How crowded is the bacterial cell?

I was wondering what is the protein concentration in an E. coli cell. When studying enzyme kinetics and activity in vitro, I would argue that the substrate and enzyme concentrations resemble those in vivo. As a result, conclusions made by such assays do not apply 100% to the naturally occurring reactions. Are there any examples in literature that address this issue?

Along those lines, what is the concentration of fatty acids/nucleic acids in the cell?

The macromolecule concentration within E Coli is estimated to be around 0.3-0.4 g/ml [1]

The concentrations of your substrate in respect to your enzyme are generally fairly analogous to in vitro studies compared to in vivo studies. However, this is heavily based on the assumption that the diffusion constants for both molecules stay consistent. In many cases that is true and errors can be corrected for using PEG to imitate the crowding effect. And yes, people have begun to look at the question [2]

However, for larger macromolecules like DNA and chromosomes that do see effects from subdiffusive transport, the molecules don't obey diffusive random-wal behavior [3]. The classic model system is the lac repressor which exhibits non-diffusive kinetics due to its interactions with DNA.


Composition of E. coli (dry weight): 55% protein, 20% RNA, 10% lipid, 15% other

Protein concentration is about 100 mg/ml or 3 mM. From the size of an E. coli cell, 1 nM is about 1 molecule/cell. This is ~1000 molecules/cell for HeLa cells.

Diffusion coefficient for an "average" protein: D ~ 5-15 microns^2/s, or ~10 ms to traverse an E. coli. For reference, a small metabolite in water diffuses about 30-100x faster.

Reference: Cell 141:1262, Key Numbers in Biology

For a great visualization of the macromolecules inside the cell, check out David Goodsell's illustrations. He tries to reproduce the protein and DNA density within the cell to show how things might be in vivo. Really great stuff.

The answer is - its very concentrated. Compare the density of the cell to that of a typical crystallized protein, which is I believe 0.8 g/ml of protein.

Bacterial Cell

Hundreds of thousands of bacterial species exist on Earth. They can be found in very diverse environments ranging from cold to hot and alkaline to acid. They live in soil, in water, and on rocks. They exist deep in the earth, high on mountains, and in deep-sea vents. They grow on and in other bacteria, worms, insects, plants, animals, and people.

Bacteria are prokaryotes . Prokaryotic cells possess simpler structures than eukaryotic cells , since they do not have a nucleus , other membrane bound organelles , or a cytoskeleton . Bacterial cells have two major compartments, the cytoplasm and cell envelope, and may also have exterior appendages , such as flagella or pili. There are two major types of prokaryotes: bacteria and archaea. Archaea (also called archaebacteria) are often found in extreme environments, and while they are clearly prokaryotic, they have evolved separately from bacteria. Mitochondria and chloroplasts are two membrane-bound organelles carried within eukaryotic cells that are thought to have been derived from free-living prokaryotic organisms that became irreversibly engulfed by ancestral eukaryotes.


Once vesicles are produced in the endoplasmic reticulum and modified in the golgi body they make their way to a variety of destinations within the cell. Vesicles first leave the golgi body and are released into the cytoplasm in a process called budding. Vesicles are then moved towards their destination by motor proteins. Once the vesicle arrives at its destination it joins with the bi-lipid layer in a process called fusion, and then releases its contents.

Budding Edit

Receptors embedded in the membrane of the golgi body bind specific cargo (such as dopamine) on the lumenal side of the vesicle. These cargo receptors then recruit a variety of proteins including other cargo receptors and coat proteins such as clathrin, COPI and COPII. As more and more of these coating proteins come together, they cause the vesicle to bud outward and eventually break free into the cytoplasm. The coating proteins are then shed into the cytoplasm to be recycled and reused. [1]

Motility between cell compartments Edit

For movement between different compartments within the cell, vesicles rely on the motor proteins myosin, kinesin (primarily anterograde transport) and dynein (primarily retrograde transport). One end of the motor proteins attaches to the vesicle while the other end attaches to either microtubules or microfilaments. The motor proteins then move by hydrolyzing ATP, which propels the vesicle towards its destination. [2]

Docking and Fusion Edit

As a vesicle nears its intended location, RAB proteins in the vesicle membrane interact with docking proteins at the destination site. These docking proteins bring the vesicle in closer to interact with the SNARE Complex found in the target membrane. The SNARE complex reacts with synaptobrevin found on the vesicle membrane. [3] This forces the vesicle membrane against the membrane of the target complex (or the outer membrane of the cell) and causes the two membranes to fuse. Depending on whether the vesicle fuses with a target complex or the outer membrane, the contents of the vesicle are then released either into the target complex or outside the cell. [4]

