Art:
something that is created with imagination and skill and that is beautiful or that expresses important ideas or feelings

https://www.britannica.com/dictionary/art

I was recently made aware of an article by Dr. Peter McCullough which supposedly contained “difficult to deny” evidence for the existence of “SARS-COV-2.” This evidence was supposed to shut up those of us who state that no “virus” has ever been properly purified and isolated directly from the fluids of a sick patient and proven pathogenic in a natural way. Thus, I was a bit curious to see what Dr. McCullough had in store for us. Was he finally going to show the evidence we have been asking for? Did he have an actual scientific study adhering to the scientific method which could meet the burden of proof required to claim the existence of these fictional entities?

Let’s jump right in and find out just what kind of “difficult to deny” evidence that Dr. McCullough has to share with the class. I have provided McCullough’s full article detailing a study where the researchers claimed to work with various strains of “SARS-COV-2” while using cryo-EM to image and study the particles. Please note that the title of McCullough’s article claims to be seeing “Covid” up close rather than “SARS-COV-2.” This is an interesting error by the Dr. right off the bat as “Covid” is the disease while “SARS-COV-2” is the “virus.” Not off to a good start:

Seeing COVID up Close Makes It Difficult to Deny Its Existence

The endless frustrations of the SARS-CoV-2 crisis and pandemic response has led some to push back denying existence of the virus altogether.  

Laboratory methods in virology are well accepted and utilize a series of experiments to demonstrate cellular invasion, replication, transfer and repeated infection.  Whole genomic sequencing has aided in identification of variants and subvariants and helped greatly in forecasting what is coming next.  The CDC Nowcast system is an excellent application of targeted sequencing of viral samples.[i]

Nonetheless, some have said if SARS-CoV-2 cannot be cultured like a bacteria and “isolated” then it does not exist.  I have always responded that the principles of laboratory virology, sequencing, and the mass production of viruses such as that done by the Max Planck Institute for Dynamics of Complex Technical Systems are concrete processes that rely on the presence of the virus.[ii]

My understanding from the body of medical literature and firsthand clinical experience are consistent with the conclusion that COVID-19 is indeed a unique illness distinguishable from influenza and other viral infections.   I have always been impressed with the absence of bacterial superinfection and micro- and macro-thrombosis being features that separate COVID-19 from influenza and other viral syndromes.

Calder, et al, at the Francis Crick Institute has gone a step farther with advanced forms of electron microscopy to see the virus up close and personal.[iii]

A picture speaks a thousand words and should help even the most skeptical “viral denier” come onto the rational team that is trying to treat high risk patients, end ridiculous contagion control measures, and bring our world back to normal.

So, the next time someone at a cocktail party says “COVID-19 is a hoax, the virus has never been isolated, “show them some of these works of art!”

https://www.theepochtimes.com/health/seeing-covid-up-close-makes-it-difficult-to-deny-its-existence_4870522.html?welcomeuser=1

According to Dr. McCullough, the “difficult to deny” evidence required to definitively prove the naysayers wrong about the existence of “SARS-COV-2” is not purified and isolated “viral” particles proven pathogenic in a natural way. Dr. McCullough’s air tight evidence comes in the form of the provided cryo-EM images, or “works of art” as he calls them, an interesting choice of words to use when attempting to claim the accompanying cryo-EM images are the required proof of existence. A picture is worth a thousand words, right Dr. McCullough? We can therefore conclude that a picture of Santa Claus is direct proof for the existence of the magical man in red. Bigfoot has been photographed numerous times, so I guess it is settled that he is off the endangered mythological creatures list. The Loch Ness monster? Yep, that fits the bill as well as ol’ Nessy is famous for striking a pose for curious onlookers. Thus it seems that using pictures as direct proof of existence is a rational thought process. As I can see no faults in Dr. McCullough’s line of thinking here, I guess I’m on McCullough’s Team Rational now!

However, if one were to be nitpicky, how the images were created and obtained may be the perfect place to start in regards to finding some holes in McCullough’s “logic.” Obviously, that security camera image of Santa is most likely of some kid’s parent and was taken from the very “trustworthy” Youtube video of the top ten times Santa was caught in the act. That can hardly be considered evidence of the “difficult to deny” variety. We know that the controversial Bigfoot image most likely came from a man dressed in a monkey costume. The fanous Loch Ness monster photograph was of a toy submarine with a plastic head attached. Thus, perhaps the source of the image as well as how it was created and obtained is more important than the actual image itself. After a careful bit of contemplation, my commitment to Team Rational may be wavering a bit here. Let’s see what we can uncover about the creation of McCullough’s works of art.

Looking to some of the highlights taken from the paper that Dr. McCullough was so mesmerized by, we find that the researchers attempted to study the structure of four different strains (Wuhan, Aplha, Beta, and Delta) of “SARS-COV-2” through the use of cryotomography. This is a form of electron microscopy that, according to Nature, is a technique where an electron microscope is used to record a series of two-dimensional images as a biological sample held at cryogenic temperatures is tilted. The “virus strains” used for the imaging were cultured and “grown” in Vero cells offsite at the World Influenza Centre, Francis Crick Institute, London, UK. The “viruses” were then maintained in Dulbecco’s Modified Eagle Medium (DMEM) Gibco™, with 100 U/ml penicillin, 100 μg/ml streptomycin (Pen-Strep) and 10% (v/v) heat-inactivated fetal calf serum (FCS). Thus, we are already off to a bad start as the researchers are not working with assumed “viral” particles purified and isolated directly from the fluids of any sick human but from unpurified cell culture supernatant assumed to contain the “viral” particles.

Digging into the results from the study, the researchers claim that the particles observed were cylindrical in shape with spikes protruding from the surface. This is in direct contrast to earlier research which they admit showed particles that were spherical or ellipsoidal in morphology and shape. Thus, the slam-dunk evidence that McCullough is presenting oddly gives us a completely different shape for “SARS-COV-2.”

The rest of the highlights detail some of the methods and programs used to reconstruct the 3-D images of the cultured particles such as fiducial alignment, motion correction, dose-weighting, phase flipping, backplotting, postprocessing, reference mapping, etc. In order to create the 3-D model, it is stated that the particles were symmetrised using the EMAN program in order to generate a crude model from the best views of various particles. A brief explanation of what this process involves:

“As single particle cryo-EM images are 2-D projections of the to-be- determined 3-D structure at random views, the inverse problem is to determine the 3-D structure from these 2-D images using computational image processing methods. Current image processing methods rely on iterative processes in which the 3-D reconstruction is iteratively improved. It is critical that the initial 3-D model is correctly constructed before proceeding to full refinement.”

“Symmetry view method. This EMAN method intentionally searches for particle images with best five-, three-, and twofold symmetry characteristics and uses these particles to construct the first crude 3-D model that will be further refined. This method is available in the EMAN program starticos.”

