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CRISPR-Mediated Tagging of Endogenous Proteins with a Luminescent Peptide

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Promega Corporation, Madison, Wisconsin 53711, United States
Department of Pharmaceutics and Pharmaceutical Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
Cite this: ACS Chem. Biol. 2018, 13, 2, 467–474
Publication Date (Web):September 11, 2017
https://doi.org/10.1021/acschembio.7b00549

Copyright © 2017 American Chemical Society. This publication is licensed under these Terms of Use.

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Abstract

Intracellular signaling pathways are mediated by changes in protein abundance and post-translational modifications. A common approach for investigating signaling mechanisms and the effects induced by synthetic compounds is through overexpression of recombinant reporter genes. Genome editing with CRISPR/Cas9 offers a means to better preserve native biology by appending reporters directly onto the endogenous genes. An optimal reporter for this purpose would be small to negligibly influence intracellular processes, be readily linked to the endogenous genes with minimal experimental effort, and be sensitive enough to detect low expressing proteins. HiBiT is a 1.3 kDa peptide (11 amino acids) capable of producing bright and quantitative luminescence through high affinity complementation (KD = 700 pM) with an 18 kDa subunit derived from NanoLuc (LgBiT). Using CRISPR/Cas9, we demonstrate that HiBiT can be rapidly and efficiently integrated into the genome to serve as a reporter tag for endogenous proteins. Without requiring clonal isolation of the edited cells, we were able to quantify changes in abundance of the hypoxia inducible factor 1A (HIF1α) and several of its downstream transcriptional targets in response to various stimuli. In combination with fluorescent antibodies, we further used HiBiT to directly correlate HIF1α levels with the hydroxyproline modification that mediates its degradation. These results demonstrate the ability to efficiently tag endogenous proteins with a small luminescent peptide, allowing sensitive quantitation of the response dynamics in their regulated expression and covalent modifications.

SPECIAL ISSUE

This article is part of the Chemical Biology of CRISPR special issue.

