Essential Cell Biology (Part 3)

CSI 5180 - Machine Learning for Bioinformatics

Marcel Turcotte

Version: Jan 17, 2025 10:51

Preamble

Quote of the Day

 What will viruses do next? AI is helping scientists predict their evolution

The holy grail of pandemic preparedness is being able to predict how a virus will evolve just by looking at its genetic sequence. Those days are still a way off, but a growing number of research groups are using artificial intelligence (AI) to predict the evolution of SARS-CoV-2, influenza and other viruses.

Mallapaty (2025) (6 to 7 minutes)

Previsous Lecture

• The Central Dogma delineates the flow of genetic information: DNA is transcribed into RNA, which is subsequently translated into proteins.

• This process involves three primary stages: replication, transcription, and translation.

• Given that DNA resides in the nucleus, while protein synthesis occurs in the cytoplasm, the intermediate molecule messenger RNA (mRNA) is essential for conveying genetic information.

• Base pair complementarity is crucial for the fidelity of both replication and transcription processes.

• Proteins such as helicase, polymerase, and primase are integral to these processes, facilitating DNA unwinding, strand synthesis, and primer formation, respectively.

• Transcription initiation of protein-coding genes is regulated by specific DNA sequences known as promoter signals.

Summary

This lecture examines the latter stages of the central dogma, focusing on translation and its dependence on the genetic code, codons, and tRNA-mediated amino acid delivery. It then shifts to genome organization, highlighting repetitive DNA and its impact on assembly algorithms and disease. The lecture concludes by outlining proteomic concepts and the intricate networks of biological interactions, emphasizing the multifaceted nature of gene expression and regulation.

General objective

• Describe the central dogma, transcription, translation, and genetic code.

Learning Outcomes

• Explain the role of mRNA, tRNA, and ribosomes in protein synthesis.
• Recognize how codons and the degenerate genetic code direct amino acid selection.
• Identify start and stop codons, and interpret open reading frames (ORFs).
• Compare genomic components (exons, introns, repetitive sequences) and their organization.
• Distinguish between the genome, transcriptome, and proteome, and assess their dynamic nature.
• Understand how repetitive elements complicate sequence assembly and associate with disease.
• Recall the importance of protein–protein and protein–DNA interactions in biological networks.

As a reminder, for individuals accessing the network via a uOttawa IP address, two introductory textbooks on fundamental cellular biology concepts tailored for computer scientists are available for free download: Cohen and Cohen (2024) and Widła (2013). Today’s lecture will focus on exploring Chapters 3, 4, 5, 6, and 9 from Widła (2013).

Translation

Translation (RNA to Protein)

Attribution: www.yourgenome.org

Translation (RNA to Protein)

• The genetic code cannot follow a one-to-one mapping:

\[ 4^1 < 20 \]

\[ 4^2 < 20 \]

\[ 4^3 > 20 \]

A genetic code of one or two nucleotides per codon is insufficient to encode all 20 amino acids. A single nucleotide provides only 4 combinations (A, T, C, G), and two nucleotides offer 16 combinations (\(4^2\)), both of which are inadequate. A three-nucleotide codon yields 64 combinations (\(4^3\)), providing redundancy and accommodating all amino acids.

Translation (RNA to Protein)

• Each set of three consecutive nucleotides forms a codon, which specifies a unique amino acid.

\[ 4^3 = 64 \]

Translation (RNA to Protein)

• Codons are arranged in contiguous, non-overlapping triplets.

• Given the 64 possible codons, the genetic code is degenerate, meaning that multiple codons can correspond to the same amino acid.

Transcription, the process of synthesizing RNA from DNA, can be reversed to regenerate the original DNA sequence, a mechanism utilized by retroviruses through an enzyme known as reverse transcriptase. This enzyme facilitates the integration of viral RNA into the host genome by converting it back into DNA. In contrast, the translation process, which synthesizes proteins from RNA, is inherently irreversible. This irreversibility arises because the genetic code is degenerate: multiple codons can encode the same amino acid, and the specific codon sequence used during translation is not retained in the resulting protein, precluding the reconstruction of the original RNA sequence.

