Untranslated Region Sequences and the Efficacy of mRNA Vaccines against Tuberculosis
Open accessAbstract
mRNA vaccines have been shown to be effective in combating the COVID-19 pandemic. The amount of research on the use of mRNAs as preventive and therapeutic modalities has undergone explosive growth in the last few years. Nonetheless, the issue of the stability of mRNA molecules and their translation efficiency remains incompletely resolved. These characteristics of mRNA directly affect the expression level of a desired protein. Regulatory elements of RNA—5′ and 3′ untranslated regions (UTRs)—are responsible for translation efficiency. An optimal combination of the regulatory sequences allows mRNA to significantly increase the target protein’s expression. We assessed the translation efficiency of mRNA encoding of firefly luciferase with various 5′ and 3′UTRs in vitro on cell lines DC2.4 and THP1. We found that mRNAs containing 5′UTR sequences from eukaryotic genes HBB, HSPA1A, Rabb, or H4C2, or from the adenoviral leader sequence TPL, resulted in higher levels of luciferase bioluminescence 4 h after transfection of DC2.4 cells as compared with 5′UTR sequences used in vaccines mRNA-1273 and BNT162b2 from Moderna and BioNTech. mRNA containing TPL as the 5′UTR also showed higher efficiency (as compared with the 5′UTR from Moderna) at generating a T-cell response in mice immunized with mRNA vaccines encoding a multiepitope antigen. By contrast, no effects of various 5′UTRs and 3′UTRs were detectable in THP1 cells, suggesting that the observed effects are cell type specific. Further analyses enabled us to identify potential cell type-specific RNA-binding proteins that differ in landing sites within mRNAs with various 5′UTRs and 3′UTRs. Taken together, our data indicate high translation efficiency of TPL as a 5′UTR, according to experiments on DC2.4 cells and C57BL/6 mice.
AI snapshot
Written from the paper’s full text.
TL;DR
This study tested how different 5′ and 3′ untranslated region (UTR) sequences affect mRNA translation efficiency and used the best 5′UTR to build a multiepitope mRNA vaccine against *Mycobacterium tuberculosis*. The adenoviral TPL 5′UTR increased luciferase expression in DC2.4 cells and improved T-cell responses and bacterial control in mice compared with the mRNA-1273 5′UTR.
Key findings
- In DC2.4 cells, 5′UTRs from HBB, HSPA1A, Rabb, H4C2, and TPL increased luciferase bioluminescence at 4 h after transfection compared with the 5′UTRs used in BNT162b2 and mRNA-1273 and compared with C3 [Kruskal–Wallis: H(11, N = 66) = 85.2, p < 0.0001]. In THP1 cells, only HBB showed elevated luciferase at 24 h versus C3 [Kruskal–Wallis: H(11, N = 60) = 31.05, p = 0.001], suggesting cell type-specific effects.
- 3′UTR effects were detected only in DC2.4 cells at 8, 24, and 72 h [8 h: H(11, N = 66) = 38.37, p < 0.001; 24 h: H(11, N = 66) = 38.49, p < 0.001; 72 h: H(11, N = 66) = 30.49, p = 0.001]. AES-HBB and mtRNR-HBB produced the lowest luciferase levels, and no tested 3′UTR outperformed the mRNA-1273 or BNT162b2 3′UTRs.
- Predicted mean ribosomal loading (MRL) correlated with bioluminescence in DC2.4 cells at 4 h (r² = 0.43, p = 0.024). TPL had the highest MRL (7.7), versus 5.74 for the mRNA-1273 5′UTR.
- In mice, the TPL 5′UTR vaccine produced more IFNγ-secreting cells than the mRNA-1273 5′UTR vaccine (13.6 ± 1.9 versus 5.6 ± 0.7). TPL-vaccinated mice also showed delayed-type hypersensitivity and lower lung CFU versus PBS and LNP controls (p < 0.05), whereas the mRNA-1273 5′UTR vaccine differences were not statistically significant.
Methods
- Twenty-two firefly luciferase mRNA constructs with various 5′ and 3′UTRs were transfected into DC2.4 and THP1 cells; luciferase activity was measured at 4, 8, 24, and 72 h, normalized to NanoLuc, with 4–6 biological replicates.
- C57BL/6JCit and I/StSnEgYCit mice were immunized twice with 50 μg mRNA-LNP vaccines encoding a multiepitope *M. tuberculosis* antigen, using either TPL or mRNA-1273 as the 5′UTR and mRNA-1273 as the 3′UTR. Outcomes included ELISpot IFNγ responses, delayed-type hypersensitivity, and lung CFU after infection with *M. tuberculosis* H37Rv at 500,000 CFUs per mouse.
- Bioinformatics included Optimus 5-Prime MRL prediction, RNAFold secondary-structure energy, RBPmap binding-site prediction, and RNA-seq differential expression of RNA-binding protein genes between THP1 and DC2.4 cells. Statistics used Kruskal–Wallis with Dunn’s multiple comparison and correlation analysis.
Limitations
- The paper states that no significant 3′UTR differences were found, possibly due to assay limitations and the relatively short half-life of luciferase; it notes that definitive UTR conclusions should use direct or indirect target antigen expression and further animal-model research.
- The paper states that the impact of UTR selection on mRNA stability should be evaluated further, that the MRL predictive model was tested only for 5′UTRs up to 100 bp, and that unmodified uridine was used rather than modified uridine analogs.
- The text makes evident that the cell-based effects were cell type specific, tested in only two cell lines, and the in vivo comparison tested only TPL versus mRNA-1273 5′UTR with the mRNA-1273 3′UTR, limiting generalization across other UTR combinations, cell types, and vaccine contexts.
Model-written summary. Check it against the paper before relying on it.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
21 of 45 cited sources checked · 6 supported · 0 flagged · accuracy not yet measured
- Premisecitation
UTRs can influence mRNA translation efficiency and resistance to degradation by interacting with RNA-binding proteins and microRNAs.
“It is known that UTRs are associated with processes of mRNA translation, and by interacting with RNA-binding proteins (RBPs) and microRNAs, UTRs can influence mRNA’s translation efficiency and resistance to degradation [3,4,5,6,7].”
Quote in the paperSubstantial claim4 of 5 sources checked- cites [3] Schlake, 2012, Developing mRNA-vaccine technologies, RNA Biol. source
The mRNA Design section says UTRs affect translation and stability and that miRNA-binding sites in UTRs can destabilize mRNA. The copy does not explain these effects as arising from interactions with RNA-binding proteins; it mentions UTR-binding factors only in a reference title. No page number is available for these passages. (LLM, conf=0.82)
Experimental — accuracy not yet measured - cites [4] Lacroix, 2020, Tailoring mRNA Vaccine to Balance Innate/Adaptive Immune Response, Trends Mol. Med. source
- cites [5] Xu, S., Yang, K., Li, R., and Zhang, L. (2020). mRNA Vaccine Era-Mechanisms, Drug Platform and Clinical Prospection. Int. J. Mol. Sci., 21. source
Section 2.2 (page not provided) says UTRs can alter mRNA decay and translation efficiency through interactions with RNA-binding proteins. Section 2.4 mentions microRNA-mediated translation inhibition in its discussion of the poly(A) tail, but does not say that UTRs interact with microRNAs to produce the claimed effects. (LLM, conf=0.87)
Experimental — accuracy not yet measured - cites [6] Kim, 2022, Modifications of mRNA vaccine structural elements for improving mRNA stability and translation efficiency, Mol. Cell. Toxicol. source
The “5ʹ- and 3ʹ-UTRs” section says that UTR interactions with RNA-binding proteins can influence mRNA degradation and translation efficiency. It does not mention microRNAs as part of that mechanism, so that portion of the attributed claim is unsupported by our copy. (LLM, conf=0.88)
Experimental — accuracy not yet measured - cites [7] Kirshina, A., Vasileva, O., Kunyk, D., Seregina, K., Muslimov, A., Ivanov, R., and Reshetnikov, V. (2023). Effects of Combinations of Untranslated-Region Sequences on Translation of mRNA. Biomolecules, 13. source
- Premisecitation
There are two experimental studies that demonstrated efficacy of mRNA vaccines against tuberculosis.
“There are two experimental studies that demonstrated efficacy of the mRNA vaccines against tuberculosis [34,35].”
Quote in the paperSubstantial claim2 of 2 sources checked- cites [34] Larsen, S.E., Erasmus, J.H., Reese, V.A., Pecor, T., Archer, J., Kandahar, A., Hsu, F.C., Nicholes, K., Reed, S.G., and Baldwin, S.L. (2023). An RNA-Based Vaccine Platform for Use against Mycobacterium tuberculosis. Vaccines, 11. source
- cites [35] Xue, 2004, RNA encoding the MPT83 antigen induces protective immune responses against Mycobacterium tuberculosis infection, Infect. Immun. source
- Premisecitation
Cap-independent translation plays a major role only during periods of cellular stress, apoptosis, and certain stages of the cell cycle.
“cap-independent translation plays a major role only during periods of cellular stress, apoptosis, and certain stages of the cell cycle [2].”
Quote in the paperSubstantial claim1 of 1 sources checked- cites [2] Pichon, 2012, RNA binding protein/RNA element interactions and the control of translation, Curr. Protein Pept. Sci. source
The Internal Ribosome Entry Segments section says cap-dependent translation is inhibited during stress, apoptosis, and certain cell-cycle stages, and describes cap-independent translation under stress. It does not establish that cap-independent translation plays a major role only during those periods; the exclusivity and magnitude are unsupported. (LLM, conf=0.84)
Experimental — accuracy not yet measured
- Interpretationcitation
The relatively short half-life of luciferase may have an impact on the results, preventing the detection of differences in cumulative transgene expression.