As protein expression and post-translational modifications are fundamental to cellular physiology, their disruption can lead to pathophysiological conditions such as cancer, neurodegeneration, and inflammatory diseases. (1, 2) Elucidating the intrinsic dynamics of these processes can thus offer insight into disease mechanisms and provide predictive models for drug discovery. Common approaches for quantifying protein levels and their modifications in complex biological samples include mass spectrometry and antibody-based methodologies, such as ELISA and Western blotting. Mass spectrometry is relatively low-throughput and usually requires specialized procedures to achieve reliable quantitation. It also has limited dynamic range and struggles with detection of low abundance proteins. (3) While antibody detection systems share many of these limitations, dependable quantitation is also limited by the availability of high-quality antibodies. (4) Dynamic processes in cells are routinely revealed using genetically encoded protein fusions with reporter tags, most commonly GFP or similar autofluorescent proteins. Typically, this is accomplished in mammalian cells by overexpressing recombinant proteins from genetic vectors containing strong transcriptional promoters. However, by omitting the endogenous genetic loci for protein expression, the absence of proper regulatory elements can produce an imbalance in protein levels leading to nonphysiological artifacts. (5)
In recent years, CRISPR/Cas9 has emerged as a prominent technology for genome editing due to its simplicity and ease of use. By combining the site-specific cleaving abilities of CRISPR/Cas9 with the native cellular DNA repair mechanisms, reporters can be precisely inserted at endogenous loci. CRISRP/Cas9-mediated integration of full-length GFP and luciferase reporters has been reported, although the procedures are generally cumbersome and relatively inefficient. (6, 7) Recently, the ability to tag endogenous proteins with a 16-amino acid peptide derived from GFP was described. (8) This peptide tag (GFP11) generates fluorescence when coexpressed with its complementary fragment, GFP1–10. The small size of the tag allowed the donor DNA templates encoding GFP11 to be made as synthetic single-stranded oligodeoxynucleotides (ssODNs). In combination with a ribonucleoprotein complex (RNP) comprising synthetic guide RNA (gRNA) and purified Cas9, this allowed efficient genome editing without molecular cloning.
While the productivity of this approach encourages proteome-wide tagging, the detection sensitivity of GFP may be insufficient for the expression level of most endogenous proteins. (8) In particular, proteins involved in cellular signaling tend to be expressed at relatively low levels and thus may be difficult to detect. Moreover, fluorophore maturation of the reconstituted GFP complex is quite slow, limiting its suitability for quantifying dynamic processes. (9) Conversely, luciferase reporters are recognized for providing highly sensitive detection and rapid quantitation over an extensive concentration range. (10) Taking advantage of this, we independently developed a similar approach for tagging endogenous proteins based on the very bright NanoLuc luciferase. This luciferase is approximately 100-fold brighter than firefly or Renilla luciferases, and its molecular weight (19 kDa) is substantially less than GFP. (11)
Complementing subunits of a split NanoLuc were previously engineered to accurately measure protein interaction dynamics within cells. (12) This reporter system (NanoBiT) comprises an 11-amino acid peptide (SmBiT) that interacts with very low affinity (KD > 100 μM) to an 18 kDa polypeptide (LgBiT) to form a luminescent complex. During the development of this system, other peptides of different affinities to LgBiT were also identified. One in particular (HiBiT) was found to have an exceptionally high affinity (KD = 700 pM) to LgBiT. Through its ability to efficiently complex with LgBiT, we envision that HiBiT could serve as a quantitative luminescent peptide tag. Due to its small size, we also reasoned that HiBiT is well-suited for efficiently tagging endogenous proteins using ssODN donor templates together with CRISPR/Cas9 RNP complexes.
To evaluate HiBiT as a means for quantifying cellular protein levels, we selected the hypoxia-inducible pathway in which both protein abundance and post-translational modifications play a role in regulating cellular functions. (13) The hypoxia-inducible factor 1A (HIF1α) regulates many cellular processes, including angiogenesis, cell survival, migration, and nutrient metabolism. Altered expression of HIF1α can trigger aberrant activation of downstream genes, potentially contributing to one of several HIF1α-associated pathologies. We show that appending HiBiT onto HIF1α and associated proteins can be accomplished rapidly using Cas9 RNP complexes and ssODN homology-directed repair (HDR) templates. The high integration efficiency and assay sensitivity of HiBiT enable quantification of protein levels in the mixed population of edited cells without requiring clonal isolation. This allows reporter measurements to be made within 24 to 48 h of editing in either live cells or lysates.
In addition to reporting on protein expression, the HiBiT tag also creates an avenue for detecting covalent modifications on the tagged protein. A myriad of post-translational modifications mediate diverse protein attributes, including conformation, processing, localization, activity, and interactions. (14) Immunoassays provide a convenient means for detecting these modifications, although achieving selectivity for a single target can be challenging. With this in mind, we developed a homogeneous immunoassay for measuring post-translational modifications that relies upon bioluminescence resonance energy transfer (BRET) between the HiBiT/LgBiT reconstituted luciferase and a fluorescently labeled antibody. Because BRET data are presented as a ratio of signals from the energy donor (i.e., the luciferase) and acceptor (i.e., the fluorophore), this approach indicates the degree of modification normalized to protein abundance. Detection specificity is achieved because antibody bound to inappropriate targets is nonproductive for energy transfer due to absence of a donor signal.
Dynamic regulation of these modifications can also be correlated to changes in protein expression, since the energy donor simultaneously provides a measure of protein abundance. We used this to correlate prolyl hydroxylation of HIF1α with the controlled degradation of this transcription factor. The coordinated fluctuations revealed by this method corroborate the underlying mechanism linking these elements in the signaling pathway. Even though a fluorophore is involved in this assay design, high detection sensitivity and dynamic range are achieved due to the bright luminescence of the energy donor and large spectral shift to the acceptor (>175 nm). (15) Correlations involving post-translational modifications should be possible simply by changing the binding specificity of the fluorescent antibody. Together, our results demonstrate that the HiBiT peptide tag can readily be appended onto endogenous proteins using CRISPR/Cas9, allowing sensitive quantification of both protein abundance and post-translational modifications.

