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The cytoplasm is the material inside a cell membrane but outside the cell nucleus, when one is present. It includes the cytosol, the organelles suspended in it, and other structures; it is not just a name for the liquid. In a prokaryote, which has no cell nucleus, the nucleoid and ribosomes are within the cytoplasm. See Clark, Douglas and Choi, Biology 2e, 4.3: cytoplasm and cytosol and Clark, Douglas and Choi, Biology 2e, 4.2: prokaryotic organization.

Try classifying four positions in the diagram. A point in the pale blue region belongs to both cytosol and cytoplasm. A point inside the mitochondrion belongs to an organelle included in the cytoplasm, but not to the surrounding cytosol. A point on a free ribosome belongs to the cytoplasm, but the ribosome itself is not cytosol. A point inside the cell nucleus belongs to neither cytoplasm nor cytosol. These distinctions prevent the misleading inference that everything outside the cell nucleus shares one undivided liquid environment.

The usefulness of the cytoplasm is this combination of shared surroundings and specialized structures: enzymes in the cytosol carry out many steps of metabolism, while organelles maintain their own internal conditions. A soluble protein made by a free ribosome may work in the cytosol or be transported elsewhere, including into the cell nucleus. Cellular organization therefore combines separation with exchange, rather than assigning each protein permanently to its place of synthesis. See Alberts et al., Molecular Biology of the Cell (2002): traffic between nucleus and cytosol.

The cytosol is the aqueous part of the cytoplasm surrounding its structures, including organelles. It contains water, ions and dissolved molecules, including many proteins; it is a crowded working environment rather than pure water. The liquid inside a cell nucleus or a membrane-bounded organelle is not the surrounding cytosol.

Endosymbiosis is an ecological association in which one organism, the endosymbiont, lives inside another. The definition specifies location, not that both partners benefit, nor that the internal partner has become an organelle. An intracellular association can remain an association between distinct organisms. Endosymbiotic theory addresses a different question: how particular ancestral bacteria became inherited, functionally integrated organelles during evolution.

The striking consequence is that a eukaryotic biological cell can combine histories: its nuclear lineage and its mitochondria need not have the same ancestry. Mitochondria have bacterial ancestry related to Alphaproteobacteria; the plastids of plants and many algae, including chloroplasts, have ancestry within cyanobacteria. These are ancestral lineages, not a claim that a named living bacterial species is the literal ancestor. Present-day bacteria and organelles have both evolved since their shared ancestors. ^[ref]

Escherichia coli, often abbreviated E. coli, is a bacterial species widely used to study DNA replication and gene expression. Its chromosome is in a nucleoid, and its ribosomes work in the cytoplasm, outside any cell nucleus. A result from one laboratory strain should not automatically be generalized to every member of the species.

The original 1997 report by Blattner and colleagues presented the K-12 MG1655 genome sequence as a circular chromosome of $4,639,221$ base pairs. See Blattner laboratory: original K-12 sequence and 1997 paper. As a bookkeeping example, one complete round of DNA replication from one such chromosome produces two daughter sequence copies totaling $2\times 4,639,221=9,278,442$ base pairs. This is twice the copied material, not twice the length of the reference genome; it does not specify the instantaneous DNA content of a rapidly growing E. coli cell.

A eukaryote is an organism belonging to the lineage characterized by a membrane-bounded cell nucleus and extensive cellular compartmentalization. A nuclear envelope surrounds the nuclear genome; nuclear chromosomes are typically linear. Ribosomes perform biological translation outside the cell nucleus. See OpenStax Microbiology, 3.4: nuclear organization and protein synthesis. Specialized biological cells can lose their cell nucleus, as mature mammalian red blood cells do, while remaining parts of eukaryotic organisms; see OpenStax Biology 2e, 40.2: mature red blood cells.