“The relatively short half-life of luciferase may have an impact on the results [43], preventing the detection of differences in the cumulative transgene expression.”
Quote in the paperSubstantial claim1 of 1 sources checked- cites [43] Krishnamachary, 2018, Hypoxia-Induced Reporter Genes with Different Half-Lives, Methods Mol. Biol. source
The Introduction states that luciferase has a half-life of only 2 hours, and the paper contrasts short-half-life luciferase with long-half-life GFP reporters. It does not state that luciferase's half-life prevented detection of differences in cumulative transgene expression; that proposed effect on the citing study's results is not supported by this source. (LLM, conf=0.82)
Experimental — accuracy not yet measured
- Findingown data
AES-EMCV as 3′UTR showed lower bioluminescence values 72 h after transfection of DC2.4 cells compared with mRNA-1273 3′UTR.
“showed lower bioluminescence values 72 h after the transfection of DC2.4 cells as compared with the mRNA-1273 3′UTR (p < 0.05).”
Quote in the paperSubstantial claim
- Findingown data
In THP1 cells, mRNA with the 5′UTR from human β-globin showed elevated luciferase levels 24 h after transfection compared with mRNA with the 5′UTR from C3.
“In the THP1 cell line, mRNA with the 5′UTR sequence from human β-globin mRNA also showed elevated luciferase levels 24 h after the transfection as compared with mRNA with the 5′UTR sequence from C3 mRNA.”
Quote in the paperSubstantial claim - Findingown data
AES-EMCV as 3′UTR caused higher relative bioluminescence compared with mRNA-1273 3′UTR in Luc RNA at 8 and 24 h after transfection of DC2.4 cells.
“Even the 3′UTR sequence AES-EMCV—which caused higher relative bioluminescence as compared with the mRNA-1273 3′UTR in Luc RNA at 8 and 24 h after the transfection of DC2.4 cells—showed lower bioluminescence”
Quote in the paperNot a substantial claim - Findingown data
mRNAs containing 5′UTR sequences from HBB, HSPA1A, Rabb, H4C2, or TPL produced higher luciferase bioluminescence in DC2.4 cells at 4 h after transfection than mRNAs with 5′UTRs from mRNA-1273 and BNT162b2.
“We found that mRNAs containing 5′UTR sequences from eukaryotic genes HBB, HSPA1A, Rabb, or H4C2, or from the adenoviral leader sequence TPL, resulted in higher levels of luciferase bioluminescence 4 h after transfection of DC2.4 cells as compared with 5′UTR sequences used in vaccines mRNA-1273 and BNT162b2 from Moderna and BioNTech.”
- Also stated in: § 2.1. The Effect of the 5′UTR Sequence on Translation Efficiency · plain
“5′UTRs from mRNAs of eukaryotic genes HBB, HSPA1A, Rabb, and H4C2 and the adenoviral 5′UTR termed “tripartite leader sequence” (TPL) significantly increased protein levels 4 h post-transfection in DC2.4 cells as compared with the 5′UTRs used in the BNT162b2 (Pfizer-BioNTech) and mRNA-1273 (Moderna) vaccines and compared with the 5′UTR from complement gene C3 (Figure 2).”
Quote in the paperSubstantial claim - Also stated in: § 2.1. The Effect of the 5′UTR Sequence on Translation Efficiency · plain
- Findingown data
No effects of various 5′UTRs and 3′UTRs on luciferase bioluminescence were detectable in THP1 cells.
“By contrast, no effects of various 5′UTRs and 3′UTRs were detectable in THP1 cells, suggesting that the observed effects are cell type specific.”
Quote in the paperSubstantial claim - Findingown data
Twenty differentially expressed RBP genes have a presumed landing site in the UTRs under study.
“Twenty differentially expressed RBP genes were found to have a presumed landing site in the UTRs under study (Table 1).”
Quote in the paperNot a substantial claim - Findingown data
None of the tested 3′UTR sequences raised luciferase levels compared with control Luc RNAs containing 3′UTR sequences from mRNA-1273 and BNT162b2.
“On the other hand, none of the tested 3′UTR sequences raised luciferase levels as compared with the control Luc RNAs containing 3′UTR sequences from mRNA-1273 and BNT162b2.”
Quote in the paperSubstantial claim - Findingown data
The 3′UTR sequence affected luciferase levels in DC2.4 cells at 8, 24, and 72 h after transfection.
“In this context, an effect of the 3′UTR on luciferase levels was registered 8, 24, and 72 h after the transfection of DC2.4 cells [Kruskal–Wallis test 8 h: H (11, N = 66) = 38.37, p < 0.001; 24 h: H (11, N = 66) = 38.49, p < 0.001; and 72 h: H (11, N = 66) = 30.49, p = 0.001].”
Quote in the paperSubstantial claim - Findingown data
Expression of 85 RBP genes differs between THP1 and DC2.4 cells.
“We revealed that the expression of 85 RBP genes differs between THP1 and DC2.4 cells (Supplementary Table S1).”
Quote in the paperSubstantial claim - Findingown data
There were no significant differences in bioluminescence among 3′UTRs in the THP1 cell line.
“There were no significant differences in the THP1 cell line.”
Quote in the paperNot a substantial claim - Findingown data
In DC2.4 cells, AES-AES, AES-EMCV, and AES-HBB as 3′UTR resulted in the lowest levels of luciferase compared with BNT162b2 and mRNA-1273 3′UTR sequences.
“However, in DC2.4 data sequences, AES-AES, AES-EMCV, and AES-HBB, when used as the 3’ UTR in Luc RNA, resulted in the lowest levels of luciferase compared with the BNT162B2 and mRNA-1273 data sequences.”
Quote in the paperSubstantial claim - Findingown data
There is no correlation between MRL and bioluminescence in THP1 cells.
“In the THP1 cell line, however, there was no correlation between these parameters.”
Quote in the paperNot a substantial claim - Findingown data
The 5′UTR from mRNA-1273 has a predicted landing site for HNRNPH1.
“On the other hand, the 5′UTR from mRNA-1273 has a predicted landing site for HNRNPH1;”
Quote in the paperSubstantial claim - Findingnone given
The theoretical amount of capped RNA was ~80%.
“the theoretical amount of capped RNA was ~80%”
Quote in the paperNot a substantial claim - Findingown data
Mice immunized with the mRNA vaccine containing TPL as 5′UTR showed marked enlargement of the tuberculin injection site compared with the LNP group (p < 0.05).
“Mice immunized with the mRNA vaccine containing the TPL sequence as the 5′UTR showed marked enlargement of the site of tuberculin injection as compared with the group of mice injected with LNPs (p < 0.05).”
Quote in the paperSubstantial claim - Findingown data
In the 5′UTR sequences of HBB, HSPA1A, Rabb, H4C2, and TPL, binding sites for only two RBPs (PABPC3 and RBM22) were found.
“In the 5′UTR sequences of HBB, HSPA1A, Rabb, and H4C2, and in TPL, binding sites for only two RBPs (PABPC3 and RBM22) were found;”
Quote in the paperSubstantial claim - Findingown data
Mice immunized with the mRNA vaccine containing mRNA-1273 as 5′UTR did not differ from control groups in delayed-type hypersensitivity.
“On the other hand, mice immunized with the mRNA vaccine containing the mRNA-1273 sequence as the 5′UTR did not differ from control groups.”
Quote in the paperSubstantial claim - Findingown data
There is no correlation between minimum free energy (of either a 3′UTR alone or the entire RNA) and bioluminescence intensity.
“We also failed to find a correlation between minimum free energy (MFE) (of either a 3′UTR alone or the entire RNA) and bioluminescence intensity (Supplementary Figure S1).”
Quote in the paperNot a substantial claim - Findingown data
MRL has a marginally significant correlation with bioluminescence at 24 and 72 h after transfection in DC2.4 cells (r2 = 0.3 and r2 = 0.29).
“and a marginally significant correlation at later time points (24 and 72 h after transfection: r2 = 0.3 and r2 = 0.29).”
Quote in the paperNot a substantial claim - Findingown data
Vaccination with two doses of mRNA vaccines had an effect on M. tuberculosis load in lungs 50 days after infection.
“Finally, vaccination with two doses of mRNA vaccines had an effect on the of M. tuberculosis load in lungs 50 days after the infection [Kruskal–Wallis test: H(3,20) = 12.58, p = 0.006].”
Quote in the paperSubstantial claim - Findingown data
The ELISpot assay proved the vaccination to be effective.
“The ELISpot assay proved the vaccination to be effective [Kruskal–Wallis test: H(3, 18) = 14.82, p = 0.002].”
Quote in the paperSubstantial claim - Findingown data
Most of the 5′UTR and 3′UTR sequences contain predicted binding sites for various RBPs, many of which directly affect mRNA stability and translation efficiency.
“Most of the 5′UTR and 3′UTR sequences were found to contain the predicted binding sites for various RBPs, many of which directly affect the stability and translation efficiency of mRNA (Table 2).”
Quote in the paperNot a substantial claim - Findingown data
mRNA with 5′UTR TPL gives a more than two-fold increase in the number of IFNγ-secreting cells after immunization compared with mRNA with the mRNA-1273 5′UTR (13.6 ± 1.9 versus 5.6 ± 0.7).
“A comparison of two mRNA vaccines showed that mRNA with the 5′UTR TPL sequence gives a more than two-fold increase in the number of IFNγ-secreting cells after the immunization as compared with the mRNA with the mRNA-1273 5′UTR sequence (13.6 ± 1.9 versus 5.6 ± 0.7).”
