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Protein that exit from the cell - as marker

Protein that exit from the cell - as marker


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Searching for some protein, that I could use as extracellular marker for mammalian cells. I need to insert mRNA to cell, and to detect the protein outside the cell (not on membrane) if the mRNA successfully enter and been translated. (not GFP, I need protein that exit from the cell in big numbers)

Thank you.


You can always express GFP or your favorite protein in a secretory vector like pSecTag or pSecTag2 from Invitrogen/Life/ThermoFisher/SuperUltraBioMegaMart. There are probably others, but those were the first ones I came across. They contain the mouse Igκ signal sequence for efficient secretion (so the website says, I've never used it).

I don't know the details of your experiment, but are you sure you want to use a secreted protein as a transfection marker? Remember, it's possible that only a small fraction of your cell population will take up the vector (or mRNA, if that's what you're using, but there are issues with that), but you will see secreted protein regardless of the number of cells that take it up.


SEAP, secreted alkaline phosphatase, and vectors engineered to express fusions to this reporter gene may be well-suited to solve your problem.


Protein that exit from the cell - as marker - Biology

Secreted proteins, together making up the secretome, can be defined as proteins that are actively transported out of the cell. In humans, cells such as endocrine cells and B-lymphocytes are specialized in protein secretion, but all cells secrete proteins to a certain extent. Proteins that are secreted from the cell play a crucial role in many physiological, developmental and pathological processes and are important for both intercellular and intracellular communication. In addition to being a rich source of new therapeutics and drug targets, a large fraction of the blood diagnostic tests used in the clinic are directed towards secreted proteins, emphasizing the importance of this class of proteins for medicine and biology. Medically important secreted proteins include cytokines, coagulation factors, growth factors and other signaling molecules. We predict 1708 proteins, or 9% of the human proteome, to be secreted based on results from multiple prediction methods.

The most common secretion pathway is the secretory pathway (Figure 1). Newly synthetized proteins are transported from the endoplasmic reticulum (ER), passing the Golgi apparatus and packed into vesicles. The vesicles are then transported to the plasma membrane. Vesicles and plasma membrane merge, thereby releasing proteins into the extracellular space (exocytosis). The signal sequence that targets proteins to the ER is called a signal peptide (SP) and consists of a short, hydrophobic N-terminal sequence (von Heijne G&period (1985)). Membrane proteins may also contain a SP, but most often the N-terminal transmembrane (TM) region functions as the signal sequence. The signal sequences are recognized by chaperone proteins that guide the synthesizing ribosomes to the rough ER, where a co-translational translocation of the newly synthesized peptide occurs with the help of a protein complex referred to as the translocon (Johnson AE et al. (1999)). Membrane proteins are transferred to the lipid bilayer of the ER membrane via the translocon, whereas secretory proteins are released into the ER lumen after proteolytic cleavage of the SP. Proteins that pass the quality control in the ER lumen are transported via vesicles to the Golgi apparatus, where they are further modified and sorted for transport to their final destination, which most often is the plasma membrane, lysosomes or secretion out from the cell.

Figure 1. Overview of the secretory pathway.

The functions of secreted proteins are diverse, but cell signalling is an important example. Signaling between or within cells via secreted signaling molecules can be paracrine, autocrine, endocrine or neuroendocrine depending on the target. Among the most important signaling proteins are cytokines, kinases, hormones and growth factors (Farhan H et al. (2011)).

A large fraction of the clinically approved treatment regimens today use drugs directed towards (or consisting of) secreted proteins or cell surface-associated membrane proteins. Out of the 754 protein targets with known pharmacological action for approved drugs on the market at present (Wishart DS et al. (2006)), 163 are predicted to be secreted.

Secreted proteins are often enriched in the organelles of the secretory pathway (ER, Golgi apparatus, vesicles), before they are released to the extracellular matrix. This enables a detection of the protein by IF, although their final destination lies outside of the cell. In Figure 2, IF images of three predicted secreted proteins are shown.

Figure 2. Examples of three different predicted secreted proteins are shown in the neuron-like SH-SY5Y cell line: CHGB and SCG3 are found in secretory vesicles, while NPY is enriched in the Golgi apparatus.

Secreted proteins can often be identified based on their SPs, which have a number of features suitable for computational prediction models. The SP is typically 15-30 amino acids long and primarily recognized by a short hydrophobic and mostly positive N-terminal alpha-helix (n-region) combined with a hydrophobic h-region and a C-terminal polar uncharged c-region (Emanuelsson O et al. (2007)). There are many algorithms which use these features to predict the presence of SPs in proteins, and there are also a number of methods which incorporate a SP prediction model into transmembrane (TM) topology prediction algorithms, to allow for more reliable results when it comes to distinguishing an SP and a TM segment.

