Why difference in degree of folding in a cell?

Why difference in degree of folding in a cell?

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For a cell to maintain constant volume, input should be equal to output of substances.

My question is, if the basolateral membrane, by less folding can attain the same rate of transport as of the apical surface with microvilli, then why do cells produce more foldings (microvilli)?

Why is there a difference in degree of foldings on each side?

What are proteins and why do they fold?

The Google company DeepMind says its artificial intelligence system AlphaFold can predict the structure of proteins. A protein's structure determines how well it functions. Here's why that's important for your health.

Immunoglobulin G antibody protein

The proteins in our bodies are easily confused with the protein in food. There are similarities and links between the two — for example, both consist of amino acids.

But, when scientists talk about proteins in biology, they are talking about tiny but complex molecules that perform a huge range of functions at a cellular level, keeping us healthy and functioning as a whole.

Scientists will often talk about proteins "folding" and say that when they fold properly, we're OK. The way they fold determines their shape, or 3D structure, and that determines their function.

But, when proteins fail to fold properly, they malfunction, leaving us susceptible to potentially life-threatening conditions.

We don't fully understand why: why proteins fold and how, and why it doesn't always work out.

When proteins go wrong: 'Lewy bodies' or protein deposits in neurons can lead to Parkinson's cisease

The whole thing has been bugging biologists for 50 or 60 years, with three questions summarized as the "protein-folding problem."

Comparing protein folding in vitro and in vivo: foldability meets the fitness challenge

This review discusses how folding in the test tube differs from folding in vivo.

New research is shedding light on the complex in vivo folding landscape.

Many selective pressures, in addition to foldability, shape protein sequence space.

In this review, we compare and contrast current knowledge about in vitro and in vivo protein folding. Major advances in understanding fundamental principles underlying protein folding in optimized in vitro conditions have yielded detailed physicochemical principles of folding landscapes for small, single domain proteins. In addition, there has been increased research focusing on the key features of protein folding in the cell that differentiate it from in vitro folding, such as co-translational folding, chaperone-facilitated folding, and folding in crowded conditions with many weak interactions. Yet these two research areas have not been bridged effectively in research carried out to date. This review points to gaps between the two that are ripe for future research. Moreover, we emphasize the biological selection pressures that impact protein folding in vivo and how fitness drives the evolution of protein sequences in ways that may place foldability in tension with other requirements on a given protein. We suggest that viewing the physicochemical process of protein folding through the lens of evolution will unveil new insights and pose novel challenges about in-cell folding landscapes.

Why difference in degree of folding in a cell? - Biology

Beginning biology students are introduced to the macromolecules of the cell (proteins, nucleic acids, lipids and carbohydrates) as being the key players in cellular function. What is disturbingly deceptive about this picture is that it makes no reference to the many ion species without which cells could not function at all. Ions have a huge variety of roles in cells. Several of our favorites include the role of ions in electrical communication (Na + , K + , Ca 2+ ), as cofactors in dictating protein function with entire classes of metalloproteins (constituting by some estimates at least ¼ of all proteins) in processes ranging from photosynthesis to human respiration (Mn 2+ , Mg 2+ , Fe 2+ ), as a stimulus for signaling and muscle action (Ca 2+ ), and as the basis for setting up transmembrane potentials that are then used to power key processes such as ATP synthesis (H + , Na + ).

Figure 1: Ionic composition in mammalian organisms. Three distinct regions are characterized: the cellular interior (“intracellular fluid”), the medium between cells (“intercellular fluid”) and the blood plasma that is outside the tissue, beyond the capillary wall. The y-axis is in units of ionic concentration called Eq for “equivalents”, which are equal to the ion concentration multiplied by its absolute charge. These units make it easy to see that the total amount of positive and negative charge is equal in each compartment, in line with the principle of electro-neutrality. Even though it is not evident from the figure, the total free solute concentrations (sum of concentrations of both positive and negative components not taking into account their charge) are the same in the intracellular and intercellular fluid. This reflects that the two compartments are in osmotic balance. (Adapted from O. Andersen, “Cellular electrolyte metabolism” in Encyclopedia of Metalloproteins, Springer, pp. 580-587, 2013, BNID 110754.

A census of the ionic charges in a mammalian tissue cell as well as in the surrounding intercellular aqueous medium in the tissue is shown in Figure 1 left and middle panels. The figure also shows the composition of another bodily fluid, the blood plasma, which is separated from tissues through the capillary walls. The figure makes it clear that in each region the sum of negative ion charges equals the sum of positive charges to a very high accuracy. This is known as the law of electroneutrality. The relatively tiny deviations we might expect are quantified in the vignette on “What is the electric potential difference across biological membranes?”. Figure 1 also shows that blood ionic composition is very similar to that of the interstitial fluid. Yet, the composition of the cell interior is markedly different from the milieu outside the cell. For example, the dominant positive ion within the cell is potassium with a concentration that is more than 10-fold higher than that of sodium. Outside the cell the situation reverses with sodium as the dominant positive ion. These and the other differences are carefully controlled by both channels and pumps and we discuss some of their functional importance below.

Table 1: Ionic concentrations in sea water, a bacterial and yeast cell, inside a mammalian cell and in the blood. Concentrations are all in units of mM. Values are rounded to one significant digit. Unless otherwise noted, concentration is total including both free and bound ions. Note that concentrations can change by more than an order of magnitude depending on cell type and physiological and environmental conditions such as the medium osmolarity or external pH. Na+ concentrations are especially hard to measure due to trapping and sticking of ions to cells. Most Mg2+ ions are bound to ATP and other cellular components. More BNIDs used to construct table: 104083, 107487, 110745, 110754.

