Temperature effects on the fidelity of a thermostable HIV-1 reverse transcriptase

Tutorial: Guidelines for Single-Cell RT-qPCR

Reverse transcription quantitative PCR (RT-qPCR) has delivered significant insights in understanding the gene expression landscape. Thanks to its precision, sensitivity, flexibility, and cost effectiveness, RT-qPCR has also found utility in advanced single-cell analysis. Single-cell RT-qPCR now represents a well-established method, suitable for an efficient screening prior to single-cell RNA sequencing (scRNA-Seq) experiments, or, oppositely, for validation of hypotheses formulated from high-throughput approaches. Here, we aim to provide a comprehensive summary of the scRT-qPCR method by discussing the limitations of single-cell collection methods, describing the importance of reverse transcription, providing recommendations for the preamplification and primer design, and summarizing essential data processing steps. With the detailed protocol attached in the appendix, this tutorial provides a set of guidelines that allow any researcher to perform scRT-qPCR measurements of the highest standard.

Performance Comparison of Reverse Transcriptases for Single-Cell Studies

BACKGROUND

Recent advances allowing quantification of RNA from single cells are revolutionizing biology and medicine. Currently, almost all single-cell transcriptomic protocols rely on reverse transcription (RT). However, RT is recognized as a known source of variability, particularly with low amounts of RNA. Recently, several new reverse transcriptases (RTases) with the potential to decrease the loss of information have been developed, but knowledge of their performance is limited.

METHODS

We compared the performance of 11 RTases in quantitative reverse transcription PCR (RT-qPCR) on single-cell and 100-cell bulk templates, using 2 priming strategies: a conventional mixture of random hexamers with oligo(dT)s and a reduced concentration of oligo(dT)s mimicking common single-cell RNA-sequencing protocols. Depending on their performance, 2 RTases were further tested in a high-throughput single-cell experiment.

RESULTS

All tested RTases demonstrated high precision (R2 > 0.9445). The most pronounced differences were found in their ability to capture rare transcripts (0%-90% reaction positivity rate) and in their absolute reaction yield (7.3%-137.9%). RTase performance and reproducibility were compared with Z scores. The 2 best-performing enzymes were Maxima H- and SuperScript IV. The validity of the obtained results was confirmed in a follow-up single-cell model experiment. The better-performing enzyme (Maxima H-) increased the sensitivity of the single-cell experiment and improved resolution in the clustering analysis over the commonly used RTase (SuperScript II).

CONCLUSIONS

Our comprehensive comparison of 11 RTases in low RNA input conditions identified 2 best-performing enzymes. Our results provide a point of reference for the improvement of current single-cell quantification protocols.

Reverse Transcriptase: From Transcriptomics to Genome Editing

Reverse transcriptases (RTs) are enzymes that can generate a complementary strand of DNA (cDNA) from RNA. Coupled with PCR, RTs have been widely used to detect RNAs and to clone expressed genes. Classical retroviral RTs have been improved by protein engineering. These enzymes and newly characterized RTs are key elements in the development of next-generation sequencing techniques that are now being applied to the study of transcriptomics. In addition, engineered RTs fused to a CRISPR/Cas9 nickase have recently shown great potential as tools to manipulate eukaryotic genomes. In this review, we discuss the properties and uses of wild type and engineered RTs in biotechnological applications, from conventional RT-PCR to recently introduced prime editing.

Poly(A) inclusive RNA isoform sequencing (PAIso-seq) reveals wide-spread non-adenosine residues within RNA poly(A) tails

Message RNA poly(A) tails are vital for their function and regulation. However, the full-length sequence of mRNA isoforms with their poly(A) tails remains undetermined. Here, we develop a method at single-cell level sensitivity that enables quantification of poly(A) tails along with the full-length cDNA while reading non-adenosine residues within poly(A) tails precisely, which we name poly(A) inclusive RNA isoform sequencing (PAIso−seq). Using this method, we can quantify isoform specific poly(A) tail length. More interestingly, we find that 17% of the mRNAs harbor non-A residues within the body of poly(A) tails in mouse GV oocytes. We show that PAIso−seq is sensitive enough to analyze single GV oocytes. These findings will not only provide an accurate and sensitive tool in studying poly(A) tails, but also open a door for the function and regulation of non-adenosine modifications within the body of poly(A) tails.

The poly(A) tails on mRNA are vital for their function but it is difficult to map full-length sequences of mRNA isoforms with the entire poly(A) tails. Here the authors develop PAIso−seq which can measure isoform specific poly(A) tail length and base composition at single-cell sensitivity.

