“If all viruses suddenly disappeared, the world would be a wonderful place for about a day and a half, and then we’d all die – that’s the bottom line,” says Tony Goldberg, an epidemiologist at the University of Wisconsin-Madison. “All the essential things they do in the world far outweigh the bad things. ...
"Most
people are not aware of the role viruses play in supporting much of
life on Earth, because we tend to focus only on the ones that cause
humanity trouble. Nearly all virologists solely study pathogens; only
recently have a few intrepid researchers begun investigating the viruses
that keep us and the planet alive, rather than kill us."
“It’s a small school of scientists who are trying to provide a fair
and balanced view of the world of viruses, and to show that there are
such things as good viruses,” Goldberg says.
"What scientists know for sure is that without viruses, life and the
planet as we know it would cease to exist. And even if we wanted to, it
would probably be impossible to annihilate every virus on Earth. But by
imagining what the world would be like without viruses, we can better
understand not only how integral they are to our survival, but also how
much we still have to learn about them."
Because, as is pointed out in the quote above "Nearly all virologists solely study pathogens", and I might add that they work for those who are of the "kill anything that moves" ilk (On The Origin of The Bully Religion - 2).
The application of quantum mechanics to OHC is trivial once one has calculated potential enthalpy using the TEOS-10 Org software.
Dredd Blog uses the C++ version (which can be downloaded at no charge here) because the C++ version was crafted by regular Dredd Blog reader Randy.
These quantum mechanical aspects have not yet been grafted into the TEOS-10 library, but that library is essential to accurate preparation prior to calculations of photon dynamics (see Section VI at Quantum Oceanography).
In that first post of this series, one can see the potential enthalpy patterns and their relation to quantum photon patterns.
The photon patterns match the potential enthalpy patterns (OHC).
It is a series that has up until now dealt with some of the perplexing questions that scientists wonder about concerning how viruses and their genes came into existence in the first place (The Uncertain Gene - 2, On The Origin of the Genes of Viruses).
Now that genetics has become part of the saga, the "genes" part of a virus genome expressed by virologists consists of an arrangement of "bases" ("ACGT") in various sequences ("CATG", "TCGA", "ATGC", etc.) which result in a different viral "look and feel" ... and behavior.
II. Parts Are Parts
Viruses
are not living carbon-based life forms like cells that can reproduce
themselves.
No, instead they are like other machines in that they require carbon based life forms to reproduce them.
They cannot reproduce themselves; they must be reproduced by
biotic, carbon-based life forms (cells).
So, combinations of virus parts like the "gene" can be compared to equipment that has special functions (carburetor, transmission, axles, wheels, and the like).
Using the word "gene" is a hangover from a couple of hundred years ago when the science was absent of the concept of abiology, and was of the notion that viruses and DNA were alive, were biotic (DNA is Not Alive).
An abundance of the viral parts, comprising large parts lists, have been found on the surface of biological cells:
"Typically, the nuclear genome encoded RNAs (ngRNA) are not expected to be present on the surface of eukaryotic cells with intact cell membranes ... [except for 'leakage'] To confirm that the Surface-FISH signals are not a result of RNA leakage from damaged cell membranes, we combined Malat1 Surface-FISH with a transmission-through-dye (TTD) microscopic analysis, where only live cells with intact membranes are fluorescently labeled ... signals appeared on cells with perfectly intact membranes ... [thus, their techniques] suggest the presence of specific nuclear-encoded transcripts on the surface of intact live cells."
(RNA on Cell Surface, emphasis added). That paper is about parts just laying around on the surface of a cell like parts in a junk yard.
But again, viruses are like machines in another aspect, that is, they can modify other machines.
