Biological cells depend not only on the physical matter but essentially on pre-programmed information and at least a twenty five informational code and language systems which are used to host and store that information, in order to arrange and produce the complex cellular structures essential for life, and keep the life-essential functions, that is the reproduction, metabolism. food uptake, intracellular organizational arrangement, growth and development, permanence, change, and adaptation. Living cells host multiple kinds of informational code systems which are used to store complex instructional/specifying information ( CSI ). All code systems, languages, information, and translation systems can be tracked back to an intelligent origin. Evolution is not a driving force to explain the origin of cells and its language systems and programmed information content. Nor does physicochemical attraction explain the arrangement of nucleotides, molecules and amino acids resulting in the formation of complex molecular machines and intracellular molecular production lines. The only alternative to intelligence is random self-assembly by unguided lucky events. Random chaotic events are however too unspecific to explain the extremely organized, controlled, error check and repair mechanisms, and factory-like production systems that cells host. Therefore, biological cells, cell code systems and the coded information ( CSI ), have most probably a mind as the causal origin.
1. Regulation, governing, controlling, recruiting, interpretation, recognition, orchestrating, elaborating strategies, guiding, instruct are all tasks of the gene regulatory network.
2. Such activity can only be exercised if no intelligence is present if the correct actions were pre-programmed by intelligence.
3. Therefore, most probably, the gene regulatory network was programmed by an intelligent agency.
Another outstanding implication of the existence of organic codes in Nature comes from the fact that any code involves meaning and we need therefore to introduce in biology, with the standard methods of science, not only the concept of biological information but also that of biological meaning. The study on the organic codes, in conclusion, is bringing to light new mechanisms that operated in the history of life and new fundamental concepts. It is an entirely new field of research, the exploration of a vast and still largely unexplored dimension of the living world, the real new frontier of biology.
The Genetic Code
The Genomic regulatory Code
The Splicing Codes
The Metabolic Code
The Signal Transduction Codes
The Signal Integration Codes
The Histone Code
The Tubulin Code
The Sugar Code
The Glycomic Code
The non-ribosomal code
The Calcium Code
The RNA code
A domain substrate specificity code of Nonribosomal peptide synthetases (NRPS)
The DNA methylation Code
The coactivator/corepressor/epigenetic code
The transcription factor code
The post-translational modification code for transcription factors
The HOX Code
The Synaptic Adhesive Code
The Apoptosis Code
The Ubiquitin Code
The bioelectric code
The transcriptional cis-regulatory code
The phosphorylation code
CONTROL OF TRANSCRIPTION BY SEQUENCESPECIFIC DNA-BINDING PROTEINS
The transcription factor code: defining the role of a developmental transcription factor in the adult brain.
For the human brain to develop and function correctly, each of its 100 billion neurons must follow a specific and pre-programmed code of gene expression. This code is driven by key transcription factors that regulate the expression of numerous proteins, moulding the neurons identity to create its unique shape and electrical behaviour.
Unraveling a novel transcription factor code determining the human arterial-specific endothelial cell signature
Our pioneering profiling study on freshly isolated ECs unveiled a combinatorial transcriptional code that induced an arterial fingerprint more proficiently than the current gold standard, HEY2, and this codeconveyed an in vivo arterial-like behavior upon venous ECs.
The transcriptional regulatory code of eukaryotic cells--insights from genome-wide analysis of chromatin organization and transcription factor binding.
The term 'transcriptional regulatory code' has been used to describe the interplay of these events in the complex control of transcription. With the maturation of methods for detecting in vivo protein-DNA interactions on a genome-wide scale, detailed maps of chromatin features and transcription factor localization over entire genomes of eukaryotic cells are enriching our understanding of the properties and nature of this transcriptional regulatory code.
The Splicing code
rigin and evolution of spliceosomal introns
The rna binding protein binding code
A compendium of RNA-binding motifs for decoding gene regulation
microRNA binding code
The code within the code: microRNAs target coding regions
The Glycan or Sugar Code
Biological information transfer beyond the genetic code: the sugar code
The non-ribosomal code
A allowed the identification of amino acid residues that play a decisive role in the coordination of the substrate and have lead to the concept of the so-called nonribosomal code, which allows the prediction of A-domain selectivity on the basis of its primary sequence
CONTROL OF TRANSCRIPTION BY SEQUENCESPECIFIC DNA-BINDING PROTEINS 1
Coded information can always be tracked back to a intelligence, which has to set up the convention of meaning of the code, and the information carrier, that can be a book, the hardware of a computer, or the smoke of a fire of a indian tribe signalling to another. All communication systems have an encoder which produces a message which is processed by a decoder. In the cell there are several code systems. DNA is the most well known, it stores coded information through the four nucleic acid bases. But there are several others, less known. Recently there was some hype about a second DNA code. In fact, it is essential for the expression of genes. The cell uses several formal communication systems according to Shannon’s model because they encode and decode messages using a system of symbols. As Shannon wrote :
“Information, transcription, translation, code, redundancy, synonymous, messenger, editing, and proofreading are all appropriate terms in biology. They take their meaning from information theory (Shannon, 1948) and are not synonyms, metaphors, or analogies.” (Hubert P. Yockey, Information Theory, Evolution, and the Origin of Life, Cambridge University Press, 2005).