Examples In eukaryotes Edit

  1. Intracellular trafficking occurs between subcellular compartments like Golgi cisternae and multivesicular endosomes for transport of soluble proteins as MVs.
  2. Budding of MVs directly from plasma membrane as microvesicles released outside the secretory cells.
  3. Exosomes are MVs that can form inside an internal compartment like multivesicular endosome. Exosomes are released eventually due to fusion of this endosome with plasma membrane of cell.
  4. Hijacking of exosomal machinery by some viruses like retroviruses, wherein viruses bud inside multivesicular endosomes and get secreted subsequently as exosomes.

All these types (1-4) of modes of membrane vesicle trafficking, taking place in eukaryotic cells have been explained diagrammatically. [5]

Unlike in eukaryotes, membrane vesicular trafficking in prokaryotes is an emerging area in interactive biology for intra-species (quorum sensing) and inter-species signaling at host-pathogen interface, as prokaryotes lack internal membrane-compartmentalization of their cytoplasm.

For more than four decades, cultures of gram negative microbes revealed the presence of nanoscale membrane vesicles. A role for membrane vesicles in pathogenic processes has been suspected since the 1970s, when they were observed in gingival plaque by electron microscopy. [6] These vesicles were suspected to promote bacterial adhesion to the host epithelial cell surface. [7] Their role in invasion of animal host cells in vivo was then demonstrated. [8] In inter-bacterial interactions, OMVs released by Pseudomonas aeruginosa microbes were shown to fuse with outer membrane of other gram negative microbes causing their bacteriolysis these OMVs could lyse gram-positive microbes as well. [9] Role of OMVs in Helicobacter pylori infection of human primary antral epithelial cells, as model that closely resembles human stomach, has also been confirmed [10] VacA-containing OMVs could also be detected in human gastric mucosa, infected with H. pylori.. [11] Salmonella OMVs were also shown to have direct role in invasion of chicken ileal epithelial cells in vivo in the year, 1993 (ref 4) and later, in hijacking of defense macrophages into sub-service for pathogen replication and consequent apoptosis of infected macrophages in typhoid-like animal infection. [12] These studies brought the focus on OMVs into membrane vesicle trafficking and showed this phenomenon as involved in multifarious processes like genetic transformation, quorum sensing, competition arsenal among microbes, etc., and invasion, infection, immuno-modulation, etc., of animal hosts. [6] A mechanism has already been proposed for generation of OMVs by gram negative microbes involving, expansion of pockets of periplasm (named, periplasmic organelles) due to accumulation of bacterial cell secretions and their pinching off as outer membrane bounded vesicles (OMVs) on the lines of a 'soap bubble' formation with a bubble tube, and further fusion or uptake of diffusing OMVs by host/target cells (Fig. 2). [13]

In conclusion, membrane vesicle trafficking via OMVs of Gram-negative organisms, cuts across species and kingdoms - including plant kingdom [14] - in the realm of cell-to-cell signaling.

Responses of Microorganisms to Osmotic Stress

The cytoplasm of bacterial cells is a highly crowded cellular compartment that possesses considerable osmotic potential. As a result, and owing to the semipermeable nature of the cytoplasmic membrane and the semielastic properties of the cell wall, osmotically driven water influx will generate turgor, a hydrostatic pressure considered critical for growth and viability. Both increases and decreases in the external osmolarity inevitably trigger water fluxes across the cytoplasmic membrane, thus impinging on the degree of cellular hydration, molecular crowding, magnitude of turgor, and cellular integrity. Here, we assess mechanisms that permit the perception of osmotic stress by bacterial cells and provide an overview of the systems that allow them to genetically and physiologically cope with this ubiquitous environmental cue. We highlight recent developments implicating the secondary messenger c-di-AMP in cellular adjustment to osmotic stress and the role of osmotic forces in the life of bacteria-assembled in biofilms.

Keywords: biofilms c-di-AMP osmoprotectants osmoregulation osmosensing transporters and channels.

Show/hide words to know

Bacteria: one-celled, microscopic organisms that grow and multiply everywhere on Earth. They can be either useful or harmful to animals. more

Enamel: a hard, white substance that works as a protective covering. The outsides of human teeth are enamel. more

Gland: an organ that releases materials for use in certain places in the body or on the outside of the body. more

Hostile: unfriendly or difficult.