Quote in the paperSubstantial claim - Findingown data
Only for eight differentially expressed genes of RBPs is the influence of such proteins on RNA stability known.
“Only for eight differentially expressed genes of RBPs is the influence of such proteins on RNA stability known (Table 2).”
Quote in the paperNot a substantial claim - Findingown data
The proportion of encapsulated RNA was more than 95%.
“The proportion of encapsulated RNA was more than 95%.”
Quote in the paperNot a substantial claim - Findingown data
In lung tissue, there was a lower number of CFUs in mice immunized with 5′-TPL-mEpitope-mRNA1273-3′ compared with PBS and LNP groups (p < 0.05).
“In lung tissue, there was a lower number of colony-forming units (CFUs) in mice immunized with mRNA vaccine 5′-TPL-mEpitope-mRNA1273-3′ in comparison to the PBS and LNP groups (p < 0.05).”
Quote in the paperSubstantial claim - Findingcitation
TPL as the 5′UTR had the highest MRL (7.7).
“On the other hand, TPL as the 5′UTR had the highest MRL (7.7); this parameter evaluates experimental data on ribosomal loading by means of neural networks [37].”
Quote in the paperSubstantial claim - Findingown data
MRL correlates with bioluminescence intensity at 4 h after transfection in DC2.4 cells (r2 = 0.43, p = 0.024).
“Our results uncovered a significant correlation of MRL with bioluminescence intensity at 4 h after transfection in DC2.4 cells (r2 = 0.43, p = 0.024; Figure 4)”
Quote in the paperSubstantial claim - Findingown data
Other 5′UTR sequences (from Rabb, HSPA1A, HBB, and H4C2) that manifested higher translation efficiency compared with the mRNA-1273 5′UTR also had higher MRL than the mRNA-1273 5′UTR (6.59, 6.58, 6.52, and 6.17 versus 5.74).
“Of note, other 5′UTR sequences (from Rabb, HSPA1A, HBB, and H4C2) that manifested higher translation efficiency (when tested as part of mRNA), as compared with the mRNA-1273 5′UTR, also had higher MRL than the mRNA-1273 5′UTR sequence did (6.59, 6.58, 6.52, and 6.17 versus 5.74).”
Quote in the paperSubstantial claim - Findingown data
Vaccination with mRNA vaccine containing TPL as 5′UTR increased the number of IFNγ-secreting cells after stimulation with M. tuberculosis sonicate compared with PBS or LNP control groups (p < 0.01).
“The number of IFNγ-secreting cells after stimulation with the M. tuberculosis sonicate was higher for splenocytes of mice vaccinated with the mRNA vaccine containing the TPL sequence as the 5′UTR compared with splenocytes of mice from control groups (PBS or LNP wo RNA, p < 0.01; Figure 5D).”
Quote in the paperSubstantial claim - Findingown data
Vaccination led to the development of a delayed-type hypersensitivity reaction.
“The vaccination led to the development of the delayed-type hypersensitivity reaction [Kruskal–Wallis test: H(3,31) = 9.07, p = 0.028].”
Quote in the paperSubstantial claim - Findingown data
The 5′-TPL-mEpitope-mRNA1273-3′ vaccine is stable for at least 6 months when stored at +2 to +8 °C.
“Although we have demonstrated the stability of the 5′-TPL-mEpitope-mRNA1273-3′ vaccine for at least 6 months when stored at +2 to +8 °C, the impact of UTR selection on the stability of mRNA should be evaluated further.”
Quote in the paperSubstantial claim - Findingnone given
TPL as a 5′UTR provides high translation efficiency.
“TPL as a 5′UTR provides high translation efficiency”
Quote in the paperSubstantial claim - Interpretationown data
The effects of 5′UTRs on translation efficiency are cell type specific.
“By contrast, no effects of various 5′UTRs and 3′UTRs were detectable in THP1 cells, suggesting that the observed effects are cell type specific.”
- Also stated in: § 2.1. The Effect of the 5′UTR Sequence on Translation Efficiency · hedged
“The observed differences among the cell lines in translation efficiency of Luc RNAs containing various 5′UTRs suggested that the effects of 5′UTRs were distinctly cell type specific.”
Quote in the paperSubstantial claim - Also stated in: § 2.1. The Effect of the 5′UTR Sequence on Translation Efficiency · hedged
- Interpretationreasoning
AES-HBB and mtRNR-HBB within mRNA lead to a decrease in mRNA stability.
“Because the 3′UTR is primarily responsible for RNA stability in the cell and prevents the RNA degradation mediated by binding to microRNA, our findings implied that 3′UTR sequences AES-HBB and mtRNR-HBB within mRNA lead to a decrease in its stability.”
Quote in the paperSubstantial claim- Rests on an assumption: The 3′UTR is primarily responsible for RNA stability in the cell and prevents RNA degradation mediated by binding to microRNA.
- Interpretationreasoning
The lack of pronounced differences between different 3′UTR sequences may be due to peculiarities of the translational machinery and to assay limitations.
“The lack of pronounced differences between different 3′UTR sequences may be due both to peculiarities of the translational machinery and to assay limitations.”
Quote in the paperSubstantial claim - Premisenone given
Regulatory elements 5′ and 3′ UTRs are responsible for translation efficiency.
“Regulatory elements of RNA—5′ and 3′ untranslated regions (UTRs)—are responsible for translation efficiency.”
Quote in the paperSubstantial claim - Interpretationreasoning
The TPL 5′UTR sequence contains apparently unique sequences that are associated with high ribosome loading.
“Therefore, these findings indicate that the TPL 5′UTR sequence contains apparently unique sequences that are associated with high ribosome loading.”
Quote in the paperSubstantial claim - Interpretationown data
The TPL sequence as a 5′UTR can significantly improve the effectiveness of mRNA therapeutics.
“Thus, the TPL sequence as a 5′UTR can significantly improve the effectiveness of mRNA therapeutics.”
Quote in the paperSubstantial claim - Interpretationown data
The selection of UTRs for translation efficiency in vitro and in silico can predict vaccine immunogenicity.
“Altogether, our findings suggest that the selection of UTRs for translation efficiency in vitro and in silico can predict vaccine immunogenicity.”
Quote in the paperSubstantial claim - Premisecitation
Binding of HNRNPH1 is associated with higher RNA stability.
“the binding of this RBP is associated with higher RNA stability [30].”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [30] Khan, 2021, HnRNP F and hnRNP H1 regulate mRNA stability of amyloid precursor protein, Neuroreport source
- Interpretationown data
Our study is the first to compare mRNA vaccines with various 5′UTRs.
“Our study is the first one to compare mRNA vaccines with various 5′UTRs; we have shown that use of TPL as a 5′UTR compared with the 5′UTR from mRNA-1273 evoked more pronounced protective adaptive immune responses in mice leading to higher preclinical efficacy of mRNA vaccines against tuberculosis.”
Quote in the paperSubstantial claim
- Classified as probably not a substantial claim. 33
- May combine two claims. 23
- The quote only partly states this claim. 1
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationMtRNR1 is mitochondrial noncoding 12S ribosomal RNA.
“MtRNR1 is mitochondrial noncoding 12S ribosomal RNA (rRNA) [18].”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites [18] Chinnery, 2013, Mitochondrial genetics, Br. Med. Bull. source
The mtDNA > Structure section identifies 12S rRNA as a mitochondrial gene product that is RNA rather than a protein. The Transcription and translation section names MTRNR1 as one of the mtDNA genes contributing to mitoribosomes, but our copy does not explicitly identify MTRNR1 as the 12S rRNA gene. (LLM, conf=0.78)
Experimental — accuracy not yet measured
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationTPL is a nucleotide sequence in the 5′UTR of adenovirus late mRNAs and has previously been thought to initiate translation of late adenoviral mRNAs in a cap-independent manner.
“TPL is a nucleotide sequence in the 5′UTR of adenovirus late mRNAs and has previously been thought to initiate translation of late adenoviral mRNAs in a cap-independent manner [15,36].”
Quote in the paperNot a substantial claim1 of 2 sources checked- cites [15] Kaufman, 1985, Identification of the components necessary for adenovirus translational control and their utilization in cDNA expression vectors, Proc. Natl. Acad. Sci. USA source
- cites [36] Logan, 1984, Adenovirus tripartite leader sequence enhances translation of mRNAs late after infection, Proc. Natl. Acad. Sci. USA source
The paper’s introductory passage identifies the tripartite leader as a 5′ nontranslated sequence shared by most late adenoviral mRNAs. The Discussion says it likely plays a role in translation initiation, but does not say that initiation is cap-independent; that mechanism is unsupported by this source. (LLM, conf=0.88)
Experimental — accuracy not yet measured
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationImmunization with an mRNA vaccine based on the full-length MPT83 antigen triggered production of specific antituberculosis antibodies.
“Immunization with an mRNA vaccine based on the full-length MPT83 antigen triggered production of specific antituberculosis antibodies [35].”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites [35] Xue, 2004, RNA encoding the MPT83 antigen induces protective immune responses against Mycobacterium tuberculosis infection, Infect. Immun. source
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe direction of the influence of an RBP on the stability and translation efficiency of RNA can depend on the cell type and on the target RNA, as exemplified by PCBP2.
“Nevertheless, it should be noted that the direction of the influence of an RBP on the stability and translation efficiency of RNA can depend on the cell type and on the target RNA, as exemplified by PCBP2: it can stabilize some mRNAs but promotes the degradation of other mRNAs [25,26,27].”
