Life

Energy and Earth’s Energy Budget

Sun is the ultimate source of energy on Earth; Earth receives energy as solar radiation and re-emits as terrestrial radiation.
Two main sources of energy for Earth:
- Solar energy (primary)
- Geothermal energy (secondary)
Key flows (recall from Lecture 3):
- Solar energy enters Earth’s system as solar radiation → increases temperature and decreases entropy of the incoming system.
- Earth re-emits energy as terrestrial radiation → decreases temperature and increases entropy of the surroundings.
- Geothermal energy enters Earth’s surface from interior as geothermal heat flux → increases surface temperature, decreases local entropy; Earth emits terrestrial radiation → decreases surface temperature and increases entropy of surrounding space.
Quantities (definitions):
- Let P_absorb denote the rate at which solar energy is absorbed by Earth.
- Let P_geo denote the rate at which geothermal energy flows to the Earth’s surface.
Numerical constants and cross-sections (from Lecture 3 and additional assumptions):
- Albedo α ≈ 0.3 (Earth’s reflectivity)
- Solar constant GSC ≈ 1,361 W/m²
- Earth’s cross-sectional area πR⊕² with R⊕ ≈ 6.37×10⁶ m
- Geothermal heat flux F_geo ≈ 0.087 W/m²
Solar power absorbed (P_absorbed):
- Formula: $P{absorbed} = (1 - \alpha) \, G{SC} \, \pi \, R_⊕^2$
- Using α = 0.3, GSC = 1361 W/m², and Earth geometry, P_absorbed ≈ 1.21 × 10¹⁷ W.
Geothermal power (P_geo):
- Formula: $P{geo} = F{geo} \, A⊕$ where A⊕ is Earth’s surface area.
- With Fgeo = 0.087 W/m² and A⊕ ≈ 4πR⊕², Pgeo ≈ 4.4 × 10¹³ W.
Comparison:
- Geothermal power is negligible compared to solar power: Pgeo / Pabsorbed ≈ 3.6 × 10⁻⁴ (≈ 0.036%).
Recap metaphor (bicycle wheel): Solar input acts as the primary driver of energy dissipation on Earth; geothermal input is a much smaller, internal source that contributes to entropy production but is orders of magnitude smaller than solar input.
Total absorbed energy debate: The Sun remains the ultimate energy source for Earth’s climate and biosphere; geothermal input is a minor contributor to the energy budget.

Entropy, Temperature, and Wavelength

Temperature values (K):
- Sun’s surface: T☉ ≈ 5,770 K
- Top of Earth’s atmosphere: ≈ 5,760 K
- Earth’s surface: T_surf ≈ 288 K
- Terrestrial radiation from Earth’s atmosphere: ≈ 252 K
Wien’s displacement law (peak emission wavelength):
- Formula: $\lambda_{max} = \frac{b}{T}$
- Constant: $b \approx 2.9 \times 10^{-3}\ \text{m K}$
- Peaks:
- Solar radiation at Sun’s surface: $\lambda_{max,⊙} \approx \frac{2.9\times 10^{-3}}{5770} \approx 5.03\times 10^{-7}\ \text{m}$ (≈ 503 nm, visible)
- Terrestrial radiation (Earth’s surface): $\lambda_{max,Earth} \approx \frac{2.9\times 10^{-3}}{252} \approx 1.15\times 10^{-2}\ \text{m}$ (≈ 11.5 μm, infrared)
Implication: Solar peaks in visible; terrestrial peaks in infrared.
Entropy production setup (rate of entropy production):
- General form: $\dot S = P{in} \left( \frac{1}{T{sink}} - \frac{1}{T_{source}}\right)$
- For solar energy:
- Source temperature: T_source = T☉ ≈ 5770 K
- Sink temperature: T_sink ≈ 252 K (Earth’s atmosphere/near-surface environment)
- For geothermal energy:
- Source temperature: T_source ≈ 2000 K (mantle)
- Sink temperature: T_sink ≈ 288 K (Earth’s surface)
Practical numerical values:
- Solar entropy production rate:
 $\dot S{sol} \approx P{absorbed} \left( \frac{1}{252} - \frac{1}{5770} \right) \approx 4.6 \times 10^{14}\ \text{W K}^{-1}$
- Geothermal entropy production rate:
 $\dot S{geo} \approx P{geo} \left( \frac{1}{288} - \frac{1}{2000} \right) \approx 1.31 \times 10^{11}\ \text{W K}^{-1}$
Comparison: Entropy production from solar input is several orders of magnitude larger than that from geothermal input; solar-driven processes dominate Earth’s entropy production.
Key conceptual takeaway: The energy flow from hot Sun to cold Earth increases the total entropy of the universe; life and Earth’s processes act as pathways that dissipate energy and generate entropy rather than violate the second law.