What are the implications of the final point?

Universal Genetic Code

First make sure to understand the code. During translation, messenger RNA (mRNA) is read sequentially in non-overlapping triplets of nucleotides known as codons. Each codon corresponds to a specific amino acid or a stop signal in protein synthesis. For instance, the codon UUU encodes phenylalanine (Phe), while AGA encodes arginine (Arg).

It is important to note that amino acids do not have a uniform number of corresponding codons. Arginine, for example, is encoded by six different codons, whereas methionine is encoded by only one. Phenylalanine has two codons, while leucine is represented by six.

Mutations at the first and second positions of a codon typically alter the encoded amino acid, potentially affecting the protein’s structure and function depending on the mutation’s location and nature. Conversely, mutations at the third position often do not change the amino acid, resulting in what are known as silent mutations. These silent mutations are generally more tolerated than those at the first or second positions, leading to differing mutation rates. Consequently, the third position is of particular interest in evolutionary studies.

A mutation can also introduce a stop codon, prematurely terminating protein synthesis. For example, the codon UCA encodes serine (Ser). However, if the second nucleotide, C, is mutated to A, the codon becomes UAA, a stop signal, thereby halting protein synthesis prematurely.

Additionally, insertion or deletion mutations (indels) can shift the reading frame, altering not only the affected codon but all subsequent codons in the sequence.

Throughout my 25 years at the University of Ottawa, I have had the privilege of serving on numerous thesis committees in biology examining various aspects of the genetic code. Topics such as the number of codons per amino acid, codon usage patterns, the frequency of specific codon usage within genes or organisms, and the abundance of corresponding transfer RNA molecules all reveal intriguing properties of the genetic code.

DNA-RNA-Protein Relationships

    DNA: TAC CGC GCC TAT TAC TGC CAG GAA GGA ACT
    RNA: AUG GCG CCG AUA AUG ACG GUC CUU CCU UGA
Protein:  M   A   P   I   M   T   V   L   P   *  

    DNA: TAC CGC GCC TAT TAC TGC CAG GAA GGA ACT
    RNA: AUG GCG CCG AUA AUG ACG GUC CUU CCU UGA
Protein: Met Ala Pro Ile Met Thr Val Leu Pro Stop

Example from Jones and Pevzner (2004), page 65.

Translation (RNA to Protein)

• Translation involves the ribosome, a riboprotein complex, which works alongside transfer RNA (tRNA) molecules and various regulatory proteins.

• These components ensure that tRNAs are charged with the correct amino acids.

Translation (Basic)

Translation (Intermediate)

Translation (Detailed)

Protein Synthesis

Attribution: Brown (2006), Figure 13-1.

Protein Synthesis

Observe the elegance inherent in the translation process. During translation, the ribosome translocates along the messenger RNA (mRNA) strand, facilitating protein synthesis without direct engagement with the genetic code itself. Instead, the translation of this code is mediated by transfer RNA (tRNA) molecules. These tRNAs exhibit a structural uniformity that allows them to occupy the P (peptidyl) and A (aminoacyl) sites of the ribosome effectively. However, they also possess distinct features that enable each of the 20 aminoacyl-tRNA synthetases to accurately identify and bind the appropriate tRNA subset. This specificity is crucial for the synthetases to attach the correct amino acid to the tRNA, based on the anti-codon sequence, thereby ensuring accurate translation of the genetic information.

Attribution: Boumphreyfr vector conversion by Glr, CC BY-SA 3.0, via Wikimedia Commons

tRNA: 1, 2, 3

Transfer RNA (tRNA)

• Transfer RNAs (tRNAs) function as adaptor molecules crucial for protein synthesis.

• They are encoded by non-protein-coding genes within the genome.

• These genes undergo transcription to produce RNA, which serves as the final functional product.

Transfer RNA (tRNA)

• Diversity: Bacteria possess approximately 30 to 45 distinct tRNAs, while eukaryotic organisms can have up to 50 distinct types, with humans having 48.

• Structure and Function: Each tRNA is covalently bonded to a specific amino acid at one terminus and contains a triplet nucleotide sequence, termed the anti-codon, at the opposite terminus. This sequence is complementary to the mRNA codon.