Results and Discussion

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HiBiT Quantitation

For quantifying protein abundance, it is essential that the luminescence of HiBiT be proportional to its concentration when reconstituted with the LgBiT. Moreover, to be suitable across the broad range of expression levels exhibited by endogenous proteins, this linear relationship must extend to very low concentrations. For both full-length NanoLuc and LgBiT complexed with the low affinity SmBiT, this has been demonstrated previously through biochemical means, as well as in living and lysed cells. (11, 12)
Using purified proteins in a biochemical format allows unambiguous correlation of luminescence to the concentration of the tag. A serial dilution of purified HiBiT fusion in the presence of saturating LgBiT produced a linear correlation extending over 8 orders of magnitude, with similar results obtained both in buffer and in the presence of cell lysates (Figures 1a, s1). Light intensity was also comparable to NanoLuc, with measurable signal detected to less than 1 amol. In a typical sample of 10 000 cells, this would correspond to about 10 molecules per cell. Titration of transfected DNA encoding HiBiT into cultured mammalian cells produced a linear correlation spanning 4 orders of magnitude, evident for both live cells and cell lysates (Figure 1b). Measurement of HiBiT in live cells was achieved by having the LgBiT expressed from a chromosomally integrated expression cassette. As the nonlinearity evident at high DNA concentration is similar for both lytic and live cells, this is apparently not caused by any restriction in measuring the HiBiT/LgBiT complex within the cells. Considering that detection of HiBiT from lysates should be analogous to the biochemical format, the comparably reduced linear range found using cells is probably caused by a limitation of protein expression from transfected DNA.

Figure 1

Figure 1. Linearity of luminescence generated by HiBiT. (a) Luminescent signal generated either by full-length recombinant NanoLuc or by Halo-Tag HiBiT incubated with saturating LgBiT. (b) Luminescent signal in live cells and cell lysates. HEK293 cells stably expressing LgBiT were transfected with varying concentrations of an expression plasmid for HaloTag-HiBiT, and luminescence was measured before (live cell) or after (lytic) lysis. For both panels, data represent luminescence after subtraction of the background caused by reagent (panel a) or untransfected cells (panel b). Shown are mean values, n = 4, with variability expressed as SD.

HiBiT Tagging of HIF1α

To append HiBiT onto endogenous proteins, we electroporated RNP complexes consisting of recombinant Cas9 and synthetic gRNA into cells in the presence of a ssODN donor template (Figure s2). (8) To minimize introduction of insertions or deletions (indels) within gene coding sequences, gRNA sequences were designed, when possible, to direct Cas9 cleavage to untranslated regions, while donor templates were designed to prevent recutting of edited genes by disrupting the gRNA target sequence (Table s1). Expression of HiBiT in the edited cell pools was readily confirmed by measuring luminescence in lysates following the addition of recombinant LgBiT. Because expression of the peptide tag directly from a ssODN template is highly improbable, as is a random integration resulting in expression of a functional peptide, luminescence in the presence of LgBiT signifies HiBiT expression at the targeted loci.
We assessed the effectiveness of this approach by editing HeLa cells to express HIF1α with HiBiT fused to the C-terminus. The frequency of HiBiT insertion across all alleles in the pools of edited cells was approximated by quantitative PCR using primers designed to recognize the sequences encoding either HIF1α-HiBiT or total HIF1α. From five independently generated pools of edited cells, the average allelic editing efficiency was determined to be 52 ± 16% (Table s2). Clonal cell populations were isolated by limiting dilution and used for further genetic characterization of the edited cells. Targeted amplicon sequencing of genomic DNA isolated from clones confirmed the presence of in-frame HiBiT insertion.
The dynamic regulation of HIF1α expression offered an apt model for assessing rapid changes in protein abundance. Under normal oxygen conditions, HIF1α is rapidly turned over via a mechanism that involves HIF1α hydroxylation by prolyl hydroxylase-domain (PHD) enzymes, recognition and ubiquitination by the E3 ligase von Hippel Lindau (VHL) tumor suppressor protein, and degradation by the proteasome. Conversely, oxygen deprivation leads to inhibition of PHD enzymes, loss of hydroxylation of proline residues 402 and 564, and stabilization of HIF1α. (16) As expected, luminescence corresponding to HIF1α-HiBiT was low, but still above background, when edited cells were grown under normoxic conditions. However, the luminescent signal increased over 7-fold after transferring the cells to a hypoxia chamber for 6 h, reflecting stabilization of the HIF1α-HiBiT (Figure 2a, s3a,b). The signal correlated with the accumulation of total HIF1α protein in the edited cells, as determined by Western blotting (Figure s3c,d).