The human 'secretome' can be defined as all genes encoding at least one secreted protein and has been analyzed here by performing a whole-proteome scan using three methods for SP prediction: SignalP4.0 (Petersen TN et al. (2011) Käll L et al. (2004)) , Phobius and SPOCTOPUS (Viklund H et al. (2008)), which have all been shown to give reliable prediction results in comparative analyses. A majority decision-based method (MDSEC) has been constructed using the results from the three different SP prediction methods to obtain a list of predicted secreted proteins (Uhlén M et al. (2015)). All proteins with a predicted SP by at least two of the three methods are considered secreted and these were further annotated in order to exclude genes that are predicted to reside in intracellular locations such as ER or Golgi, despite having a signal peptide prediction, from the set. Since signal peptides are found both in secreted proteins and in certain types of membrane proteins, the results were filtered using the majority decision-based method (MDM) for membrane protein topology prediction (Fagerberg L et al. (2010)). All proteins with a predicted SP in combination with a predicted TM region according to the MDM are considered membrane-spanning and therefore not secreted. The resulting numbers of genes encoding a predicted secreted protein based on the three methods as well as the majority-decision based method and the result from annotation of the secretome are shown in Table 1. The resulting lists of predicted secreted proteins as well as predicted membrane proteins were used as a classification of the human proteome.

Table 1. Prediction of the human secretome by three different prediction methods for signal peptides as well as the MDSEC and the final prediction resulting from manual annotation.

Protein class Number of genes Number of proteins Source
Predicted secreted proteins 1708 4361 HPA
Secreted proteins predicted by MDSEC 2943 6743 HPA
SignalP predicted secreted proteins 2525 5816 SignalP
Phobius predicted secreted proteins 3338 7613 Phobius
SPOCTOPUS predicted secreted proteins 3710 8165 SPOCTOPUS

An analysis of tissue distribution categories based on RNA-sequencing data shows that a larger fraction of the genes encoding secreted proteins belongs to the tissue enhanced, tissue enriched or group enriched genes, compared to all genes presented in the Cell Atlas (Uhlén M et al. (2015)) (Figure 3). Only a relatively small portion of the genes in the secretome show low tissue specificity. This is in agreement with the tissue specific functions for many secreted proteins. The secreted class contains many of the most abundantly expressed genes and the highest expression levels of secreted proteins are found in pancreas and salivary gland.

Figure 3. Bar plot showing the percentage of genes in different tissue specificity categories for secreted protein-coding genes, compared to all genes in the Cell Atlas. Asterisk marks a statistically significant deviation (p≤0.05) in the number of genes in a category based on a binomial statistical test. Each bar is clickable and gives a search result of proteins that belong to the selected category.

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NIH scientists discover key pathway in lysosomes that coronaviruses use to exit cells

Targeting cells’ ‘trash compactor’ could lead to new antiviral strategy to fight COVID-19.

Illustration shows components of the lysosome exocytosis pathway, which coronaviruses use to exit cells. Also shown are components of the normal biosynthetic secretory pathway. NIH

Researchers at the National Institutes of Health have discovered a biological pathway that the novel coronavirus appears to use to hijack and exit cells as it spreads through the body. A better understanding of this important pathway may provide vital insight in stopping the transmission of the virus—SARS-CoV-2—which causes COVID-19 disease.

In cell studies, the researchers showed for the first time that the coronavirus can exit infected cells through the lysosome, an organelle known as the cells’ “trash compactor.” Normally the lysosome destroys viruses and other pathogens before they leave the cells. However, the researchers found that the coronavirus deactivates the lysosome’s disease-fighting machinery, allowing it to freely spread throughout the body.

Targeting this lysosomal pathway could lead to the development of new, more effective antiviral therapies to fight COVID-19. The findings, published today in the journal Cell, come at a time when new coronavirus cases are surging worldwide, with related U.S. deaths nearing 225,000.

Scientists have known for some time that viruses enter and infect cells and then use the cell’s protein-making machinery to make multiple copies of themselves before escaping the cell. However, researchers have only a limited understanding of exactly how viruses exit cells.

Conventional wisdom has long held that most viruses—including influenza, hepatitis C, and West Nile—exit through the so-called biosynthetic secretory pathway. That’s a central pathway that cells use to transport hormones, growth factors, and other materials to their surrounding environment. Researchers have assumed that coronaviruses also use this pathway.