Transfer RNA (tRNA)

• Notation: tRNA^Phe denotes a tRNA specifically charged with phenylalanine, one of the 20 standard amino acids.

• Conformation: Typically, tRNAs are 70 to 90 nucleotides in length, adopting a conserved cloverleaf secondary structure. This common structural motif was illustrated on the preceding slide.

Transfer RNA (tRNA)

• To facilitate protein synthesis, it is essential that all tRNAs exhibit a uniform structure, enabling their efficient interaction with the ribosome.

Transfer RNA (tRNA)

• Aminoacyl-tRNA synthetases are enzymes that catalyze the attachment of specific amino acids to their corresponding tRNAs. Typically, organisms possess 20 distinct aminoacyl-tRNA synthetases, each dedicated to linking a particular amino acid to all isoaccepting tRNAs—that is, different tRNAs that are charged with the same type of amino acid.

• Each tRNA possesses distinct characteristics that ensure its specific aminoacylation with the correct amino acid.

Protein Synthesis

Again, base pair complementary plays an essential role.

Attribution: Brown (2006), Figure 13-6.

Protein Synthesis

Attribution: Brown (2006), Figure 13-7a.

Wobble base pairs are possible and reduce the number of tRNAs needed since the same tRNA binds 2 or possibly 3 codons.

Ribosomes: Key Players in Translation

• Ribosomes are complex macromolecular structures comprising 3 to 4 RNA molecules and 55 to 83 proteins.

• In bacterial cells, ribosome numbers reach approximately 20,000, with eukaryotic cells hosting even more.

• Ribosomes facilitate protein synthesis by precisely aligning messenger RNAs (mRNAs), transfer RNAs (tRNAs), and requisite protein factors.

• They also play a catalytic role in several biochemical reactions integral to protein synthesis.

Ribosomes

Attribution: Brown (2006), Figure 13-10.

Ribosomes

Attribution: Brown (2006), Figure 13-11.

Ribosomes

Attribution: Brown (2006), Figure 13-13.

DNA-RNA-Protein Relationships

    DNA: TAC CGC GCC TAT TAC TGC CAG GAA GGA ACT
    RNA: AUG GCG CCG AUA AUG ACG GUC CUU CCU UGA
Protein:  M   A   P   I   M   T   V   L   P   *  

    DNA: TAC CGC GCC TAT TAC TGC CAG GAA GGA ACT
    RNA: AUG GCG CCG AUA AUG ACG GUC CUU CCU UGA
Protein: Met Ala Pro Ile Met Thr Val Leu Pro Stop

Example from Jones and Pevzner (2004), page 65.

Reading Frame

• Protein translation initiates at the start codon ATG (AUG in RNA), establishing the reading frame. It terminates at a stop codon.

• Typically, proteins begin with methionine; however, alternative start codons such as GUG or UUG may be employed in specific mRNAs. Additionally, post-translational modifications can remove the N-terminal segment of the protein.

Reading Frame

• There are three stop codons, which are non-sense codons.

• Of the 64 possible codons, 61 are sense codons, encoding 20 amino acids, with one codon specifically serving as the start codon, coding for methionine.

• The genetic code is described as degenerate because multiple codons can encode the same amino acid. Consequently, a single amino acid sequence may be derived from multiple distinct DNA sequences, ensuring a unique translation.

Worked Example

Summary

• Genetic sequences are organized into triplets known as codons.
• The start codon is AUG, encoding the amino acid methionine (Met).
• There are three stop codons that terminate the polypeptide chain, preventing further amino acid addition.

Summary

• Around 30 to 50 distinct transfer RNAs (tRNAs) exist, each linked to a specific amino acid corresponding to its anticodon sequence. These tRNAs, as nucleic acids, adhere to standard base-pairing rules during codon-anticodon recognition.

Summary

• An Open Reading Frame (ORF) is a sequence of codons beginning with a start codon (AUG) and concluding with a stop codon, defining a potential protein-coding region.
• Given that the genetic code consists of nucleotide triplets, each DNA strand offers three potential reading frames, depending on whether the start codon is positioned at \(i \bmod 3 = 0, 1,\) or \(2\).
• Considering the anti-parallel nature of the two complementary DNA strands, this results in a total of six possible reading frames for translation.