Abiogenesis and the Emergence of Life

Abiogenesis: The emergence of living organisms from non-living matter; a phase transition from abiotic Earth (lower complexity) to biotic Earth (higher complexity).
Core questions: How does a biotic Earth thermodynamically compare with an abiotic Earth?
Three main hypotheses (and their historical context):
- H1: The Oparin–Haldane “primordial soup” hypothesis
- Life arose from a reducing atmosphere rich in inorganic precursors, forming a primitive soup that led to complex organics.
- Darwin’s related idea: warm little pond with ammonia, phosphoric salts, electricity, etc., enabling synthesis of protein compounds.
- Oparin (1924) and Haldane (1929) extension: life emerges from inorganic molecules in a reducing environment.
- H2: RNA world hypothesis
- RNA molecules could have been the original biomolecule, capable of both storing genetic information and catalyzing reactions (ribozymes).
- This resolves the prior chicken-and-egg problem of proteins vs nucleic acids by positing RNA as both information carrier and catalyst.
- H3: LUCA (Last Universal Common Ancestor) hypothesis
- There exists a hypothetical ancestral cell from which ALL current life on Earth descends (the root of the tree of life).
- RNA plays a key role in explaining origins and in reconstructing the family tree of life.
Why oxygenation mattered historically: Oxygen interfered with formation of complex organic molecules; reducing atmospheres are thought to have favored abiotic synthesis of organics (H1/H1′ logic).
Foundational experiments and evidence:
- Miller–Urey experiments (1953, revised 1959): Electric discharges in a reducing- atmosphere simulation produced several amino acids, demonstrating plausibility for abiotic synthesis of organics.
- The experimental setup (simplified): a chamber with gases simulating early Earth (water vapor, methane, ammonia, hydrogen), with energy input (electric spark) to drive chemical synthesis.
RNA world details:
- The discovery of catalytic RNA showed RNA can act as both information carrier and enzyme, enabling a solution to the chicken-and-egg problem in origin-of-life research.
- This led to a division of labor: DNA carries genetic information, proteins catalyze chemistry; yet RNA played a central initiating role.
Schrödinger, Boltzmann, and the thermodynamics framing:
- Boltzmann’s perspective: life does not violate the second law; instead, organisms may increase the universe’s total entropy by creating and dissipating energy pathways.
- Life amplifies abiotic entropy production by providing new, irreversible channels for energy dissipation.
Central take-away: The emergence of life is not a violation of thermodynamics but an amplification of entropy production through biotic pathways that augment abiotic processes.

The Genetic Material: DNA, RNA, and Nucleobases

Nucleotides: basic units of nucleic acids (DNA and RNA).
- Adenine (A): C₅H₅N₅
- Cytosine (C): C₄H₅N₃O
- Guanine (G): C₅H₅N₅O
- Thymine (T): C₅H₆N₂O₂
- Uracil (U): C₄H₄N₂O₂ (RNA only)
Hydrogen-bonding and base-pair rules:
- DNA: A pairs with T (2 H-bonds); G pairs with C (3 H-bonds).
- RNA: A pairs with U (2 H-bonds); G pairs with C (3 H-bonds).
- Wobble base pairing (Crick, 1966): G can pair with U (2 H-bonds) in some contexts.
Structural differences:
- DNA: typically double-stranded; RNA: typically single-stranded.
Nucleobase chemistry and representations:
- Nucleobases and their formulas are listed above to understand composition; colors (CPK scheme) are used in models.

The Central Dogma and the Origin of Life

Genetic information flow (Crick, 1970): DNA → RNA → Proteins is unidirectional in the classic view; information flows from nucleic acids to proteins, with transcription and translation as intermediaries.
Chicken-and-egg problem (Eigen, 1971): Proteins enable replication/synthesis of DNA, but DNA is needed to code for proteins.
Resolution: Catalytic RNA (ribozymes) discovered in the 1980s (Cech et al., 1981; Doudna & Szostak, 1989; Kruger et al., 1982) showed RNA could be both information carrier and catalyst, solving part of the chicken-and-egg issue.
Resulting view: RNA-based initiation (RNA world) then division of labor into DNA for information storage and proteins for catalysis.
LUCA context: LUCA represents a common ancestral node in the tree of life, supporting a single origin of life that predates the divergence of current lineages.