But in a pivotal experiment, Nihal Altan-Bonnet, Ph.D., chief of the Laboratory of Host-Pathogen Dynamics at the NIH’s National Heart, Lung, and Blood Institute (NHLBI) and her post-doctoral fellow Sourish Ghosh, Ph.D., the study’s main authors, found something different. She and her team exposed coronavirus-infected cells (specifically, mouse hepatitis virus) to certain chemical inhibitors known to block the biosynthetic pathway.

“To our shock, these coronaviruses got out of the cells just fine,” Altan-Bonnet said. “This was the first clue that maybe coronaviruses were using another pathway.”

To look for that pathway, the researchers designed additional experiments using microscopic imaging and virus-specific markers involving human cells. They discovered that coronaviruses somehow target the lysosomes, which are highly acidic, and congregate there.

That finding raised yet another question for Altan-Bonnet’s team: If coronaviruses are accumulating in lysosomes and lysosomes are acidic, why are the coronaviruses not destroyed before exiting?

In a series of advanced experiments, the researchers demonstrated that lysosomes get de-acidified in coronavirus-infected cells, significantly weakening the activity of their destructive enzymes. As a result, the viruses remain intact and ready to infect other cells when they exit.

“These coronaviruses are very sneaky,” Altan-Bonnet said. “They’re using these lysosomes to get out, but they’re also disrupting the lysosome so it can’t do its job or function.”

The researchers also discovered that disrupting normal lysosome function appears to harm the cells’ immunological machinery. “We think this very fundamental cell biology finding could help explain some of the things people are seeing in the clinic regarding immune system abnormalities in COVID patients,” Altan-Bonnet said. This includes cytokine storms, in which an excess of certain pro-inflammatory proteins in the blood of COVID patients overwhelm the immune system and cause high death rates.

Now that this mechanism has been identified, researchers may be able to find ways to disrupt this pathway and prevent lysosomes from delivering viruses to the outside of the cell or re-acidify lysosomes in order to restore their normal functions in coronavirus-infected cells so they can fight COVID. The authors have already identified one experimental enzyme inhibitor that potently blocks coronaviruses from getting out of the cell.

“The lysosome pathway offers a whole different way of thinking about targeted therapeutics,” she said, adding that further studies will be needed to determine if such interventions will be effective and whether existing drugs can help block this pathway. She notes the findings could go a long way toward stemming future pandemics caused by other coronaviruses that may emerge.

Research reported in this study was funded by the Division of Intramural Research of NHLBI, part of the National Institutes of Health. Additionally, the research was supported by NIH grants including NIH R01 AI091985-05 NIH R01 NS36592 F32-AI113973 NIH R37GM058615 and NIH R01AI135270. All other co-authors were supported by intramural NIH and National Cancer Institute funds.

Study: β-Coronaviruses use lysosomes for egress instead of the biosynthetic secretory pathway DOI: 10.1016/j.cell.2020.10.039

This news release describes a basic research finding. Basic research increases our understanding of human behavior and biology, which is foundational to advancing new and better ways to prevent, diagnose, and treat disease. Science is an unpredictable and incremental process — each research advance builds on past discoveries, often in unexpected ways. Most clinical advances would not be possible without the knowledge of fundamental basic research.


Author Summary

Enteroviruses are significant human pathogens, causing myocarditis, aseptic meningitis and encephalitis. The mechanisms of enterovirus dissemination in the host and cell-to-cell spread may be critical factors influencing viral pathogenesis. Here, we have generated a recombinant coxsackievirus expressing “fluorescence timer” protein (Timer-CVB3) which assists in following the progression of infection within the host. Unexpectedly, we observed the shedding of microvesicles containing virus in partially-differentiated progenitor cells infected with Timer-CVB3. These extracellular microvesicles (EMVs) were released in high levels following cellular differentiation, and may play a role in virus dissemination. Timer-CVB3 will be a valuable tool in monitoring virus spread in the infected host.

Citation: Robinson SM, Tsueng G, Sin J, Mangale V, Rahawi S, McIntyre LL, et al. (2014) Coxsackievirus B Exits the Host Cell in Shed Microvesicles Displaying Autophagosomal Markers. PLoS Pathog 10(4): e1004045. https://doi.org/10.1371/journal.ppat.1004045