Ion channels serve as passive barriers that can be opened or closed in response to environmental cues such as voltage across the membrane, the concentration of ligands or membrane tension. Pumps, by way of contrast, use energy in the form of protons or ATP in order to pump charged species against their concentration gradient. The differences in concentration mediated by these membrane machines can often be several orders of magnitude and in the extreme case of calcium ions correspond to a 10,000-fold greater concentration of ions outside of the cell than inside as shown in Table 1. The dominant players in terms of abundance inside the cell are potassium (K + ), chloride (Cl – ) and magnesium (Mg 2+ ) (though the latter is mostly bound to ATP, ribosomes and other macromolecules and metabolites such that its free concentration is orders of magnitude lower). Table 1 shows some typical ionic concentrations in bacteria, yeast and mammalian cells. Some ion concentrations are regulated tightly, particularly toxic metal ions that are also essential for certain processes, but also regulation of K + by osmolarity, which is essential for growth. Other ions are less tightly regulated, Na + being one such example. One of the provocative observations that emerges from this table is that positive ions are much more abundant than negative ions. What is the origin of such an electric imbalance in the simple ions? Many of the metabolites and macromolecules of the cell are negatively charged. This negative charge is conferred by phosphate in small metabolites and DNA and by carboxylic groups on the acidic amino acids, such as the most abundant free metabolite, glutamate. Much more on these cellular players can be found in the vignette on “What are the concentrations of free metabolites in cells?”.

Potassium is usually close to equilibrium in animal and plant cells. Given that its concentration inside the cell is about 10 to 30 fold higher than outside the cell, how can it be in equilibrium? Assume we start with this concentration difference across the membrane, and with no electric potential difference (there are counter ions on each side of the membrane to balance the initial charges and they cannot move). As the potassium ions diffuse down their concentration gradient, from the inside to the outside, they quickly create an electric potential difference due to their positive net charge (the net charge movement is miniscule compared to the ion concentrations on the two sides of the membrane as discussed in the vignette on “What is the electric potential difference across membranes?”). The potential difference will increase until its effect will exactly balance the diffusive flux and this is when equilibrium will be reached. This type of equilibrium is known as electrochemical equilibrium. Indeed from the equilibrium distribution we can infer that the cell has a negative electric potential inside and by how much. The direction of the voltage difference across the cell membrane is indeed from positive outside to negative inside as can be naively expected from pumping of protons out of the cell, and as discussed in quantitative terms in the vignette on “ What is the electric potential difference across membranes?”.

The concentrations described above are in no way static. They vary with the organism and the environmental and physiological conditions. To flesh out the significance of these numbers, we examine a case study from neuroscience. For example, how different is the charge density in a neuron before and during the passage of an action potential? As noted above, the opening of ion channels is tantamount to a transient change in the permeability of the membrane to charged species. In the presence of this transiently altered permeability, ions rush across the membrane as described in detail in the vignette on “How many ions pass through an ion channel per second?”. But how big a dent does this rush of charge actually make to the overall concentrations? Muscle cells in which such depolarization leads to muscle contraction often have a diameter of about 50 μm, and a simple estimate (BNID 111449) reveals that the change in the internal charge within the cell as a result of membrane depolarization is only about a thousandth of a percent (10 -5 ) of the charge within the cell. This exemplifies how minor relative changes can still have major functional implications.

  • As a cell grows, its volume increases much more rapidly than its surface area. Since the surface of the cell is what allows the entry of oxygen, large cells cannot get as much oxygen as they would need to support themselves.
  • As animals increase in size they require specialized organs that effectively increase the surface area available for exchange processes.

At 0.1 to 5.0 &mum in diameter, prokaryotic cells are significantly smaller than eukaryotic cells, which have diameters ranging from 10 to 100 &mum. The small size of prokaryotes allows ions and organic molecules that enter them to quickly diffuse to other parts of the cell. Similarly, any wastes produced within a prokaryotic cell can quickly diffuse out. This is not the case in eukaryotic cells, which have developed different structural adaptations to enhance intracellular transport.

Figure (PageIndex<1>): Relative Size of Atoms to Humans: This figure shows relative sizes on a logarithmic scale (recall that each unit of increase in a logarithmic scale represents a 10-fold increase in the quantity being measured).

In general, small size is necessary for all cells, whether prokaryotic or eukaryotic. Consider the area and volume of a typical cell. Not all cells are spherical in shape, but most tend to approximate a sphere. The formula for the surface area of a sphere is 4&pir 2 , while the formula for its volume is 4&pir 3 /3. As the radius of a cell increases, its surface area increases as the square of its radius, but its volume increases as the cube of its radius (much more rapidly).

Therefore, as a cell increases in size, its surface area-to-volume ratio decreases. This same principle would apply if the cell had the shape of a cube (below). If the cell grows too large, the plasma membrane will not have sufficient surface area to support the rate of diffusion required for the increased volume. In other words, as a cell grows, it becomes less efficient. One way to become more efficient is to divide another way is to develop organelles that perform specific tasks. These adaptations lead to the development of more sophisticated cells called eukaryotic cells.

Figure (PageIndex<1>): Surface Area to Volume Ratios: Notice that as a cell increases in size, its surface area-to-volume ratio decreases. When there is insufficient surface area to support a cell&rsquos increasing volume, a cell will either divide or die. The cell on the left has a volume of 1 mm3 and a surface area of 6 mm2, with a surface area-to-volume ratio of 6 to 1, whereas the cell on the right has a volume of 8 mm3 and a surface area of 24 mm2, with a surface area-to-volume ratio of 3 to 1.

Smaller single-celled organisms have a high surface area to volume ratio, which allows them to rely on oxygen and material diffusing into the cell (and wastes diffusing out) in order to survive. The higher the surface area to volume ratio they have, the more effective this process can be. Larger animals require specialized organs (lungs, kidneys, intestines, etc.) that effectively increase the surface area available for exchange processes, and a circulatory system to move material and heat energy between the surface and the core of the organism.