Microbe: a living thing so tiny that you would need a microscope to see it. more

Microbiome: the community of microorganisms that live inside and/or on your body.

Bacteria among us, on us, and inside us

Trillions of bacteria and other microbes live all over the outside and inside the human body. Altogether, these microbes are called the human microbiome. Many types of bacteria have a bad reputation. They cause all sorts of illness and disease. But other kinds of bacteria do many helpful things in the body.

Scientists estimate that each of us carry 10 times more bacterial cells than all the cells that make up the human body. Many kinds of bacteria live on our skin. Bacteria live all over our bodies— there are lots in our mouths, too. They live in our saliva. And some bacteria even live under our eyelids on the surface of our eyes. However, the largest number of bacteria live in our guts.

Bacteria in our guts: Healthy gut equals healthy body

Our guts are important. The gut includes the stomach, small intestine, and large intestine. Together, these pieces make up a large part of the digestive system. Scientists know that the gut has a huge impact on each and every human body system. Some experts say that as much as 70 percent of the immune system actually lives in the gut.

The human gut is home to more than 100 trillion microorganisms. This massive crowd includes more than 400 kinds of bacteria. Some are good. Some are not so good. And some are downright ugly and nasty. Good bacteria in the gut are important. They play key roles in keeping the body working smoothly and efficiently. Nasty bacteria can make you sick. They can cause diseases and infections. Luckily, most bacteria inside you right now are harmless. They live peacefully side-by-side with the cells of your body.

Bacteria in our stomachs

Our stomachs are filled with powerful acid. The acid helps to digest all of the food that we eat. Most living things cannot survive in acid. That includes most microbes.

Still, some types of bacteria can survive in the hostile environment of the stomach. Heliobacter pylori are bacteria shaped like tight spirals. Scientists know that this microbe can attach to the stomach’s cell lining. It can cause peptic ulcer disease and might be a cause of stomach cancer. Scientists are still exploring what roles this bacteria may play in our digestive process.

Bacteria in our mouths

The number and type of bacteria on any given part of the body varies from person to person. Plenty of bacteria live in our mouths. They live on our tongues and on our teeth. Bacteria are part of a sticky substance called plaque. You brush your teeth to get rid of the plaque. When you don’t brush well, the plaque hardens into a substance called tartar. Dentists call it calculus. These same bacteria secrete acid that can dissolve tooth enamel. This can cause cavities and tooth decay. These bacteria are always in your mouth, but it is important to go see the dentist so that you can clean out old build up.

Bacteria in our eyes

Some bacteria even live on the cells that form the inside of our eyelids and the surface of our eyes. That cell lining is called the conjunctiva. Glands in our eyes make fluid constantly. That fluid keeps the conjunctiva moist. When we blink, the eyelids wash away bacteria, dust, and other harmful substances from the surface of our eyeballs. Our tears also contain chemicals that keep bacteria from growing out of control.

Bacteria in our lungs

The lungs are a major part of our respiratory system. We must breathe air to get oxygen into our blood. But air is always filled with microbes. Our lungs have built-in ways to remove bacteria and other harmful microbes. Special cells produce mucous, which is a thick, sticky substance that traps bacteria.

Other special cells are always moving the mucous out of the lungs. When you cough or sneeze, you might spew millions of droplets of mucous into the air. That mucous is filled with bacteria. That is why it is always important to cover your mouth when you cough or sneeze.

Bacteria on our skin

Our skin acts as a barrier. It keeps nasty, disease-causing microbes from getting inside our bodies. However, plenty of bacteria live in our hair, on our scalps, and all over every square inch of our skin. Some live on the skin’s surface. Some live deep among the many layers of our skin.

Lots of bacteria are found near the tiny glands that produce oil and sweat. These glands provide the bacteria with water and nutrients to grow and reproduce. By itself, human sweat has no smell. The bacteria living near sweat glands play a role in producing body odor. It’s true, bacteria can make you stink.