Quote in the paperNot a substantial claim3 of 3 sources checked- cites [25] Smirnova, 2019, eIF4G2 balances its own mRNA translation via a PCBP2-based feedback loop, RNA source
The Introduction says poly(rC)-binding proteins can stabilize or destabilize mRNAs, and the Conclusions show that PCBP2’s effects on translation differ by isoform and target RNA. But the paper does not establish that PCBP2 itself stabilizes some mRNAs and promotes degradation of others, or that the direction of its effect reverses by cell type. Its Results and Discussion instead report no significant stability differences among the reporters tested in Huh7 or 293T cells. (LLM, conf=0.84)
Experimental — accuracy not yet measured - cites [26] Han, 2013, RNA-binding protein PCBP2 modulates glioma growth by regulating FHL3, J. Clin. Investig. source
The results (section labeled “Conflict of interest”; page unavailable) show that PCBP2 knockdown prolonged FHL3 mRNA half-life in T98G glioma cells, supporting the claim that PCBP2 can promote degradation of a target mRNA. The paper also cites work on stabilization of other mRNAs, but its own experiments do not establish that the direction of PCBP2’s effect depends on cell type. (LLM, conf=0.82)
Experimental — accuracy not yet measured - cites [27] Ren, 2016, RNA-binding Protein PCBP2 Regulates p73 Expression and p73-dependent Antioxidant Defense, J. Biol. Chem. source
The Results section reports that loss of PCBP2 shortens p73 mRNA half-life in HCT116 and H1299 cells, supporting PCBP2 as an example of an RBP that stabilizes a target RNA. The paper also describes PCBP2 as regulating the stability and translation of several RNAs, but it does not show PCBP2 promoting degradation of another mRNA or reversing the direction of its effect by cell type. (LLM, conf=0.86)
Experimental — accuracy not yet measured
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationThere are at least two pathways (cap-dependent and cap-independent) that trigger translation through these elements, and the efficiency of triggering translation via these mechanisms depends on the cellular state.
“There are at least two pathways (cap-dependent and cap-independent) that trigger translation through these elements, and each pathway requires certain trans-acting proteins; the efficiency of the triggering of translation via these mechanisms depends on the cellular state [2].”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites [2] Pichon, 2012, RNA binding protein/RNA element interactions and the control of translation, Curr. Protein Pept. Sci. source
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationRBPs can compete for binding to microRNA, thereby having either synergistic or opposing effects on RNA stability.
“In addition, RBPs can compete for binding to microRNA, thereby having either synergistic or opposing effects on RNA stability [38,39,40].”
Quote in the paperNot a substantial claim2 of 3 sources checked- cites [38] Orom, 2008, MicroRNA-10a binds the 5’UTR of ribosomal protein mRNAs and enhances their translation, Mol. Cell source
The Discussion (page not available) speculates that miR-10a competes with an unidentified negative regulator near the 5′TOP motif, which gives limited support for competition involving a microRNA. It does not identify that regulator as an RBP or report synergistic or opposing effects on RNA stability. The Results instead say RP mRNA levels were unaffected and describe predominantly translational regulation. (LLM, conf=0.84)
Experimental — accuracy not yet measured - cites [39] Peng, 2012, Functional Interactions Between microRNAs and RNA Binding Proteins, MicroRNA source
The Introduction says RBPs and miRNAs can act synergistically or oppose each other in transcript decay. The section ‘Competition for the Same Binding Position’ describes competition for sites on target mRNAs as antagonistic, not competition for binding to the microRNA itself or competition that produces synergy. Page numbers are unavailable in our copy. (LLM, conf=0.88)
Experimental — accuracy not yet measured - cites [40] Palanisamy, 2012, Control of cytokine mRNA expression by RNA-binding proteins and microRNAs, J. Dent. Res. source
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationIn the 5′UTR portions, among the specific sequences that affect translation efficiency, there are the TOP sequence, IRESs, CITEs, uORFs, and protein-binding motifs.
“In the 5′UTR portions, among the specific sequences that affect translation efficiency, there are the terminal oligopyrimidine tract (TOP) sequence, consisting of 7–14 residues of cytosine and thymine forming a TCT motif; internal ribosome entry sites (IRESs); cap-independent translation enhancers (CITEs); upstream open reading frames (uORFs); and protein-binding motifs [2].”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites [2] Pichon, 2012, RNA binding protein/RNA element interactions and the control of translation, Curr. Protein Pept. Sci. source
The Introduction identifies TOP motifs, IRESs and uORFs in the 5′ UTR as elements that influence translation, and the TOP section describes a cytosine followed by a 7–14-residue oligopyrimidine tract. The paper also discusses proteins binding 5′-UTR elements, but the passages do not identify CITEs. The TOP section says a TCT motif is required for transcription of most of these mRNAs; it does not say the oligopyrimidine tract forms that motif. Page numbers were not available in our copy. (LLM, conf=0.87)
Experimental — accuracy not yet measured
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationAES regulates androgen receptor genes' transcriptional activity and Notch and Wnt signaling, and acts as a tumor suppressor.
“AES is a distinct member of the family of Groucho/Transducin-like enhancers of split genes; it regulates androgen receptor genes’ transcriptional activity and Notch and Wnt signaling, and acts as a tumor suppressor [19].”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites [19] Costa, A.M., Pereira-Castro, I., Ricardo, E., Spencer, F., Fisher, S., and da Costa, L.T. (2013). GRG5/AES interacts with T-cell factor 4 (TCF4) and downregulates Wnt signaling in human cells and zebrafish embryos. PLoS ONE, 8. source
The Introduction (page unavailable) identifies GRG5/AES as a distinct short Groucho family member, and the Results (page unavailable) show that it downregulates Wnt/β-catenin signaling. The paper also cites a study of AES inhibition of androgen receptor-mediated transcription (References, page unavailable). The passages found do not establish that AES regulates Notch signaling or acts as a tumor suppressor; the tumor-suppressor references concern APC, not AES. (LLM, conf=0.88)
Experimental — accuracy not yet measured
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe dynamic association of RBPs with mRNA monitors the localization of mRNA, including its movements between actively translating ribosomes, stress granules, and p bodies in a context-dependent manner.
“Furthermore, the dynamic association of RBPs with mRNA monitors the localization of mRNA, in particular its movements between actively translating ribosomes, stress granules, and p bodies in a context-dependent manner [42].”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites [42] Bourke, 2023, De-centralizing the Central Dogma: mRNA translation in space and time, Mol. Cell source
The ‘Ingredients and mechanisms for local translation’ section (page not provided) says that dynamic RBP–mRNA association regulates mRNA transport and translation, and that RBP-dependent localization is context-dependent. It identifies stress granules and P-bodies as associated with translationally repressed mRNA, but does not describe RBP association monitoring mRNA movements between those granules and actively translating ribosomes. (LLM, conf=0.85)
Experimental — accuracy not yet measured
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductcitationThe predictive model (Optimus 5-Prime) was tested only for 5′UTR sequences up to 100 bp in length.
“It is worth noting that the predictive model in question was tested only for 5′UTR sequences up to 100 bp in length.”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites [37] Sample, 2019, Human 5’ UTR design and variant effect prediction from a massively parallel translation assay, Nat. Biotechnol. source
May combine two claims.
Findingown dataAES-HBB and mtRNR-HBB as 3′UTR yielded the lowest luciferase levels compared with AES-AES and mtRNR-mtRNR at 8 h, compared with AES-EMCV at 8 and 24 h, and compared with mRNA-1273 3′UTR at 24 and 72 h in DC2.4 cells.
“Sequences AES-HBB and mtRNR-HBB, when used as the 3′UTR in Luc RNA, yielded the lowest level of luciferase (i) as compared with 3′UTR sequences AES-AES and mtRNR-mtRNR at 8 h after the transfection (p < 0.05), (ii) as compared with 3′UTR sequence AES-EMCV at 8 and 24 h after the transfection (p < 0.05), and (iii) as compared with the 3′UTR from mRNA-1273 at 24 an 72 h after the transfection.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataMice immunized with 5′-mRNA1273-mEpitope-mRNA1273-3′ exhibited a >1.5-fold lower bacterial load compared with control groups, but the differences were statistically insignificant (p > 0.05).
“Mice immunized with mRNA vaccine 5′-mRNA1273-mEpitope-mRNA1273-3′ also exhibited a >1.5-fold lower bacterial load as compared with the control groups, but the differences were statistically insignificant (p > 0.05).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataZeta potential was in the range −0.22 to −0.37 mV.
“Zeta potential was in the range −0.22 to −0.37 mV.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataThe mRNA vaccine containing mRNA-1273 5′UTR produced a numerically larger number of IFNγ-secreting cells compared with control or LNP groups, but the differences were not significant.
“As for the mRNA vaccine containing the mRNA-1273 5′UTR, the respective experimental group had a numerically larger number of IFNγ-secreting cells compared with the control group (5.6 ± 0.7 vs. 1.3 ± 0.6) or the LNP group (5.6 ± 0.7 vs. 1.0 ± 0.4), but these differences were not significant.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataParticle size was 80 to 90 nm.
“Particle size proved to be 80 to 90 nm”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataOnly the 3′UTR sequences mtRNR-mtRNR and mRNA-1273, both of which produced the best results, contain a predicted binding site for HNRNPK, which is associated with stabilization of mRNA.
“Regarding 3′UTRs, only the sequence mtRNR-mtRNR and the mRNA-1273 3′UTR, both of which produced the best results, contain a predicted binding site for an RBP, HNRNPK, which is associated with the stabilization of mRNA.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataThe area of target peaks of RNA in capillary electropherograms exceeded 85% of the total RNA.
