SARS-CoV2 infects cells ONLY with ACE2 receptors, yes? SO how on earth that suppose to be worse than nanos which cross ANY cellular membrane??? That's the result of having TONS of antibodies delivered by all the cells with outsticking SPikes on them! W@ish there would be some real experts here a not random writers with engineering background...
Feb 28, 2022·edited Feb 28, 2022Liked by Brian Mowrey
As someone who has used all the methods reported in this paper in various contexts, here are my views:
1) Choice of cell line. Cell and molecular biology studies use immortalised cell lines, i.e. those derived from cancer, all the time mainly because they are easy to grow in the lab. A study with primary cells (directly derived from an animal) or an animal model would be much harder to do and would have taken a lot longer. The reason for choosing Huh7 over other cell lines was noted to because of their hepatic lineage, but also was likely because the researchers simply had easy access to those cells; the latter is not a great reason, but reflects the simple reality that most studies like this make such choices due to simple practicalities. Results from cell lines obviously are not necessarily indicative of what would happen in other cells, but are usually the first step in such a study. They should, however, have performed the experiments in multiple cell lines, to improve confidence in these results.
2) Despite the use of a poor model, it does still show that BNT162b2 RNA can be reverse transcribed in vitro in human cells. This is still an improvement over the "theoretical argument that is already available" because theoretical arguments are still theoretical, and experimental evidence is needed to prove this. Despite its flaws, the study provides the first evidence that reverse transcription of BNT162b2 RNA in human cells. This is presumably due to endogenous LINE-1 (as they didn't add any retrovirus), but the evidence that LINE-1 was responsible is circumstantial at best; the data showing induction of LINE-1 is also poor. In addition, the study doesn't itself rule out the presence of retrovirus infection in these cells, which is another potential flaw in the study.
3) There was no realistic way to obtain "blank" mRNA or LNP controls. Pfizer would not have provided these, and any substitutions for "similar" reagents would erode their usefulness as controls. In addition, such controls would be interesting, but not strictly necessary. Even if the effects are occurring due to "other ingredients of the product", the whole product is what is being injected, and the effects don't need to be due to the mRNA itself. (Obviously, the LNP plus mRNA combination is needed to achieve anything, as the mRNA wouldn't get into the cells without the LNP).
4) Figure 3 is a mess but if you look at the text, they don't actually refer to the cross time-point comparisons ("Significantly increased LINE-1 expression compared to control was observed at 6 h by 2.0 µg/mL BNT162b2, while lower BNT162b2 concentrations decreased LINE-1 expression at all time points (Figure 3)."). They should have removed the statistical comparisons from Figure 3. The criticism about the induction of LINE-1 in the Ctrl at 48 h is valid but is not too surprising - culturing cells easily changes the expression of various genes. Criticism that this could be due to normalisation by housekeepers is also valid, but this is inherit in the vast majority qPCR gene expression designs, which almost invariably use housekeeper normalisation.
5) The differences in fluorescence intensity in Figure 4 do indicate that any quantification of such images is a problem. I'm not too surprised by this - obtaining consistent labelling intensity across different samples using fluorescence microscopy is extremely difficult in practice. Therefore, trying to quantified fluorescence intensity from such images is always a somewhat dubious method. Doing this "properly" generally requires addition of some kind of labelling control on the slide to normalise to, but this is usually not possible for most targets/experimental designs. Nevertheless, this method is used a lot in such studies, despite known issues, so this is no worse there thousands of other cell biology papers doing so. In addition, the researchers appear to have done a flawed statistical analysis for Figure 5 - they have used n=15 cells from two images, and quantified the fluorescence from this n=30. This is an example of pseudo-replication. The cells are NOT proper replicates as treatments are being applied to the wells of cells, not individual cells, and thus the correct level of replication needs to be at the level of wells. Yet, it seems that there was only n=1 well for each condition (for which two images were taken), which is extremely poor. It should be noted, however, that although most cell biology researchers would see the flaw in doing only n=1 well/experiment, most still incorrectly do statistical analysis on the pseudo-replicates of cells rather than wells, reflecting a poor level of training and understanding in statistics in the field (proper analysis of such a design involves treating it as a nested model, which is beyond the capabilities of most cell biologists).
