PrimerSelect: a transcriptome-wide oligonucleotide primer pair design program for kinetic RT-PCR-based transcript profiling

The web-based multiplex PCR primer design software Ultiplex and the associated experimental workflow: up to 100- plex multiplicity

Background

A large number of variants have been employed in various medical applications, such as providing medication instructions, disease susceptibility testing, paternity testing, and tumour diagnosis. A high multiplicity PCR will outperform other technologies because of its lower cost, reaction time and sample consumption. To conduct a multiplex PCR with higher than 100 plex multiplicity, primers need to be carefully designed to avoid the formation of secondary structures and nonspecific amplification between primers, templates and products. Thus, a user-friendly, highly automated and highly user-defined web-based multiplex PCR primer design software is needed to minimize the work of primer design and experimental verification.

Results

Ultiplex was developed as a free online multiplex primer design tool with a user-friendly web-based interface (http://ultiplex.igenebook.cn). To evaluate the performance of Ultiplex, 294 out of 295 (99.7%) target primers were successfully designed. A total of 275 targets produced qualified primers after primer filtration, and 271 of those targets were successfully clustered into one compatible PCR group and could be covered by 108 primers. The designed primer group stably detected the rs28934573(C > T) mutation at lower than a 0.25% mutation rate in a series of samples with different ratios of HCT-15 and HaCaT cell line DNA.

Conclusion

Ultiplex is a web-based multiplex PCR primer tool that has several functions, including batch design and compatibility checking for the exclusion of mutual secondary structures and mutual false alignments across the whole genome. It offers flexible arguments for users to define their own references, primer Tm values, product lengths, plex numbers and tag oligos. With its user-friendly reports and web-based interface, Ultiplex will provide assistance for biological applications and research involving genomic variants.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-08149-1.

Prediction of PCR amplification from primer and template sequences using recurrent neural network

We have developed a novel method to predict the success of PCR amplification for a specific primer set and DNA template based on the relationship between the primer sequence and the template. To perform the prediction using a recurrent neural network, the usual double-stranded formation between the primer and template nucleotide sequences was herein expressed as a five-lettered word. The set of words (pseudo-sentences) was placed to indicate the success or failure of PCR targeted to learn recurrent neural network (RNN). After learning pseudo-sentences, RNN predicted PCR results from pseudo-sentences which were created by primer and template sequences with 70% accuracy. These results suggest that PCR results could be predicted using learned RNN and the trained RNN could be used as a replacement for preliminary PCR experimentation. This is the first report which utilized the application of neural network for primer design and prediction of PCR results.

Expression of the Biologically Active Insulin Analog SCI-57 in Nicotiana Benthamiana

Diabetes mellitus is a growing problem worldwide; however, only 23% of low-income countries have access to insulin, and ironically it costs higher in such countries than high-income ones. Therefore, new strategies for insulin and insulin analogs production are urgently required to improve low-cost access to therapeutic products, so as to contain the diabetes epidemic. SCI-57 is an insulin analog with a greater affinity for the insulin receptor and lower thermal degradation than native insulin. It also shows native mitogenicity and insulin-like biological activity. In this work, SCI-57 was transiently expressed in the Nicotiana benthamiana (Nb) plant, and we also evaluated some of its relevant biological effects. An expression plasmid was engineered to translate an N-terminal ubiquitin and C-terminal endoplasmic reticulum-targeting signal KDEL, in order to increase protein expression and stability. Likewise, the effect of co-expression of influenza M2 ion channel (M2) on the expression of insulin analog SCI-57 (SCI-57/M2) was evaluated. Although using M2 increases yield, it tends to alter the SCI-57 amino acid sequence, possibly promoting the formation of oligomers. Purification of SCI-57 was achieved by FPLC cation exchange and ultrafiltration of N. benthamiana leaf extract (NLE). SCI-57 exerts its anti-diabetic properties by stimulating glucose uptake in adipocytes, without affecting the lipid accumulation process. Expression of the insulin analog in agroinfiltrated plants was confirmed by SDS-PAGE, RP-HPLC, and MS. Proteome changes related to the expression of heterologous proteins on N. benthamiana were not observed; up-regulated proteins were related to the agroinfiltration process. Our results demonstrate the potential for producing a biologically active insulin analog, SCI-57, by transient expression in Nb.

DNA methylation profiling identifies PTRF/Cavin-1 as a novel tumor suppressor in Ewing sarcoma when co-expressed with caveolin-1

Epigenetic modifications have been shown to be important in developmental tumors as Ewing sarcoma. We profiled the DNA methylation status of 15 primary tumors, 7 cell lines, 10 healthy tissues and 4 human mesenchymal stem cells lines samples using the Infinium Human Methylation 450K. Differential methylation analysis between Ewing sarcoma and reference samples revealed 1166 hypermethylated and 864 hypomethylated CpG sites (Bonferroni p < 0.05, δ-β-value with absolute difference of >0.20) corresponding to 392 and 470 genes respectively. Gene Ontology analysis of genes differentially methylated in Ewing sarcoma samples showed a significant enrichment of developmental genes. Membrane and cell signal genes were also enriched, among those, 11 were related to caveola formation. We identified differential hypermethylation of CpGs located in the body and S-Shore of the PTRF gene in Ewing sarcoma that correlated with its repressed transcriptional state. Reintroduction of PTRF/Cavin-1 in Ewing sarcoma cells revealed a role of this protein as a tumor suppressor. Restoration of caveolae in the membrane of Ewing sarcoma cells, by exogenously reintroducing PTRF, disrupts the MDM2/p53 complex, which consequently results in the activation of p53 and the induction of apoptosis.

A robust PCR primer design platform applied to the detection of Acidobacteria Group 1 in soil

Environmental biosurveillance and microbial ecology studies use PCR-based assays to detect and quantify microbial taxa and gene sequences within a complex background of microorganisms. However, the fragmentary nature and growing quantity of DNA-sequence data make group-specific assay design challenging. We solved this problem by developing a software platform that enables PCR-assay design at an unprecedented scale. As a demonstration, we developed quantitative PCR assays for a globally widespread, ecologically important bacterial group in soil, Acidobacteria Group 1. A total of 33,684 Acidobacteria 16S rRNA gene sequences were used for assay design. Following 1 week of computation on a 376-core cluster, 83 assays were obtained. We validated the specificity of the top three assays, collectively predicted to detect 42% of the Acidobacteria Group 1 sequences, by PCR amplification and sequencing of DNA from soil. Based on previous analyses of 16S rRNA gene sequencing, Acidobacteria Group 1 species were expected to decrease in response to elevated atmospheric CO(2). Quantitative PCR results, using the Acidobacteria Group 1-specific PCR assays, confirmed the expected decrease and provided higher statistical confidence than the 16S rRNA gene-sequencing data. These results demonstrate a powerful capacity to address previously intractable assay design challenges.