Increased volume can lead to biological problems. King Kong, the fictional giant gorilla, would have insufficient lung surface area to meet his oxygen needs, and could not survive. For small organisms with their high surface area to volume ratio, friction and fluid dynamics (wind, water flow) are relatively much more important, and gravity much less important, than for large animals.

However, increased surface area can cause problems as well. More contact with the environment through the surface of a cell or an organ (relative to its volume) increases loss of water and dissolved substances. High surface area to volume ratios also present problems of temperature control in unfavorable environments.

Protein Glycosylation

Glycosylation is a critical function of the biosynthetic-secretory pathway in the endoplasmic reticulum (ER) and Golgi apparatus. Approximately half of all proteins typically expressed in a cell undergo this modification, which entails the covalent addition of sugar moieties to specific amino acids. Most soluble and membrane-bound proteins expressed in the endoplasmic reticulum are glycosylated to some extent, including secreted proteins, surface receptors and ligands, and organelle-resident proteins. Additionally, some proteins that are trafficked from the Golgi to the cytoplasm are also glycosylated. Lipids and proteoglycans can also be glycosylated, significantly increasing the number of substrates for this type of modification.


Protein glycosylation has multiple functions in the cell. In the ER, glycosylation is used to monitor the status of protein folding, acting as a quality control mechanism to ensure that only properly folded proteins are trafficked to the Golgi. Sugar moieties on soluble proteins can be bound by specific receptors in the trans Golgi network to facilitate their delivery to the correct destination. These sugars can also act as ligands for receptors on the cell surface to mediate cell attachment or stimulate signal transduction pathways (1). Because they can be very large and bulky, oligosaccharides can affect protein–protein interactions by either facilitating or preventing proteins from binding to cognate interaction domains. Because they are hydrophilic, they can also alter the solubility of a protein (2).


Glycosylated proteins (glycoproteins) are found in almost all living organisms that have been studied, including eukaryotes, eubacteria and archae (3,4). Eukaryotes have the greatest range of organisms that express glycoproteins, from single-celled to complex multicellular organisms.

Glycoprotein diversity

Glycosylation increases the diversity of the proteome to a level unmatched by any other post-translational modification. The cell is able to facilitate this diversity, because almost every aspect of glycosylation can be modified, including:

  • Glycosidic linkage—the site of glycan (oligosaccharide) binding
  • Glycan composition—the types of sugars that are linked to a particular protein
  • Glycan structure—branched or unbranched chains
  • Glycan length—short- or long-chain oligosaccharides

Glycosylation is thought to be the most complex post-translational modification because of the large number of enzymatic steps involved (5). The molecular events of glycosylation include linking monosaccharides together, transferring sugars from one substrate to another and trimming sugars from the glycan structure. Unlike other cell processes such as transcription or translation, glycosylation is non-templated, and thus, all of these steps do not necessarily occur during every glycosylation event. Instead of using templates, cells rely on a host of enzymes that add or remove sugars from one molecule to another to generate the diverse glycoproteins seen in a given cell. While it may seem chaotic because of all of the enzymes involved, the different mechanisms of glycosylation are highly-ordered, step-wise reactions in which individual enzyme activity is dependent upon the completion of the previous enzymatic reaction. Because enzyme activity varies by cell type and intracellular compartment, cells can synthesize glycoproteins that differ from other cells in glycan structure (5).

Enzymes that transfer mono- or oligosaccharides from donor molecules to growing oligosaccharide chains or proteins are called glycosyltransferases (Gtfs). Each Gtf has specificity for linking a particular sugar from a donor (sugar nucleotide or dolichol) to a substrate and acts independent of other Gtfs. These enzymes are broad in scope, as glycosidic bonds have been detected on almost every protein functional group, and glycosylation has been shown to incorporate most of the commonly occurring monosaccharides to some extent (6).

Glycosidases catalyze the hydrolysis of glycosidic bonds to remove sugars from proteins. These enzymes are critical for glycan processing in the ER and Golgi, and each enzyme shows specificity for removing a particular sugar (e.g., mannosidase).

Types of glycosylation

Glycopeptide bonds can be categorized into specific groups based on the nature of the sugar–peptide bond and the oligosaccharide attached, including N-, O- and C-linked glycosylation, glypiation and phosphoglycosylation. Because N- and O-glycosylation and glypiation are the most commonly detected types of glycosylation, more emphasis in this article will be placed on these modifications.

Types of Glycosylation
N-linkedGlycan binds to the amino group of asparagine in the ER
O-linkedMonosaccharides bind to the hydroxyl group of serine or threonine in the ER, Golgi, cytosol and nucleus
GlypiationGlycan core links a phospholipid and a protein
C-linkedMannose binds to the indole ring of tryptophan
PhosphoglycosylationGlycan binds to serine via phosphodiester bond

Proteins are not restricted to a particular type of glycosylation. Indeed, proteins are often glycosylated at multiple sites with different glycosidic linkages, which depends on multiple factors including those described below.

1. Enzyme availability

Glycosylation is controlled by moving proteins to areas with different enzyme concentrations the cell sequesters enzymes into specific compartments to regulate their activity. For example, after a protein is N-glycosylated in the ER, glycan processing occurs in a step-wise fashion by trafficking proteins to distinct Golgi cisternae that contain high concentrations of specific Gtfs and glycosidases.

2. Amino acid sequence

Besides the requirement for the right amino acid (e.g., Asn for N-linked Ser/Thr for O-linked), many enzymes have consensus sequences or motifs that enable formation of the glycosidic bond (6).