Yeasts, plants and animals are all eukaryotes. Typical cells in these groups have mitochondria, but chloroplasts belong to photosynthetic plant and algae lineages, not to every eukaryote. A cell wall occurs in typical plant and fungus cells but is absent from animal cells. These are comparisons of representative cells, not a checklist every specialized cell must satisfy. See OpenStax Biology 2e, 4.3: nucleus, organelles and representative cells.

The interesting feature is controlled separation: cell membranes and organelle membranes let different cellular processes occupy distinct compartments while membrane transport connects them. The evolution of eukaryotes also involved partnership: mitochondria descend from a bacterial endosymbiosis. Modern phylogenetics supports an archaeal ancestry for the nuclear lineage, alongside this bacterial contribution; see two-domain system. Thus the history of a whole eukaryote cannot be read as the history of just one of its genes.

A genome is the complete set of genetic information under discussion. For a cellular organism it is encoded in DNA, including genes and other sequences. Specify whether a comparison concerns a nuclear genome, a mitochondrion's genome or all cellular genetic material: the cell nucleus does not contain every DNA sequence in a typical eukaryote. See NHGRI: genome.

An intracellular receptor recognizes a ligand inside a biological cell, including in the cytoplasm or cell nucleus. Some intracellular receptors regulate transcription after binding a membrane-permeable signal; an intracellular receptor does not universally imply direct control of DNA. See the receptor-location reference under receptor.

Ploidy counts sets of chromosomes; DNA amount counts material. Let $n$ be the number of chromosomes in one complete set and $C$ the DNA amount of one unreplicated set. For the ordinary diploid model, read each row per completed cell nucleus, not as a total across all products:

In the illustrated $n=2$ example, the starting biological cell has four chromosomes. DNA replication gives eight chromatids, organized into four replicated chromosomes. Each product of meiosis I has two replicated chromosomes, hence four chromatids; each final product has two unreplicated chromosomes. Across completed products, $2(2C)=4C$ after meiosis I and $4(C)=4C$ after meiosis II: division redistributes the replicated DNA. A haploid cell nucleus can therefore have $2C$ without becoming diploid.

A morphogen is a signal whose spatial concentration helps specify different biological cell fates or behaviors during biological development. A morphogen gradient provides a positional cue: biological cells at different distances from a source experience different local concentrations and can follow different developmental pathways. A spatial concentration variation alone does not establish that a substance is a morphogen; its graded developmental effects matter. See Alberts et al., Molecular Biology of the Cell, 4th edition (2002): morphogens as graded developmental signals.

The beautiful idea is that one distributed signal can help organize several regions of a developing body. A continuous morphogen gradient can supply the input for distinct domains of gene expression, rather than requiring a separate signal for every position. A morphogen response threshold is a useful idealization of that interpretation: high, intermediate and low concentrations are assigned different outcomes. The morphogen reaction-diffusion equation describes one way to generate a morphogen gradient; the equation is a model of transport and reaction, while the morphogen is the signal being transported.

Detection and interpretation also depend on the receiving biological cell. For an extracellular morphogen, receptors and signal transduction connect the local concentration to a response; receptor binding occupancy is only one step in that connection. The same morphogen gradient can be interpreted differently in different tissues because their developmental context differs. Thus a morphogen response threshold summarizes a particular response in a particular context, rather than being a universal property of the signal. See Scott F. Gilbert, Developmental Biology, 6th edition (2000): positional information and context-dependent interpretation.