NuSeT is a robust nuclear segmentation tool

Tools for segmenting fluorescent nuclei need to address multiple features and limitations of biological images.[6,33] Typical issues and limitations include:

  1. Boundary assignment ambiguity: biological samples frequently have very high cell density with significant overlap between objects.
  2. Signal intensity variation: Within one image, the signal can vary within each nucleus (e.g. due to different compaction states of the DNA in heterochromatin vs. euchromatin) and across nuclei (e.g. due to cell to cell differences in nuclear protein expression levels and differences in staining efficiency).
  3. Non-cellular artifacts and contaminants: Fluorescence microscopy samples are often contaminated with auto-fluorescent cell debris as well as non-cellular artifacts.
  4. Low signal to noise ratios (SNRs): Low SNRs typically result from lower expression levels of fluorescent targets and/or high background signal, such as sample autofluorescence. (S1 Fig).

We used an end-to-end training approach that incorporates both U-Net and Region Proposal Network (RPN)[15,18] to address these issues (Methods). In our approach, the training and inference step consists of running an input image in parallel in both U-Net and RPN. The final output of U-Net consists of two feature maps of the same shape as the input image, representing background and foreground pixel-assignment scores.[10] The final foreground prediction is then computed from the maximum class score of each pixel. Although U-Net alone performs well on some microscopy datasets[30,34], we incorporated RPN since it was originally designed to detect objects in images with high information content.[18] We reasoned that the accurate performance of RPN in detecting objects can be leveraged to improve nuclear segmentation performance. To achieve robust separation of touching nuclei, we used RPN bounding boxes to determine nuclear centroids, which were then supplied as seeds to a watershed algorithm.[35,36] To improve segmentation accuracy in images with large nuclear size variations, we modified the original RPN architecture to use bounding box dimensions based on average nuclear size for each image (S2 Fig). Instead of training U-Net and RPN separately, we merged the feature-extraction part of RPN with the down-sampling part of U-Net to avoid longer training time and more memory cost (Fig 1A).[10,15,18,19] In this way, the instance detection insights of RPN are extracted from the model structure. To evaluate the segmentation performance of the different algorithms, we computed the mean intersection over union for foreground and background (mean IoU), Root Mean Square Error (RMSE), and pixel accuracy (to benchmark pixel-level performance). Since in biological image processing the primary focus is on cell-level segmentation rather than pixel-level accuracy, we also included object-level segmentation metrics, including the rate of correctly separating overlapping nuclei, correct and incorrect detections, splits, merges, catastrophes, and both the false-positive and false-negative detection rates (Methods).[29,30] Two separate datasets, ‘MCF10A’ and ‘Kaggle’, were used to compare the performance of the algorithms.[33] The MCF10A dataset consists of images of relatively uniformly fluorescent nuclei of a non-tumorigenic breast epithelial cell line[37], grown to different levels of confluence. The Kaggle dataset was adapted from a public dataset[33] representing cells from different organisms (including humans, mice, and flies) and containing images with a wide range of brightness, cell densities, and nuclear sizes. The overall comparison in S1 Table and S2 Table suggests that NuSeT achieves similar pixel-level segmentation accuracy compared with a current state-of-the-art pixel-level cell segmentation approach (U-Net) but has higher separation rates for overlapping nuclei and fewer merge errors. With the Kaggle dataset, NuSeT improved the separation of touching nuclei by more than 75% compared with U-Net. Compared with another state-of-the-art instance segmentation approach, Mask R-CNN, NuSeT achieved much lower false-negative detection rates in Kaggle dataset, leading to significantly better pixel-level segmentation accuracy. To make NuSeT more user-friendly, we have prepared a cross-platform graphic user interface (GUI) for the scientific community. Our GUI comes with the pretrained model which we used to benchmark NuSeT performance for various nuclei segmentation tasks. The GUI also allows the use of training and predicting modules (Fig 1B), allowing the users to perform custom segmentation tasks with NuSeT.

Osmosis and Diffusion

Diffusion – model diffusion using a plastic baggie, iodine and a beaker. This article explains what happens.

Cell Membrane Transport – simple diagram shows how molecules enter the cell through diffusion, facilitated diffusion, and osmosis

Cell Membrane Images – work in groups to create captions and titles for images depicting the cell membrane and transport across it.

Case Study: Cystic Fibrosis – for AP Biology, examines the role of cell membrane proteins in clearing mucus from the lungs.

Observing Osmosis – use an egg, vinegar, corn syrup, will take a few days
Salt and Elodea – quick lab to observe the effects of salt water on elodea cells

Osmosis in Cells – AP Lab 1, modified, using dialysis tubes and sugar solutions to observe water movement

Using Dilutions to Find CFU

The procedure to find CFU of a given sample involves first diluting that sample. The dilutions are then plated onto plates with the correct growth medium. Multiple dilutions are often a good idea since the original sample can be very concentrated.