3. Protein conformation (availability)

As proteins are synthesized, they begin to fold into their nascent secondary structure, which can make specific amino acids inaccessible for glycosidic binding. Thus, the target amino acids must be conformationally accessible for glycosylation to occur.

Protein Folding and Disease

00:00:08.00 Hi there. I'm Susan Lindquist.
00:00:10.29 I'm at the Whitehead Institute in the Department of Biology at MIT,
00:00:14.19 and I'm here to tell you about protein folding.
00:00:18.10 Protein folding is a universal problem
00:00:21.19 of biological systems,
00:00:23.09 and it winds up influencing
00:00:25.29 every aspect of biology that you can imagine.
00:00:30.23 So, these are very simple organisms
00:00:33.19 called the yeast, Saccharomyces cerevisiae.
00:00:35.18 It's a microorganism.
00:00:37.16 This is obviously a very, very large magnification of these organisms.
00:00:41.06 That organism is responsible for beer, bread, wine --
00:00:44.29 all kinds of things that make life worth living.
00:00:48.12 Anyway, that organism is also
00:00:52.04 a wonderful experimental system
00:00:53.26 that has the same types of problems with protein folding
00:00:56.08 that those organisms over there have.
00:00:59.22 This is a universal aspect of life.
00:01:03.05 And we're used to thinking about life
00:01:05.27 in terms of all the very different things
00:01:07.22 that make up different individuals,
00:01:09.18 but there's a unifying principle of life
00:01:12.15 that relates to protein folding
00:01:14.24 and that plays out from this organism to that organism,
00:01:18.28 in ways that allow us to deeply understand
00:01:22.17 some the worst problems in human biology
00:01:24.08 and try to find clever solutions to fix them.
00:01:31.10 So, proteins are us.
00:01:34.09 Many people think about proteins as being food,
00:01:38.01 but the reason why we think of them as being food
00:01:40.21 is because we need to take some of those elements
00:01:43.15 of proteins into ourselves,
00:01:45.06 chop them up into little pieces,
00:01:48.02 and reassemble them into our own proteins.
00:01:50.29 Because proteins do just about everything
00:01:52.20 that you can think of in our bodies.
00:01:54.12 Proteins are the muscle that powers our arms and legs.
00:01:59.12 Proteins are carrying pigments in our eyes,
00:02:03.05 and it's when light strikes those pigments
00:02:06.11 -- that causes the protein to change shape --
00:02:08.04 that sends a signal to our brain,
00:02:10.00 and that's how we see.
00:02:11.19 Proteins are parked in our stomachs
00:02:13.22 and ready to receive the food we eat and.
00:02:16.14 and tear it apart into little component parts
00:02:19.12 that we can use to build up new proteins,
00:02:21.18 that, as I mentioned,
00:02:24.17 do just about everything in our biology
00:02:27.11 that we think about as a living system.
00:02:31.07 Now, the problem with protein folding
00:02:34.11 is that these things look kinda complicated, right?
00:02:37.19 And they are very complicated.
00:02:39.12 But they start out very simply.
00:02:42.08 So, the code of life
00:02:45.03 is often called the double helix.
00:02:46.18 And it's a very long, linear string of information.
00:02:51.09 It itself doesn't look too interesting.
00:02:53.24 But along different parts of this,
00:02:57.13 it codes for the essential elements of proteins
00:03:00.14 that make up living systems.
00:03:02.27 And a good analogy for the way
00:03:05.18 in which this information is encoded
00:03:08.06 in this long, linear molecule
00:03:11.02 is to think about cassette tapes.
00:03:14.02 Now, cassette tapes were something
00:03:16.20 I played all the time when I was young.
00:03:18.24 I know that you're mostly playing CDs
00:03:21.22 and other digital forms of music.
00:03:24.05 But the cassette tape provides a really great analogy
00:03:26.10 for the way in which very complex information
00:03:30.04 can be encoded by a simple, long thread.
00:03:34.15 So, here we go.
00:03:37.04 Here's a cassette tape.
00:03:38.28 You look at the tape that's wound around those two spools,
00:03:42.10 and it doesn't look the least bit interesting.
00:03:44.12 But when you put it into this machine
00:03:47.05 that decodes the information
00:03:48.20 -- just like DNA is decoded in the machinery of the cell --
00:03:53.18 out comes the most amazing and complex
00:03:57.07 and beautiful sounds.
00:04:11.06 And you can play another piece of the tape
00:04:13.02 and get completely different sounds.
00:04:23.14 And another piece of the tape.
00:04:33.24 So, how does that complexity
00:04:36.10 get encoded in that simple, linear molecule?
00:04:40.19 Well, that's a problem biologists have worked on for a long time,
00:04:44.02 and we understand how the code
00:04:46.23 gets decoded into particular elements.
00:04:48.08 So, there's one particular part of it
00:04:50.06 we still don't perfectly understand,
00:04:52.06 and that we need to understand
00:04:54.24 because it impinges on all aspects of human biology and medicine.
00:04:58.15 These proteins need to fold up into
00:05:01.10 very precise shapes
00:05:03.19 in order to do anything interesting in the cell.
00:05:05.22 And those shapes are incredibly complicated.
00:05:07.18 So, let's look at some real protein structures.
00:05:12.29 You can see each of these different parts of the code
00:05:16.06 has been decoded into a long, linear string,
00:05:18.00 but that folds up and folds up
00:05:20.25 and moves back and forth and back and forth
00:05:23.26 on top of itself.
00:05:26.02 And it's the complexity of this fold
00:05:27.29 that can actually do something powerful.
00:05:30.20 Now, the difficulty in terms of how this plays out in living systems
00:05:35.10 is we don't really understand the forces
00:05:37.18 that allow the protein to fold so precisely
00:05:39.22 into exactly the right shape.
00:05:42.06 What we are understanding, however,