An organism’s DNA encodes all of the RNA and protein molecules required to construct its cells. Yet a complete description of the DNA sequence of an organism—be it the few million nucleotides of a bacterium or the few billion nucleotides of a human—no more enables us to reconstruct the organism than a list of English words enables us to reconstruct a play by Shakespeare. In both cases, the problem is to know how the elements in the DNA sequence or the words on the list are used. Under what conditions is each gene product made, and, once made, what does it do? The different cell types in a multicellular organism differ dramatically in both structure and function. If we compare a mammalian neuron with a liver cell, for example, the differences are so extreme that it is difficult to imagine that the two cells contain the same genome. The genome of a organism contains the instructions to make all different cells, and the expression of either a neuron cell or liver cell can be regulated at many of the steps in the pathway from DNA to RNA to Protein. The most important imho is CONTROL OF TRANSCRIPTION BY SEQUENCESPECIFIC DNA-BINDING PROTEINS, called transcription factors or regulators. These proteins recognize specific sequences of DNA (typically 5–10 nucleotide pairs in length) that are often called cis-regulatory sequences. Transcription regulators bind to these sequences, which are dispersed throughout genomes, and this binding puts into motion a series of reactions that ultimately specify which genes are to be transcribed and at what rate. Approximately 10% of the protein-coding genes of most organisms are devoted to transcription regulators. Transcription regulators must recognize short, specific cis-regulatory sequences within this structure. The outside of the double helix is studded with DNA sequence information that transcription regulators recognize: the edge of each base pair presents a distinctive pattern of hydrogen-bond donors, hydrogen-bond acceptors, and hydrophobic patches in both the major and minor grooves. The 20 or so contacts that are typically formed at the protein–DNA interface add together to ensure that the interaction is both highly specific and very strong.
These instructions are written in a language that is often called the ‘gene regulatory code’. The preference for a given nucleotide at a specific position is mainly determined by physical interactions between the aminoacid side chains of the TF ( transcription factor ) and the accessible edges of the base pairs that are contacted. It is possible that some complex code, comprising rules from each of the different layers, contributes to TF– DNA binding; however, determining the precise rules of TF binding to the genome will require further scientific research. So, Genomes contain both a genetic code specifying amino acids, and this regulatory code specifying transcription factor (TF) recognition sequences. We find that ~15% of human codons are dual-use codons (`duons') that simultaneously specify both amino acids and TF recognition sites. Genomes also contain a parallel regulatory code specifying recognition sequences for transcription factors (TFs) , and the genetic and regulatory codes have been assumed to operate independently of one another, and to be segregated physically into the coding and non-coding genomic compartments. the potential for some coding exons to accommodate transcriptional enhancers or splicing signals has long been recognized
In order for communication to happen, 1. The sequence of DNA bases located in the regulatory region of the gene is required , and 2. transcription factors that read the code. If one of both is missing, communication fails, the gene that has to be expressed, cannot be encountered, and the whole procedure of gene expression fails. This is a irreducible complex system. The gene regulatory code could not arise in a stepwise manner either, since if that were the case, the code has only the right significance if fully developed. Thats a example par excellence of intelligent design.. The fact that these transcription factor binding sequences overlap protein coding sequences, suggest that both sequences were designed together, in order to optimize the efficiency of the DNA code. As we learn more and more about DNA structure and function, it is apparent that the code was not just hobbled together by the trial and error method of natural selection, but that it was specifically designed to provide optimal efficiency and function.
Stephen Meyer puts it that way in his excellent book: Darwins doubt pg.270:
INTEGRATED CIRCUITRY: DEVELOPMENTAL GENE REGULATORY NETWORKS
Keep in mind, too, that animal forms have more than just genetic information. They also need tightly integrated networks of genes, proteins, and other molecules to regulate their development—in other words, they require developmental gene regulatory networks, the dGRNs . Developing animals face two main challenges. First, they must produce different types of proteins and cells and, second, they must get those proteins and cells to the right place at the right time.20 Davidson has shown that embryos accomplish this task by relying on networks of regulatory DNA-binding proteins (called transcription factors) and their physical targets. These physical targets are typically sections of DNA (genes) that produce other proteins or RNA molecules, which in turn regulate the expression of still other genes.