Figure 2

Figure 2. Quantification of endogenous HIF1α-HiBiT abundance. HIF1α-HiBiT levels in edited HeLa cells were measured in lytic format following 6 h treatment with (a) hypoxia (1% O2) or (b) the following compounds: Phenanthroline (Phen, 20 μM), ML228 (2 μM), DFO (300 μM), IOX2 (100 μM), FG2216 (100 μM), FG4592 (50 μM), DMOG (250 μM), MG132 (10 μM), and MLN4924 (1 μM). (c) HIF1α-HiBiT abundance measured in lytic format following treatment with different concentrations of compound. For panels a–c, shown are mean luminescence values (after subtraction of reagent background) from four independent experiments (at least five replicates per experiment) with variability expressed as SEM. Dashed line (panel b) denotes luminescence generated by untreated HIF1α-HiBiT-expressing HeLa cells.

Modulation of HIF1α levels can also be achieved pharmacologically with inhibitors of prolyl hydroxylases (phenanthroline, ML228, DFO, FG2216, FG4592, DMOG, and IOX2), the proteasome (MG132), and the NEDD8-activating enzyme (MLN4924). (17-22) Treatment of cells with these compounds revealed the predicted increase in luminescence in the HIF1α-HiBiT edited cells but not in unedited HeLa cells (Figures 2b, s4a,b, Table s3). While these data were collected using pools of edited cells, equivalent results were obtained for clonal populations (Figure s4c). To verify that the luminescence originates from the correct HiBiT-tagged protein, an antibody-free blotting technique was used to confirm a single luminescent band corresponding to the correct molecular weight (Figure s4d). Stabilization and proper nuclear localization of the HiBiT-tagged HIF1α was also observed by luminescence imaging of live cells after phenanthroline treatment (Figure s5). By increasing exposure time during imaging, HIF1α-HiBiT was also detectable in the cytoplasm of cells grown under normal oxygen conditions, as previously reported. (23)
The varied responses to different compounds suggest that HIF1α-HiBiT could be used to quantify drug potency and efficacy. Measurement of HIF1α-HiBiT luminescence from cells treated with dilutions of phenanthroline, MG132, and MLN4924 revealed both differing potencies (5.4 μM, 4.4 μM, and 350 nM, respectively) and maximal efficacies (Figure 2c). Western blotting for total HIF1α confirmed that the dose-dependent increase in luminescence was accompanied by a corresponding increase in protein levels (Figure s6a,b).

Tagging Downstream Targets

Because HIF1α is a key regulator of cellular adaptation to hypoxia, significant effort has been centered on identifying drugs that modulate HIF1α and its downstream effects. However, the mechanism by which cells respond to hypoxia is complex and involves transactivation of numerous genes responsible for cell survival. How these downstream regulators contribute to malignancy remains unclear, but understanding their mode of action could aid in the identification of disease markers and future therapeutic targets.
We selected four putative HIF1α target genes (ANKRD37, BNIP3, HILPDA, and KLF10) identified in previous studies to tag with HiBiT. (24) The allelic HiBiT editing efficiency at these loci ranged from 6 to 80% (Table s4). Differences in editing efficiency for different genes could simply be attributed to gRNA and HDR template design; however, it could also reflect the chromatin state at the individual editing sites. (25) Targeted amplicon sequencing of the insertions in clonal populations confirmed in-frame HiBiT insertion at the c-terminus of the genes.
With HiBiT appended onto these genes, the regulated expression of their corresponding proteins could be examined under hypoxic conditions. Expression of ANKRD37, BNIP3, and HILPDA increased by 6-, 12-, and 3-fold, respectively, indicating that these targets are upregulated under hypoxic conditions (Figures 3a–c, s7a–c). Interestingly, no significant elevation in KLF10 protein was observed, suggesting that KLF10 is not directly involved in the immediate hypoxic response (Figures 3d, s7d). The observed differences in signal intensity among the various targets may arise from several possible factors, including variations in editing efficiencies, gene expression, or protein stabilities.

Figure 3

Figure 3. Hypoxia response of HIF1α target proteins. Levels of endogenous (a) BNIP3-, (b) ANKRD37-, (c) HILPDA-, and (d) KLF10-HiBiT in HeLa cells following 20 h of hypoxia treatment. Shown are mean luminescence values (after subtraction of background) from five independent experiments (at least five replicates per experiment), with variability expressed as SEM.