00:05:44.16 is that when they don't fold into exactly that right shape,
00:05:46.29 disaster occurs.
00:05:50.07 And a way of thinking about this.
00:05:52.12 again, to kind of.
00:05:54.04 to illustrate this process,
00:05:57.00 is to think again about that music.
00:05:59.03 that long, linear piece of information in the cassette tape
00:06:02.10 that encodes extraordinary music.
00:06:04.16 well, it's played by instruments, right?
00:06:07.10 And the instruments are together,
00:06:09.14 playing together, and they make great music,
00:06:12.01 just like the proteins are together in a cell
00:06:14.05 and they make wonderful, wonderful biology.
00:06:16.20 And we have different proteins
00:06:18.17 making different types of biology
00:06:20.02 in your digestive system,
00:06:21.25 in your brain, in your heart.
00:06:24.26 The problem is that making these complex folds
00:06:27.14 is very much like taking a lon. lot.
00:06:32.14 long sheet or square sheet of metal
00:06:34.12 and moving it into forming a musical instrument.
00:06:42.17 So, if you get the fold exactly right,
00:06:46.11 it can play some beautiful music.
00:06:53.09 But if there's some very small element of the fold that's.
00:06:57.06 you get almost right, but you don't get it quite right.
00:07:04.10 it can be a disaster.
00:07:07.15 Here's another example.
00:07:10.26 A different piece of metal,
00:07:12.24 folding up into a different shape,
00:07:14.22 making and doing different things in the cell.
00:07:19.19 But if you don't get it just right,
00:07:21.16 the fold isn't quite right.
00:07:24.04 it's a disaster.
00:07:25.23 So, now you've got this orchestra of proteins
00:07:29.00 that make up the living system,
00:07:31.22 and they need to play together exactly right.
00:07:33.19 They need to fold properly,
00:07:35.00 and then they need to play together exactly right
00:07:37.13 if you want the living system to be disease-free.
00:07:41.00 So, let's take a look at how these protein instruments
00:07:43.21 are actually functioning together inside of a living cell.
00:07:47.29 You'll. you're gonna see pictures of proteins serving as architecture --
00:07:51.25 the structural integrity of the cell.
00:07:54.04 You'll see proteins talking to each other between cells.
00:07:58.09 You'll see proteins cutting proteins,
00:08:00.12 assembling into various structures,
00:08:03.19 disassembling.
00:08:05.01 And all of these are part of the orchestration of life
00:08:07.17 inside the living cell.
00:09:21.19 That's a very special kind of protein
00:09:23.20 that's moving along the information highway
00:09:26.08 of the cell
00:09:28.24 and bringing packets of goodies from one end of the cell
00:09:31.15 to the other end of the cell.
00:09:33.03 Anyway, you can see, I think,
00:09:36.05 the extraordinary complexity of living systems and the proteins
00:09:38.10 that are operating in it to keep us
00:09:41.03 biologically active and doing all the amazing things
00:09:42.12 that we can do.
00:09:44.07 I urge you, by the way, to get on the web
00:09:46.22 and plug in that reference
00:09:49.01 and take a look longer look at the.
00:09:50.28 at the movie,
00:09:52.16 and there's also an animation that will tell you exactly what you're looking at all.
00:09:54.28 all. in various parts of it.
00:09:56.26 It's. I've just shown you a very small snippet.
00:10:00.28 But this incredibly complicated biology
00:10:06.16 that's represented by this beautiful movie
00:10:08.28 is misrepresented in just one particular way.
00:10:11.15 And that is that in order to illustrate
00:10:13.25 how these proteins are moving about and doing their things
00:10:16.28 and interacting with other proteins in the cell,
00:10:18.27 they've taken most of the proteins
00:10:21.13 out of that system so that you can see them.
00:10:25.00 In reality, the cell is
00:10:27.17 much, much, much more crowded.
00:10:29.22 So, if you think about this complicated protein fold
00:10:33.28 and the fact that different proteins have different folds,
00:10:38.04 they have to go from a long, linear string of amino acids
00:10:41.02 into those complicated folds
00:10:43.08 so that they can interact with themselves properly.
00:10:47.10 And they have to do that in a really crazy environment.
00:10:50.16 They have to do this in an environment
00:10:52.23 that's this packed with proteins.
00:10:55.15 So, each one of these colors
00:10:57.10 actually represents a different protein
00:10:59.10 in its complex, beautiful shape
00:11:02.11 that can change and move around
00:11:05.21 and do various things.
00:11:07.08 But this image, although it represents the crowding of a cell,
00:11:11.08 is missing one other piece.
00:11:13.18 By the way, this is a beautiful movie by Adrian Elcock.
00:11:16.01 And again, it's. it's.
00:11:18.09 you can find it on the web.
00:11:20.24 The thing that this particular image does not convey
00:11:24.22 is how energetic the system is.
00:11:27.22 Proteins are actually moving about like crazy all the time,
00:11:30.04 and it's this aspect of proteins being able
00:11:33.27 to move and signal and.
00:11:35.08 from one end of the cell to the other end of the cell,
00:11:38.13 help us to interpret what we see.
00:11:40.00 one moment, I'm looking here at you,
00:11:42.04 or looking over here at the screen.
00:11:43.24 I completely change everything I understand about
00:11:46.10 what I'm looking at because the proteins
00:11:48.11 are changing shape so fast.
00:11:50.12 So, living systems have proteins that work
00:11:53.26 at incredible speed.
00:11:55.13 And here's an example of the way they move about
00:11:57.22 and how the crowding is.
00:11:59.16 is jostling and banging into each other all the time.
00:12:03.01 The one way in which this animation
00:12:05.14 doesn't quite convey what's happening in the cell
00:12:07.22 is that it too, for the.
00:12:09.21 for the purposes of clarity,
00:12:11.24 has been modified in a certain way.
00:12:14.04 And that is it's been slowed down.