“The area of target peaks of RNA in capillary electropherograms exceeded 85% of the total RNA.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataTPL does not function as an internal ribosome entry site.
“Furthermore, although it is currently unclear whether the TPL sequence is capable of initiating translation in a cap-independent manner, evidence from our research group suggests that TPL does not function as an internal ribosome entry site (unpublished data).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataThree of the top five UTRs (from HBB, Rabb, and H4C2 mRNAs) do not have RBP-binding sites, and TPL and HSPA1A carry binding sites for RBPs whose influence on RNA stability is not clear.
“Of note, three of the top five UTRs (from HBB, Rabb, and H4C2 mRNAs) do not have RBP-binding sites, and the other two (TPL and HSPA1A) carry binding sites for the RBPs whose influence on RNA stability is not clear.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataThe polydispersity index was less than 0.15.
“and the polydispersity index was less than 0.15.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationThe 5′UTR of rabbit β-globin mRNA is thought to mediate efficient cap-dependent translation and does not contain secondary structures or sequence elements that may negatively affect translation.
“The 5′UTR of rabbit β-globin mRNA is thought to mediate efficient cap-dependent translation and does not contain any secondary structures or sequence elements that may negatively affect translation [10].”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [10] Kozak, 1994, Features in the 5’ non-coding sequences of rabbit alpha and beta-globin mRNAs that affect translational efficiency, J. Mol. Biol. source
Probably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation3′UTR AU-rich elements can determine the rate of mRNA decay under various conditions.
“3′UTR AU-rich elements can determine the rate of mRNA decay under various conditions [1,8].”
Quote in the paperNot a substantial claim0 of 2 sources checkedMay combine two claims.
PremisecitationSample et al. demonstrated that MRL values range from two to 11; among the highest MRLs, only in the range six-eight was there a high correlation (r2 = 0.77) between predicted and observed values.
“On the basis of 280,000 different 5′UTR sequences, the Sample et al. [37] study demonstrated that MRL values range from two to 11; however, among the highest MRLs, only in the range six–eight was there a high correlation (r2 = 0.77) between the predicted and observed values.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [37] Sample, 2019, Human 5’ UTR design and variant effect prediction from a massively parallel translation assay, Nat. Biotechnol. source
Not checked in the free run.
May combine two claims.
InterpretationcitationThe contribution of cap-independent translation initiation to our results appears negligible because the theoretical amount of capped RNA was ~80% and cap-independent translation plays a major role only during periods of cellular stress, apoptosis, and certain stages of the cell cycle.
“Nonetheless, the contribution of this alternative mechanism of translation initiation to our results appears to be negligible because the theoretical amount of capped RNA was ~80%, and cap-independent translation plays a major role only during periods of cellular stress, apoptosis, and certain stages of the cell cycle [2].”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [2] Pichon, 2012, RNA binding protein/RNA element interactions and the control of translation, Curr. Protein Pept. Sci. source
Checked before — its earlier verdict is held back until a new check runs.
May combine two claims. The quote only partly states this claim.
Interpretationown dataThe 5′-TPL-mEpitope-mRNA1273-3′ vaccine induced stronger adaptive immunity and protection against M. tuberculosis than the mRNA-1273 5′UTR vaccine.
“Taken together, our results indicate that the 5′-TPL-mEpitope-mRNA1273-3′ vaccine induced stronger adaptive immunity and protection against M. tuberculosis.”
Quote in the paperSubstantial claimMay combine two claims.
Interpretationown dataUse of TPL as a 5′UTR compared with the 5′UTR from mRNA-1273 evoked more pronounced protective adaptive immune responses in mice, leading to higher preclinical efficacy of mRNA vaccines against tuberculosis.
“Our study is the first one to compare mRNA vaccines with various 5′UTRs; we have shown that use of TPL as a 5′UTR compared with the 5′UTR from mRNA-1273 evoked more pronounced protective adaptive immune responses in mice leading to higher preclinical efficacy of mRNA vaccines against tuberculosis.”
Quote in the paperSubstantial claimMay combine two claims.
PremisecitationmRNA therapeutics require optimization of mRNA sequences because their effectiveness primarily depends on the rate of degradation and the rate of translation initiation.
“Nevertheless, mRNA therapeutics require the optimization of mRNA sequences because their effectiveness primarily depends on the rate of degradation (and the rate of translation initiation) of mRNA [1,2].”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [1] Garneau, 2007, The highways and byways of mRNA decay, Nat. Rev. Mol. Cell Biol. source
- cites [2] Pichon, 2012, RNA binding protein/RNA element interactions and the control of translation, Curr. Protein Pept. Sci. source
Checked before — its earlier verdict is held back until a new check runs.
Classified as probably not a substantial claim. May combine two claims.
PremisecitationC57BL/6Cit and I/StSnEgYCit mice are extremely susceptible to tuberculosis.
“C57BL/6Cit and I/StSnEgYCit mice, which are extremely susceptible to tuberculosis [33].”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [33] Radaeva, 2005, Direct comparison of low-dose and Cornell-like models of chronic and reactivation tuberculosis in genetically susceptible I/St and resistant B6 mice, Tuberculosis source
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductnone givenThe transfection procedures and bioluminescence assessment for each construct were performed in 4-6 biological replicates, with 3 technical repetitions for each.
“The transfection procedures and bioluminescence assessment for each construct were performed in 4–6 biological replicates (with 3 technical repetitions for each).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationAdenovirus TPL can enhance protein expression by enhancing translation initiation.
“Some regulatory elements, such as adenovirus TPL (tripartite leader), can enhance protein expression by enhancing translation initiation [15].”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [15] Kaufman, 1985, Identification of the components necessary for adenovirus translational control and their utilization in cDNA expression vectors, Proc. Natl. Acad. Sci. USA source
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationGlobin gene sequences are often used to ensure high translation efficiency.
“Globin gene sequences are often used to ensure high translation efficiency.”
Quote in the paperNot a substantial claim0 of 3 sources checked- cites [9] Babendure, 2006, Control of mammalian translation by mRNA structure near caps, RNA source
Checked before — its earlier verdict is held back until a new check runs.
- cites [10] Kozak, 1994, Features in the 5’ non-coding sequences of rabbit alpha and beta-globin mRNAs that affect translational efficiency, J. Mol. Biol. source
- cites [11] Annweiler, 1991, A strategy for efficient in vitro translation of cDNAs using the rabbit beta-globin leader sequence, Nucleic Acids Res. source
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationAnother mRNA vaccine contains four full-length tuberculosis antigens fused with a synthetic TLR4 agonist.
“Another mRNA vaccine contains four full-length tuberculosis antigens fused with a synthetic TLR4 agonist [34].”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [34] Larsen, S.E., Erasmus, J.H., Reese, V.A., Pecor, T., Archer, J., Kandahar, A., Hsu, F.C., Nicholes, K., Reed, S.G., and Baldwin, S.L. (2023). An RNA-Based Vaccine Platform for Use against Mycobacterium tuberculosis. Vaccines, 11. source
Checked before — its earlier verdict is held back until a new check runs.
May combine two claims.
Interpretationnone givenThe function of PABPC3 and RBM22 is related to ensuring the stability of the poly(A) tail or regulation of alternative splicing and plays a negligible role in the translation of heterologous RNAs.
“however, the function of these RBPs is related to either ensuring the stability of the poly(A) tail or regulation of alternative splicing and plays a negligible role in the translation of heterologous RNAs.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationRBPs monitor mRNA stability and decay and control the correct translation of mRNA.
“RBPs monitor mRNA stability and decay and control the correct translation of mRNA.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [42] Bourke, 2023, De-centralizing the Central Dogma: mRNA translation in space and time, Mol. Cell source
Checked before — its earlier verdict is held back until a new check runs.
Classified as probably not a substantial claim.
Study design and conductnone givenAll obtained data were not normally distributed.
“All obtained data were not normally distributed, and therefore we chose nonparametric analysis.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationThe transport function of RBPs can be mediated either by their direct binding to motor proteins or indirectly through motor protein cargo adaptors.
“The transport function of RBPs can be mediated either by their direct binding to motor proteins or, indirectly, through motor protein cargo adaptors [42].”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [42] Bourke, 2023, De-centralizing the Central Dogma: mRNA translation in space and time, Mol. Cell source
Checked before — its earlier verdict is held back until a new check runs.
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenBioluminescence data from firefly luciferase were normalized to the bioluminescence of NanoLuc luciferase, which served as an internal control.
“Bioluminescence data from firefly luciferase were normalized to the bioluminescence of NanoLuc luciferase, which served as an internal control.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown dataThe desired length and homogeneity of the synthesized RNA molecules were verified by capillary electrophoresis.
“The desired length and homogeneity of the synthesized RNA molecules were verified by capillary electrophoresis on a TapeStation instrument (Agilent Technologies, Santa Clara, CA, USA).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationEffects of many RBPs on translation are yet to be identified.
“Nonetheless, effects of many RBPs on translation are yet to be identified [41].”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [41] Gerstberger, 2014, A census of human RNA-binding proteins, Nat. Rev. Genet. source
Checked before — its earlier verdict is held back until a new check runs.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationOrlandini von Niessen et al. showed that 3′UTRs containing mtRNR1 and AES promote the expression of the upstream gene.
“They showed that 3′UTRs containing mtRNR1 and AES promote the expression of the upstream gene.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [17] Poleganov, 2019, Improving mRNA-Based Therapeutic Gene Delivery by Expression-Augmenting 3’ UTRs Identified by Cellular Library Screening, Mol. Ther. J. Am. Soc. Gene Ther. source
May combine two claims.