That change, to a certain degree, is automated:
"Genetic instability of microorganisms is an inherent property allowing rapid microbial evolution to adapt to ever changing ecologic niches. This is particularly true of RNA viruses such as influenza viruses, flaviviruses, enteroviruses, and coronaviruses, which have inherently deficient or absent polymerase error correction mechanisms and are transmitted as quasispecies or swarms of many, often hundreds or thousands of, genetic variants. Emergences of viral diseases begin with the genetic plasticity of the infectious agent, which may repeatedly encounter ecologic niches into which it can evolve and adapt under facilitative circumstances, e.g., those provided by the hosts in the context of the host environment. For viruses transmitted by person-to-person mechanisms, transmission by quasispecies may increase the likelihood that one or more viral variants within the quasispecies will be infectious for cells of a new host, leading to infection, viral amplification, and expansion of a new and different quasispecies, facilitating onward transmission ...".
...
"Major portals of host entry for infectious agents include those that are visibly external to the environment such as the skin or that can be reached directly from the environment such as the respiratory and gastrointestinal tracts, as well as organs reached systemically such as the liver, heart, and other internal organs. Human beings have many different organ systems, each with many different cell types, and with each cell having arrays of different receptors; therefore, it is not surprising that switching of a pathogen from an animal host to humans results in very different clinical and epidemiologic outcomes, including different disease manifestations and transmission mechanisms. These factors ultimately relate to the potential for establishment of infection in the new host as well as the likelihood of sustained transmission within the new host population and, as such,have a bearing on whether host-switching succeeds or fails. SARS-CoV and SARS-CoV-2 enter cells via ACE-2 receptors (Wang et al., 2020), found on lung alveolar epithelial cells, gastrointestinal enterocytes, arterial and venous endothelial cells, and arterial smooth muscle cells, among other cell types (Hamminget al., 2004; Wang et al., 2020), which explains the excretion of SARS-CoV-2 and potential transmission via the respiratory and enteric routes. With regard to the latter, although SARS-CoV-2 infects cells of the gastrointestinal tract, fecal transmission has not to date been implicated in significant person-to-person viral spread."
(How We Got to COVID-19, emphasis added). The "enteric routes" mentioned in that paper goes from the mouth to the anus/rectum (it's the gut microbiome).
The Dredd Blog series "On The Origin Of The Home Of COVID-19" (links are in the first sentence of Section I above) has hypothesized that "the mass-slaughter-of-animals-for-food industry" is a source of the transmission of the genes of viruses (On The Origin Of The Home Of COVID-19-15).
The posts in that series include the hypothesis that the export of slaughtered meat saturated with viral parts is a source of the spread of that tiny, but pathogenic, machine world.
In fact, that human gut filled with food from "the mass-slaughter-of-animals-for-food industry" is an early warning system for Covid-19:
"A surge in internet searches about gut ailments is helping researchers predict the next Covid-19 hotspots, a study has revealed. Massachusetts General Hospital found areas where there was a spike in Google queries relating to diarrhea and loss of appetite frequently reported a sharp rise in cases of coronavirus three to four weeks later. Other markers included a loss of taste, nausea and abdominal pain."
Thus, our diet is the major factor impacting the gastrointestinal realm:
"The composition of the human gut microbiome is determined by
many factors. Eran Segal and colleagues performed an extensive
statistical analysis of the largest metagenomics-sequenced human cohort
so far to determine the contribution of host genotype to microbiome
composition. Host genetics has only a minor influence on microbiome variability, which is more strongly associated with environmental factors such as diet.
The authors propose a 'microbiome-association index' that describes the
association of the microbiome with host phenotype. Combining this
measurement with host genetic and environmental data improves the
accuracy of predictions about several human metabolic traits, such as
glucose and obesity traits."
... A wealth of evidence suggests that this incredibly diverse microbial community is regulated by host genetic factors, and more importantly, environmental and dietary factors."
(On The Origin Of The Home Of COVID-19-15). So, it is a logical deduction to say that our research should include a search of the human gut microbiome for "equipment" and "parts" of the viruses that make up the Coronaviridae realm.
III. The Appendices
The appendices to today's post include searches and comparisons of the Coronaviridae realm (Coronavirus genomes – NCBI Datasets) with the viruses in the GVD (human gut database) ... (GVD Download) (the five largest bases in the GVD are used in the comparisons).
The appendices detail that the "fragmented" residue of Coronaviridae viruses exists in the human gut microbiome.