Editor: Ted C. Pierson, National Institutes of Health, United States of America

Received: October 26, 2012 Accepted: February 17, 2014 Published: April 10, 2014

Copyright: © 2014 Robinson et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: This work was supported by National Institutes of Health (NIH) R01 Award NS054108 (to RF), NIH R01 Awards AI042314 and HL093177 (to JLW), NIH R01 Award HL092136 (to RAG) an NIH Research Supplement to Promote Diversity in Health-Related Research Award 3R01NS054108-01A2S1 (to RF and SMR), an SDSU University Grants Program Award (to RF), a National Institutes of Mental Health (NIMH) Minority Research Infrastructure Support Program (M-RISP) R24 Faculty Fellow Award MH065515 (to RF), and an NIH F32 Ruth L. Kirschstein National Research Service Award AI-065095 (to CTC). GT is a recipient of an Achievement Rewards for College Scientists (ARCS) Foundation Scholarship, the Inamori Fellowship, and the Gen-Probe Fellowship. SMR is a recipient of the Rees-Stealy Research Foundation and the San Diego State University Heart Institute Fellowship. SR is a recipient of the SDSU McNair Scholars Program and the National Science Foundation S-STEM Scholars Program. CC and AMS were supported in part by NSF DEB 1046413: Dimensions: Viral Diversity in Coral Reef Ecosystems. TEM equipment was purchased with support by the National Science Foundation grant DBI-030829. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. No conflicts of interest exist between the subject matter and the authors included in the manuscript.

Competing interests: The authors have declared that no competing interests exist.


10 Must-have Markers for Senescence Research

Interested in studying senescence? Understanding when and why cell cycle arrest occurs is critical to many fields of research, including (but not limited to) studies of development, aging, and cancer. We all know the best tools produce the best results, so make sure you have all your bases covered with this list of the top 10 targets for your senescence research!

Senescent cells are known to express β-Galactosidase in a pH-dependent fashion, specifically detectable at pH 6 (1). This handy staining kit contains everything you need to detect β-galactosidase activity at pH 6 in cells - or even frozen tissue! Perfect for quickly and easily testing multiple cell populations or tissue samples, the directions are straightforward, and the blue staining is bright and clear.

β-Galactosidase staining at pH 6 on normal WI38 cells at population doubling 29 (left) and senescent WI38 cells at population doubling 36 (right).

p53 is so well-studied it almost needs no introduction! A major player in the DNA Damage Response (DDR) pathways, p53 is also a critical regulator of the cell cycle, where accumulated phosphorylated p53 will drive activation of cyclin dependent kinase inhibitors (CDKIs) and ultimately lead to cell cycle arrest.

Confocal Immunofluorescent analysis of HT-29 cells using p53 (7F5) Rabbit mAb (green). Actin filaments have been labeled with DY-554 phalloidin (red).

As mentioned above, senescent cell-cycle arrest relies heavily on phospho-53, which accumulates and activates multiple different CDKIs. Comparative analysis between p53 and phospho-p53 levels is often a critical step in studying the DDR pathway and senescence.

Confocal immunofluorescent analysis of MCF-7 cells, untreated (left) or etoposide-treated (right), using Phospho-p53 (Ser46) Antibody (green). Actin filaments have been labeled with DY-554 phalloidin (red).

One of the most well-established senescence markers, p21 is a CDKI downstream of phospho-p53. p21 acts as an inhibitor of the cell cycle by blocking progression through G1/S when associated with CDK2 (1).

Confocal immunofluorescent analysis of MCF7 cells using p21 Waf1/Cip1 (12D1) Rabbit mAb (red) and Phospho-Histone H3 (Ser10) (6G3) Mouse mAb #9706 (green). Blue pseudocolor = DRAQ5® #4084 (fluorescent DNA dye).

Another common and reliable senescence marker, expression of p16 is thought to drive cells into senescence (2). p16 is a member of the INK4 family of CDKIs, which acts with CDK4 and CDK6 to arrest the cell cycle in G1 (3).

Western blot analysis of extracts from HeLa and HUVEC cells using p16 INK4A (D3W8G) Rabbit mAb (upper) or β-Actin (D6A8) Rabbit mAb #8457 (lower).

Senescent cells often exhibit morphological changes, making LaminB1 another useful indicator of senescence. A marker for nuclear morphology, LaminB1 expression is lost in senescent human and murine cells (4). Loss of LaminB1 and increased accumulation of p21 and p16 are all important, classic hallmarks of senescence.

Confocal immunofluorescent analysis of HT-29 cells using Lamin B1 (119D5-F1) Mouse mAb (green) and β-Actin (13E5) Rabbit mAb (Alexa Fluor® 647 Conjugate) #8584 (red). Blue pseudocolor = Propidium Iodide (PI)/RNase Staining Solution #4087 (fluorescent DNA dye).

