2α-RNAi), we were able to successfully knockdown LC2 expression, which results in a slow, jerky swimming phenotype. Here, we will use RT-qPCR to compare LC2 expression levels between wild type (WT), tet-induced, and tet-uninduced trypanosome cells to validate the efficacy of our LC2 RNAi knockdown.

RT-qPCR is a technique that allows real-time quantification of RNA through reverse transcription, followed by PCR amplification (Fig 2). It relies on a dsDNA-binding fluorescent dye that hybridizes with the target as DNA amplification occurs. The quantity of DNA is measured after each reaction cycle through the intensity of the fluorescent signal and a threshold cycle (Ct) value is calculated as the cycle at which the fluorescent signal exceeds the baseline (Fig 3a). Ct values for samples of known starting DNA concentrations are plotted against log quantity of DNA to generate a standard curve, which can be used to ascertain the quantity of unknown DNA samples and/or determine reaction efficiency (Fig 3b). In this way, the technique can be used either to absolutely quantify unknown samples or compare relative expression of a gene of interest, the latter of which we will use in our experiments.

Figure 2. The workflow for both one-step and two-step RT-qPCR [2].

Figure 3a. A typical quantitative PCR (qPCR) amplification plot showing the baseline, threshold, and calculation of Ct values [3].

Figure 3b. A standard curve of Ct values from a qPCR experiment plotted against log starting quantity of DNA [3].

Materials and Methods

We extracted total RNA from both wild type (WT) and pZJM-LC2α-RNAi-expressing cells induced with doxycycline for 24 hours, and then synthesized a composite cDNA library from WT RNA through a reverse transcription reaction (Fig 4). To construct a standard curve, we first amplified FLAM3 (a constitutively expressed flagellar protein to be used as a control), LC2α, and LC2β cDNA using sequence-specific primers in a traditional PCR reaction, which we confirmed through gel electrophoresis. We then purified the amplified cDNA and performed a ten-fold serial dilution to obtain . We performed a qPCR reaction using SYBR® Green dye detection on all samples in triplicate, alongside a composite cDNA control (CCC) and a no-template control (NTC), both run in duplicate. Ct values from samples with concentrations ranging from 10^-3 to 10^-7 ng/μL were then plotted against log DNA concentration to determine reaction efficiency.

Figure 4. The workflow for two-step RT-qPCR used to generate the standard curve from FLAM3, LC2α, and LC2β RNA.


Sequence-specific primers facilitated successful amplification of FLAM3, LC2α, and LC2β RNA from WT cells using both traditional and qPCR. The standard curves generated from the qPCR reaction were linear for samples ranging from 10^-3 to 10^-7 ng/μL and all reaction efficiencies were over 100 percent [5]. However, only two dilution series, one FLAM3 and one LC2β replicate, demonstrated efficiencies within the acceptable range (90-110%) of a robust quantitative PCR reaction. All other reactions efficiencies were well above 100 percent.

Figure 5. A standard curve of Ct values with reaction efficiencies from amplification of FLAM3, LC2α, and LC2β cDNA in triplicate.


Successful amplification of FLAM3, LC2α, and LC2β RNA from WT cells was obtained as evidenced by the linearity of the standard curves of all sample replicates after quantitative PCR. The exceptionally high efficiencies in most of the samples, however, was likely due to polymerase inhibition, caused by artifacts left over from previous extraction and purification steps. Artifacts may include ethanol, enzymes, nucleotides, primers, and buffer components, all of which can decrease the sensitivity of qPCR by inhibiting the extension step of the reaction. This ultimately slows the reaction, increases the number of cycles needed for the fluorescent signal to cross the threshold, and increases the Ct values. Because polymerase inhibition is exacerbated at higher DNA concentrations, Ct values for samples with a concentration of 10^-3 ng/μL and above are the most affected, thereby flattening the standard curves and bringing the efficiencies well above 100 percent.

Future Directions


    Re-attempt standard curve procedure using the following modifications:

    • Use 40 μg PCR clean-up kit
    • Dry column twice after final ethanol wash during RNA extraction
    • Scale-up reverse transcription (cDNA synthesis) reaction

    Compare WT expression of LC2α RNA with that of tet-induced and tet-uninduced pZJM-LC2α-RNAi cell lines


    Use qPCR to assess efficacy of both RNAi knockdown and CRISPR/Cas9 knockout of endogenous LC2

    Apply qPCR to RNAi knockdowns of flagellar proteins planned for the future (i.e. LC1, ACS1, ACS2, ACS3, etc.) (Fig 6)

Figure 6. A representation of various recently identified flagellar tip proteins of T. brucei, including both flagellar connector proteins (FCPs) and axonemal capping structures (ACSs) [4].