Induction of protein expression was also examined with the same inhibitor panel used to induce HIF1α levels. Only BNIP3 responded similarly to the compounds as HIF1α, while ANKRD37 and HILPDA exhibited activation profiles markedly distinct from HIF1α (Figures 4a–c, s8a–c, Table s5). These results suggest that up-regulation of ANKRD37 and HILPDA may involve additional factors in the hypoxia response. In contrast to the other targets, KLF10 showed no appreciable increase in protein abundance following treatment with PHD inhibitors, implying that KLF10 is not a direct target of HIF1α (Figures 4d, s8d). However, the proteasome inhibitor MG132 stimulated a 4-fold increase in KLF10, indicating that protein turnover may be involved in regulation of KLF10 levels.

Figure 4

Figure 4. Response of HIF1α target proteins to hypoxia mimetics. Levels of endogenous (a) BNIP3-, (b) ANKRD37-, (c) HILPDA-, and (d) KLF10-HiBiT in HeLa cells following 24 h treatment with the following compounds: Phenanthroline (Phen, 20 μM), ML228 (2 μM), DFO (300 μM), IOX2 (100 μM), FG2216 (100 μM), FG4592 (50 μM), DMOG (250 μM), MG132 (10 μM), and MLN4924 (1 μM). Data represent luminescence acquired in lytic format after background subtraction from five independent experiments, with variability expressed as SEM. Dashed line denotes luminescence generated by untreated HiBiT-edited cells.

The findings obtained in these single dose experiments were further corroborated in compound titration experiments (Figure 5a–d, Table s6). Dose–response curves generated from the edited cells show markedly distinct compound profiles, further supporting that the mechanism by which expression of these proteins is regulated involves factors in addition to HIF1α. Again, the compound profile of BNIP3 most closely matches that of HIF1α. In addition, phenanthroline-inducible expression and proper subcellular localization of the ANKRD37, BNIP3, HILPDA, and KLF10 were confirmed using bioluminescence imaging (Figure s9).

Figure 5

Figure 5. Dose response of HIF1α target proteins. Compound-induced accumulation of endogenous (a) BNIP3-, (b) ANKRD37-, (c) HILPDA-, and (d) KLF10-HiBiT in edited HeLa cells treated for 20 h with hypoxia mimetics. Shown are mean luminescence values (after subtraction of reagent background) from five independent experiments (at least five replicates per experiment), with variability expressed as SEM. Dashed line denotes luminescence generated by untreated HiBiT-edited HeLa cells.

HiBiT Tagging in Primary Cells

Although CRISPR/Cas9-mediated HiBiT tagging was an effective strategy for detecting endogenous proteins in HeLa cells, applying this method in primary cell lines could potentially present additional challenges. Primary cells typically resemble the differentiated phenotype of the tissues from which they were derived and are believed to provide a more biologically relevant model for studying certain aspects of cellular physiology. However, use of these cells can be complicated by more complex culturing procedures, lower transfection efficiencies, and finite cell divisions. These same limitations may complicate the ability to utilize CRISPR/Cas9 for inserting reporter tags.
Nonetheless, considering the high detection sensitivity achievable with HiBiT, CRISPR-mediated tagging may be sufficiently efficient in primary cells to support luminescent measurements directly in the unsorted pools. To evaluate the feasibility of CRISPR-mediated tagging in primary cells, we attempted to tag HIF1α, the putative HIF1α target BNIP3, and the angiogenic growth factor VEGFA using primary human umbilical vein endothelial cells (HUVECs).
Pools of edited cells were treated with a subset of the compounds we had used to induce HIF1α expression. Significant increases in luminescence of at least 2-fold were detectable following incubation with the PHD enzyme inhibitors (phenanthroline, ML228, and DFO) but not the proteasome or neddylation inhibitors (Figure 6a–c, Table s7). The magnitude of induction was lower in HUVEC cells compared with the results obtained in HeLa cells. However, the results are consistent with published results and may reflect differing genetic backgrounds between the cell types. (26)

Figure 6

Figure 6. Quantification of HiBiT-tagged proteins in primary cells. Levels of endogenous (a) HIF1α-, (b) BNIP3-, and (c) VEGFA-HiBiT in edited HUVEC cells. Cells were treated for 6 h with phenanthroline (Phen, 20 μM), ML228 (2 μM), DFO (300 μM), MG132 (10 μM), and MLN4924 (1 μM) and then analyzed for luminescence in lytic format. Data are represented as luminescence with background subtracted, n = 4, with variation expressed as SD. Dashed line indicates luminescence generated by untreated HiBiT-edited HUVEC cells.