Phylogenetics and the Tree of Life

Five-kingdom classification (Whittaker, 1969): Monera, Protista, Fungi, Plantae, Animalia.
RNA-based phylogenetics (Woese & Fox, 1977): Ribosomal RNA (rRNA) is highly conserved; 18S rRNA in eukaryotes and 16S rRNA in prokaryotes are key markers for reconstructing relationships.
Three-domain system (Woese et al., 1990): Archaea, Bacteria, Eukarya; rooted at LUCA.
LUCA (Last Universal Common Ancestor): a common, cell-based ancestor of all current life on Earth.
Phylogenetics in practice:
- RNA-based phylogenetics supports an RNA-centric view of early life and informs the deep branches of the tree of life.
- The interactive “tree of life” can be explored via tools like ITOL (Interactive Tree Of Life).

In-class Colab Session: 18S/16S rRNA and BLAST

Practical focus: Use 18S rRNA for eukaryotes and 16S rRNA for prokaryotes as molecular markers.
FASTA format: FASTA is a text-based format for representing nucleotide sequences.
Downloadable FASTA files used in class:
- Human 18S rRNA gene: NCBI entry fasta
- Chimpanzee 18S rRNA gene: NCBI entry fasta
- Banana (Musa acuminata) 18S rRNA: NCBI entry fasta
BLAST (Altschul et al., 1990): algorithm for finding regions of similarity between biological sequences; used locally in Colab for sequence comparison.
Colab practical workflow (summary):
- Prepare FASTA files for the query (human) and target organism (chimpanzee, banana).
- Use BLASTN to compare sequences; generate results in XML/other formats.
Example results:
- Identity between human and chimpanzee: 99.79% (1,865/1,869 matches) with 1,869 nt length for human and chimpanzee alignment; very high similarity.
- Identity between human and banana: 82.10% (1,587/1,587 matches) with 1,587 nt length; more distant but still sharing a deep ancestry.
Summary takeaway: RNA-based phylogenetics and sequence comparisons illuminate relatedness among species and support the LUCA framework.

Practical BLAST and Data Analysis (Appendix Overview)

FASTA files and data sources:
- Human 18S rRNA, chimpanzee 18S rRNA, banana 18S rRNA (FASTA format from NCBI).
BLAST in Colab:
- Install BLAST+ and Biopython.
- Upload FASTA files to Colab.
- Create a BLAST database from the target FASTA.
- Run BLASTN with the human FASTA as query against the target database.
- Parse results to extract identity, alignment length, percent identity, E-value, and score.
Example interpretation:
- High identity (≈100%) between human and chimpanzee confirms close relatedness.
- Moderate identity (~82%) with banana reflects distant common ancestry.

Chance vs Design in Origin-of-Life Debates

Central question: Was the origin of life a product of chance, design, or a combination?
White (2007) presents pebble-pattern arguments to illustrate how patterns might arise by chance, physical law, or design:
- Pattern 1: Pebbles scattered randomly on a sidewalk – can be attributed to chance.
- Pattern 2: Pebbles sorted by size toward the shore – explained by physical laws (not chance or design).
- Pattern 3: Pebbles arranged as a stick figure with a smile – attributed to design (intentional action).
Chance vs design formalism (conceptual):
- C: A process that results in a state S is due to chance; P(C) > P(C|S) under certain probability conditions.
- BI: Intentional biasing – evidence for design; BN: Non-intentional biasing – natural laws or biases in nature.
- T1, T2, T3 and partitioning of hypotheses B_i to understand how different bias sources affect probabilities of C given S.
Pattern analysis and inference:
- Pattern 1 does not necessarily make C less probable; Pattern 2 makes C less probable; Pattern 3 makes C less probable under certain Bayesian criteria.
Preference problem (White, 2007):
- Humans have known preferences in making patterns, but an agent with vastly greater power and intelligence could behave in unpredictable ways.
- Theistic or intelligent-design explanations have been invoked; however, in scientific reasoning, non-intentional explanations are generally preferred when they suffice.
Key question for philosophy of science: Do we need to rethink the assumptions underlying origin-of-life research? White argues for a reassessment of how we treat chance, design, and their roles in biological origins.