Mutations within coding regions directly impact the gene’s resultant protein product.

Fun

This cartoonist’s approach to biology may engage some of you.

Fun (continued)

Video playlists by the Amoeba Sisters, “on a mission to demystify science with humor and relevance.”

• Cell Structure and Function (5 videos)
• Biomolecules and Biochemistry (5 videos)
• DNA, RNA, and Protein Synthesis (5 videos)
• DNA Replication, Cell Cycle, and Cell Division (5 videos)
• Viruses, Bacteria, and Cancer (3 videos)

Genome

Genome Sizes

Species	Size
Potato spindle tuber viroid (PSTVd)	360
Obelisk	1,000
Human immunodeficiency virus (HIV)	9,700
SARS-CoV-d (COVID-19)	29,000
Bacteriophage lambda (\(\lambda\))	48,500
Mycoplasma genitalium (bacterium)	580,000
Escherichia coli (bacterium)	4,600,000
Ramazzottius varieornatus (tardigrade)	55,800,000
Drosophila melanogaster (fruit fly)	120,000,000
Homo sapiens (human)	3,000 000,000
Bufo bufo (common toad)	6,900,000,000
Podisma pedestris (mountain grasshopper)	17,000,000,000
Lilium longiflorum (easter lily)	90,000,000,000
Necturus lewisi (a salamander)	118,000,000,000
Amoeba dubia (amoeba)	670,000,000,000

Generated by Google AI Overview on 2025-01-17

Obelisks are a newly discovered class of RNA elements that are similar to viroids, but have distinct genetic sequences: - Discovery:Obelisks were discovered in human stool and oral microbiomes by searching RNA databases for elements similar to the circular RNA of viroids. - Characteristics: Obelisks are rod-like in shape, with a genome assembly of about 1 kb. They have open reading frames that encode a novel “Oblin” protein superfamily. Some obelisks also contain a self-cleaving “hammerhead” type ribozyme. - Prevalence: Obelisks are prevalent in human microbiomes, found in about 7% of stool samples and 50% of saliva samples. Some people have harbored obelisks for more than 300 days. - Relationship to viroids: Obelisks are similar to viroids in shape, but are two to four times larger and have different genetic sequences. - Implications: Obelisks could be the oldest, most primitive forms of life, or at least a predecessor to it. They could also have played a role in shaping the diversity of species on Earth. - Future research: Scientists will need to study obelisks further to determine if they can infect or cause disease. They will also need to study how obelisks evolved, and whether viruses evolved from them or vice versa.

See What’s an Obelisk, Anyway? by Derek Lowe for a more reliable source of information.

Genome sizes

• Haemophilus influenzae (bacterium), dna = 1.8 Mbp
• Escherichia coli (bacterium), dna = 4.6 Mbp
• Saccharomyces cerevisiae (yeast), dna = 12 Mbp
• Caenorhabditis elegans (worm), dna = 97 Mbp
• Arabidopsis thaliana (flowering plant), dna = 115 Mbp
• Drosophila melanogaster (fruit fly), dna = 137 Mbp
• Smallest Human chromosome (Y), dna = 50 Mbp
• Largest Human chromosome (1), dna = 250 Mbp
• Whole Human genome, dna = 3 Gbp
• Mus musculus (mouse), dna = 3 Gbp.

Mbp = million base pairs

DNA is organized into chromosomes

 NLM Useful Glossary: Chromosome

The self-replicating genetic structures of cells containing the cellular DNA that bears in its nucleotide sequence the linear array of genes. In prokaryotes, chromosomal DNA is circular, and the entire genome is carried on one chromosome. Eukaryotic genomes consist of a number of chromosomes whose DNA is associated with different kinds of proteins.

Work by Thomas Morgan in the 1920s established the connection between traits (genes) and chromosomes (DNA).

Genome of Multicellular Animals

The human genome consists of two primary components: nuclear and mitochondrial genome.