6) I can't see why Ctrl 5/6 are a "red flag". Ctrl 5 and 6 seem to be exactly as stated: RNA extractions with and without RNAse. Both a negative controls, and they lack a positive control in those images. An appropriate positive control would have been RNA/no RNAse with a reverse transcription step before running the PCR. Nevertheless, Ctrl 5 and 6 seem to serve their purpose and are meant to be interpreted together. Ctrl5 (RNA/no RNAse) would indicate whether the PCR amplification occurred from an RNA extract, i.e. the PCR doesn't amplify RNA. As expected, there is no band here, as PCR will not amplify RNA (prior reverse transcription is needed convert to RNA). If Ctrl 5 had been positive, however, it would not be clear that this is due to PCR amplification of RNA instead of DNA contamination of the RNA. This is what Ctrl 6 (RNA/RNAse) is for. If Ctrl 5 had been positive (it wasn't), a positive Ctrl 6 sample would have shown that the Ctrl 5 band was likely due to DNA contaminating the RNA extract (as any RNA would have been degraded by the RNAse). If Ctrl 6 had been negative, it would have shown that the Ctrl5/6 bands were somehow due to amplification of RNA (but they were negative). Ctrl6 also serves to control for the presence of contaminating DNA in the RNAse, which would have been another possible source of a band in the other lanes.
7) Gels of PCR bands are at best semi-quantitative due to a variety of issues (which I can expand on if anyone wants me to), and therefore, in my view, it doesn't make sense to infer much from the band intensities in Figure 5. In addition, the three different images suggest three different gels. Comparing band intensities across gels is a huge no-no. The normal way to interpret these gels is simply the presence or otherwise of bands, which is exactly what the authors did.
In conclusion, I'd say this isn't a great study, and has some clear flaws in it, but it still is the first experimental evidence that BNT162b2 RNA can be reverse transcribed in vitro in human cells. This evidence is limited in that it is only in one cell line, and evidence linking this to LINE-1 is circumstantial and weak. Clearly more studies need to be done on this but (1) I doubt anyone is in a hurry to fund or perform such studies, given the prevailing narrative surrounding these vaccines, which makes questioning them a "cancellable" offence even in the scientific community and (2) such things take time. The flaws in the present study likely reflect the simply practicalities of doing such research when no one wants it do be done.
Really, detailed studies checking for the possibility of endogenous reverse transcription of the BNT162b2 RNA in human cells, and the possibility of genomic integration, should have been demanded from Pfizer prior to approval, so this study also serves to highlight what might have been found if these had been done.
I was surprised that most other analyses of this paper didn’t also flunk the LINE-1 expression mechanism. Our lying eyes and all.
Given findings from this paper (https://academic.oup.com/nar/article/38/12/3909/2409521) determining that L1-related transcripts were an order of magnitude higher in testis than in other tissues, perhaps using (non-cancerous) testes cells might have given clearer/more useful results (at least regarding L1 expression)?
Also from the paper: “The observation of differential L1 processing in normal human tissues suggests that the production of the full-length L1 mRNA in various tissues may depend not only on the L1 promoter strength but also on the amount of the RNA processing supported by a specific cell type. A primary example is testis where overall high expression of the L1-related mRNAs indicates efficient L1 transcription ( Figure 1 and Supplementary Figure S1A ), whereas the full-length L1 transcripts remain below the detection sensitivity of the assay.”
Could the LINE-1 suppression we see here be due to excess RNA processing leading to non-full-length L1 transcripts? And if so, implications of that?
I will have to review this study a bit more. As someone who has done Sanger sequencing I wish they included the BNT sequence as well to compare, but that's a personal gripe. I think the analysis of the gel may be incorrect. It appears that Ctrl 5 and 6 were done to show that their amplicon had to have been arrived from DNA, such that Ctrl 5 and 6 essentially did an RNA extraction. Because both did not have any RNA, no amplicon was found. I think their wording made it confusing. They should not have said they performed PCR on RNA purified from the cells but that they did an RNA extraction to see if they could find any RNA to begin with.
It seems like they may have used these cells because of their ability to replicate, so I suppose it may have been done to mimic effects in rapidly dividing cells.
This is an interesting study, but it definitely means more research should be looked into. If true they should try replicating this study in mice models. I think they should have discussed the possible ramifications. Viruses known to cause cancer usually do so by integrating into host genome. Then, when the viral genome is clipped the process is usually sloppy with either a little too much of the host genome being taken or a bit of the viral genome may be left behind causing a frameshift mutation.
I will hold off on this study and reserve judgement, but I would hope it provides more avenues of research to examine.
It is most incredible to have disagreements on substack and your article is very interesting. Thanks for discussing it. I am also baffled by LINE-1 expression not matching what I would have expected.