00:12:17.10 So, just as the other movie I showed you
00:12:21.13 was not very crowded,
00:12:23.09 and things were moving around rather slowly,
00:12:25.28 in this movie, which shows the crowding,
00:12:28.07 things are actually not moving at real speed,
00:12:33.00 so you can illustrate and understand and look
00:12:35.22 at how they these proteins are interacting with each other
00:12:38.16 and moving around.
00:12:40.06 In order to get a realistic idea of how fast these proteins
00:12:42.01 are moving around in the cell,
00:12:43.16 you'd have to speed that movie up
00:12:45.16 not ten times, not a hundred times,
00:12:47.23 not a thousand times,
00:12:49.23 not a hundred thousand times,
00:12:51.22 but 1 million times.
00:12:54.15 So, that movie is real slow motion
00:12:57.02 compared to what's happening in the biology of a living system.
00:13:01.13 And there you have the heart of the protein folding problem.
00:13:04.21 Because if these long, linear strings of amino acids
00:13:07.12 have to fold up into these very, very precise shapes,
00:13:10.12 without getting into trouble with other proteins
00:13:13.28 while they're doing it,
00:13:15.13 under such incredibly kinetic, energetic conditions,
00:13:19.11 you can imagine that sometimes
00:13:21.14 they get that fold wrong.
00:13:22.26 Just like those musical instruments,
00:13:24.29 if you don't. don't fold.
00:13:26.09 wouldn't fold the metal exactly right,
00:13:28.01 it could ruin an orchestra.
00:13:29.17 The same thing can happen in living systems.
00:13:33.27 So, I want to give you one more illustration,
00:13:36.22 one more analogy.
00:13:38.07 What happens when proteins start to misfold,
00:13:41.13 and bang into each other in inappropriate ways,
00:13:43.19 and stick to each other,
00:13:45.25 and. it's something.
00:13:48.05 a process we call protein aggregation.
00:13:50.04 And you know exactly what protein aggregation is like.
00:13:54.00 I know that you've seen it many times.
00:13:56.08 The egg white in this little photograph
00:14:01.28 is actually a solution of protein.
00:14:03.28 And the proteins are all folded properly,
00:14:06.01 and so they're clear and beautiful,
00:14:08.12 and they're not in any trouble.
00:14:10.23 But when you apply heat to that system,
00:14:13.20 the proteins start to move around a little faster.
00:14:16.06 They start banging into each other.
00:14:18.05 They start unfolding a little bit.
00:14:19.29 And what happens is the properties of the biological system
00:14:23.03 change completely.
00:14:24.26 And that is, in fact, what you get.
00:14:28.05 So, those are aggregated proteins.
00:14:29.22 And it's just a nice visual illustration
00:14:34.19 of the problem that can occur
00:14:37.16 when proteins don't fall properly in our living systems.
00:14:41.02 So, we want to understand
00:14:43.18 how we can keep the proteins looking more like this,
00:14:46.24 and how, if they start to go off pathway
00:14:50.07 and start to form little bitty aggregates,
00:14:53.04 we can bring them back to life.
00:14:55.04 Because just a little bit of that aggregation state
00:14:58.16 causes disaster for a living system.
00:15:02.27 So, what are the solutions that life has found?
00:15:05.21 Well, the first way we started to discover and learn something
00:15:09.02 about the solutions to that problem
00:15:11.01 actually involved heat.
00:15:13.23 So, here we have a very simple experiment
00:15:16.27 that was done with yeast cells.
00:15:19.04 We're growing yeast cells in a culture,
00:15:21.04 in a shaking Erlenmeyer flask.
00:15:24.00 And we took some of those cells out.
00:15:28.01 We took two identical aliquots of cells out.
00:15:31.04 What I mean by an aliquot
00:15:33.03 is just a little portion of the culture.
00:15:34.17 So, we took two identical portions of the culture out,
00:15:36.29 and that one on the top there
00:15:41.01 was exposed directly to a high temperature,
00:15:43.10 and the proteins denatured and killed the cell.
00:15:47.00 This one on the bottom was first exposed
00:15:50.08 to an intermediate temperature,
00:15:51.26 to allow it to kind of condition.
00:15:54.02 Basically, it was exposed for half an hour to 39 degrees
00:15:59.04 instead of being shifted directly to 50 degrees.
00:16:01.19 And as you can see, that short, half-hour pretreatment
00:16:05.24 provided tremendous increased capacity of the cells
00:16:09.11 to survive that second, higher heat treatment.
00:16:13.05 Now, this is a universal property of life.
00:16:18.01 And so, it is not only true for yeast cells.
00:16:20.08 It's true for Arabidopsis seedlings.
00:16:23.13 This is basically the same experiment.
00:16:24.27 Arabidopsis seedlings were planted in these little dishes,
00:16:27.00 one treated directly at high temperatures,
00:16:30.08 the other one given this intermediate treatment
00:16:32.19 that allowed it to condition itself
00:16:34.15 and then to withstand the rigors of that more intense condition.
00:16:39.03 And these are human cells in culture.
00:16:41.26 Basically the same experiment.
00:16:44.21 You can do this experiment with all living organisms on Earth,
00:16:48.03 because all living organisms face this same problem
00:16:50.28 of protein folding,
00:16:52.10 and they all prepare for problems in protein folding
00:16:55.26 the same way,
00:16:57.12 by making other proteins that help the proteins
00:17:01.12 to stay in their normal shapes and sizes.
00:17:05.03 So, how do we find out
00:17:07.24 what they're doing during those conditioning pretreatments?
00:17:09.20 What we do is we, again,
00:17:11.17 take out a small portion of the cells
00:17:13.25 and label them with radioactive amino acids
00:17:16.09 so that, as the ce.
00:17:18.06 as the cell is making its own proteins,
00:17:21.06 each of those proteins will get radioactive amino acids
00:17:24.21 incorporated into it.
00:17:26.18 That allows us, then, to visualize it. what's happened.
00:17:30.08 We spread those proteins out on a gel,