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4020923/

I will leave it up to the reader to decide whether or not the numerous processes and computer programs used throughtout this herculean reconstruction effort results in the creation of an actual image or an artists interpretation conjured up and designed by computer software:

Electron cryotomography of SARS-CoV-2 virions reveals cylinder-shaped particles with a double layer RNP assembly

“SARS-CoV-2 is a lipid-enveloped Betacoronavirus and cause of the Covid-19 pandemic. To study the three-dimensional architecture of the virus, we perform electron cryotomography (cryo-ET) on SARS-Cov-2 virions and three variants revealing particles of regular cylindrical morphology. The ribonucleoprotein particles packaging the genome in the virion interior form a dense, double layer assembly with a cylindrical shape related to the overall particle morphology. This organisation suggests structural interactions important to virus assembly.

Introduction

SARS-Cov-2, the causative agent of Covid-19, has been the object of intense investigation, including structural studies by cryo-EM of individual component proteins at high-resolution, as well as cryotomography of viruses1,2,3 and infected cells4,5. Cryotomography of frozen-hydrated virus particles enables the visualisation of particle exterior and interior in three dimensions and thus is an important method for understanding the three-dimensional architecture of pleomorphic lipid-enveloped viruses. These previous studies have described SARS-CoV-2 virions as spherical or ellipsoidal and in addition have mainly visualised the spike protein (S) in pre-fusion and post-fusion states on the virus surface and ribonucleoprotein assemblies in the virus interior. Other virus structural components such as the membrane protein (M), the envelope protein (E) and additional non-structural proteins may play important roles in virus structure and assembly.

Because a number of fundamental questions remain about the virus architecture, such as how virion components interact in three-dimensions to assemble particles and how the large positive strand genome is packaged, we apply cryotomography to study the architecture of virions of the original Wuhan strain of SARS-CoV-2 and three variants that arose during the first year of the pandemic. The tomograms show the particles are of a uniform cylindrical shape with spike proteins distributed over the whole envelope. The interior of the particle reveals an organised RNP assembly with implications for virus assembly.

Results and Discussion

We recorded tilt-series and reconstructed cryotomograms of frozen-hydrated SARS-CoV-2 virions from the original Wuhan strain and Alpha (B.1.1.7), Beta (B.1.351) and Delta (B.1.617) variants. The tomograms show that the virions are predominantly of a single and uniform morphology which is an extremely flat cylindrical shape.”

Methods

SARS CoV-2 virus seed stock production

“Four different viral strains were obtained as follows:

Wuhan (hCoV-19/England/02/2020), (GISAID EpiCov™ accession EPI_ISL_407073) from The Respiratory Virus Unit, Public Health England (PHE), UK.

Alpha variant B.1.1.7 (hCoV-19/England/204690005/2020) from PHE through Professor Wendy Barclay, Imperial College, London, UK.

Beta variant B.1.351 (501Y.V2.HV001) from the African Health Institute, Durban, South Africa.

Delta variant B.1.617.2 (GISAID accession EPI_ISL1731019) from Professor Wendy Barclay, through Genotype-to-Phenotype National Virology Consortium.

All viruses were grown at the World Influenza Centre, Francis Crick Institute, London, UK under Biosafety level 3 conditions in Vero V1 cells, provided by Professor Steve Goodbourne, St George’s Hospital, University of London, UK and maintained in Dulbecco’s Modified Eagle Medium (DMEM) Gibco™ 41965039, with 100 U/ml penicillin, 100 μg/ml streptomycin (Pen-Strep) and 10% (v/v) heat-inactivated fetal calf serum (FCS).”

Tomogram generation

“Talos-acquired tilt series were fiducial aligned with the IMOD package18 and reconstructed with SIRT, 5 iterations. Resulting tomograms were binned 4x and filtered with 10 iterations of Nonlinear Anisotropic Diffusion.

Movie frames of Krios acquired tilt series were motion corrected, dose-weighted and fiducial-aligned using the IMOD package. The contrast transfer function was estimated with CTFFIND419, tomograms were CTF corrected by phase flipping and reconstructed with novaCTF20, producing a weighted back-projection tomogram and a SIRT-like filtered tomogram. For visual analysis the SIRT-like filtered tomograms were binned 4x and subjected to 20 iterations of Nonlinear Anisotropic Diffusion filtering using the Bsoft21 program bnad with default parameters (λ = 0.1).

Subtomogram averaging

268 whole virions from 20 tomograms were picked manually from the 4-fold binned SIRT/NAD-filtered tomograms using EMAN 2.9122. Particles were then extracted from the unbinned, CTF-corrected WBP tomograms with 4-fold downsampling (box size 1598 Å, 8.88 Å/pixel sampling) using Relion 3.123. Reference-free alignment of all subtomograms produced an initial map which was used as a reference for further 3D classification and alignment. A loose, soft mask around the outer surface of the virion envelope was used during further alignment, classification and postprocessing. The average map of 2-layered virions was estimated to have a resolution of 44 Å at the FSC = 0.143 cutoff by Relion postprocessing. After the alignment of all subtomograms, 3D classification into 5 classes without alignment was then carried out to examine the varying morphologies of the virions.

For PCA analysis, the virion subtomograms were re-imported into EMAN 2.9122, aligned against the Relion map and analysed using PCA-based classification, starting from 3 initial basis vectors and requesting 3 output classes.

Spike particles were picked manually from the 4-fold binned SIRT/NAD-filtered tomograms using IMOD. 4418 particles from 251 virions in 18 tomograms were then extracted from the full-size WBP tomograms with 2-fold downsampling (box size 444 Å, 4.44 Å/pixel sampling) for subtomogram averaging in Relion 3.1. Reference-free initial model generation in C1 produced a map with clear 3-fold features, which was symmetrised and used as a reference for further refinement with C3 symmetry applied and with a loose mask around the ectodomain. Upon convergence of refinement, the particles were reclassified with relaxation of C3 symmetry, revealing a class with the 1-RBD-up conformation. The classes were separated and the closed conformation particles were finally refined with C3 symmetry, while the 1-RBD-up particles were refined without symmetry. The final resolutions were estimated as 30 Å (closed conformation) and 28 Å (1-RBD-up conformation) at the FSC = 0.143 cutoff by Relion postprocessing.