These interdependent networks of genes and gene products present a striking appearance of design. Davidson's graphical depictions of these dGRNs look for all the world like wiring diagrams in an electrical engineering blueprint or a schematic of an integrated circuit, an uncanny resemblance Davidson himself has often noted. "What emerges, from the analysis of animal dGRNs," he muses, "is almost astounding: a network of logic interactions programmed into the DNA sequence that amounts essentially to a hardwired biological computational device." These molecules collectively form a tightly integrated network of signaling molecules that function as an integrated circuit. Integrated circuits in electronics are systems of individually functional components such as transistors, resistors, and capacitors that are connected together to perform an overarching function. Likewise, the functional components of dGRNs—the DNA-binding proteins, their DNA target sequences, and the other molecules that the binding proteins and target molecules produce and regulate—also form an integrated circuit, one that contributes to accomplishing the overall function of producing an adult animal form.
Davidson himself has made clear that the tight functional constraints under which these systems of molecules (the dGRNs) operate preclude their gradual alteration by the mutation and selection mechanism. For this reason, neo-Darwinism has failed to explain the origin of these systems of molecules and their functional integration. Like advocates of evolutionary developmental biology, Davidson himself favors a model of evolutionary change that envisions mutations generating large-scale developmental effects, thus perhaps bypassing nonfunctional intermediate circuits or systems. Nevertheless, neither proponents of "evo-devo," nor proponents of other recently proposed materialistic theories of evolution, have identified a mutational mechanism capable of generating a dGRN or anything even remotely resembling a complex integrated circuit. Yet, in our experience, complex integrated circuits—and the functional integration of parts in complex systems generally—are known to be produced by intelligent agents—specifically, by engineers. Moreover, intelligence is the only known cause of such effects. Since developing animals employ a form of integrated circuitry, and certainly one manifesting a tightly and functionally integrated system of parts and subsystems, and since intelligence is the only known cause of these features, the necessary presence of these features in developing Cambrian animals would seem to indicate that intelligent agency played a role in their origin
The Calcium Code
Steady-state stomatal closure could be restored if calcium oscillations similar to wild type were imposed; thus, the cells have an intact downstream signaling pathway, but cannot initiate the proper calcium oscillation code to trigger the pathway.
Defined changes of cytosolic Ca2+ concentration are triggered by cellular second messengers, such as NAADP, IP3, IP6, Sphingosine-1-Phospate, and cADPR and it is evident that the identity and intensity of a specific stimulus impulse results in stimulus-specific and dynamic alterations of cytosolic Ca2+ concentration. This heterogeneity of increases in cytosolic-free Ca2+ ion concentration in terms of duration, amplitude, frequency, and spatial distribution lead A.M. Hetherington and coworkers to formulate the concept of “Ca2+ signatures”. Signal information would be encoded by a specific Ca2+ signature that is defined by precise control of spatial, temporal, and concentration parameters of alterations in cytosolic Ca2+ concentration.
The RNA code
In 2004, oncologist Gideon Rechavi at Tel Aviv University in Israel and his colleagues compared all the human genomic DNA sequences then available with their corresponding messenger RNAs — the molecules that carry the information needed to make a protein from a gene.
They were looking for signs that one of the nucleotide building blocks in the RNA sequence, called adenosine (A), had changed to another building block called inosine (I). This 'A-to-I editing' can alter a protein's coding sequence, and, in humans, is crucial for keeping the innate immune response in check. “It sounds simple, but in real life it was really complicated,” Rechavi recalls. “Several groups had tried it before and failed” because sequencing mistakes and single-nucleotide mutations had made the data noisy. But using a new bioinformatics approach, his team uncovered thousands of sites in the transcriptome — the complete set of mRNAs found in an organism or cell population — and later studies upped the number into the millions1.
Inosine is something of a special case: researchers can readily detect this chink in the armour by comparing DNA and RNA sequences. But at least one-quarter of our mRNAs harbour chemical tags — decorations to the A, C, G and U nucleotides — that are invisible to today's sequencing technologies. (Similar chemical tags, called epigenetic markers, are also found on DNA.) Researchers aren't sure what these chemical changes in RNA do, but they're trying to find out.
A wave of studies over the past five years — many of which focus on a specific RNA mark called N6-methyladenosine (m6A) — have mapped these alterations across transcriptomes and demonstrated their importance to health and disease. But the problem is vast: these marks coat not only mRNA but other RNA transcripts as well, and they cut across all the domains of life and beyond, marking even viruses with their presence.
The modifications themselves are not new. What has given them meaning and driven epitranscriptomics into the spotlight is the discovery of enzymes that can add, remove and interpret them. In 2010, chemical biologist Chuan He at the University of Chicago, Illinois, proposed that these chemical tags could be reversible and important regulators of gene expression. Not long afterwards, his group demonstrated2 the first eraser of these marks on mRNA, an enzyme called FTO. That discovery meant that m6A wasn't just a passive mark — cells actively controlled it. And this realization came at about the same time that global approaches, harnessing the power of next-generation sequencing, made it possible to map m6A and other modifications across the transcriptome.
Last edited by Admin on Wed Feb 27, 2019 9:36 am; edited 35 times in total