Senescent cells have many common traits, but they are not by any means identical. Each senescent population is characterized by unique levels of cytokines, growth factors, and proteases this is called the senescence-associated secretory phenotype (SASP). The SASP Antibody Sampler Kit contains a robust collection of antibodies for various proteins for studying senescent cells. This collection will allow you to determine the SASP specific to your cell population.

Western blot analysis of recombinant Human Interleukin-1β (hIL-1β) #8900 using IL-1β (D3U3E) Rabbit mAb.

Typically, phosphorylation of Rb is necessary to relieve repression of transcriptional targets and progress the cell cycle. Inhibition of the cell-cycle by various CDKIs, including p21 and p16, leads to hyperactivation of Rb this ultimately promotes the arrest of the cell cycle and senescence (4).

Confocal immunofluorescent image of SH-SY5Y cells, using RB (4H1) Mouse mAb (green). Actin filaments have been labeled with Alexa Fluor® 555 phalloidin (red).

Since Rb must be phosphorylated to progress the cell cycle, phospho-Rb is not found in senescent cells. Like p53, comparative analysis of Rb and phospho-Rb is paramount when investigating senescence.

Confocal immunofluorescent analysis of MCF7 (left) and BT-549 (right) cells, untreated (upper) or λ phosphatase-treated (lower) using Phospho-Rb (Ser807/Ser811) (D20B12) XP® Rabbit mAb (green). Actin filaments were labeled with DY-554 phalloidin (red). Blue pseudocolor = DRAQ® #4084 (fluorescent DNA dye).

gamma-H2A.X is a classic marker of the DDR pathway. DNA damage results in a quick and robust response where H2A.X is phosphorylated at Ser139, forming gamma H2A.X (5), making it a powerful tool for studying the DDR pathway and senescence.

Immunohistochemical analysis of paraffin-embedded HT-29 cells untreated (left) or UV-treated (right), using Phospho-Histone H2A.X (Ser139) (20E3) Rabbit mAb.

53BP1 was originally identified as a binding partner for p53, and suggested to enhance its transcriptional activity (6, 7). 53BP1 plays an essential role in DNA repair it is known to be recruited to sites of DNA damage, and retention of 53BP1 at these sites is dependent on gamma-H2A.X (8).

Confocal immunofluorescent analysis of HeLa cells using 53BP1 Antibody (green). Actin filaments have been labeled with Alexa Fluor® 555 phalloidin (red).

Sometimes the best way to detect something is to determine what it’s not doing. Ki67 is a nuclear protein that is a frequently used marker of proliferating cells. This detection ranges anywhere from G1 through the end of mitosis, but is not detectable when cells are in G0 resting phase (9). A hallmark of senescent cells is a permanent exit from the cell cycle, and so senescent cells do not express Ki67.

Immunohistochemical analysis of paraffin-embedded human breast carcinoma using Ki-67 (8D5) Mouse mAb.

*Pro tip! There are many markers of senescent cells, so why choose just one? We recommend starting with the Senescence Marker Antibody Sampler Kit, which contains several of these fundamental markers, making it perfect for beginning to identify your senescent cells!


Related Links

References: β-Coronaviruses Use Lysosomes for Egress Instead of the Biosynthetic Secretory Pathway. Ghosh S, Dellibovi-Ragheb TA, Kerviel A, Pak E, Qiu Q, Fisher M, Takvorian PM, Bleck C, Hsu VW, Fehr AR, Perlman S, Achar SR, Straus MR, Whittaker GR, de Haan CAM, Kehrl J, Altan-Bonnet G, Altan-Bonnet N. Cell. 2020 Oct 27:S0092-8674(20)31446-X. doi: 10.1016/j.cell.2020.10.039. Online ahead of print. PMID: 33157038.

Funding: NIH’S National Heart, Lung, and Blood Institute (NHLBI), National Institute of Allergy and Infectious Diseases (NIAID), National Institute of Neurological Disorders and Stroke (NINDS), National Institute of General Medical Sciences (NIGMS), and National Cancer Institute (NCI).


Monoclonal Antibodies Included in the Organelle Marker Panel

This organelle marker panel of mouse monoclonal antibodies against a selection of important subcellular locations for mapping, characterizing and revealing the role of the protein in cellular processes, can be used as a reference to stain and confirm the location of the protein of interest. The panel members have been selected for high RNA levels in as many cell lines as possible and are validated in ICC-IF in up to five cell lines. Most of them are also validated in IHC and WB. All panel members belong to the Prestige Antibody brand and have been developed under the same stringent conditions, with a secured continuity and stable supply.