The subtomogram averaging maps were backplotted into the frame of reference of the original tomogram using in-house scripts (available from the authors). Spike particles were visually inspected and removed if they were misaligned (i.e. had a relative tilt of over 90° with respect to the normal of the viral envelope) or duplicate particles which converged to the same position during alignment.”

https://www.nature.com/articles/s42003-022-04183-1

Why were the images of the “SARS-COV-2 virions” in this study of a different shape and morphology than those seen in the many studies that came before? If we look into the various processes and limitations associated with electron cryotomography, we can get an idea as to why this may have been the case. It must be understood that the cryo-EM images are 3-D reconstructions which require different computer programs and software to combine and create the images seen. In this process, the sample is frozen and then put through a series of recordings in which the sample is tilted on a different axis and at various angles to obtain multiple images which are then merged together to create a 3-D reconstruction. However, in order to generate these “works of art,” there are some problems which are regularly encountered which can distort the final result.

For frozen biological samples, radiation damage is a major concern. The longer the sample is exposed to the electron beam through various tilts, the quicker the sample heats up and becomes unusable. As more electrons are used, the originally sharp edges of macromolecular structures degrade and eventually “bubbles” which causes distortions and creates difficulties with interpretation. Another issue is missing wedges of information which remain unmeasured due to limitations in acquiring images at a certain angle. This creates worse resolution of the 3-D reconstruction in the direction parallel to the electron beam than the resolution perpendicular. This in turn can cause spherical objects to appear ellipsoidal. Various computer software and algorithms were created to try and correct these issues yet they still remain and can make identifying structures challenging. This is all detailed in highlights from the below source:

Electron Cryotomography

INTRODUCTION—THE STORY OF FtsZ

“ECT can produce three-dimensional (3-D) reconstructions of intact cells in near-native states to “molecular” resolution (∼4 nm), and has thus begun providing unprecedented views into the ultrastructure of bacterial cells.”

Tilt-Series Acquisition and Fundamental Limitations

“The word “tomography” means imaging by sections or sectioning. The most familiar use of the word is the medical “CT,” or “computed tomography” scan, wherein X-ray projection images through a subject are recorded from a number of directions and then merged to produce a 3-D anatomical model. Similarly, in electron tomography, a “tilt-series” of projection images are recorded of a single object like a bacterial cell as it is incrementally tilted around one, and sometimes two axes, and these images are then merged to produce a 3-D “reconstruction” or “tomogram” (Fig. 2). The basic workflow is that a grid is inserted into the EM, a target is chosen and centered under the electron beam, a projection image is recorded, the sample is rotated (tilted) a degree or two, another projection image is recorded, and the cycle of rotation and imaging is repeated as far as useful images can be obtained (until the sample becomes prohibitively thick or the grid or grid holder begins to block the beam, usually ∼65°). Images of the inverse tilt angles (i.e., 0° to −65°) are recorded similarly, or alternatively, the tilt-series can begin at one extreme tilt angle (like 65°) and proceed through the untilted position to the opposite extreme (i.e., −65°). Unfortunately, for frozen-hydrated biological materials, radiation damage prohibits this. As the imaging electrons pass through the sample, they can remain unscattered, scatter elastically, scatter inelastically, or suffer multiple scattering events. Although image contrast (the information content) is produced by the interference of the unscattered and the elastically scattered electrons, the inelastically scattered electrons gradually destroy the sample. Inelastic scattering events break covalent bonds, deposit heat, and more rarely even knock atomic nuclei out of place. Because for every useful elastic scattering event there are approximately 3 damaging inelastic scattering events (Henderson 1995), as more and more electrons are used to build up an image, sample damage accumulates. The originally sharp edges of macromolecular structures degrade and eventually “bubbles” of (presumably) radiolytic fragments appear and catastrophically disrupt the structure (Comolli and Downing 2005; Iancu et al. 2006b; Wright et al. 2006). Thus the most fundamentally limiting factor in ECT is the total number of electrons that can be used to record images before the sample is destroyed.”

“Because with even the thinnest samples, useful images at tilt angles higher than ∼65–70° cannot usually be collected, there is a “wedge” of information (the tilt angles surrounding 90°) that remains unmeasured. As a result, the resolution of the 3-D reconstruction in the direction parallel to the electron beam is significantly worse than the resolution perpendicular. In simple visual terms, this causes spherical objects to appear somewhat ellipsoidal (smeared in the direction of the beam), and continuous objects such as filaments and membranes are more visible in some orientations than in others. This is why in “xz” or “yz” tomographic slices (such as Fig. 1D), the membranes do not appear to connect around the “top” and “bottom” of the cell. Although the missing wedge may be reduced to a missing “pyramid” by rotating the grid 90° and collecting a second, orthogonal tilt-series (a so-called “dual-axis” data set), this procedure is more than twice as time consuming, the dose that can be used per image is halved, and alignment errors between the tilt-series can erode the benefit (Nickell et al. 2003; Iancu et al. 2005). Thus a third fundamental limitation in ECT is the anisotropic resolution caused by tilt limitations (the “missing wedge”).”

3-D Reconstruction and Interpretation

“As mentioned earlier, because no goniometer is perfect, specimens move laterally and vertically within the column throughout the tilt-series. The images must therefore be precisely aligned before a 3-D reconstruction can be calculated. As an additional challenge, because of the physics of electron optics, changes in height/focus within the column cause images to rotate and show subtly different magnifications. Further, although the tilt angle of each image is approximately known, the actual angles reached must be determined more accurately. Sophisticated software has therefore been written to refine estimates of the translations, rotation, magnification, tilt axis, and tilt angle of each image in the tilt-series (Mastronarde 2008). The colloidal gold beads typically added to the samples provide precise fiducial markers to facilitate this process.

Once the images are aligned, 3-D reconstructions can be calculated with a variety of algorithms. The most intuitive is “back-projection,” in which a reconstruction is built up by “smearing” the densities in each image back through space in the opposite direction they were projected (Fig. 2B) (Crowther et al. 1970b). To understand this reconstruction in Fourier space, the key principle is that the 2-D Fourier transform of a projection image is a central slice of the 3-D Fourier transform of the object (the “Projection theorem”) (Crowther et al. 1970a). Thus the 3-D Fourier transform of the sample can be “filled” with the transforms of the 2-D images, and then re-sampled onto a regular (for instance Cartesian) coordinate system and inverse transformed to produce a real-space reconstruction (Lee et al. 2008). Various software packages have been written to perform these calculations, including IMOD (Mastronarde 2008), the TOM toolbox (Nickell et al. 2005), and RAPTOR (Amat et al. 2008). Once reconstructed, tomograms can be “denoised” to improve image contrast and enhance interpretability (Frangakis and Hegerl 2001; Narasimha et al. 2008) and/or “segmented” to allow specific features to be visualized in isolation or as surfaces (Pruggnaller et al. 2008).”

“In summary, ECT produces 3-D images of intact cells in near-native states to “molecular resolution,” but the sample must be thin (< 0.5 µm), the interpretability of the resulting tomograms is limited by radiation damage, the resolution is anisotropic because of tilt limitations, the procedure is complicated and requires expensive electron cryo-microscopes, and identifying structures of interest in the tomograms can be challenging.”