Genome of Multicellular Animals

• Nuclear Genome: The nuclear genome comprises 23 chromosome pairs, amounting to 24 unique linear DNA molecules: 22 autosomes and the X and Y sex chromosomes. Chromosomal lengths range from about 50 million nucleotides for the shortest to over 205 million for the longest. Cumulatively, the nuclear genome encompasses approximately 3.2 billion nucleotides and encodes approximately 20,000 protein-coding genes.

Genome of Multicellular Animals

• Mitochondrial Genome: The mitochondrial genome comprises a single circular DNA molecule, 16,569 nucleotides in length, present in multiple copies within the mitochondria. It encodes 37 genes essential for protein synthesis.

Genomic Composition Across Cells

• The adult human body comprises approximately \(10^{13}\) cells, each possessing an identical genomic sequence.

Human Chromosomal Composition

• Human somatic cells are diploid, containing two sets of the 22 autosomes and two sex chromosomes: XX in females, XY in males.
• Somatic cells, synonymous with diploid cells, contrast with gametes.
• Gametes are haploid, possessing only one set of the 22 autosomes and a single sex chromosome.

Genes

What are the genes?

 biotech.icmb.utexas.edu/search/dict-search.html

The fundamental physical and functional unit of heredity. A gene is an ordered sequence of nucleotides located in a particular position on a particular chromosome that encodes a specific functional product (i.e., a protein or RNA molecule).

• Can be several thousands nt (nucleotides) long.
• Occurs on either strand, not often but sometimes overlapping.

Genome Organisation

In higher organisms, protein-coding genes are composed of subsegments known as exons, which are interspersed with intervening sequences termed introns.

Genomic Organization

Contrary to common perception, genomes are not densely packed with genes.

Genomic Organization

In the human genome, the structure is as follows:

• Approximately 60% consists of repetitive sequences:
  • One-third of these are satellite DNAs, characterized by low complexity, short length, and high repetition.
  • The remaining two-thirds are composed of complex repeats, including transposable elements and similar structures.

Genomic Organization (continued)

• Unique sequences contribute to a smaller portion:
  • Only 1.2% are protein-coding regions.
  • Introns account for around 20% of the genome.

DNA-Repeat Expansion & Diseases

Handsaker et al. (2025)

Genome Organisation

• “About one-half of the platypus genome consists of interspersed repeats derived from transposable elements.”

Warren et al. (2008)

Attribution: Charles J. Sharp, CC BY-SA 4.0, via Wikimedia Commons

Platypus

The platypus is a unique, semi-aquatic mammal native to eastern Australia, including Tasmania. It is notable for its unusual combination of features: a duck-bill, webbed feet, and a beaver-like tail. Unlike most mammals, it lays eggs and has venomous spurs on the males’ hind legs. The platypus is one of the few monotremes, a primitive group of egg-laying mammals, and it uses electroreception to locate prey underwater.

Bioinformaticist’s Perspective

• DNA Sequencing (traditional or high-throughput)
• Gene Finding (stochastic grammatical models)
• Identifying Signals (pattern discovery, now deep learning)

Bioinformaticist’s Perspective

• Repetitive sequences pose significant challenges to algorithms employed in sequence assembly due to their complex structures and redundancy.

• The association of repetitive sequences with various diseases underscores their detection as a critical area of research in bioinformatics.

Proteome

Proteome

• The proteome encompasses the complete set of proteins expressed by an organism at a specific time, while proteomics investigates the interactions and functions of these proteins.

Proteome

• Analogous to the transcriptome, the proteome is inherently dynamic, reflecting the organism’s physiological state and environmental interactions.

Proteome

• Proteins serve as critical cellular components, not only forming structural elements but also catalyzing the majority of biochemical reactions.

Proteome

• As Brown (2006) notes, understanding how a genome defines a cell’s biochemical capabilities remains a central challenge in contemporary biology.

Proteome

• There is a paradigm shift from traditional hypothesis-driven, reductionist methodologies to holistic, data-driven, systems-based approaches.