An important experimental example came in 1988. Wolfgang Driever and Christiane Nüsslein-Volhard used antibodies to examine the bicoid protein in early fruit-fly embryos. They reported a concentration profile approximately described by an exponential function, highest at the front, with the protein concentrated in cell nuclei. Their abstract proposed diffusion from localized messenger RNA and dispersed degradation as a likely origin of the morphogen gradient, rather than proving a unique transport mechanism. ^[ref]

In a companion study, Driever and Nüsslein-Volhard genetically changed the amount and distribution of bicoid messenger RNA, measured the resulting protein morphogen gradient, and compared developmental maps. Increased local bicoid protein levels shifted prospective anterior structures toward the rear; decreased levels shifted them toward the front. This linked a measured concentration profile to positional effects in biological development. The toy calculations below illustrate that logic with arbitrary numbers, not measured bicoid parameters. ^[ref]

A multicellular organism has a body of multiple biological cells whose growth and activities are integrated into the life of the whole organism. Extensive cell differentiation is common in complex examples, but specialized biological cells are not a prerequisite for every simple form. Ask how the body develops, how its parts cooperate and how it produces descendants, rather than counting attached biological cells alone. The boundary with a biological colony depends on the degree of integration and the criteria being investigated; there is no universal cell-count threshold. See the Queller and Strassmann account cited under unicellular organism.

Specialization makes the whole capable of combinations that one general-purpose biological cell cannot achieve in the same way. In an animal, a neuron transmits signals while a red blood cell carries oxygen; each still requires a working cell membrane and metabolism. A mature mammalian red blood cell lacks a cell nucleus and mitochondria, illustrating how a useful part need not retain the equipment of a self-reproducing organism. See Clark, Douglas and Choi, Biology 2e, 40.2: red blood cell specialization. Cell differentiation generally involves different gene expression, rather than a different inherited genome for each function. Biological development must coordinate growth, position, interactions and specialization: increasing the number of biological cells is only one component. See Alberts et al., Molecular Biology of the Cell, chapter 21 (2002): construction of multicellular bodies.

A motivating experiment: select for a property of groups. Ratcliff, Denison, Borrello and Travisano's 2012 study began with Saccharomyces cerevisiae growing as unicellular organisms. Daily transfer favored rapidly settling material. Their initial protocol allowed a $10\mathrm{mL}$ culture to settle for $45\min$, discarded the upper $9.9\mathrm{mL}$, and transferred the bottom $100\mu \mathrm{L}$ into fresh medium. After seven days, they instead sampled $1.5\mathrm{mL}$ and centrifuged it at $100$ times gravitational acceleration for $10\mathrm{s}$, again transferring the bottom $100\mu \mathrm{L}$. Faster settling made it more likely that a lineage would seed tomorrow's culture; the procedure selected a physical outcome without specifying how it must arise. These protocol details are explicitly recounted in Gulli, Herron and Ratcliff, Evolution of altruistic cooperation among nascent multicellular organisms (2019): original settling protocol.

The primary 2012 paper reports snowflake yeast dominating all ten initial replicate populations by 60 transfers. To distinguish the joining of previously separate biological cells from clonal development, the researchers enzymatically separated clusters and followed individual biological cells for $16\mathrm{h}$: attached descendants rebuilt clusters, with no such joining observed. Staining localized attachments at bud scars. Time-lapse observations also showed clusters releasing smaller multicellular offspring, called propagules; small clusters grew before they reproduced. See Ratcliff et al., Experimental evolution of multicellularity (2012), figures 1–3: emergence, development and reproduction.

The experimental comparisons ask different questions. Competition with the unicellular organism ancestor showed a reported $34\%$ advantage under settling selection. Without settling selection, the estimated $10\%$ disadvantage had a one-sided $P=0.06$, so it was suggestive rather than decisive evidence of a cost. Separately, three populations derived from one evolved isolate retained the cluster form through 35 transfers without settling selection. That persistence tests stability, not whether clusters always outperform single biological cells. See Ratcliff et al. (2012), figure 2 and the cluster-formation results cited above.

A 2015 follow-up added a causal test: deleting the gene ACE2 in the unicellular organism ancestor produced snowflake yeast, while supplying functional ACE2 to one evolved isolate restored separation into single biological cells. Sequence changes altering the encoded protein were found in ACE2 in five of ten examined lineages; the study did not identify that same sequence-change mechanism in every lineage. The deletion and restoration comparisons support a mechanism beyond the observation that clusters settle quickly. See Ratcliff, Fankhauser, Rogers, Greig and Travisano, Origins of multicellular evolvability in snowflake yeast (2015), figure 1.