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2869529/

My reasoning for including this last source is because it provides a great amount of detail covering what goes into obtaining cryotomography images from the data generated. I have highlighted information on both single-particle imagery as well as tomograms from cryo-EM. This is to showcase the numerous steps involved in creating the fine art McCullough enjoys as well as other “works of art” constructed using this process. There is a great deal of interesting information within the article which I had to leave out for space considerations so I do recommend giving the full article a read if there is a desire for greater clarity on the subject. Once again, I will leave it up to the reader to decide what, if anything, can be gleaned from these computer-generated recreations.

In this source, it is stated that data preprocessing involves three separate steps for reconstruction of the images such as screening, boxing, and CTF determination. 3-D reconstruction of a “virus” from multiple single particle images is the last step in the computationally intensive process of particle alignment. The majority of 3-D maps assume an icosahedral symmetry and even though non-icosahedral reconstructions represent the ideal target, this remains complicated due to the requirement of far more data needed for reconstruction. There are numerous programs to choose from for 3-D reconstruction in regards to particle alignment and refinement and it is ultimately up to personal preference as to which one is used. These programs use alignment algorithms which require an accurate initial model, although there are some programs where it is stated that this is unecessary. In order to generate a model, it must be determined how many particles are to be used for reconstruction and which ones are high quality as lower quality images can contain aberrations which may do more harm than good in enhancing the resolution of a reconstruction. It is said that in order to determine the number of particles required to achieve a specific resolution reconstruction, assumptions must be made about the data, both without and with noise. After these various steps are performed, it is possible to reconstruct the 3-D model of the “virus” by merging all of the 2-D particle images, after CTF correction, into a single 3-D map using computer programs. For tomography, image alignment is crucial and is performed using a graphical user interface (GUI) computer program. The final step in the structural determination of a “virus” is interpretation of the 3-D density map in regards to resolution determination, segmentation, and model fitting and care must be taken not to overinterpret the map beyond its best approximated resolution. The rest of the process involves fitting to a model for visualisation:

1.16 Cryo-Electron Microscopy and Tomography of Virus Particles

“Virus reconstruction typically relies on one of two primary imaging modalities – single particle and tomography – the choice of which depends on the structural heterogeneity of the virus either in vitro or in the presence of a host cell. The major difference between the two techniques is the manner in which the data are recorded. In single particle data collection, individual virus particles on the grid are imaged only once, and it is the collection of thousands of these images that is used to reconstruct the virus (Figure 2 ). In cryo-ET, a single area of a grid containing many viral particles is imaged multiple times, at a variety of tilt angles, and it is the combination of these images that is used to generate a tomogram and subsequently an averaged density map (Figure 3 ). Although single particle data collection is often used for subnanometer resolution structural studies, in the case in which either structural or conformational non-uniformity exists (e.g., viral infection of a cell), tomography proves a more fruitful endeavor. Regardless of the technique used, implicit in each of these techniques is the need to process the raw data, and although the means of doing so are quite unique, the basic principle of aligning and averaging the data remains the same.

This chapter outlines common techniques used in the field of cryo-EM and cryo-ET for virus reconstruction, from data collection to processing and interpretation. Although many of these techniques have been well reviewed in the past,[18], [21], [19], [20] because cryo-EM is a rapidly evolving field, advancements in both data collection procedures and data processing algorithms are a frequent occurrence. The methodologies discussed in this chapter are commonly used at the National Center for Macromolecular Imaging (NCMI) for the reconstruction of viruses by cryo-EM and cryo-ET.”

1.16.2. Single Particle Reconstruction

“As a result of the conformational uniformity with which virus particles are produced, and the ease with which they can be purified, single particle reconstruction has long been used to solve the structure of icosahedral viruses.[1], [2] Single particle reconstruction relies on imaging hundreds to hundreds of thousands of viral particles, computationally isolating each particle, and then combining the individual particles into a single 3-dimensional (3-D) density map (Figure 2). Because cryo-EM provides a projection of the virus onto the recording medium, the lack of an even distribution in the 3-D orientation of the particles can introduce bias when reconstructing the data. Accordingly, a single particle imaging session should result in the collection of a series of 2-D images that taken together offer a well-sampled view of the many different orientations of the particles. The process of single particle reconstruction involves isolating each viral particle from a set of images, determining its orientation and center, and then using this information to stitch the data back together into a single 3-D representation of the virus.

Although the first single particle cryo-EM reconstructions were published approximately 40 years ago,[1], [2], [22] advancements are still being made in the field that have enabled the resolution of these reconstructions to push well beyond the subnanometer threshold.[4], [6], [8], [10], [5], [9] The driving force behind these advancements is the ability to identify not only the secondary structural elements but also the Cα backbone and side chains of the individual subunits of a virus.

1.16.3. Tomography

Although purified samples with high structural uniformity are ideal for single particle reconstruction, it is not always possible to work within a system that lends itself to the single particle approach. In the presence of structurally diverse samples, a technique that can capitalize on the information content of just a few particles of similar or identical conformation is needed. The theory behind tomography is that by collecting a series of images from a sample, at a variety of tilt angles, it is possible to reconstruct a 3-D volume density from the 2-D projections (Figure 3(a)).[23], [24] This approach allows for a great deal of low-resolution 3-D information to be extracted from the handful of particles in the tomogram. Under standard tomographic imaging conditions, a series of 71 images are taken from −70° to 70° at a step size of 2° (60° and 80° tilt holders are available as well). These images can then be aligned to each other using fiducial markers present in the images (Figure 3(b)), from which a volume (a tomogram) can be extracted (Figure 3(c)).25 From this volume, it is possible to extract individual subtomograms corresponding to each of the particles. These subtomograms can then be classified, aligned, and averaged to obtain a single 3-D model.[26], [28], [27]

One consideration for tomography is the high dose that the sample receives during the tilt-series imaging. In single particle data collection, the sample is often subjected to between 20 and 25 electrons per Å2 per micrograph.[20], [29] In tomography, however, because a single area of the grid is imaged approximately 70 times, the sample is subjected to far more radiation, making damage a consideration. In general, during tomography, the dose per image is set to a point at which the total dose per tomogram (71 images) is between 80 and 100 electrons per Å2.27 Even at this dose level, radiation damage begins to become an issue and will limit the maximum achievable resolution through this technique.[30], [31] Therefore, in order to limit the total dose delivered in a single tomogram, on average, the dose per image must be reduced to nearly 1/20th of what is commonly used for a single particle micrograph. Lowering the total dose per image reduces the signal-to-noise ratio (SNR) in the data and effectively lowers the maximum attainable resolution from the data, the gain from ‘dose fractionation’ notwithstanding.32 Due to the manner in which a single tomographic series is recorded, the maximum resolution achieved so far with these techniques only approaches the nanometer threshold,33 which is far below the current standard set by the single particle approach.[4], [11], [5], [6], [7], [8], [9], [10]”

1.16.6. Data Preprocessing

“The next step in the reconstruction workflow is preprocessing the electron micrographs collected from the microscope. For single particle reconstructions, preprocessing typically follows the same three steps: screening, boxing, and CTF determination. Each of these steps is essential to the reconstruction process, and although they can be as time-consuming as the data collection process, efforts have been made to automate them.[51], [52] Alternatively, preprocessing tomogram data entails aligning the series of tilt images to each other. Due to the nature in which tomogram data are collected, the data are screened during data collection to ensure that if there is an aberrant image in the tilt series, another can be collected at the same tilt angle to prevent a loss of data for that angle.