After allowing the bacteria to grow on the plates for a given amount of time, individual colonies are counted on a plate. If the sample was too concentrated then instead of individual colonies you will see a large area covered with bacterial growth which is called a lawn. This means you should further dilute your sample and try growing again so that you can see individual colonies.

As individual colonies come from a single bacteria that replicated itself many times over, only these count toward the CFU.

News Alert: Rare Bacterial Infection On News

In May 2017, an Aquarium in Vancouver, BC had a bizarre incident where a little girl was grabbed into the water by a sea lion and that video went viral on social media. According to the Aquarium officials, the girl could have contracted a rare bacterial disease called “Seal Finger.” A particular type of bacteria called Mycoplasma bacteria lives in the sea mammals’ mouth. In the Aquarium incident, the bitten girl contracted this bacteria from the sea lion’s bite. If this disease kept untreated, then the infected person could lose fingers and even limbs.

You can watch that viral video here:

First Self-Replicating Synthetic Bacterial Cell

Genomic science has greatly enhanced our understanding of the biological world. It is enabling researchers to "read" the genetic code of organisms from all branches of life by sequencing the four letters that make up DNA. Sequencing genomes has now become routine, giving rise to thousands of genomes in the public databases. In essence, scientists are digitizing biology by converting the A, C, T, and G's of the chemical makeup of DNA into 1's and 0's in a computer. But can one reverse the process and start with 1's and 0's in a computer to define the characteristics of a living cell? We set out to answer this question.

In the field of chemistry, once the structure of a new chemical compound is determined by chemists, the next critical step is to attempt to synthesize the chemical. This would prove that the synthetic structure had the same function of the starting material. Until now, this has not been possible in the field of genomics. Structures have been determined by reading the genetic code, but they have never been able to be verified by independent synthesis.

In 2003, JCVI successfully synthesized a small virus that infects bacteria. By 2008, the JCVI team was able to synthesize a small bacterial genome however they were unable to activate that genome in a cell at that time.

Colonies of the transformed Mycoplasma mycoides bacterium.

Image Credit: J. Craig Venter Institute.

Now, this scientific team headed by Drs. Craig Venter, Hamilton Smith and Clyde Hutchison have achieved the final step in their quest to create the first synthetic bacterial cell. In a publication in Science magazine, Daniel Gibson, PhD and a team of 23 additional researchers outline the steps to synthesize a 1.08 million base pair Mycoplasma mycoides genome, constructed from four bottles of chemicals that make up DNA. This synthetic genome has been "booted up" in a cell to create the first cell controlled completely by a synthetic genome.

The assembly of a synthetic M. mycoides genome in yeast. Figure from Gibson, D. G., J. I. Glass, et al. 2010. Creation of a bacterial cell controlled by a chemically synthesized genome. Science, Published online May 20 2010.

The work to create the first synthetic bacterial cell was not easy, and took this team approximately 15 years to complete. Along the way they had to develop new tools and techniques to construct large segments of genetic code, and learn how to transplant genomes to convert one species to another. The 1.08 million base pair synthetic M. mycoides genome is the largest chemically defined structure ever synthesized in the laboratory.

While this first construct — dubbed M. mycoides JCVI-syn1.0, is a proof of concept, the tools and technologies developed to create this cell hold great promise for application in so many critical areas. Throughout the course of this work, the team contemplated, discussed, and engaged in outside review of the ethical and societal implications of their work.

Negatively stained transmission electron micrographs of dividing M. mycoides JCVI-syn1. Freshly fixed cells were stained using 1% uranyl acetate on pure carbon substrate visualized using JEOL 1200EX transmission electron microscope at 80 keV. Electron micrographs were provided by Tom Deerinck and Mark Ellisman of the National Center for Microscopy and Imaging Research at the University of California at San Diego.

The ability to routinely write the software of life will usher in a new era in science, and with it, new products and applications such as advanced biofuels, clean water technology, and new vaccines and medicines. The field is already having an impact in some of these areas and will continue to do so as long as this powerful new area of science is used wisely. Continued and intensive review and dialogue with all areas of society, from Congress to bioethicists to laypeople, is necessary for this field to prosper.

Watch the video: Μικροσκοπική παρακολούθηση βακτηρίων (December 2021).