What follows, and what does not. The evidence supports inherited cluster formation, clonal development and a reproducing collective whose properties can respond to natural selection. Calling these simple multicellular organisms recognizes those demonstrated properties; it does not turn every clump into an animal or establish animal-like cell differentiation. This laboratory route also does not reconstruct the actual ancestry of animals or show that complex developmental integration must follow. The interesting achievement is narrower and testable: a change in how descendants remain connected creates a new scale at which growth and reproductive success can be measured.

For the toy figure, let $p$ be the fraction of tracked units of type C before transfer and let $s_C,s_U$ be the respective probabilities of transfer for C and U. Assume equally weighted units and equal multiplication between transfers. When overall transfer probability is nonzero, conditioning on transfer givesWith $p=1/5$, $s_C=4/5$ and $s_U=1/10$, the numerator is $4/25$ and the denominator $6/25$, giving $p_{\mathrm{after}}=2/3$. If both types have the same nonzero transfer probability, the fraction stays $1/5$. This is conditional probability, not a model of the full experimental life cycle: real cluster sizes, growth and fragmentation affect which quantity a frequency measures. In particular, a fraction of clusters is not automatically a fraction of biological cells.

A neuron is a specialized biological cell that receives, integrates and transmits signals. Its shape separates places where inputs arrive from places where outputs reach other biological cells: this functional asymmetry is neuronal polarity. Understanding a neuron therefore means connecting its anatomy to changes in membrane potential, rather than treating it as a wire that merely forwards every input.

In a common multipolar neuron, branching dendrites receive inputs at synapses; the soma contains the cell nucleus and most major organelles; the axon carries signals to distant or nearby targets; and axon terminals form output contacts. All these regions belong to one biological cell enclosed by a continuous cell membrane. An axon can branch, allowing one neuron to influence several receiving biological cells.^[ref]

At an input chemical synapse, a neurotransmitter acts on a receptor, changing an electric current directly or through signal transduction.^[ref] A resulting synaptic potential contributes to synaptic integration in the dendrites and soma. In many spiking neurons, sufficiently strong depolarization recruits voltage-gated ion channels in the axon initial segment, initiating an action potential that propagates along the axon. At an output chemical synapse, calcium entry through voltage-gated ion channels promotes synaptic vesicle exocytosis, releasing neurotransmitter. An action potential is thus regenerated electrically along a cell membrane; it is not a packet of neurotransmitter travelling from the dendrites to the axon terminals.^[ref]

The compartments are specializations, not exclusive jobs. Inputs can contact the soma or axon as well as dendrites; dendrites can support active voltage-gated ion channels. Paired recordings from a pyramidal neuron's soma and dendrite or axon established that an action potential can begin in the axon and propagate back into the dendrites. The usual output direction therefore does not make every electrical signal strictly one-way.^[ref] An electrical synapse, which directly couples cytoplasms through gap junctions, also differs from the sending-and-receiving arrangement of a chemical synapse.^[ref]

Nor does every neuron have the upper diagram's shape. A bipolar neuron has two main processes, one dendrite and one axon; a multipolar neuron has several dendrites; and a pseudounipolar neuron has a single process from the soma that divides into peripheral and central branches. In the last arrangement, sensory signals can travel past the soma rather than obligatorily through it. These shape categories do not specify every neuron's receptor, connectivity or firing behavior.^[ref] Some neurons in the retina communicate through graded changes in membrane potential without generating action potentials.^[ref]