RESULTS

A mutant luciferase protein is sequestered to Hsp42-SPGs in chronologically aged yeast cells

Previously, Hsp42-SPGs were found to be enriched in long-lived quiescent yeast cells (Lee et al., 2016 Liu et al., 2012), suggesting that formation of Hsp42-SPGs influences cell physiology during chronological aging. When the viability of stationary phase cells was examined in rebudding assays, cells without Hsp42-SPGs exhibited significantly reduced viability in 1-month cultures (46±1.6% of wild-type cells vs 26±0.3% of hsp42Δ cells, two-tailed t-test, P=0.0049) (Fig. 1A). However, in order to understand the biochemical states of Hsp42-SPG components during granule formation, a sensitive functional assay of protein folding and enzymatic activities is needed.

Formation of Hsp42-containing granules regulates enzyme activities during stationary phase. (A) Cells without Hsp42-SPGs are less viable after 30 days in stationary phase. Cell rebudding rate was used to represent the cell viability of wild-type and hsp42Δ cells (see Materials and Methods for details). The experiments were repeated using at least three independent colonies and >100 cells were counted in each repeat. ***P<0.005, two-tailed Student's t-test. Error bars represent s.e.m. (B) Granules formed by luciferase-EGFP (green) colocalize with Hsp42-BFP granules (red) in stationary phase cells. Cells were grown in SC-URA medium at 28°C for 5 days before images were taken. Scale bar: 5 μm. (C) Granule formation of luciferase-EGFP depends on Hsp42. Wild-type and hsp42Δ cells carrying luciferase-EGFP were collected from 1-day, 4-day, 7-day and 14-day-old cultures, and images were taken. Scale bar: 5 μm. (D) Formation of Hsp42-SPGs facilitates downregulation of luciferase activity during chronological aging. Mean luciferase activity per mg of total cell lysate was calculated from three repeats. P values were calculated using two-tailed Student's t-test. *P<0.05, ***P<0.005. Error bars represent s.e.m. (E) The protein amount of luciferase in the hsp42Δ mutant (–) is not higher compared to that in the wild-type strain (+). Total cell lysates were analyzed by western blotting and luciferase, Hsp42 and G6PDH were detected by using anti-GFP (for luciferase-EGFP), anti-Hsp42, and anti-G6PDH (for loading control) antibodies. (F) Luciferase activity in wild-type cells recovers quickly without new protein synthesis when cells exit stationary phase. To see fold changes more easily, the luciferase activity of refreshed cells was normalized to that of the same cell culture before refreshment. Stationary phase cells were refreshed with fresh medium for 1 h in the presence of 100 μg/ml cycloheximide and then lysed to measure luciferase activity. 14-day-old wild-type cells had the largest fold change because most of the luciferase protein was stored in Hsp42-SPGs at this time point.

Formation of Hsp42-containing granules regulates enzyme activities during stationary phase. (A) Cells without Hsp42-SPGs are less viable after 30 days in stationary phase. Cell rebudding rate was used to represent the cell viability of wild-type and hsp42Δ cells (see Materials and Methods for details). The experiments were repeated using at least three independent colonies and >100 cells were counted in each repeat. ***P<0.005, two-tailed Student's t-test. Error bars represent s.e.m. (B) Granules formed by luciferase-EGFP (green) colocalize with Hsp42-BFP granules (red) in stationary phase cells. Cells were grown in SC-URA medium at 28°C for 5 days before images were taken. Scale bar: 5 μm. (C) Granule formation of luciferase-EGFP depends on Hsp42. Wild-type and hsp42Δ cells carrying luciferase-EGFP were collected from 1-day, 4-day, 7-day and 14-day-old cultures, and images were taken. Scale bar: 5 μm. (D) Formation of Hsp42-SPGs facilitates downregulation of luciferase activity during chronological aging. Mean luciferase activity per mg of total cell lysate was calculated from three repeats. P values were calculated using two-tailed Student's t-test. *P<0.05, ***P<0.005. Error bars represent s.e.m. (E) The protein amount of luciferase in the hsp42Δ mutant (–) is not higher compared to that in the wild-type strain (+). Total cell lysates were analyzed by western blotting and luciferase, Hsp42 and G6PDH were detected by using anti-GFP (for luciferase-EGFP), anti-Hsp42, and anti-G6PDH (for loading control) antibodies. (F) Luciferase activity in wild-type cells recovers quickly without new protein synthesis when cells exit stationary phase. To see fold changes more easily, the luciferase activity of refreshed cells was normalized to that of the same cell culture before refreshment. Stationary phase cells were refreshed with fresh medium for 1 h in the presence of 100 μg/ml cycloheximide and then lysed to measure luciferase activity. 14-day-old wild-type cells had the largest fold change because most of the luciferase protein was stored in Hsp42-SPGs at this time point.