InterpretationreasoningA direct relation between the presence of an RBP landing site and RNA stability was difficult to discern because some RBPs stabilize RNA, some destabilize it, and others regulate RNA stability in a context-dependent manner.
“Nonetheless, a direct relation between the presence of a landing site and the RNA stability was difficult to discern because some RBPs stabilize RNA, some destabilize it, and other RBPs can regulate RNA stability in a context-dependent manner, as is the case for PCBP2 (Table 2).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisereasoningRegulatory sequences of constitutively expressed genes are often used to enhance the translation efficiency of heterologous mRNAs.
“To sum up the data on natural 5′UTRs, one can conclude that regulatory sequences of constitutively expressed genes are often used to enhance the translation efficiency of heterologous mRNAs.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationThe effect of HSP70 5′UTR has been observed in several cell lines, indicating that this effect is not cell type specific.
“The effect of HSP70 5′UTR has been observed in several cell lines [14], indicating that this effect is not cell type specific.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [14] Vivinus, 2001, An element within the 5’ untranslated region of human Hsp70 mRNA which acts as a general enhancer of mRNA translation, Eur. J. Biochem. source
Checked before — its earlier verdict is held back until a new check runs.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationTPL contains an internal ribosome entry site enabling it to recruit a ribosome independently of interactions with the mRNA 5′ 7-methyl G cap.
“TPL contains an internal ribosome entry site enabling it to recruit a ribosome independently of interactions with the mRNA 5′ 7-methyl G cap.”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [15] Kaufman, 1985, Identification of the components necessary for adenovirus translational control and their utilization in cDNA expression vectors, Proc. Natl. Acad. Sci. USA source
- cites [36] Logan, 1984, Adenovirus tripartite leader sequence enhances translation of mRNAs late after infection, Proc. Natl. Acad. Sci. USA source
Checked before — its earlier verdict is held back until a new check runs.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductnone givenCells without stimulation or stimulated with concanavalin A served as negative and positive controls in the ELISpot procedure.
“Cells without the stimulation or stimulated with concanavalin A (Sigma-Aldrich, Darmstadt, Germany) at a dose of 5 μg/mL served, respectively, as negative and positive controls in the ELISpot procedure.”
Quote in the paperNot a substantial claim
The paper relies on this without support.
The 3′UTR is primarily responsible for RNA stability in the cell and prevents RNA degradation mediated by binding to microRNA.
“Because the 3′UTR is primarily responsible for RNA stability in the cell and prevents the RNA degradation mediated by binding to microRNA, our findings implied that 3′UTR sequences AES-HBB and mtRNR-HBB within mRNA lead to a decrease in its stability.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In mRNA vaccines, use of different 5′ UTR sequences can substantially enhance immunological properties, including increased antibody titers and improved T-cell responses.
“In the setting of mRNA vaccines, the use of different 5′ UTR sequences can substantially enhance immunological properties, including increased antibody titers and improved T-cell responses [18,19].”
From Identification of novel 5’ UTR variants for enhanced mRNA translation and vaccine immunogenicity (2026) · cites this paper as [18]
Results §2.5 reports that a tuberculosis mRNA vaccine with the TPL 5′ UTR produced more than twice as many IFNγ-secreting cells in immunized mice as one with the mRNA-1273 5′ UTR, supporting the T-cell-response portion. The paper does not report increased antibody titers from changing 5′ UTRs; the antibody finding mentioned in Discussion §3 concerns a different study. (LLM, conf=0.88)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Kruskal-Wallis statistic exceeds its maximum for 66 observations
MajorFor N = 66, the Kruskal-Wallis H statistic cannot exceed N − 1 = 65, including with a tie correction. The reported H of 85.2 is therefore impossible for the stated sample size.
Reported 85.2 · recomputed 65
“[Kruskal–Wallis test: H (11, N = 66) = 85.2, p < 0.0001]”
THP1 5′UTR effect is both reported and denied
MajorThe abstract says no effect of the tested UTRs was detectable in THP1 cells, but the results report a significant 5′UTR effect there at 24 hours.
“By contrast, no effects of various 5′UTRs and 3′UTRs were detectable in THP1 cells”
“in human monocyte cell line THP1 at 24 h after transfection [Kruskal–Wallis test H (11, N = 60) = 31.05, p = 0.001; Figure 2]”
Discussion denies reported 3′UTR differences
MajorThe discussion says there were no significant differences among tested 3′UTRs, whereas the results report a significant 3′UTR effect in DC2.4 cells at three time points.
“Unexpectedly, there were no significant differences between the 3′UTR sequences tested in our cell-based assay”
“an effect of the 3′UTR on luciferase levels was registered 8, 24, and 72 h after the transfection of DC2.4 cells [Kruskal–Wallis test 8 h: H (11, N = 66) = 38.37, p < 0.001; 24 h: H (11, N = 66) = 38.49, p < 0.001; and 72 h: H (11, N = 66) = 30.49, p = 0.001]”
Cites
featureCounts: an efficient general purpose program for assigning sequence reads to genomic features
Liao, Y., Smyth, G. K., & Shi, W. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btt656 · Cited by 27,219 · see citing works
Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype
Kim, D., Paggi, J. M., Park, C., Bennett, C., & Salzberg, S. L. (2019) · Nature Biotechnology · doi:10.1038/s41587-019-0201-4 · Cited by 15,022 · see citing works
Lorenz, R., Bernhart, S. H., Höner zu Siederdissen, C., Tafer, H., Flamm, C., Stadler, P. F., & Hofacker, I. L. (2011) · Algorithms for Molecular Biology · doi:10.1186/1748-7188-6-26 · Cited by 5,098 · see citing works
A census of human RNA-binding proteins
Gerstberger, S., Hafner, M., & Tuschl, T. (2014) · Nature Reviews Genetics · doi:10.1038/nrg3813 · Cited by 2,032 · see citing works
MicroRNA-10a binds the 5’UTR of ribosomal protein mRNAs and enhances their translation
Ørom, U. A., Nielsen, F. C., & Lund, A. H. (2008) · Molecular Cell · doi:10.1016/j.molcel.2008.05.001 · Cited by 1,384 · see citing works
The highways and byways of mRNA decay
Garneau, N. L., Wilusz, J., & Wilusz, C. J. (2007) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm2104 · Cited by 1,294 · see citing works
Developing mRNA-vaccine technologies
Schlake, T., Thess, A., Fotin-Mleczek, M., & Kallen, K.-J. (2012) · RNA Biology · doi:10.4161/rna.22269 · Cited by 622 · see citing works
Sidrauski, C., McGeachy, A. M., Ingolia, N. T., & Walter, P. (2015) · eLife · doi:10.7554/elife.05033 · Cited by 616 · see citing works
Regulation by 3′-Untranslated Regions
Mayr, C. (2017) · Annual Review of Genetics · doi:10.1146/annurev-genet-120116-024704 · Cited by 588 · see citing works
RBPmap: a web server for mapping binding sites of RNA-binding proteins
Paz, I., Kosti, I., Ares, M., Cline, M., & Mandel‐Gutfreund, Y. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku406 · Cited by 572 · see citing works
Human 5′ UTR design and variant effect prediction from a massively parallel translation assay
Sample, P. J., Wang, B., Reid, D. W., Presnyak, V., McFadyen, I. J., Morris, D. R., & Seelig, G. (2019) · Nature Biotechnology · doi:10.1038/s41587-019-0164-5 · Cited by 442 · see citing works
Combinatorial optimization of mRNA structure, stability, and translation for RNA-based therapeutics
Leppek, K., Byeon, G. W., Kladwang, W., Wayment-Steele, H. K., Kerr, C. H., Xu, A. F., Kim, D. S., Topkar, V. V., Choe, C., Rothschild, D., et al. (2021) · doi:10.1101/2021.03.29.437587 · Cited by 399 · see citing works
Combinatorial optimization of mRNA structure, stability, and translation for RNA-based therapeutics
Leppek, K., Byeon, G. W., Kladwang, W., Wayment-Steele, H. K., Kerr, C. H., Xu, A. F., Kim, D. S., Topkar, V. V., Choe, C., Rothschild, D., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-28776-w · Cited by 399 · see citing works