00:17:32.25 and we put a film on top of it,
00:17:35.01 and wherever there's radioactivity
00:17:37.20 from a newly made protein,
00:17:39.11 we can see the imprint and a line on the gel.
00:17:41.26 And so, you can see that at 25 degrees,
00:17:45.12 the normal temperature for this organism,
00:17:47.01 it's making one group of proteins.
00:17:49.04 At 39 degrees, it started making a whole bunch of other proteins.
00:17:52.28 And the sole function of all of those proteins
00:17:55.17 is to cope with this protein folding problem,
00:17:58.18 to help other proteins in the cell
00:18:00.16 maintain their normal shapes,
00:18:02.10 or to get rid of them when they've lost their normal shapes.
00:18:07.06 Now, this is a very broadly used survival response.
00:18:11.06 We first started working with it with heat
00:18:14.00 because that's an awfully simple manipulation to make within the laboratory.
00:18:18.12 But it turns out these same proteins provide protection
00:18:22.06 against all sorts of different difficult conditions:
00:18:25.20 changes in pH, changes in the energy balance of the cell,
00:18:28.28 changes in osmotic strength.
00:18:30.28 many, many, many different changes in the cell.
00:18:34.26 In fact, these proteins are constantly being made.
00:18:37.20 made in smaller amounts,
00:18:39.19 over and over and over again,
00:18:41.13 to help cope with this very broad problem in protein folding.
00:18:46.11 So, this very broadly used survival response, as.
00:18:49.10 I showed you yeast cells.
00:18:51.01 I showed you Arabidopsis seedlings.
00:18:52.23 Arabidopsis is a small little mustard plant.
00:18:55.07 I showed you human cells.
00:18:57.10 Every organism on Earth is making very highly conserved,
00:19:00.09 very similar patterns of proteins under these stress conditions.
00:19:03.21 And it turns out that that plays into human biology and medicine
00:19:07.13 in just an extraordinary variety of different ways.
00:19:11.16 One of the major reasons
00:19:13.28 why we want so deeply to understand this problem
00:19:17.00 is that it drives many aspects of human disease.
00:19:21.11 So, one of the things that it drives
00:19:23.22 is the process of infection.
00:19:25.21 When organisms come into our body.
00:19:29.13 and you can see here we've got a fungus
00:19:32.15 that is growing under normal conditions.
00:19:35.04 not inside the body.
00:19:36.23 But when it starts to grow inside the body,
00:19:38.16 it senses this change in temperature,
00:19:41.07 and it. and it starts to realize
00:19:43.25 that it can invade the biological system.
00:19:46.07 And the only way it can do that
00:19:49.02 is by making new proteins
00:19:51.20 and by making this survival response
00:19:53.19 that allows those new proteins to fold properly.
00:19:57.22 So, that's one aspect of.
00:19:59.29 of disease biology that uses that survival response
00:20:03.00 all of the time.
00:20:04.29 Here's another aspect of human biology
00:20:06.18 that uses this survival response.
00:20:08.16 So, what you have in blue is normal proteins,
00:20:12.10 and what you have labeled in brown here
00:20:15.18 is the master regulator of this survival response.
00:20:20.14 And that's normal tissue over there.
00:20:22.20 And you can see that the survival response protein
00:20:27.16 is kind of tucked away in little corners of the cells,
00:20:30.26 because it's not being used under.
00:20:32.20 in this normal biological system.
00:20:35.11 But in the cancer cells,
00:20:37.08 you can see that that master regulator
00:20:39.05 has been amplified a great deal.
00:20:41.05 It's actually present, now, in the center of the cell,
00:20:44.03 and it's directing a whole new program of gene expression,
00:20:47.18 whole new sets of proteins that are being made,
00:20:51.14 at the dictum of the cancer cells
00:20:53.20 to help protect those cancer cells
00:20:56.12 and drive the malignant state.
00:20:58.06 And neurodegenerative disease.
00:21:00.26 these are two brain sections,
00:21:04.22 from a normal person and from someone with a.
00:21:07.13 who has died from neurodegenerative disease.
00:21:10.05 And what you're seeing here is the devastation
00:21:12.17 brought by misfolded proteins in the brain.
00:21:16.19 So, it turns out that,
00:21:18.19 in terms of human beings,
00:21:20.20 we are a bit between a rock and a hard place
00:21:23.19 with regard to this problem in protein folding.
00:21:27.28 Because cancer cells and infectious organisms
00:21:29.19 are using their resp.
00:21:32.09 their survival response, this heat shock response,
00:21:35.05 to kill us, because it strengthens them
00:21:38.04 and allows them to survive the rigors
00:21:40.26 of a living.
00:21:44.06 of a living system. And our brains, conversely,
00:21:47.01 are not using this survival response
00:21:50.06 when we would normally think they should be.
00:21:52.09 Because when we die of neurodegenerative diseases,
00:21:54.12 it's because proteins have misfolded, misfunctioned,
00:21:56.28 and just like those instruments that are not playing right with the orchestra,
00:22:01.23 they're causing devastating disease.
00:22:04.17 Now, this puts us in a difficult position,
00:22:08.00 but it's not a place where we can't move
00:22:10.06 and we can't do something important
00:22:12.20 in biological experimentation.
00:22:14.07 And the reason why we can do things
00:22:16.26 that will help to fix these problems
00:22:18.21 is because it is such a universal problem.
00:22:22.06 And so, we can take these very simple organisms
00:22:25.07 here, these yeast cells,
00:22:26.19 and understand more about how that.
00:22:29.04 the biology of that system is driven,
00:22:31.11 how to correct protein folding
00:22:33.26 and how it goes wrong,
00:22:35.21 in order to help these people over here
00:22:37.29 with all those different protein folding problems
00:22:40.13 I just mentioned to you.
00:22:42.06 So, I'll be talking to you about that in the next lectures.