1.16.7. Single Particle Reconstruction

The 3-D reconstruction of a virus from multiple single particle images is the last step in the computationally intensive process of particle alignment.1 The general principle behind the theory is that given a series of single particle images, once you have determined their icosahedral (or asymmetric) orientations, you can combine the data to form one cohesive 3-D model. Although this process can be applied to a small number of particles, unless a large number of particles are used, many features – such as preferred orientation, limited defocus range, and noise – keep a reconstruction from reaching high resolution. To circumvent these issues, it has been common practice to use an ever-increasing number of particles.”

1.16.7.1. Particle Alignment and Refinement

“Three-dimensional reconstruction has been the source of a great deal of research in the field and has led to the development of many programs, including EMAN,51 EMAN2,52 MPSA,58 Spider,61 XMIPP,62 IMAGIC,63 FREALIGN,64 AUTO3DEM,65 SPARX,66 and IMIRS.67 Although some of these programs are more efficient than others, the choice of which to use is usually a matter of personal preference.”

1.16.7.1.2. Asymmetric alignment 

“The majority of virus reconstructions published in the literature are of specimens for which there is some assumed symmetry to the map. For many viruses, the assumed symmetry is icosahedral; however, due to the nature in which these viruses are built and mature, there are important molecular components in their overall structure that are not symmetric. Accordingly, there has been an increased interest in the determination of the structure of these viruses without imposed symmetry because it will help shed light on the process of viral assembly and maturation.[6], [12], [16], [70], [13], [14], [15] The assumption of symmetry is often made because it simplifies the process of orientation determination. Furthermore, by icosahedrally averaging a map, the information content of a data set is enhanced, making it possible to achieve high-resolution reconstructions with nearly 60 times less data than for a reconstruction in which no symmetry is assumed.68 The process of orientation determination for an asymmetric reconstruction differs from the traditional symmetric orientation search in that one must be able to identify the non-icosahedral components in the virus particle.6 In the case of a phage such as P-SSP7, which has a large tail and portal structure, it is conceptually easy to understand how one would determine the asymmetric orientation of the particles because the non-icosahedrally symmetric feature is visible in the raw micrographs (Figure 15 (a)). However, in the case of a virus such as HSV-1 in which the structure does not have such a protruding feature that is readily identifiable in raw micrographs, it is more difficult to find the true asymmetric orientation of the particle (Figure 15(b)). Once the asymmetric orientation of every particle has been determined, the process of reconstructing the virus asymmetrically is identical to any other reconstruction in which symmetry is assumed.

1.16.7.2. Single Particle Data Subset Selection

Traditionally, the resolution of a map is improved as increasingly more particles are added to the reconstruction. However, this must be weighed against the observation that some data are of better quality than others, and inclusion of data that contain aberrations may in fact do more harm than good in enhancing the resolution of a reconstruction. The quality of a single particle can be thought of as a metric of conformational heterogeneity, icosahedral symmetry, and imaging conditions.56 The better all three of these factors are, the more likely the particle will contribute to producing a high-resolution reconstruction.

The number of particles required to achieve a specific resolution reconstruction depends on assumptions made about the data, both without and with noise.[71],”

“Often, the ‘best’ particles are those that have been determined, through the process of iterative alignment and refinement, to consistently score higher than other particles.58 Although there is no concrete method to determine a priori which particles are the best, there are many steps that can be taken to ensure that the quality of data you put into your reconstruction is of the highest quality possible. First, in the event that an accurate initial model for your sample exists, there is no need to collect data at a defocus higher than 2 μm. In addition, by carefully screening your data on the front end, it is possible to eliminate entire micrographs of poor-quality data. A second level of screening can be performed at the level of boxing, where it is possible to identify and remove particles that may be experiencing the effects of local charging. Although there is no way to directly control for conformational heterogeneity within your sample, if there are visible differences in the raw particle data, it is possible to ameliorate this problem by selecting subsets of the data (Figure 9). Nevertheless, even if ‘bad’ particles make it through these steps of screening, in some cases, the process of data refinement will eliminate particles that are not consistent with the existing pool of data.

1.16.7.3. Three-Dimensional Reconstruction

Once the orientations of all of the particles in a data set have been determined, it is possible to reconstruct the 3-D model of the virus. This process works by merging all of the 2-D particle images, after CTF correction, into a single 3-D map. 3-D reconstruction programs typically have a method to generate these 3-D density maps, and to achieve this task EMAN and EMAN2 use the programs make3d and e2make3d, respectively. These two programs are based on a direct Fourier inversion method to generate the 3-D volumetric data, and they have a variety of command line parameters that allow the user to specify symmetries or data preprocessing steps.”

1.16.8.2. Alignment and the ‘Missing Wedge’

“Just as in single particle cryo-EM, there are a variety of schemes for determining the orientation and alignment of the particles in the extracted subtomograms.[25], [26], [28], [51], [76] Accordingly, a well-resolved tomographic average requires the individual subtomograms containing the extracted particles to be aligned with respect to each other – a process that is rarely as straightforward as in single particle cryo-EM. Because most cryo-holders have a maximum tilt angle of ±70° (although some 80° holders are available), the total coverage for a tomogram is limited to 140° at best (Figure 17 (a)). Ideally, a tomogram would contain data collected across a full 180°; however, because this is not possible with the currently available cryo-holders, this lack of information from 70° to 90° is manifested as a missing wedge of data in Fourier space (Figure 17(b) and (c)), and if it is not corrected for, it can distort the final reconstruction. An additional complicating factor is that because the tilt angle for a group of particles in a single tomogram is identical, all the particles have the same missing wedge. However, because the particles are randomly oriented in the sample, each particle has different missing wedge data with respect to its orientation (Figure 17(b) and (c)). Because the missing wedge is manifest as a value of zero in the FFT of the data, calculation of the cross-correlation between two particles can result in the elimination of a great deal of information in Fourier space because cross-correlation involves multiplication by these zeros (Figure 17(c)). To address the fact that the presence of missing data in the Fourier space can hinder proper alignment of the subvolumes,[27], [28] procedures have been developed to circumvent this problem by normalizing the cross-correlations calculated for two particles at different orientations (Figure 17(f)).28 Although this approach has been met with success, there is no guarantee that the missing wedge problem has been solved, especially for high-resolution tomographic reconstructions.