The Big Picture: Synthesis and Implications

Abiogenesis is framed as the thermodynamic and informational emergence of life in a universe that tends toward higher entropy.
Life does not violate the second law; instead, it enables more efficient dissipation and entropy production through new pathways (biochemical and ecological processes).
RNA as a pivotal molecule demonstrates how information storage and catalytic function can be unified, enabling the transition from an RNA world to a DNA/protein world.
Phylogenetic analyses anchored by rRNA sequences provide robust evidence for LUCA and for the three-domain model of life, shaping our understanding of the deep history of biology.
Practical laboratory tools (e.g., Miller-Urey experiments, BLAST in Colab) connect theoretical ideas to empirical evidence, illustrating how chemistry, biology, and computation converge in origin-of-life studies.

Appendix: Quick Reference to Equations and Key Values

Solar power absorbed by Earth: $P{absorbed} = (1 - \alpha) \; G{SC} \; \pi R_⊕^2$
- With α ≈ 0.3, G{SC} ≈ 1361\,\text{W/m}^2, R⊕ ≈ 6.37\times 10^6\,\text{m}
- Result: $P_{absorbed} \approx 1.21 \times 10^{17}\ \text{W}$
Geothermal power: $P{geo} = F{geo} \; A_⊕$
- With Fgeo ≈ 0.087\,\text{W/m}^2, A⊕ ≈ 4\pi R_⊕^2
- Result: $P_{geo} \approx 4.4 \times 10^{13}\ \text{W}$
Ratio of powers:
$\frac{P{geo}}{P{absorbed}} \approx 3.6 \times 10^{-4} \; (\approx 0.036\%)$
Wien’s displacement law:
$\lambda_{max} = \frac{b}{T}, \quad b \approx 2.9\times 10^{-3}\ \text{m K}$
Peak wavelengths:
- Sun’s surface: $\lambda_{max,⊙} \approx 5.03\times 10^{-7}\ \text{m}$ (≈ 503 nm)
- Earth’s surface: $\lambda_{max,Earth} \approx 1.15\times 10^{-2}\ \text{m}$ (≈ 11.5 μm)
Entropy production rates:
- Solar: $\dot S{sol} \approx P{absorbed} \left( \frac{1}{252} - \frac{1}{5770} \right) \approx 4.6 \times 10^{14}\ \text{W K}^{-1}$
- Geothermal: $\dot S{geo} \approx P{geo} \left( \frac{1}{288} - \frac{1}{2000} \right) \approx 1.31 \times 10^{11}\ \text{W K}^{-1}$
Nucleobases and pairing (summary):
- A ↔ T (DNA), A ↔ U (RNA), G ↔ C (both DNA and RNA), with wobble pairing G ↔ U in some contexts.
Nucleobase formulas (examples):
- Adenine: $\text{Adenine} = \text{C}5\text{H}5\text{N}_5$
- Cytosine: $\text{Cytosine} = \text{C}4\text{H}5\text{N}_3\text{O}$
- Guanine: $\text{Guanine} = \text{C}5\text{H}5\text{N}_5\text{O}$
- Thymine: $\text{Thymine} = \text{C}5\text{H}6\text{N}2\text{O}2$
- Uracil: $\text{Uracil} = \text{C}4\text{H}4\text{N}2\text{O}2$
Implied probabilities for sequence space (chance vs design):
- Nucleotide sequences of length 1000: $4^{1000} \approx 10^{602}$ (unfeasibly large; exact form used in lectures: 4^{1000})
- Protein sequences of length 104 (20 amino acids): $20^{104} \approx 10^{135}$
Key conceptual lines:
- Life emerges from energy dissipation pathways, not from energy abundance alone.
- RNA’s catalytic capability provides a plausible bridge in origin-of-life scenarios.
- Scientific reasoning often favors non-intentional explanations unless there is compelling evidence for design; origin-of-life research remains a dynamic interdisciplinary field.

Note: The numbers above are taken from the provided transcript and rounded to be suitable for study notes. Where possible, I’ve kept the original symbols (Pabsorbed, Pgeo, α, GSC, etc.) and included the approximate values given in the source. If you have a copy of the figures or a calculator, you can reproduce the numeric steps for Pabsorbed and Pgeo using the exact Earth radius and constants you’ll be tested on.