Real-Time Measurements in Cells

Because cells are programmed to react rapidly to environmental changes, the ability of a reporter to respond to variation without delay becomes crucial for the analysis of dynamic processes within the cell. In particular, being able to measure protein abundance in real time provides temporal information that is exceedingly difficult to obtain using end point assays. In the case of hypoxia, cells must quickly adapt to oxygen deprivation by stimulating pathways that lead to HIF1α stabilization and subsequent activation of survival genes. We wanted to determine if HiBiT could provide a real time readout of temporal changes in endogenous protein levels in the HIF1α pathway.
To analyze expression kinetics in living cells, clonal cell lines having HiBiT tagged onto HIF1α, BNIP3, HILPDA, ANKRD37, and KLF10 were transduced with BacMam containing an expression cassette for LgBiT, and luminescence was recorded for 10 h following phenanthroline treatment (Figure 7a). HIF1α accumulation was detected within 30 min of compound addition, reached a steady state after 3 h, and remained steady for the duration of the experiment. This was also observed using luminescence imaging (Figure s10). Increases in the HIF1α-inducible proteins (BNIP3, HILPDA, and ANKRD37) were not detectable until the HIF1α reached a steady state. Interestingly, accumulation of the target proteins appears to occur in a sequential fashion with ANKRD37 emerging soon after HIF1α induction. In contrast, accumulation of HILPDA and BNIP3 is delayed by as much as 3 h compared to ANKRD37. Consistent with previous results, KLF10 did not show appreciable elevation over the tested time period.

Figure 7

Figure 7. Real-time measurement of induced changes in protein abundance. (a) HeLa cells expressing HiBiT-edited HIF1α and downstream target proteins were transduced with BacMam-LgBiT, and luminescence was monitored following phenanthroline addition. Signal-to-background (S/B) ratios were derived using the formula: (RLUphenanthroline – RLUbackground)/(RLUuntreated – RLUbackground), where background is determined from parental HeLa cells. (b) Edited HeLa cells were transduced with BacMam-LgBiT and incubated for 20 h under hypoxia. Luminescence was measured immediately following release from the hypoxia chamber. Shown are mean relative responses, n = 3, with variability represented as SD.

Reoxygenation of hypoxic tissues or cells leads to rapid reactivation of PHD enzymes, resulting in hydroxylation and degradation of HIF1α. (27) Previous studies used Western blotting to show that this process was rapid with an estimated half-life for HIF1α of less than 10 min after exposure to normoxic conditions. We were interested if it was possible to measure degradation of HIF1α after reoxygenation in real time. Following incubation of HIF1α-HiBiT edited cells in a hypoxia chamber, cells were returned to normoxia, and luminescence was measured every 30 s. The results show a brief plateau followed by a rapid decline of signal, indicating a half-life for HIF1α-HiBiT of less than 6 min, which is in agreement with previously published data (Figure 7b). (28)

Measuring Post-Translational Modifications

Post-translational modifications often serve as the mechanistic triggers in cell signaling. Regarding hypoxia, both activity and stability of HIF1α are intimately connected to several covalent post-translational modifications, including hydroxylation, acetylation, and phosphorylation. (29) For example, hydroxylation of HIF1α at proline residues 402 and 564 promotes interaction of HIF1α with VHL, followed by ubiquitination, and ultimately degradation.
Recognizing that immunoassays can present a convenient and inexpensive approach for detecting protein modifications, we devised a homogeneous format that relies upon bioluminescence resonance energy transfer (BRET) between the HiBiT/LgBiT luciferase complex and a fluorophore-labeled antibody. The energy transfer is proportional to the amount of modification of interest normalized to the tagged target protein.
To detect changes in hydroxylation at proline residue 564 (hydroxy-Pro564) upon inhibition of PHD enzymes, edited cells were treated with a serial dilution of phenanthroline combined with a proteasome inhibitor (MG132) to slow the degradation of HIF1α. Detection of hydroxy-Pro564 HIF1α was performed by first replacing the medium with lysis buffer containing recombinant LgBiT and a hydroxy-Pro564 HIF1α antibody. Following the addition of fluorescently labeled secondary antibody and furimazine, the BRET signal was recorded by measuring luminescence in the donor (460 nm) and acceptor (600 nm) channels.
As anticipated, increasing concentrations of phenanthroline led to a decrease of the BRET ratio, which is indicative of declining hydroxylation at Pro564 (Figure 8). The decline of prolyl hydroxylation should lead to increased levels of HIF1α. Indeed, increased luminescence from HiBiT was observed, and it positively correlated with phenanthroline concentration. This correlation was also confirmed by Western blotting (Figure s11). The mechanistic linkage between prolyl hydroxylation and HIF1α concentration is further corroborated by closely matching EC50 values of 1.7 and 2.8 μM, respectively. We envision that this approach will provide a simple, robust, and scalable means for quantifying the dynamics of post-translational modifications associated with HiBiT-tagged endogenous proteins.