Alignment of tomographic data requires the three Euler angles (α, β, γ) for every computationally extracted particle to be determined through a series of orientation searches. This process is typically initialized through comparison with an approximate model of the virus. However, in the event that no adequate reference model is available, it is necessary to generate an initial model from the available data. The raw data can be used to generate an adequate initial model by comparing subtomograms to each other in a process known as ‘all-vs-all’ comparison.76 This initial model can be further improved through a series of iterative refinements in which the individual subtomograms are classified, aligned, and averaged to a single or multiple 3-D models. Furthermore, as in single particle cryo-EM, particles can be aligned with respect to their asymmetric features, making it possible to generate single particle cryo-ET maps without imposing symmetry in the map. Nevertheless, again as in single particle cryo-EM, the assumption of symmetry during reconstruction dramatically enhances map resolution.16 To generate a 3-D model from cryo-ET data, once the orientation search is complete and the particles have been aligned, the data can be reconstructed into a 3-D model by averaging the individual subtomograms together while accounting for the missing wedge information from each particle.28

1.16.9. Data Interpretation

The final step in the structural determination of a virus is interpretation of the resulting 3-D density map, specifically resolution determination, segmentation, and model fitting. However, care must be taken not to overinterpret the map beyond its best approximated resolution: 20 Å for gross structure, 12 Å for individual protein domains, 9 Å for long and smooth α helices and large β sheets, 4.7 Å for bumpy α helices and possibly β strands, less than 4.5 Å to possibly determine a Cα backbone trace and bulky side chain features, and less than 3.6 Å to resolve ambiguity in β strand and loop connectivity.[77], [79], [78]

1.16.9.2. Segmentation

One of the key components in data interpretation is segmentation of a map. Because most complex macromolecules can be broken down into smaller self-assembled protein complexes (a segment), differentiating these pieces from the whole is part of understanding the viral architecture and assembly process. For viruses, when symmetry is assumed in the reconstruction, it is possible to extract just the asymmetric unit and segment it accordingly;[29], [48] however, as more viruses are reconstructed without imposed symmetry, it will become necessary to consider the map as a whole.[6], [13], [15], [14] Although a map can be segmented manually by visual inspection of the density map, simultaneous visualization of the map with fit crystallographic homologs eases the process. Traditionally, segmentation is performed manually,[75], [84], [85] but tools have been developed to automate certain aspects of the segmentation process. These programs use a variety of approaches, such as watershed86 and principal component analysis87 or multiscale segmentation,88 to identify individual protein components in the virus. Although these algorithms save a great deal of time during segmentation, their accuracy depends on the resolution and the overlapping density between adjacent molecules.

Regardless of what software is used, accurate segmentation remains a challenging task. For example, a 9-Å resolution map of the bacteriophage did not reveal the presence of two separate coat proteins in the capsid. However, when a 4.5-Å map of ε15 was obtained, a second coat protein was discovered after the Cα backbone trace of that protein revealed that it was in fact two distinct proteins.4“

1.16.11. Future Prospects

“As described in this chapter, the structural features of most viruses are lost in the noisy images recorded from the electron microscope. Fortunately, after extensive data processing and reconstruction, it becomes possible to resolve these features – in some instances at near-atomic resolutions. Although most of this work has been augmented by image processing techniques that computationally enhance image contrast, advances in fabrication techniques have enabled the microscopist to do so directly by altering the optics of the electron microscope.”

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7151817/#!po=21.0983

In Summary:

• According to McCullough, some have said if “SARS-CoV-2” cannot be cultured like a bacteria and “isolated” then it does not exist
• Wrong. We state that the existence of these particles must be proven within humans first through purification and isolation directly from the sample taken from a sick patient. Cell culturing shouldn’t even be a part of the conversation until this has been done.
• McCullough states that his understanding from the body of medical literature and firsthand clinical experience is consistent with the conclusion that “COVID-19” is indeed a unique illness distinguishable from influenza and other “viral” infections
• He believes that a picture speaks a thousand words and should help even the most skeptical “viral denier” come onto the rational team
• McCullough advises the readers that the next time someone at a cocktail party says “COVID-19″ is a hoax or that the “virus” has never been isolated, they should “show them some of these works of art!”

• The researchers performed electron cryotomography (cryo-ET) on “SARS-Cov-2 virions” and three variants which revealed particles of regular cylindrical morphology
• This is rather odd as, according to the CDC, “SARS-COV-2” is spherical in shape
• The researchers state that previous studies have described “SARS-CoV-2 virions” as spherical or ellipsoidal
• They once again state that their tomograms show the particles are of a uniform cylindrical shape with spike proteins distributed over the whole envelope
• They recorded tilt-series and reconstructed cryotomograms of frozen-hydrated “SARS-CoV-2 virions”
• The tomograms showed that the “virions” are predominantly (i.e. not all of them) of a single and uniform morphology which is an extremely flat cylindrical shape
• The researchers used 4 strains (Wuhan, alpha, beta, delta) which were “grown” at the World Influenza Centre, Francis Crick Institute, London, UK under Biosafety level 3 conditions in Vero V1 cells (monkey kidney cells)
• The cell cultured creations were maintained in Dulbecco’s Modified Eagle Medium (DMEM) Gibco™, with 100 U/ml penicillin, 100 μg/ml streptomycin (Pen-Strep) and 10% (v/v) heat-inactivated fetal calf serum (FCS)
• For tomogram generation, Talos-acquired tilt series were fiducial aligned with the IMOD package and reconstructed with SIRT, 5 iterations
• Movie frames of Krios acquired tilt series were motion corrected, dose-weighted and fiducial-aligned using the IMOD package
• The contrast transfer function was estimated with CTFFIND4, tomograms were CTF corrected by phase flipping and reconstructed with novaCTF, producing a weighted back-projection tomogram and a SIRT-like filtered tomogram
• 268 whole “virions” from 20 tomograms were picked manually from the 4-fold binned SIRT/NAD-filtered tomograms using EMAN 2.9122 (i.e. they picked the best particles that they had reconstructed from multiple images)
• Reference-free alignment of all subtomograms produced an initial map which was used as a reference for further 3D classification and alignment
• A loose, soft mask around the outer surface of the “virion” envelope was used during further alignment, classification and postprocessing
• After the alignment of all subtomograms, 3D classification into 5 classes without alignment was then carried out to examine the varying morphologies of the “virions”
• For PCA analysis, the “virion” subtomograms were re-imported into EMAN 2.91, aligned against the Relion map and analysed using PCA-based classification
• Spike particles were picked manually from the 4-fold binned SIRT/NAD-filtered tomograms using IMOD
• 4418 particles from 251 “virions” in 18 tomograms were then extracted from the full-size WBP tomograms with 2-fold downsampling for subtomogram averaging in Relion 3.1
• Reference-free initial model generation in C1 produced a map with clear 3-fold features, which was symmetrised and used as a reference for further refinement with C3 symmetry applied and with a loose mask around the ectodomain
• The subtomogram averaging maps were backplotted into the frame of reference of the original tomogram using in-house scripts
• Spike particles were visually inspected and removed if they were misaligned (i.e. had a relative tilt of over 90° with respect to the normal of the “viral” envelope) or duplicate particles which converged to the same position during alignment