Chinnery, P. F., & Hudson, G. (2013) · British Medical Bulletin · doi:10.1093/bmb/ldt017 · Cited by 395 · see citing works
Tailoring mRNA Vaccine to Balance Innate/Adaptive Immune Response
Linares-Fernández, S., Lacroix, C., Exposito, J.-Y., & Verrier, B. (2020) · Trends in Molecular Medicine · doi:10.1016/j.molmed.2019.10.002 · Cited by 376 · see citing works
mRNA Vaccine Era—Mechanisms, Drug Platform and Clinical Prospection
Xu, S., Yang, K., Li, R., & Zhang, L. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21186582 · Cited by 368 · see citing works
Orlandini von Niessen, A. G., Poleganov, M. A., Rechner, C., Plaschke, A., Kranz, L. M., Fesser, S., Diken, M., Löwer, M., Vallazza, B., Beissert, T., et al. (2019) · Molecular Therapy · doi:10.1016/j.ymthe.2018.12.011 · Cited by 365 · see citing works
Control of mammalian translation by mRNA structure near caps
Babendure, J. R., Babendure, J. L., Ding, J.-H., & Tsien, R. Y. (2006) · RNA · doi:10.1261/rna.2309906 · Cited by 339 · see citing works
Kim, S. C., Sekhon, S. S., Shin, W.-R., Ahn, G., Cho, B.-K., Ahn, J.-Y., & Kim, Y.-H. (2022) · Molecular & Cellular Toxicology · doi:10.1007/s13273-021-00171-4 · Cited by 255 · see citing works
Adenovirus tripartite leader sequence enhances translation of mRNAs late after infection
Logan, J., & Shenk, T. (1984) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.81.12.3655 · Cited by 198 · see citing works
CUGBP1 and MBNL1 preferentially bind to 3′ UTRs and facilitate mRNA decay
Masuda, A., Andersen, H. S., Doktor, T. K., Okamoto, T., Ito, M., Andresen, B. S., & Ohno, K. (2012) · Scientific Reports · doi:10.1038/srep00209 · Cited by 174 · see citing works
High-throughput 5’ UTR engineering for enhanced protein production in non-viral gene therapies
Cao, J., Novoa, E. M., Zhang, Z., Chen, W. C. W., Liu, D., Choi, G. C. G., Wong, A. S. L., Wehrspaun, C., Kellis, M., & Lu, T. K. (2021) · Nature Communications · doi:10.1038/s41467-021-24436-7 · Cited by 159 · see citing works
FUS regulates AMPA receptor function and FTLD/ALS-associated behaviour via GluA1 mRNA stabilization
Udagawa, T., Fujioka, Y., Tanaka, M., Honda, D., Yokoi, S., Riku, Y., Ibi, D., Nagai, T., Yamada, K., Watanabe, H., et al. (2015) · Nature Communications · doi:10.1038/ncomms8098 · Cited by 154 · see citing works
RNA binding protein/RNA element interactions and the control of translation
Pichon, X., A. Wilson, L., Stoneley, M., Bastide, A., A King, H., Somers, J., & E Willis, A. (2012) · Current Protein & Peptide Science · doi:10.2174/138920312801619475 · Cited by 144 · see citing works
Kaufman, R. J. (1985) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.82.3.689 · Cited by 135 · see citing works
Abou-Zeid, C., Gares, M., Inwald, J. K., Janssen, R., Zhang, Y., Young, D., Hetzel, C., Lamb, J. R., Baldwin, S. L., Orme, I. M., et al. (1997) · Infection and Immunity · doi:10.1128/iai.65.5.1856-1862.1997 · Cited by 126 · see citing works
Self-citationControl of cytokine mRNA expression by RNA-binding proteins and microRNAs
Palanisamy, V., Jakymiw, A., Van Tubergen, E. A., D’Silva, N. J., & Kirkwood, K. L. (2012) · Journal of Dental Research · doi:10.1177/0022034512437372 · Cited by 117 · see citing works
STAR RNA-binding protein Quaking suppresses cancer via stabilization of specific miRNAPreprint
Chen, A.-J., Paik, J.-H., Zhang, H., Shukla, S. A., Mortensen, R., HU, J. L., Ying, H., Hu, B., Hurt, J. A., Farny, N. G., et al. (2012) · Genes & Development · doi:10.1101/gad.189001.112 · Cited by 111 · see citing works
RNA-binding protein PCBP2 modulates glioma growth by regulating FHL3
Han, W., Xin, Z., Zhao, Z., Bao, W., Lin, X., Yin, B., Zhao, J., Yuan, J., Qiang, B., & Peng, X. (2013) · Journal of Clinical Investigation · doi:10.1172/jci61820 · Cited by 108 · see citing works
De-centralizing the Central Dogma: mRNA translation in space and time
Bourke, A. M., Schwarz, A., & Schuman, E. M. (2023) · Molecular Cell · doi:10.1016/j.molcel.2022.12.030 · Cited by 106 · see citing works
Kozak, M. (1994) · Journal of Molecular Biology · doi:10.1016/s0022-2836(05)80019-1 · Cited by 101 · see citing works
Distinctive Properties of the 5′-Untranslated Region of Human Hsp70 mRNA
Rubtsova, M. P., Sizova, D. V., Dmitriev, S. E., Ivanov, D. S., Prassolov, V. S., & Shatsky, I. N. (2003) · Journal of Biological Chemistry · doi:10.1074/jbc.m303213200 · Cited by 100 · see citing works
Yokoi, S., Udagawa, T., Fujioka, Y., Honda, D., Okado, H., Watanabe, H., Katsuno, M., Ishigaki, S., & Sobue, G. (2017) · Cell Reports · doi:10.1016/j.celrep.2017.08.100 · Cited by 96 · see citing works
Xue, T., Stavropoulos, E., Yang, M., Ragno, S., Vordermeier, M., Chambers, M., Hewinson, G., Lowrie, D. B., Colston, M. J., & Tascon, R. E. (2004) · Infection and Immunity · doi:10.1128/iai.72.11.6324-6329.2004 · Cited by 73 · see citing works
A computational approach for genome-wide mapping of splicing factor binding sites
Akerman, M., David-Eden, H., Pinter, R. Y., & Mandel‐Gutfreund, Y. (2009) · Genome biology · doi:10.1186/gb-2009-10-3-r30 · Cited by 73 · see citing works
Scoumanne, A., Cho, S. J., Zhang, J., & Chen, X. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq778 · Cited by 73 · see citing works
Vivinus, S., Baulande, S., van Zanten, M., Campbell, F., Topley, P., Ellis, J. H., Dessen, P., & Coste, H. (2001) · European Journal of Biochemistry · doi:10.1046/j.1432-1327.2001.02064.x · Cited by 67 · see citing works
An RNA-Based Vaccine Platform for Use against Mycobacterium tuberculosis
Larsen, S. E., Erasmus, J. H., Reese, V. A., Pecor, T., Archer, J., Kandahar, A., Hsu, F.-C., Nicholes, K., Reed, S. G., Baldwin, S. L., et al. (2023) · Vaccines · doi:10.3390/vaccines11010130 · Cited by 66 · see citing works
Annweiler, A., Hipskind, R. A., & Wirth, T. (1991) · Nucleic Acids Research · doi:10.1093/nar/19.13.3750 · Cited by 65 · see citing works
Morris, T., Marashi, F., Weber, L. E., Hickey, E. D., Greenspan, D. S., Bonner, J., Stein, J. L., & Stein, G. S. (1986) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.83.4.981 · Cited by 63 · see citing works
Functional Interactions Between microRNAs and RNA Binding Proteins
Jiang, P., & Coller, H. (2012) · MicroRNA e · doi:10.2174/2211536611201010070 · Cited by 62 · see citing works
Dai, J., Zhang, C., Guo, L., He, H., Jiang, K., Huang, Y., Zhang, X., Zhang, H., Wu, W., Zhang, Y., et al. (2020) · Cell Death and Disease · doi:10.1038/s41419-020-2483-3 · Cited by 46 · see citing works
Cytotoxicity and Immune Dysfunction of Dendritic Cells Caused by Graphene Oxide
Yang, Z., Pan, Y., Chen, T., Li, L., Zou, W., Liu, D., Xue, D., Wang, X., & Lin, G. (2020) · Frontiers in Pharmacology · doi:10.3389/fphar.2020.01206 · Cited by 46 · see citing works
CLOCK regulates Drp1 mRNA stability and mitochondrial homeostasis by interacting with PUF60
Xu, L., Lin, J., Liu, Y., Hua, B., Cheng, Q., Lin, C., Yan, Z., Wang, Y.-P., Sun, N., Qian, R., et al. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.110635 · Cited by 42 · see citing works
Radaeva, T. V., Nikonenko, B. V., Mischenko, V. V., Averbakh, M. M., & Apt, A. S. (2005) · Tuberculosis · doi:10.1016/j.tube.2004.09.014 · Cited by 36 · see citing works
Dai, X., Jiang, Y., Gu, J., Jiang, Z., Wu, Y., Yu, C. Y., Yin, H., Zhang, J., Shi, Q., Shen, L., et al. (2021) · Advanced Science · doi:10.1002/advs.202003636 · Cited by 33 · see citing works
RNA-binding Protein PCBP2 Regulates p73 Expression and p73-dependent Antioxidant Defense
Ren, C., Zhang, J., Yan, W., Zhang, Y., & Chen, X. (2016) · Journal of Biological Chemistry · doi:10.1074/jbc.m115.712125 · Cited by 29 · see citing works
Effects of Combinations of Untranslated-Region Sequences on Translation of mRNA
Kirshina, A., Vasileva, O., Kunyk, D., Seregina, K., Muslimov, A., Ivanov, R., & Reshetnikov, V. (2023) · Biomolecules · doi:10.3390/biom13111677 · Cited by 26 · see citing works
Self-citationeIF4G2 balances its own mRNA translation via a PCBP2-based feedback loop
Smirnova, V. V., Shestakova, E. D., Bikmetov, D. V., Chugunova, A. A., Osterman, I. A., Serebryakova, M. V., Sergeeva, O. V., Zatsepin, T. S., Shatsky, I. N., & Terenin, I. M. (2019) · RNA · doi:10.1261/rna.065623.118 · Cited by 19 · see citing works
Self-citationEffects of various mRNA-LNP vaccine doses on neuroinflammation in BALB/c mice
Kirshina, A., Kazakova, A., Kolosova, E., Имашева, Е. А., Vasileva, O., Zaborova, O. V., Terenin, I. M., Muslimov, A., & Reshetnikov, V. V. (2022) · Bulletin of Russian State Medical University · doi:10.24075/brsmu.2022.068 · Cited by 15 · see citing works