We found that a mutant form of the firefly luciferase-EGFP fusion protein might serve as a model enzyme to tackle this issue (Gupta et al., 2011). This luciferase mutant spontaneously formed cytosolic granules that colocalize with Hsp42-SPGs in stationary phase cultures even without heat shock (Fig. 1B). In contrast, the wild-type luciferase was rarely recruited to the granule (3.3±0.9% compared to 81.3±3.4% in the cells carrying the luciferase mutant). Moreover, the granule formation of luciferase strictly depended on Hsp42 the luciferase protein was distributed evenly in the cytosol in stationary phase hsp42Δ cells (Fig. 1C). The behavior of luciferase is similar to the previously identified Hsp42-SPG components Hos2 and Mca1 (Liu et al., 2012). Since this luciferase contains mutations that will readily induce protein misfolding, it raises the possibility that only proteins prone to misfolding were collected to Hsp42-SPGs. Nonetheless, it remains unclear whether the sequestered proteins are permanently damaged or can be reactivated later.

Formation of Hsp42-SPGs allows cells to regulate protein activities in stationary phase

Since the mutant luciferase was collected to Hsp42-SPGs gradually (Fig. 1C), it is possible that Hsp42-SPGs only sequester the luciferase-GFP protein that is completely misfolded or damaged during stationary phase. To test this hypothesis, we grew granule-less hsp42Δ mutant and wild-type cells and monitored the activity of luciferase at different time points. If only completely misfolded or damaged and, therefore, inactive proteins are collected to Hsp42-SPGs, wild-type and hsp42Δ mutant cells should exhibit similar luciferase activities. In contrast, wild-type cells will show much lower luciferase activities if Hsp42-SPGs can actively collect fully or partially functional proteins. In 1-day cell cultures, both strains had similar levels of total cellular luciferase activity (Fig. 1D). However, the difference in luciferase activities between hsp42Δ and wild-type cells gradually increased at later time points when luciferase granules started to form (Fig. 1C and D, ∼3-fold and ∼10-fold differences in 7-day-old and 14-day-old cells, respectively).

We also performed western blots to examine the total amount of luciferase protein. In both wild-type and hsp42Δ mutant cells, the levels of luciferase protein were gradually reduced – possibly due to the activated autophagy in stationary phase cells (Wang et al., 2001). Nonetheless, abundance of luciferase protein in hsp42Δ mutants was slightly less compared to that in the wild-type strain (Fig. 1E), negating the possibility that decreased luciferase activities in the wild-type cells was caused by reduced protein amounts. Another possible explanation for the higher luciferase activity in hsp42Δ cells is that more molecular chaperones were available in the cytosol of mutant cells. We performed an in vitro luciferase refolding assay to test this possibility (Glover and Lindquist, 1998). Cell lysates prepared from 14-day-old wild-type and hsp42Δ cells, which did not carry the luciferase-GFP construct, were measured for their ability to reactivate denatured luciferase. The result showed that hsp42Δ cells had a slightly lower level of refolding activity than wild-type cells (Fig. S1), indicating that hsp42Δ cells did not have more chaperones in the cytosol. Taken together, our results show that sequestering a specific protein to Hsp42-SPGs enables a cell to downregulate its enzymatic activity without lowering the protein level.

In stationary phase, cells encounter many challenges that are similar to stress conditions. Studies in log phase cells have revealed that cells can collect damaged or misfolded proteins into specific compartments, such as IPOD, CytoQ or Q-body, under stress conditions, and that these proteins are subsequently degraded once the stress is relieved (Escusa-Toret et al., 2013 Kaganovich et al., 2008 Miller et al., 2015). We tested whether the protein components in Hsp42-SPGs are targeted for degradation or can be refolded back into functional conformation when cells exit the quiescent state. Stationary phase cells were supplied with fresh medium containing cycloheximide to inhibit translation of new proteins. Cycloheximide treatment ensured that the detected luciferase activity came from pre-existing luciferase in stationary phase cells. Our previous study has shown that, under this condition, Hsp42-SPGs disassemble and release their components (Liu et al., 2012). Interestingly, cytosolic luciferase activity drastically increased when the protein was released from Hsp42-SPGs (Fig. 1F). In contrast, luciferase activity remained at a similar level in the granule-less hsp42Δ mutants before and after nutrient feeding. These data provide direct evidence that specific proteins stored in Hsp42-SPGs can be refolded and reactivated for later use upon re-entry into the cell cycle.