• ECT is said to produce three-dimensional (3-D) reconstructions of intact cells
• In electron tomography, a “tilt-series” of projection images are recorded of a single object like a bacterial cell as it is incrementally tilted around one, and sometimes two axes, and these images are then merged to produce a 3-D “reconstruction” or “tomogram”
• The basic workflow is that a grid is inserted into the EM, a target is chosen and centered under the electron beam, a projection image is recorded, the sample is rotated (tilted) a degree or two, another projection image is recorded, and the cycle of rotation and imaging is repeated as far as useful images can be obtained (until the sample becomes prohibitively thick or the grid or grid holder begins to block the beam, usually ∼65°).
• Unfortunately, for frozen-hydrated biological materials, radiation damage is an issue
• As the imaging electrons pass through the sample, they can remain unscattered, scatter elastically, scatter inelastically, or suffer multiple scattering events
• Inelastic scattering events break covalent bonds, deposit heat, and more rarely even knock atomic nuclei out of place
• Because for every useful elastic scattering event there are approximately 3 damaging inelastic scattering events as more and more electrons are used to build up an image, sample damage accumulates
• The originally sharp edges of macromolecular structures degrade and eventually “bubbles” of (presumably) radiolytic fragments appear and catastrophically disrupt the structure
• The most fundamentally limiting factor in ECT is the total number of electrons that can be used to record images before the sample is destroyed
  • With even the thinnest samples, useful images at tilt angles higher than ∼65–70° cannot usually be collected and there is a “wedge” of information (the tilt angles surrounding 90°) that remains unmeasured
  • As a result, the resolution of the 3-D reconstruction in the direction parallel to the electron beam is significantly worse than the resolution perpendicular and this causes spherical objects to appear somewhat ellipsoidal (smeared in the direction of the beam)
• Although the missing wedge may be reduced to a missing “pyramid” by rotating the grid 90° and collecting a second, orthogonal tilt-series (a so-called “dual-axis” data set), this procedure is more than twice as time consuming, the dose that can be used per image is halved, and alignment errors between the tilt-series can erode the benefit
• Thus a third fundamental limitation in ECT is the anisotropic resolution caused by tilt limitations (the “missing wedge”)
• Because no goniometer is perfect, specimens move laterally and vertically within the column throughout the tilt-series and fhe images must therefore be precisely aligned before a 3-D reconstruction can be calculated
• Sophisticated software has therefore been written to refine estimates of the translations, rotation, magnification, tilt axis, and tilt angle of each image in the tilt-series
• Once the images are aligned, 3-D reconstructions can be calculated with a variety of algorithms
• The most intuitive is “back-projection,” in which a reconstruction is built up by “smearing” the densities in each image back through space in the opposite direction they were projected
• Various software packages have been written to perform these calculations, including IMOD (Mastronarde 2008), the TOM toolbox, and RAPTOR and once reconstructed, tomograms can be “denoised” to improve image contrast and enhance interpretability
• Limitations of ECT include:
  • The sample must be thin (< 0.5 µm)
  • The interpretability of the resulting tomograms is limited by radiation damage
  • The resolution is anisotropic because of tilt limitations
  • The procedure is complicated and requires expensive electron cryo-microscopes
  • Identifying structures of interest in the tomograms can be challenging