Self-citationCosta, Â. M. S., Pereira-Castro, I., Ricardo, E., Spencer, F., Fisher, S., & Costa, L. T. D. (2013) · PLoS ONE · doi:10.1371/journal.pone.0067694 · Cited by 13 · see citing works
Васильева, О. О., Tereshchenko, V., Крапивин, Б. Н., Muslimov, A., Kukushkin, I. M., Pateev, I., Rybtsov, S. A., Ivanov, R. A., & Reshetnikov, V. V. (2023) · Bulletin of Russian State Medical University · doi:10.24075/brsmu.2023.021 · Cited by 13 · see citing works
Self-citationHnRNP F and hnRNP H1 regulate mRNA stability of amyloid precursor protein
Khan, M. I., Zhang, J., & Liu, Q. (2021) · NeuroReport · doi:10.1097/wnr.0000000000001662 · Cited by 12 · see citing works
Hypoxia-Induced Reporter Genes with Different Half-Lives
Krishnamachary, B., Danhier, P., Kakkad, S., Bharti, S. K., & Bhujwalla, Z. M. (2018) · Methods in Molecular Biology · doi:10.1007/978-1-4939-7860-1_9 · Cited by 4 · see citing works
Авдиенко, В. Г., Ss, B., An, G., Kondratiuk, N. A., Rusakova, L. I., Mm, A., & Gergert, V. I. (2006) · PubMed · Cited by 2 · see citing works
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Lukeman, H., Al-Wassiti, H. A., Fabb, S. A., Lim, L., Wang, T., Britton, W. J., Steain, M. C., Pouton, C. W., Triccas, J. A., & Counoupas, C. (2025) · EBioMedicine · doi:10.1016/j.ebiom.2025.105599 · Cited by 36 · see citing works
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Kazakova, A., Zhelnov, P., Sidorov, R. Y., Rogova, A. S., Vasileva, O., Ivanov, R. A., Reshetnikov, V. V., & Muslimov, A. R. (2024) · Frontiers in Immunology · doi:10.3389/fimmu.2024.1457327 · Cited by 20 · see citing works
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Shahid, U. (2025) · The Journal of Precision Medicine Health and Disease · doi:10.1016/j.premed.2025.100016 · Cited by 17 · see citing works
Kozlova, A., Pateev, I., Сергеевна, Ш. Г., Васильева, О. В., Zakharova, N. A., Yeremeev, V., Ivanov, R. A., & Reshetnikov, V. V. (2024) · Vaccines · doi:10.3390/vaccines12111267 · Cited by 16 · see citing works
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Zhou, H., Wei, D., Chen, Z., Chen, H., Dong, C., Cai, W., Wang, J., Liu, X., Li, Y., Yang, Y., et al. (2026) · Nano-Micro Letters · doi:10.1007/s40820-025-01906-x · Cited by 14 · see citing works
Sira, E. M. J. S., Fajardo, L. E., Banico, E. C., Odchimar, N. M. O., & Orosco, F. L. (2025) · Veterinary Medicine International · doi:10.1155/vmi/2638167 · Cited by 9 · see citing works
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Rezk, N., & McClean, S. (2025) · Microbial Biotechnology · doi:10.1111/1751-7915.70212 · Cited by 8 · see citing works
Suneesh, N. S., Dhotre, K., Mahajan, P., Dass, D., Banerjee, A., Siddiqi, N. J., Malik, A., Joshi, M., Khan, A. A., Nema, V., et al. (2025) · Frontiers in Immunology · doi:10.3389/fimmu.2025.1586271 · Cited by 7 · see citing works
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Volkhin, I. A., Paremskaia, A. I., Dashian, M. A., Smeshnova, D. S., Pavlov, R. E., Mityaeva, O. N., Volchkov, P. Y., & Deviatkin, A. A. (2025) · Biochemistry (Moscow) · doi:10.1134/s0006297924604659 · Cited by 7 · see citing works
Yang, L., Li, S., Bai, G., Li, L., Li, Y., Liang, X., Ye, Z., Li, L., Li, Z., Guan, J., et al. (2025) · iMetaMed · doi:10.1002/imm3.70015 · Cited by 6 · see citing works
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Roy, O., & Anderson, K. S. (2025) · Vaccines · doi:10.3390/vaccines13121222 · Cited by 5 · see citing works
Tian, Y., Zhang, M., Ali, S. L., Abduldayeva, A., Zhou, S., An, Y., Li, Y., Ni, R., Zhang, L., Liu, Y., et al. (2026) · Pathogens · doi:10.3390/pathogens15030297 · Cited by 5 · see citing works
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Huang, D., Zhang, J., Zeng, X., Zhang, Y., & Song, E. (2025) · Trends in cancer · doi:10.1016/j.trecan.2025.09.003 · Cited by 4 · see citing works
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Reshetnikov, V. V., Сергеевна, Ш. Г., Rybakova, A. D., Trashkov, A. P., Yeremeev, V., & Ivanov, R. (2024) · Bulletin of Russian State Medical University · doi:10.24075/brsmu.2024.045 · Cited by 4 · see citing works
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Self-citationSun, S., Deng, Y., Ren, J., Xiaotian, H., Bing, J., Wang, T., Hao, Z., Tian, H., Zhang, L., & Tan, W. (2026) · Molecular Biomedicine · doi:10.1186/s43556-026-00412-9 · Cited by 1 · see citing works
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Киршина, А. С., Сергеевна, Ш. Г., Khlebnikova, A. S., Maslov, A. P., Kozlova, A., Kunyk, D., Еремеев, В. В., Ivanov, R. A., & Reshetnikov, V. V. (2025) · Bulletin of Russian State Medical University · doi:10.24075/brsmu.2025.040
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Broset, E., Blasco-Machín, I., Lampaya, V., Matute, C., Toro-Córdova, A., & Martínez-Oliván, J. (2025) · doi:10.1101/2025.09.30.679448
Pereverzev, I. M., Bakhno, I. A., Yakovleva, K. I., Dovydenko, I. S., & Burkova, E. E. (2026) · Viruses · doi:10.3390/v18010137
Tang, H., Chen, Z., Yan, H., He, Z., Li, R., Xie, Y., & Wang, X. (2026) · Scientific Reports · doi:10.1038/s41598-026-45084-1
MUSTAFAYEVA, U. H., Babayeva, S. M., Mustafayev, O., HASANLI, L., Goldenkova-Pavlova, I. V., & Mammadova, A. O. (2026) · Biochemical Genetics · doi:10.1007/s10528-026-11394-2
Cherchi, R., Mukhopadhyay, D., Spanu, A., Pardini, B., Cusano, R., Naccarati, A., Zavattari, P., Bergamaschi, E., Cocco, P., & Matteis, S. D. (2026) · Expert Review of Respiratory Medicine · doi:10.1080/17476348.2026.2685338
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Pullinger, B., Harbison-Price, N., Sebina, I., Na, J., Belz, G. T., & Walker, M. J. (2026) · Clinical Microbiology Reviews · doi:10.1128/cmr.00138-26
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Chan, E. H., Lukeman, H., Counoupas, C., & Triccas, J. A. (2026) · npj Vaccines · doi:10.1038/s41541-026-01566-x
Sajjanar, B., Gopinath, S., Nadarajan, P., Marreddy, V. K., Krishnaswamy, N., Nagaleekar, V. K., Hosamani, M., Sreenivasa, B. P., Chaudhuri, P., & Basagoudanavar, S. H. (2026) · Biotechnology Letters · doi:10.1007/s10529-026-03778-6
Nair, A., & Kis, Z. (2026) · Biotechnology Advances · doi:10.1016/j.biotechadv.2026.109034
Vishwakarma, B., Mahovia, B., Gawali, A., Girkar, S., Lingawale, K., & Sen, D. (2026) · International journal of research studies in biosciences · doi:10.20431/2349-0365.1201002
- Authors
- Reshetnikov, V., Terenin, I., Shepelkova, G., Yeremeev, V., Kolmykov, S., Nagornykh, M., Kolosova, E., Sokolova, T., Zaborova, O., Kukushkin, I., Kazakova, A., Kunyk, D., Kirshina, A., Vasileva, O., Seregina, K., Pateev, I., Kolpakov, F., & Ivanov, R.
- Affiliations
- Russian Academy of Sciences (RU)
- Lomonosov Moscow State University (RU)
- Central Tuberculosis Research Institute, 107564 Moscow, Russia
- Central Scientific Research Institute of Tuberculosis Russian Academy of Medical Sciences (RU)
- Sirius University of Science and Technology (RU)
- Translational Medicine Research Center, Sirius University of Science and Technology, 354340 Sochi, Russia
- Corresponding author
- Reshetnikov, Vasiliy
- ORCID
- Venue
- International Journal of Molecular Sciences
- Publisher
- MDPI AG
- Published
- 2024-01-10
- Volume
- 25
- Issue
- 2
- Pages
- 888
- ISSN
- 1422-0067 (ISSN-L)
- PMC
- PMC10815675
- OpenAlex
- W4390806630
- Cited by
- 33
- References
- 54
- Citations by year
- 2026: 15 · 2025: 13 · 2024: 5
- FWCI
- 4.27
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- International Journal of Molecular Sciences (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- Ministry of Science and Higher Education of the Russian Federation (075-10-2021-113)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Interference and Gene Delivery
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Keywords
- mRNA vaccines, tuberculosis, untranslated regions, 5' untranslated region, 3' untranslated region, translation efficiency, firefly luciferase, T cell response, mRNA-1273, BNT162b2, DC2.4 cells, THP-1 cells
- MeSH terms
- mRNA Vaccines, BNT162 Vaccine, Animals, Blood Group Antigens, Humans, Mice, Inbred C57BL, RNA, Messenger, Tuberculosis, 5' Untranslated Regions, 3' Untranslated Regions, Mice, Pandemics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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