Figure 8

Figure 8. Simultaneous quantification of HIF1α hydroxylation at proline 564 and protein abundance. HeLa cells expressing HIF1α-HiBiT were treated for 6 h with phenanthroline in the presence of MG132. HIF1α proline hydroxylation levels are represented as BRET ratio (acceptor emission 610 nm/donor emission 460 nm; red circles). HIF1α abundance is represented as luminescence (blue circles). Shown are the mean values, n = 3, with variability represented as SD.

Summary

By combining CRISPR/Cas9 editing and HiBiT reporter technologies, we have developed a simple approach for tagging endogenous proteins with a small luminescent peptide. The HiBiT tag can be rapidly assayed with high sensitivity and linearity, allowing quantitative assessment of the dynamic processes associated with cellular signaling. This report focuses on capabilities for determining changes in protein expression and post-translational modification, although assay configurations for other processes can be contemplated. Tagging endogenous proteins with HiBiT is achieved without molecular cloning simply by delivering synthetic gRNA and oligonucleotides with purified Cas9 into the cell. Owing to the rapid action of the Cas9 nuclease and the native cellular repair processes, expression of the tagged proteins can be measured within 24–48 h of editing. Thus, this method enables the analysis of cellular proteins with the ease and speed of a transient transfection experiment but without the potential artifacts of ectopic expression.
CRISPR-mediated HiBiT tagging of endogenous proteins is a scalable strategy for investigating protein abundance and modifications that circumvents shortcomings of conventional methodologies, most notably immunoassays. Despite the longstanding popularity of immunoassays for investigating signaling pathways, obtaining reliably quantitative data through this means remains technically challenging. Central to the success of these assays is the ability to acquire a high-quality, specific antibody for the protein of interest. Although we were able to locate a qualified antibody for specific detection of HIF1α, availability of antibodies for the other target proteins was limited and protocols for their use in blotting were not as thoroughly established. In contrast, we were able to append HiBiT onto all of our desired target proteins and subsequently quantify their abundance in response to various stimuli. Unreliable antibody specificity can also be problematic in the detection of post-translational modifications. Our BRET immunoassay resolves this, as only proteins tagged with HiBiT can generate a signal indicative of antibody binding.
While antibody specificity is often limiting, low sensitivity can also restrict the ability to obtain quantitative data for many proteins. In order to capture low abundance proteins, processing of large quantities of sample may be necessary. Assay sensitivity for HiBiT allows subattomole detection, which should be sufficient for measuring most cellular proteins. Indeed, we were able to detect each of our target proteins without enrichment steps in a multiwell assay format. Significantly, this could provide a means for screening a library of compounds to identify those able to modulate specific signaling pathways.
A key differentiating aspect of HiBiT is the ability to quantify expression dynamics in real time. By introducing the complementing LgBiT subunit into cells (e.g., by viral delivery or plasmid transfection), changes in protein abundance can be observed within living cells. This can provide temporal information that is difficult to obtain from end point assays. Using HiBiT-edited cell lines transduced with BacMam-LgBiT, we were able to measure temporal changes of protein accumulation and degradation of HIF1α and its putative target proteins under different physiological conditions. Ultimately, we believe that the HiBiT peptide tag will provide a broadly beneficial capability for investigating protein dynamics in an appropriate physiological context.

Methods

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Cas9, gRNA, and ssODN

Prior to experimentation, recombinant Streptococcus pyogenes Cas9 tagged on the N-terminus with a histidine-nuclear localization signal-myc tag (Aldevron) was diluted to 20 μM in Cas9 buffer (20 mM HEPES-KOH at pH 7.5, 150 mM KCl, 1 mM TCEP). gRNA was assembled by incubating 1 nmol of Alt-R CRISPR RNA (crRNA) with 1 nmol of Alt-R trans-activating crRNA (tracrRNA) in 50 μL of Nuclease-Free Duplex Buffer (Integrated DNA Technologies, IDT) at 95 °C for 5 min and then cooling to ambient temperature. ssODN donor DNA templates were purchased as single-stranded Ultramer DNA Oligonucleotides (IDT) and resuspended to 100 μM in nuclease-free water.