• In cryo-ET, a single area of a grid containing many “viral” particles is imaged multiple times, at a variety of tilt angles, and it is the combination of these images that is used to generate a tomogram and subsequently an averaged density map
• There are common techniques used in the field of cryo-EM and cryo-ET for “virus” reconstruction, from data collection to processing and interpretation
• Single particle reconstruction relies on imaging hundreds to hundreds of thousands of “viral” particles, computationally isolating each particle, and then combining the individual particles into a single 3-dimensional (3-D) density map
• Because cryo-EM provides a projection of the “virus” onto the recording medium, the lack of an even distribution in the 3-D orientation of the particles can introduce bias when reconstructing the data
• The process of single particle reconstruction involves isolating each “viral” particle from a set of images, determining its orientation and center, and then using this information to stitch the data back together into a single 3-D representation of the “virus”
• In the presence of structurally diverse samples, a technique that can capitalize on the information content of just a few particles of similar or identical conformation is needed
• The theory behind tomography is that by collecting a series of images from a sample, at a variety of tilt angles, it is possible to reconstruct a 3-D volume density from the 2-D projections
• Under standard tomographic imaging conditions, a series of 71 images are taken from −70° to 70° at a step size of 2° (60° and 80° tilt holders are available as well)
• For single particle reconstructions, preprocessing typically follows the same three steps: screening, boxing, and CTF determination
• Alternatively, preprocessing tomogram data entails aligning the series of tilt images to each other
• The 3-D reconstruction of a “virus” from multiple single particle images is the last step in the computationally intensive process of particle alignment
• The general principle behind the theory is that given a series of single particle images, once you have determined their icosahedral (or asymmetric) orientations, you can combine the data to form one cohesive 3-D model
• The majority of “virus” reconstructions published in the literature are of specimens for which there is some assumed symmetry (the quality of being made up of exactly similar parts facing each other or around an axis) to the map
• The assumption of symmetry is often made because it simplifies the process of orientation determination
• In the case of a “virus” such as HSV-1 in which the structure does not have such a protruding feature that is readily identifiable in raw micrographs, it is more difficult to find the true asymmetric orientation of the particle
• Once the asymmetric orientation of every particle has been determined, the process of reconstructing the “virus” asymmetrically is identical to any other reconstruction in which symmetry is assumed
• The resolution of a map is improved as increasingly more particles are added to the reconstruction but this must be weighed against the observation that some data are of better quality than others, and inclusion of data that contain aberrations may in fact do more harm than good in enhancing the resolution of a reconstruction
• The number of particles required to achieve a specific resolution reconstruction depends on assumptions made about the data, both without and with noise
• The ‘best’ particles are those that have been determined, through the process of iterative alignment and refinement, to consistently score higher than other particles but there is no concrete method to determine a priori which particles are the best,
• Although there is no way to directly control for conformational heterogeneity (the quality or state of being diverse in character or content) within the sample, if there are visible differences in the raw particle data, it is possible to ameliorate this problem by selecting subsets of the data
• Even if ‘bad’ particles make it through these steps of screening, in some cases, the process of data refinement will eliminate particles that are not consistent with the existing pool of data
• The process of creating a 3-D model works by merging all of the 2-D particle images, after CTF correction, into a single 3-D map using 3-D reconstruction programs which typically have a method to generate these 3-D density maps
• A well-resolved tomographic average requires the individual subtomograms containing the extracted particles to be aligned with respect to each other – a process that is rarely as straightforward as in single particle cryo-EM
• Ideally, a tomogram would contain data collected across a full 180°; however, because this is not possible with the currently available cryo-holders, this lack of information from 70° to 90° is manifested as a missing wedge of data in Fourier space, and if it is not corrected for, it can distort the final reconstruction
• An additional complicating factor is that because the tilt angle for a group of particles in a single tomogram is identical, all the particles have the same missing wedge
• To address the fact that the presence of missing data in the Fourier space can hinder proper alignment of the subvolumes, procedures have been developed to circumvent this problem by normalizing the cross-correlations calculated for two particles at different orientations
• Although this approach has been met with success, there is no guarantee that the missing wedge problem has been solved, especially for high-resolution tomographic reconstructions
• Alignment of tomographic data requires the three Euler angles (α, β, γ) for every computationally extracted particle to be determined through a series of orientation searches
• This process is typically initialized through comparison with an approximate model of the “virus” yet, in the event that no adequate reference model is available, it is necessary to generate an initial model from the available data
• This initial model can be further improved through a series of iterative refinements in which the individual subtomograms are classified, aligned, and averaged to a single or multiple 3-D models
• To generate a 3-D model from cryo-ET data, once the orientation search is complete and the particles have been aligned, the data can be reconstructed into a 3-D model by averaging the individual subtomograms together while accounting for the missing wedge information from each particle
• The final step in the structural determination of a “virus” is interpretation of the resulting 3-D density map, specifically resolution determination, segmentation, and model fitting
• However, care must be taken not to overinterpret the map beyond its best approximated resolution
• One of the key components in data interpretation is segmentation of a map
• For “viruses,” when symmetry is assumed in the reconstruction, it is possible to extract just the asymmetric unit and segment it accordingly; however, as more “viruses” are reconstructed without imposed symmetry, it will become necessary to consider the map as a whole
• There are many programs which use a variety of approaches, such as watershed and principal component analysis or multiscale segmentation, to identify individual protein components in the “virus”
• Although these algorithms save a great deal of time during segmentation, their accuracy depends on the resolution and the overlapping density between adjacent molecules
• Regardless of what software is used, accurate segmentation remains a challenging task
• These images can then be aligned to each other using fiducial markers present in the images from which a volume (a tomogram) can be extracted
• From this volume, it is possible to extract individual subtomograms corresponding to each of the particles and these subtomograms can then be classified, aligned, and averaged to obtain a single 3-D model
• In tomography, however, because a single area of the grid is imaged approximately 70 times, the sample is subjected to far more radiation, making damage a consideration
• The structural features of most “viruses” are lost in the noisy images recorded from the electron microscope
• After extensive data processing and reconstruction, it is said that it has become possible to resolve these features – in some instances at near-atomic resolutions
• However, most of this work has been augmented by image processing techniques that computationally enhance image contrast
• Advances in fabrication techniques have enabled the microscopist to do so directly by altering the optics of the electron microscope

Dr. Peter McCullough saw some pretty pictures claiming to be “SARS-COV-2” based on reconstructed 3-D images taken from cryo-EM. In his exuberance, he rushed to write an article about this ground-breaking evidence that he was sure would convince the naysayers to join him on “Team Rational.” Dr. McCullough was certain that the computer-generated recreations would be the visual evidence needed to sway these naysayers even though they had already meticulously poured over numerous TEM images claiming to be “viruses” and remained unconvinced after doing so. “A picture is worth a thousand words,” Dr McCullough gleefully sang! “Show them these works of art!” However, what Dr. McCullough somehow forgot to take into account during his reckless abandon is that the thousand words behind the picture matter. And in the case of his “works of art,” the words behind the creation of these images speak much louder than the images themselves. 

When we break down the methods behind the creation of Dr. McCullough’s fine art, we find that the particles are once again the direct result of unpurified cell culture supernatant. The “viruses” in question were “grown” off site in Vero cells and were then maintained in Dulbecco’s Modified Eagle Medium (DMEM) Gibco™, with 100 U/ml penicillin, 100 μg/ml streptomycin (Pen-Strep) and 10% (v/v) heat-inactivated fetal calf serum (FCS). Thus, we do not have any evidence that the particles imaged were ever in the fluids of a sick host nor is there any evidence that the particles are pathogenic in any way. What we have is evidence that when numerous toxic substances and foreign materials are mixed together in a petri dish with African green monkey kidney cells and incubated for days, they break apart and die leaving various particles left in the wake. The images claiming to be “viral” particles are either cellular debris or potentially artifacts created during the imaging process. There is absolutely zero evidence that the particles reconstructed and recreated are replication-competent “viruses.”

However, if that is not enough to make one doubt the “difficult to deny” power of these images, factor in the various processes that must be undertaken just to reconstruct these works of art. After the many alterations done during the cell culture process, the sample is flash frozen, thinned to the appropriate size, and then battered with intense heat from the electron beam in order to generate images. The sample is tilted along an axis while numerous recordings are obtained. Meanwhile, the longer the sample is subjected to this extreme heat, the further it is damaged and degraded, distorting the images. After the recording, the various 2-D images are aligned and merged using computer programs and different algorithms to fill in the missing data. The computer software maps the result onto a 3-D representation of what it has determined that the particles look like. Numerous assumptions, estimates, and interpretations are made throughout this process in order to generate the desired recreation. 

Thus, when one really thinks about it, McCullough’s description of these images as “works of art” may be the most accurate description for them. The images stem from human skill and imagination. They are used to express certain ideas, emotions, and feelings. The reconstructions are derived from a creative process and displayed for the subjective interpretation of the viewer. For all intents and purposes, the cryo-EM images are “works of art.” However, one thing they are not are slam-dunk proof for the existence of “SARS-COV-2” nor any other “virus.” They are images of random particles that only have meaning to the eye of the beholder. So while McCullough’s description may be perfect for these images, I’m not certain that it conveys the message that he thinks it does. If Dr. McCullough wants these cryo-EM images to be taken seriously as proof for the existence of “SARS-COV-2,” I think we can all agree on one thing he may not have thought about in his joyous proclamation.