Why timing changes the computation. Synaptic integration can combine inputs at different locations, called spatial summation, and inputs arriving at different times, called temporal summation. A minimal example uses the leaky integrate-and-fire model with the illustrative parameters already given there: resting and reset membrane potential $-65\mathrm{mV}$, firing threshold $-50\mathrm{mV}$, electrical resistance $R=100\mathrm{M\Omega }$, capacitance $C=200\mathrm{pF}$, time constant $\tau =RC=20\mathrm{ms}$ and neuronal refractory period $2\mathrm{ms}$. These are chosen model values, not measured properties of a particular neuron. Before firing, a constant inward electric current $I$ starting from rest givesThe exponential function expresses the competition between charging the cell membrane's capacitance and leakage through its electrical resistance.^[ref]

Two $100\mathrm{pA}$ inputs, each lasting $40\mathrm{ms}$, produce different outputs depending on their timing. Either input alone reaches only $-56.3534\mathrm{mV}$. Applied together, they give $I=200\mathrm{pA}$ and reach threshold after $20\ln 4\mathrm{ms}\approx 27.7259\mathrm{ms}$, producing one action potential event during the pulse. If instead the second input begins $20\mathrm{ms}$ after the first ends, the earlier depolarization has partly decayed: the second pulse peaks at approximately $-55.9229\mathrm{mV}$ and neither pulse produces an action potential. The two-input protocols deliver the same total electric charge, $8\mathrm{pC}$, yet only the coincident protocol fires. Counting total input alone misses this timing dependence.

This example makes a neuron a detector of sufficiently clustered input, not a perfect logical gate: different parameters change the result. Actual dendrites introduce location-dependent filtering and active responses, and an inhibitory postsynaptic potential or shunting inhibition can change whether another input succeeds. The single-compartment leaky integrate-and-fire model omits these mechanisms.^[ref] Across connected neurons, branching axons distribute outputs while converging synapses combine inputs; spike trains can support temporal coding and rate coding, and synaptic plasticity changes the influence of an input. Connectivity and cellular dynamics together determine the computation.^[ref][ref]

Testing the connection between structure and function. Whole-cell recording connects anatomy to a measured membrane potential. In a published mouse protocol, a two-photon microscope guides solution-filled glass pipettes to neurons; an amplifier and bath reference electrode complete the electrical recording apparatus. A high-resistance seal forms against the cell membrane, then brief suction opens the membrane patch beneath the tip. In current clamp, the amplifier supplies a chosen electric current and records the resulting membrane potential, unlike voltage clamp, which controls voltage and measures electric current. The investigators used $500\mathrm{ms}$ current steps of several amplitudes to characterize excitability and firing, and negative current pulses to estimate input electrical resistance.^[ref]

The observable is a voltage trace, including graded responses and action potentials. Comparing injected electric current with that trace tests how input becomes output; it does not identify every underlying ion channel. The protocol checks access electrical resistance, which can distort voltage and action potential measurements, and includes intervals without stimulation to record spontaneous activity. In a teaching replication, repeated zero-input trials and monitoring baseline drift would provide further controls; these are recommended comparisons, not additional results attributed to the paper. A recording at the soma also cannot establish the local voltage everywhere in a branching dendrite, and this anesthetized preparation does not establish behavior in every awake neuron.^[ref]

A complementary experiment used simultaneous whole-cell recordings from the soma and an apical dendrite or axon of the same pyramidal neuron in a brain slice. The relative onset times of action potentials, together with sodium currents in excised dendrite membrane patches, supported axonal initiation followed by active propagation into dendrites. Pairing sites within one neuron is a useful comparison because it avoids confusing differences between cells with differences between compartments. Instrument timing and comparable recording quality would be essential controls when reproducing the inference. Only the published abstract was accessible here, so no unverified timing values, drug controls or channel distributions are supplied.^[ref]

The nuclear envelope is the double-membrane boundary around a cell nucleus. Regulated passage connects nuclear processes to the surrounding cytoplasm: transcription produces RNA in the cell nucleus, while exported messenger RNA can undergo biological translation on ribosomes outside it. See NHGRI: nuclear membrane.