Networks

Interaction Networks

• Protein-Protein interactions (PPI)
• Protein-DNA interactions
• Genetic interactions
• Metabolic networks
• Signaling network
• Transcription/regulatory network

Consider the vast search space inherent in network analysis, particularly for protein-protein interactions (PPIs). The human genome, comprising approximately 20,000 protein-coding genes, potentially results in over 200 million pairwise protein interactions.

• Protein-Protein Interactions (PPI): These are physical contacts established between two or more protein molecules as a result of biochemical events and/or electrostatic forces. They are crucial for most biological functions, including signal transduction, immune responses, and cellular structure maintenance.

• Protein-DNA Interactions: These involve the binding of proteins to DNA, which can regulate gene expression, DNA replication, and repair. Common examples include transcription factors that bind to specific DNA sequences to control gene transcription.

• Genetic Interactions: These occur when the effect of one gene is modified by one or several other genes, often referred to as epistasis. They can provide insights into gene function and the complexity of biological pathways.

• Metabolic Networks: These are complex networks of biochemical reactions within a cell, involving metabolites and enzymes. They describe how cells obtain energy, grow, and respond to environmental changes through metabolic pathways.

• Signaling Network: These networks transmit information through molecular signals from the exterior to the interior of a cell, leading to a cellular response. They are key to processes like cell growth, differentiation, and apoptosis.

• Transcription/Regulatory Network: These involve interactions between DNA, RNA, and proteins to control the expression of genes. They regulate when, where, and how much a gene is expressed, playing a critical role in cellular function and identity.

en.wikipedia.org/wiki/Biological_network

Yeast Proteome

The yeast species Saccharomyces cerevisiae has approximately 6,000 protein-coding genes.

Jeong et al. (2001)

Metabolic network

Attribution: Chakazul, CC BY-SA 4.0, via Wikimedia Commons

Resources

• Essentials of Cell Biology
• Genetics
• Khan Academy, Unit 6, Foundation 1, Biomolecules
• Cell Biology

Prologue

Summary

• We investigated the translation phase of the central dogma, emphasizing its reliance on the genetic code, codons, and tRNA-facilitated amino acid transport.

• We analyzed genome organization, focusing on repetitive DNA sequences and their implications for assembly algorithms and disease pathogenesis.

• In conclusion, we delineated proteomic principles and the complex networks of biological interactions, highlighting the intricate nature of gene expression and regulation.

Central Dogma (Futuristic Animation)

Next Lecture

• Essential Bioinformatics

References

Brown, Terence A. 2006. Genomes. 3rd ed. Oxford: Garland Science.

Cohen, W., and C. Cohen. 2024. A Computer Scientist’s Guide to Cell Biology. Springer Nature Switzerland.

Handsaker, Robert E., Seva Kashin, Nora M. Reed, Steven Tan, Won-Seok Lee, Tara M. McDonald, Kiely Morris, et al. 2025. “Long somatic DNA-repeat expansion drives neurodegeneration in Huntington’s disease.” Cell. https://doi.org/10.1016/j.cell.2024.11.038.

Jeong, H, S P Mason, A L Barabási, and Z N Oltvai. 2001. “Lethality and Centrality in Protein Networks.” Nature 411 (6833): 41–42. https://doi.org/10.1038/35075138.

Jones, N. C., and P. A. Pevzner. 2004. An Introduction to Bioinformatics Algorithm. MIT Press.

Mallapaty, Smriti. 2025. “What will viruses do next? AI is helping scientists predict their evolution.” Nature 637 (8046): 527–28. https://doi.org/10.1038/d41586-024-04195-3.

Warren, W, Ladeana W Hillier, J Marshall Graves, Ewan Birney, C Ponting, F Grützner, K Belov, et al. 2008. “Genome analysis of the platypus reveals unique signatures of evolution.” Nature 453 (7192): 175–83. https://doi.org/10.1038/nature06936.

Widła, Wiesława. 2013. Molecular Biology: Not Only for Bioinformaticians. Vol. 8248. Berlin: Springer. https://doi.org/10.1007/978-3-642-45361-8.

Marcel Turcotte

Marcel.Turcotte@uOttawa.ca

School of Electrical Engineering and Computer Science (EECS)

University of Ottawa