SARS-CoV2 infects cells ONLY with ACE2 receptors, yes? SO how on earth that suppose to be worse than nanos which cross ANY cellular membrane??? That's the result of having TONS of antibodies delivered by all the cells with outsticking SPikes on them! W@ish there would be some real experts here a not random writers with engineering background...
How about this ?
Dr. Raszek: Pfizer Docs Show Spike Protein Enters Cell Nucleus
25 Februari 2022
https://uncoverdc.com/2022/02/25/dr-raszek-pfizer-docs-show-spike-protein-enters-cell-nucleus/
As someone who has used all the methods reported in this paper in various contexts, here are my views:
1) Choice of cell line. Cell and molecular biology studies use immortalised cell lines, i.e. those derived from cancer, all the time mainly because they are easy to grow in the lab. A study with primary cells (directly derived from an animal) or an animal model would be much harder to do and would have taken a lot longer. The reason for choosing Huh7 over other cell lines was noted to because of their hepatic lineage, but also was likely because the researchers simply had easy access to those cells; the latter is not a great reason, but reflects the simple reality that most studies like this make such choices due to simple practicalities. Results from cell lines obviously are not necessarily indicative of what would happen in other cells, but are usually the first step in such a study. They should, however, have performed the experiments in multiple cell lines, to improve confidence in these results.
2) Despite the use of a poor model, it does still show that BNT162b2 RNA can be reverse transcribed in vitro in human cells. This is still an improvement over the "theoretical argument that is already available" because theoretical arguments are still theoretical, and experimental evidence is needed to prove this. Despite its flaws, the study provides the first evidence that reverse transcription of BNT162b2 RNA in human cells. This is presumably due to endogenous LINE-1 (as they didn't add any retrovirus), but the evidence that LINE-1 was responsible is circumstantial at best; the data showing induction of LINE-1 is also poor. In addition, the study doesn't itself rule out the presence of retrovirus infection in these cells, which is another potential flaw in the study.
3) There was no realistic way to obtain "blank" mRNA or LNP controls. Pfizer would not have provided these, and any substitutions for "similar" reagents would erode their usefulness as controls. In addition, such controls would be interesting, but not strictly necessary. Even if the effects are occurring due to "other ingredients of the product", the whole product is what is being injected, and the effects don't need to be due to the mRNA itself. (Obviously, the LNP plus mRNA combination is needed to achieve anything, as the mRNA wouldn't get into the cells without the LNP).
4) Figure 3 is a mess but if you look at the text, they don't actually refer to the cross time-point comparisons ("Significantly increased LINE-1 expression compared to control was observed at 6 h by 2.0 µg/mL BNT162b2, while lower BNT162b2 concentrations decreased LINE-1 expression at all time points (Figure 3)."). They should have removed the statistical comparisons from Figure 3. The criticism about the induction of LINE-1 in the Ctrl at 48 h is valid but is not too surprising - culturing cells easily changes the expression of various genes. Criticism that this could be due to normalisation by housekeepers is also valid, but this is inherit in the vast majority qPCR gene expression designs, which almost invariably use housekeeper normalisation.
5) The differences in fluorescence intensity in Figure 4 do indicate that any quantification of such images is a problem. I'm not too surprised by this - obtaining consistent labelling intensity across different samples using fluorescence microscopy is extremely difficult in practice. Therefore, trying to quantified fluorescence intensity from such images is always a somewhat dubious method. Doing this "properly" generally requires addition of some kind of labelling control on the slide to normalise to, but this is usually not possible for most targets/experimental designs. Nevertheless, this method is used a lot in such studies, despite known issues, so this is no worse there thousands of other cell biology papers doing so. In addition, the researchers appear to have done a flawed statistical analysis for Figure 5 - they have used n=15 cells from two images, and quantified the fluorescence from this n=30. This is an example of pseudo-replication. The cells are NOT proper replicates as treatments are being applied to the wells of cells, not individual cells, and thus the correct level of replication needs to be at the level of wells. Yet, it seems that there was only n=1 well for each condition (for which two images were taken), which is extremely poor. It should be noted, however, that although most cell biology researchers would see the flaw in doing only n=1 well/experiment, most still incorrectly do statistical analysis on the pseudo-replicates of cells rather than wells, reflecting a poor level of training and understanding in statistics in the field (proper analysis of such a design involves treating it as a nested model, which is beyond the capabilities of most cell biologists).