Are RNA Viruses Candidate Agents for the Next Global Pandemic? A Review

Pathogenic RNA viruses are potentially the most important group involved in zoonotic disease transmission, and they represent a challenge for global disease control. Their biological diversity and rapid adaptive rates have proved to be difficult to overcome and to anticipate by modern medical technology. Also, the anthropogenic change of natural ecosystems and the continuous population growth are driving increased rates of interspecies contacts and the interchange of pathogens that can develop into global pandemics. The combination of molecular, epidemiological, and ecological knowledge of RNA viruses is therefore essential towards the proper control of these emergent pathogens. This review outlines, throughout different levels of complexity, the problems posed by RNA viral diseases, covering some of the molecular mechanisms allowing them to adapt to new host species-and to novel pharmaceutical developments-up to the known ecological processes involved in zoonotic transmission.

Next-generation sequencing-based analysis of reverse transcriptase fidelity

In this study, we devised a simple and rapid method to analyze fidelity of reverse transcriptase (RT) using next-generation sequencing (NGS). The method comprises a cDNA synthesis reaction from standard RNA with a primer containing a tag of 14 randomized bases and the RT to be tested, PCR using high-fidelity DNA polymerase, and NGS. By comparing the sequence of each read with the reference sequence, mutations were identified. The mutation can be identified to be due to an error introduced by either cDNA synthesis, PCR, or NGS based on whether the sequence reads with the same tag contain the same mutation or not. The error rates in cDNA synthesis with Moloney murine leukemia virus (MMLV) RT thermostable variant MM4 or the recently developed 16-tuple variant of family B DNA polymerase with RT activity, RTX, from Thermococcus kodakarensis, were 0.75-1.0 × 10^-4 errors/base, while that in the reaction with the wild-type human immunodeficiency virus type 1 (HIV-1) RT was 2.6 × 10^-4 errors/base. Overall, our method could precisely evaluate the fidelity of various RTs with different reaction conditions in a high-throughput manner without the use of expensive optics and troublesome adaptor ligation.

Fidelity of classwide-resistant HIV-2 reverse transcriptase and differential contribution of K65R to the accuracy of HIV-1 and HIV-2 reverse transcriptases

Nucleoside reverse transcriptase (RT) inhibitors constitute the backbone of current therapies against human immunodeficiency virus type 1 and type 2 (HIV-1 and HIV-2, respectively). However, mutational pathways leading to the development of nucleoside analogue resistance are different in both types of HIV. In HIV-2, resistance to all approved nucleoside analogues is conferred by the combination of RT substitutions K65R, Q151M and M184V. Nucleotide incorporation kinetic analyses of mutant and wild-type (WT) HIV-2 RTs show that the triple-mutant has decreased catalytic efficiency due to the presence of M184V. Although similar effects were previously reported for equivalent mutations in HIV-1 RT, the HIV-2 enzymes were catalytically less efficient. Interestingly, in highly divergent HIV-1 RTs, K65R confers several-fold increased accuracy of DNA synthesis. We have determined the intrinsic fidelity of DNA synthesis of WT HIV-2 RT and mutants K65R and K65R/Q151M/M184V. Our results show that those changes in HIV-2 RT have a relatively small impact on nucleotide selectivity. Furthermore, we found that there were less than two-fold differences in error rates obtained with forward mutation assays using mutant and WT HIV-2 RTs. A different conformation of the β3-β4 hairpin loop in HIV-1 and HIV-2 RTs could probably explain the differential effects of K65R.

HIV-1 persistent viremia is frequently followed by episodes of low-level viremia

After the start of antiretroviral therapy (ART), plasma HIV-RNA levels should fall below the limit of detection (LOD) within 24 weeks. Hence, the prolonged decline of HIV-RNA after ART initiation is defined as persistent viremia (PV). In this retrospective study, we analyzed factors associated with PV. Next-generation sequencing of viral RNA/DNA was performed to study viral evolution and the emergence of drug-resistance mutations in HIV-infected patients with PV (n = 20). In addition, HIV-DNA species, immunological parameters, and clinical data of the patients were analyzed. We found that the possible causes for PV were divers, and both virologic and host parameters of this particular cohort were heterogeneous. We identified viruses with therapy-associated DRMs in six patients (30%); two of these were detected as minority variants. Five patients had sub-optimal drug levels (25%) and the baseline plasma viral loads were relatively high. Strikingly, we observed that >40% of the PV patients finally reaching HIV levels below the LOD later on showed up with episodes of low-level viremia (LLV). However, the amount of PBMC derived HIV-DNA species was not correlated with the likelihood of LLV after PV. According to our data, we conclude that drug-resistant viruses, sub-optimal drug level, and high baseline viral loads might be probable reasons for the prolonged RNA decline only in a sub-set of patients. In the absence of emerging DRMs and/or compliance issues, the clinical implications of PV remain unclear; however, PV appears to be a risk factor for episodes of LLV.