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Polymer models with loops

Looped polymers have a number of properties that are not observed in unlooped polymers. Entropic effects make the intermingling of two looped polymers highly unfavourable (Bohn and Heermann, 2010b), and even a small number of loops per polymer can considerably suppress mixing of polymers. Thermodynamically, such a situation can be described as repulsion between the looped polymers. This can be understood intuitively by considering a polymer that has loops covering all lengths, i.e. small, medium and large loops, relative to the total length (contour length) of the polymer. Such a polymer has a more or less sphere-like shape and is difficult to penetrate by other polymers (Fig. 3). Considering such a model predicts that chromatin loops are a key determinant of the properties of the chromatin fibre. The more loops are formed, the less space the chromatin fibre occupies and the more it is compacted. Thus, chromosomes condense as loops are formed and their intermingling is strongly reduced.

Pioneering polymer models that were developed to explain the measured properties of interphase chromatin and that take into account chromatin looping assume loops of fairly uniform size. For instance, Sachs and colleagues proposed a model in which chromatin loops of 1.5–3.5 Mb are attached to an unspecified RW backbone, with the proposed loop size being the result of fitting data on the model (Sachs et al., 1995). Others assumed that the chromatin fibre assembles in an array of rosettes of loops of uniform size (Münkel and Langowski, 1998). However, recent 3C studies of chromatin–chromatin interactions do not support the idea of loops of fixed sizes but, instead, show that chromatin loops cover a wide range of lengths, ranging from a few kb to tens of Mb (Lieberman-Aiden et al., 2009 Simonis et al., 2006). Thus far, only our dynamic random loop model (Bohn et al., 2007 Mateos-Langerak et al., 2009) and the fractal globular model developed by Dekker and co-workers (Lieberman-Aiden et al., 2009) incorporate the idea of a wide range of loop sizes.

The dynamic random loop model (Box 1) assumes a dynamic, random interaction between monomers of a polymer, creating loops that span a wide range of sizes (Bohn et al., 2007 Mateos-Langerak et al., 2009). Several characteristics of interphase chromatin folding can be explained by this model, including the observation that each interphase chromosome occupies a limited space, i.e. a chromosome territory, in the interphase nucleus. This is reflected by the levelling off of the physical distance R between pairs of sequence elements as a function of their genomic distance g the scaling exponent ν becomes zero (Fig. 2C, Box 1). Furthermore, the model predicts different degrees of compaction along the length of a chromosome that are caused by variations in local looping probabilities (Bohn et al., 2007 Mateos-Langerak et al., 2009). In contrast to the dynamic random loop model, the fractal globular model (Lieberman-Aiden et al., 2009) (Box 1) is characterised by a scaling component ν=1/3 and does not predict the experimentally observed levelling off of R as a function of g. Taken together, the dynamic random loop model, which explicitly assumes looping at all lengths, therefore best explains key properties of the chromatin folding.

Physical interaction between chromosomes. The backbones of two chromosomes are shown in red and green. Loops and ensuing entropic effects are the major driving forces for the internal organisation of chromosome territories and their segregation in the interphase cell nucleus. Two chromosomes repel each other owing to entropic repulsion between the looped polymers. This entropic repulsion is relatively weak and, therefore, some overlap between chromosome territories occurs. The degree of overlap depends on the degree of looping of the individual chromosomes.

Physical interaction between chromosomes. The backbones of two chromosomes are shown in red and green. Loops and ensuing entropic effects are the major driving forces for the internal organisation of chromosome territories and their segregation in the interphase cell nucleus. Two chromosomes repel each other owing to entropic repulsion between the looped polymers. This entropic repulsion is relatively weak and, therefore, some overlap between chromosome territories occurs. The degree of overlap depends on the degree of looping of the individual chromosomes.

Being Small Helps

Being small and spherical helps cells to maintain a good volume to surface area ratio. Other adaptations include &aposwobbly&apos membranes and flattening, all of which increase surface area and therefore the cell&aposs ability to absorb substances by diffusion.

Ruth lawson CC BY-SA 3.0 via Wikimedia Commons

The most important factor for a cell is not just its surface area, but the surface area to volume ratio. The consumption rate of substances is dependent upon volume, but it is the cell membrane&aposs surface area that determines the rate of absorption of new material.

In other words, the greater the surface area of the cell compared to its volume, the more efficient the cell will be in performing its functions.

It is interesting to note that as a cell gets bigger, its volume will increase more than its surface area. Let&aposs look at what happens if you double the size of a cell:

  • doubling a cell&aposs size increases its volume 8 times.
  • doubling a cell&aposs size increases its surface area only 4 times.

So you can see that there is a negative relationship between size and efficiency in cells. The bigger they get the more difficult it is for them to take up materials fast enough.


This article was published online ahead of print in MBoC in Press ( on May 15, 2013.

The authors declare no conflict of interest.

J.R. and M.F. designed the study and the experiments. All authors performed the experiments and analyzed and discussed the results. J.R. wrote the manuscript with input from M.F. and J.H.

carbonyl cyanide m-chlorophenyl hydrazone

intermembrane space of mitochondria

mitochondrial targeting sequence

Watch the video: 8. Protein Folding 1 (May 2022).