6) I can't see why Ctrl 5/6 are a "red flag". Ctrl 5 and 6 seem to be exactly as stated: RNA extractions with and without RNAse. Both a negative controls, and they lack a positive control in those images. An appropriate positive control would have been RNA/no RNAse with a reverse transcription step before running the PCR. Nevertheless, Ctrl 5 and 6 seem to serve their purpose and are meant to be interpreted together. Ctrl5 (RNA/no RNAse) would indicate whether the PCR amplification occurred from an RNA extract, i.e. the PCR doesn't amplify RNA. As expected, there is no band here, as PCR will not amplify RNA (prior reverse transcription is needed convert to RNA). If Ctrl 5 had been positive, however, it would not be clear that this is due to PCR amplification of RNA instead of DNA contamination of the RNA. This is what Ctrl 6 (RNA/RNAse) is for. If Ctrl 5 had been positive (it wasn't), a positive Ctrl 6 sample would have shown that the Ctrl 5 band was likely due to DNA contaminating the RNA extract (as any RNA would have been degraded by the RNAse). If Ctrl 6 had been negative, it would have shown that the Ctrl5/6 bands were somehow due to amplification of RNA (but they were negative). Ctrl6 also serves to control for the presence of contaminating DNA in the RNAse, which would have been another possible source of a band in the other lanes.
7) Gels of PCR bands are at best semi-quantitative due to a variety of issues (which I can expand on if anyone wants me to), and therefore, in my view, it doesn't make sense to infer much from the band intensities in Figure 5. In addition, the three different images suggest three different gels. Comparing band intensities across gels is a huge no-no. The normal way to interpret these gels is simply the presence or otherwise of bands, which is exactly what the authors did.
In conclusion, I'd say this isn't a great study, and has some clear flaws in it, but it still is the first experimental evidence that BNT162b2 RNA can be reverse transcribed in vitro in human cells. This evidence is limited in that it is only in one cell line, and evidence linking this to LINE-1 is circumstantial and weak. Clearly more studies need to be done on this but (1) I doubt anyone is in a hurry to fund or perform such studies, given the prevailing narrative surrounding these vaccines, which makes questioning them a "cancellable" offence even in the scientific community and (2) such things take time. The flaws in the present study likely reflect the simply practicalities of doing such research when no one wants it do be done.
Really, detailed studies checking for the possibility of endogenous reverse transcription of the BNT162b2 RNA in human cells, and the possibility of genomic integration, should have been demanded from Pfizer prior to approval, so this study also serves to highlight what might have been found if these had been done.
I was surprised that most other analyses of this paper didn’t also flunk the LINE-1 expression mechanism. Our lying eyes and all.
Given findings from this paper (https://academic.oup.com/nar/article/38/12/3909/2409521) determining that L1-related transcripts were an order of magnitude higher in testis than in other tissues, perhaps using (non-cancerous) testes cells might have given clearer/more useful results (at least regarding L1 expression)?
Also from the paper: “The observation of differential L1 processing in normal human tissues suggests that the production of the full-length L1 mRNA in various tissues may depend not only on the L1 promoter strength but also on the amount of the RNA processing supported by a specific cell type. A primary example is testis where overall high expression of the L1-related mRNAs indicates efficient L1 transcription ( Figure 1 and Supplementary Figure S1A ), whereas the full-length L1 transcripts remain below the detection sensitivity of the assay.”
Could the LINE-1 suppression we see here be due to excess RNA processing leading to non-full-length L1 transcripts? And if so, implications of that?
I will have to review this study a bit more. As someone who has done Sanger sequencing I wish they included the BNT sequence as well to compare, but that's a personal gripe. I think the analysis of the gel may be incorrect. It appears that Ctrl 5 and 6 were done to show that their amplicon had to have been arrived from DNA, such that Ctrl 5 and 6 essentially did an RNA extraction. Because both did not have any RNA, no amplicon was found. I think their wording made it confusing. They should not have said they performed PCR on RNA purified from the cells but that they did an RNA extraction to see if they could find any RNA to begin with.
It seems like they may have used these cells because of their ability to replicate, so I suppose it may have been done to mimic effects in rapidly dividing cells.
This is an interesting study, but it definitely means more research should be looked into. If true they should try replicating this study in mice models. I think they should have discussed the possible ramifications. Viruses known to cause cancer usually do so by integrating into host genome. Then, when the viral genome is clipped the process is usually sloppy with either a little too much of the host genome being taken or a bit of the viral genome may be left behind causing a frameshift mutation.
I will hold off on this study and reserve judgement, but I would hope it provides more avenues of research to examine.
It is most incredible to have disagreements on substack and your article is very interesting. Thanks for discussing it. I am also baffled by LINE-1 expression not matching what I would have expected.