That is, "equipment" (large segments of the genome ... e.g. "genes") and "parts" (small sections of "equipment") are all over the place in the human gut.
When writing the analysis software, I focused on comparing various machines and parts, that is, comparing the gene bases, the mat_peptide bases, the UTR bases, and the stem_loop bases of the Coronaviridae viruses to the human gut genome machines and parts (could I find the same or relatively similar matches in both genomes?).
Today's appendices confirm the extracted quote from the paper linked to in Section I above:
"Genetic instability of microorganisms is an inherent property ... This is particularly true of RNA viruses such as ... coronaviruses, which ... are transmitted as ... genetic variants. Emergences of viral diseases begin with the genetic plasticity ..."
(ibid). The tables in the appendices show that "genetic instability" (which I would rather characterize as "sharing of machine equipment and parts") is apparent because Coronaviridae parts and segments (parts of parts, e.g. nuts & bolts) are spread throughout the human gut microbiome.
This spread of the "equipment" and "parts" of the Coronaviridae realm throughout the human gut microbiome is to be expected according to the hypothesis that "the mass-slaughter-of-animals-for-food industry" makes Coronaviridae by destroying the homes of commensal, mutualistic, and symbiotic viruses because that industry generates the breakup of animal-gut single-celled microbes via antibiotics and other toxins.
Then the spread expands by exporting and selling meat products around the world as food which makes up the diet that goes through the human gut in many places.
So, just to reemphasize it, the diet is the food we eat which they produce:
"The composition of the human gut microbiome is determined by ... environmental factors such as diet ... this measurement with host genetic and environmental data improves the accuracy of predictions about several human metabolic traits, such as glucose and obesity traits ... regulated by ... environmental and dietary factors."
And finally, predictions of Covid-19 outbreaks can be made by analyzing the amount of gastrointestinal (gut) problems questions asked after the food is digested:
"A surge in internet searches about gut ailments is helping researchers predict the next Covid-19 hotspots ..."
The world's first Gut Virome Database (GVD) tells us a lot about viruses in homo sapiens:
"The first step in studying viruses in complex communities is being able to detect them. Problematically, identifying viral sequences in large, mixed-community datasets is notoriously challenging. ... Further, once viruses are detected there is no standard applied on how viral contigs translate into “species”-level sequences that are to be used as a “working” virus pool for downstream analysis. The lack of viral analysis standards could partly explain the estimated, highly variable (14%–87%) ... rates of virus detection between studies. In addition, factors such as differences in sample processing ... broad under-representation of viral genome space in reference databases ... lack of culturable host gut microbes ... and inter-individual variation add further variability ...
Fig. 2 Antibiotics Kill Helpful Bacteria
Further, although viral reference datasets are being generated at unprecedented rates ... these new data are rarely incorporated for cross-comparisons, which would inflate virus novelty in new datasets and/or leaves many virus sequences undetected. In response to these challenges and to enable virome-centric research in health and disease, we sought to establish a comprehensive, easy-access database dedicated to human gut viruses. This effort would enable future gut microbiome research by augmenting virus detection and helping establish processing standards for human gut viruses."
(The Gut Virome Database Reveals..., emphasis added). I downloaded an early version of the GVD which had fewer rows of data than the latest which I am processing now.
The latest has 33,242 rows which are now in my SQL database, and are being analyzed at this time.
One program is running now, which will be discussed when it finishes comparing SARS-CoV-2 with the phage DNA in the GVD (it finished up, see the appendices).
There are some unprecedented things that have been discovered about "bacteriophages" (phages) in the human enteric virus microbiome.
The mysterious intelligence of single celled creatures has
also been under-covered and understudied (the video at the end of this
post is shocking in that regard).
The presenter (Eshel Ben-Jacob) at 55 min into video below, details what some would call group co-operation or group-mind at the level of bacteria.
Fig. 4
What we call or name something may not be clear, so let's focus on what the bacteria do.
They do things as if they "knew" what to do, they do things as if they can "see", they do things as if they can communicate effectively with one another.
Fig. 5
When machines do that we call it "AI", the "I" meaning intelligence.
Shock!