Identification of the protein components in known granule structures within stationary phase cells

Our result, showing that proteins sequestered to Hsp42-SPGs could be reactivated at later stages, prompted us to search for the endogenous components of Hsp42-SPGs. To obtain a comprehensive list of Hsp42-SPG components, we performed a genome-wide screen of the subcellular localization of yeast proteins in stationary phase using the yeast GFP-fusion collection (Huh et al., 2003). In the first round, 4071 strains from the collection were grown in YPD for 5 days to enter stationary phase, and fluorescence images of cells in both log and stationary phase were analyzed (see Materials and Methods for details). The localization patterns of GFP fusion proteins in stationary phase were manually divided into six categories, i.e. no specific pattern, granule, punctate, cell periphery, nuclear periphery and fibril (Table 1 and Fig. S2A see also data on FigShare available at https://doi.org/10.6084/m9.figshare.6958307). Most of the proteins were evenly distributed in the cytosol, nucleus or vacuole in stationary phase cells and, therefore, fell into the category no specific pattern. Interestingly, more than 600 yeast proteins formed dot-like structures in stationary phase, falling into the category punctate or granule (Table 1).

Subcellular localization of yeast proteins

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Next, we focused on the 307 proteins that formed only one or two individual cytosolic dots, since this category included Hsp42 and because other proteins within the same category were more likely to be Hsp42-SPG components (Fig. S2C). When the log-phase localization patterns of these granule-forming proteins were examined, only a small proportion of them (17.9%) exhibited punctate patterns and the majority were evenly distributed in the cytosol (45.0%) or the nucleus (31.6%) (Fig. S2D). In total, more than 200 yeast proteins radically changed their original localization to form cytosolic granules during stationary phase, suggesting that granule formation is a specific response to starvation stress or aging effects in stationary phase cells.

To further identify the Hsp42-SPG components, mCherry-tagged Hsp42 was used as a marker of Hsp42-SPGs to see whether it colocalized with other proteins (see Materials and Methods for details). A plasmid containing the mCherry-tagged HSP42 gene was first transformed into each of the 307 strains that carry GFP-fusion granule-forming proteins, and the transformants were induced into stationary phase to examine the localization patterns of mCherry and GFP signals (Fig. S3A). Of the 307 strains, 61 displayed colocalization of GFP and Hsp42-mCherry signals (one example is shown in Fig. 2A), and were defined as components of Hsp42-SPGs (Table 2 and Table S1). Interestingly, different components of Hsp42-SPGs were collected to granules in order (Fig. S3B and Table S2), suggesting that the Hsp42-SPG has a specific structure.


Flow Cytometry Protocol

While laboratories around the world continue to optimize flow cytometry protocol, it conventionally includes the following steps:

  1. Cells are fixed with formaldehyde to immobilize the proteins of interest and their transient signaling events. or detergent is added to the test tube to make cells permeable to antibodies that can then enter their intracellular spaces. are added and must be chosen carefully to allow optimal targeting of the epitopes and proper antigen detection when staining multiple surface and intracellular proteins, simultaneously.
  2. The test tube is placed in the flow cytometer and the fluid is allowed to reach – and then exit through – the flow chamber, one cell at a time.
  3. As each cell crosses the laser beam, the light that bounces off it is transmitted to light/color detectors.
  4. The data retrieved from this experiment can finally undergo analysis to unravel the unique facets of the cells themselves and their patterns of cell signaling.

The antibody staining can vary, as well:

  • With direct staining, cells are incubated with an antibody directly conjugated to a fluorochrome (e.g., FITC). This is a one-step incubation and is particularly useful for intracellular staining.
  • In indirectstaining, the primary antibody is not labeled but is instead detected by a fluorochrome-labeled secondary antibody. This method means unconjugated primary antibodies can be raised against many different targets, which widens the choice of target proteins for the researcher.
  • Intracellular staining refers to a stain of intracellular antigens.
  • Finally, proteins secreted by a cell can be tagged and traced with a Golgi block, followed by intracellular staining.

Course Description

The endoplasmic reticulum (ER) orchestrates different cellular processes by which proteins are synthesized, correctly folded, modified and ultimately transported to their final destinations. As part of this crucial biosynthetic process, proteins that are not properly folded and consequently detrimental to normal cellular function are constantly generated. A common signature of many neurodegenerative diseases, including Alzheimer's and Parkinson's, is accumulation and deposition of misfolded proteins that arise when the ability of cells to deal with the burden of misfolded proteins is compromised. In this course, we will explore how the ER quality control machinery ensures that only properly assembled proteins exit the ER while distinguishing between nascent proteins en route to their biologically active folded state from those that are terminally misfolded.


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