So what is it when living organisms do it?
In Fig. 3 - Fig. 5 (snapshots from the video) two microbes communicate and exchange viruses and other valuables.
The microbes that know how to do something will share that information (and viruses) with other microbes.
What about intelligence in viruses?
What about "machine intelligence" in our gut microbiome (in the zillions of microbes and phages in, on, and around us)?
III. Machine Intelligence
Currently scientists are beginning to point out that there is an incredible amount of "machine intelligence" within the single celled microorganisms we are composed of:
“Our cells, and the cells of all organisms, are composed of molecular machines. These machines are built of component parts, each of which contributes a partial function or structural element to the machine. How such sophisticated, multi-component machines could evolve has been somewhat mysterious, and highly controversial.” Professor Lithgow said.
...
Many cellular processes are carried out by molecular ‘machines’
— assemblies of multiple differentiated proteins that physically
interact to execute biological functions ... Our experiments show that
increased complexity in an essential molecular machine evolved
because of simple, high-probability evolutionary processes, without
the apparent evolution of novel functions. They point to a plausible
mechanism for the evolution of complexity in other multi-paralogue
protein complexes.
...
The most complex molecular machines are found within cells.
...
Writing in the journal PLoS Pathogens, the team from Queen Mary's School of Biological and Chemical Sciences show how they studied the molecular machine
known as the 'type II bacterial secretion system', which is
responsible for delivering potent toxins from bacteria such as
enterotoxigenic E. coli and Vibrio cholerae into an infected
individual.
Professor Richard Pickersgill, who led the research, said: "Bacterial
secretion systems deliver disease causing toxins into host tissue. If we can understand how these machines work, then we can work out how it they might be stopped." [or started, or perpetuated as proper and necessary]
IV. A Look At The SARS-CoV-2 And The Coronavirus Realm Within
While perusing the world's first GVD mentioned in Section I above, I noticed a very large genome which I consider to be a Prophage ("It is not rare for bacteria to contain multiple prophages in their
chromosomes, which then constitute a sizable part of the total bacterial
DNA" - Prophage Genomics).
The 15 appendices to today's post display analyses of two virus types: 1) coronavirus pre-SARS-CoV-2, and 2) SARS-CoV-2 itself.
Those two are compared to the GVD prophage "Ma_2019_SRR413675", which is the largest one in the GVD (392,017 bases!).
The number of coronavirus genomes compared is 590 viruses, while the SARS-CoV-2 comparison total is 13,827 (the coronavirus and SARS-CoV-2 genomes were downloaded from GenBank).
The process is to: 1) gather a segment of the genome (composed of 10 bases, i.e. a segment of 10 "ACGT's"), 2) search the GVD prophage genome for that sequence, and 3) then move on to the next segment.
That is repeated until the end of the coronavirus or SARS-CoV-2 genome is reached.
A count of the number of matches (a segment of a coronavirus or a segment of a SARS-CoV-2 virus matches a segment in the GVD prophage genome) is shown in the appendices together with the percentage of the coronavirus or SARS-CoV-2 virus segments found in the GVD prophage's genome.
The table below is the result of comparing coronavirus DNA to the human gut's longest bacteriophage DNA identified as Ma_2019_SRR413675 which is 392,017 bases long.
map_id = coronavirus DNA's GenBank id
DNA length = the length of the coronavirus DNA
sequence matches = the count of segments (10 bases each) of the coronavirus DNA that were found in the human gut's bacteriophage DNA
matches percent = the percentage of the coronavirus DNA that was found in the human gut's bacteriophage DNA
The table below is the result of comparing SARS-Cov-2 DNA to the human gut's longest bacteriophage DNA identified as Ma_2019_SRR413675 which is 392,017 bases long.
map_id = SARS-CoV-2 DNA's GenBank id
DNA length = the length of the SARS-CoV-2 DNA
sequence matches = the count of segments (10 bases each) of the SARS-CoV-2 that were found in the human gut's bacteriophage DNA
matches percent = the percentage of the SARS-CoV-2 DNA that was found in the human gut's bacteriophage DNA