RNP Complex Assembly and Delivery

RNP complexes were assembled and electroporated into cells, as previously described. (30) Briefly, 100 pmol of Cas9 and 120 pmol of gRNA were incubated for 10 min at ambient temperature. Cells (2 × 105) were resuspended in 20 μL of 4D Nucleofector solution SE for HeLa or SF for HUVEC cells (Lonza). RNP complex and 100 pmol of donor DNA were then electroporated into the cells with the 4D Nucleofector System (Lonza) using program CN-114 for HeLa and DN-100 for HUVEC. Following electroporation, cells were incubated at ambient temperature for 5 min and then transferred to a six-well plate for culturing. At 24–48 h postelectroporation, cells were analyzed for insertion.

Lytic HiBiT Detection

Edited cells were resuspended to 2 × 104 cells in 100 μL of growth medium, plated in solid white 96-well tissue culture plates (Corning Costar #3917), and cultured for 24 h prior to treatment. Cells were then exposed either to modulators of the hypoxia pathway or to hypoxia for 6–24 h. An equal volume of Nano-Glo HiBiT Lytic Reagent (Promega N3030), consisting of Nano-Glo HiBiT Lytic Buffer, Nano-Glo HiBiT Lytic Substrate, and LgBiT Protein, was added according to the manufacturer’s protocol, and cells were incubated for 30 min at ambient temperature with shaking. In some experiments, research-grade purified LgBiT was used in place of the commercial material at a final concentration of 100 nM (refer to Supporting Information for purification details). Luminescence was then measured using a GloMax Discover System (Promega) with 0.5 s of integration time.

Live Cell HiBiT Detection

HiBiT-edited cells were plated in white 96-well tissue culture plates at a density of 2 × 104 cells per well in 100 μL of growth medium and transduced with 2% (v/v) BacMam CMV-LgBiT reagent (Kempbio, Inc., viral titer approximately 2 × 108 PFU/ml) for 24 h. The medium was then replaced with 150 μL of CO2-independent medium (GIBCO) containing 20 μM Nano-Glo Live Cell Ex-4377 (Promega), an esterase-labile time-released substrate. (31) Cells were incubated for 30 min at 37 °C and then treated with phenanthroline (20 μM, final concentration in 200 μL) in 50 μL of CO2-independent medium. The plates were immediately sealed with transparent adhesive film and placed into a GloMax Discover System set to a temperature of 37 °C. The plate was read every 6 min for 10 h using an integration time of 0.5 s.
To measure the effect of reoxygenation on protein abundance, edited cells were plated in 96-well tissue culture plates at a density of 2 × 104 cells per well in 100 μL of medium and transduced with 2% (v/v) BacMam CMV-LgBiT reagent for 24 h. The cells were then transferred to a hypoxia chamber for 20 h. Immediately after removing the cells from the chamber, 25 μL of Nano-Glo Live Cell Assay reagent (Promega) was added. Luminescence was then measured every 30 s for 20 min using a GloMax Discover System set to a temperature of 37 °C using an integration time of 0.5 s.

NanoBRET Immunoassay for Analysis of Post-Translational Modifications

HeLa HIF1α-HiBiT cells were plated in a white 96-well tissue culture plate (4 × 104 cells per well) and incubated for 24 h at 37 °C. The cells were then treated with 3 μM MG132 and a serial dilution of phenanthroline for 6 h. The medium was replaced with 25 μL of assay buffer (150 mM NaCl, 25 mM Tris-HCl, at pH 7.8, 5 mM EDTA, and 1% NP-40) containing rabbit anti-human hydroxy-HIF1α (Pro564) antibody (1:250 dilution, Cell Signaling Technology) and 100 nM LgBiT. The cells were incubated for 30 min at ambient temperature. After the addition of 25 μL of assay buffer containing Alexa Fluor 594 labeled anti-rabbit secondary antibody (1:500 dilution, Cell Signaling Technology) and 100 μM furimazine, the samples were incubated for 60 min at ambient temperature. Both total luminescence and BRET signal (acceptor channel 460/60 nm, donor channel 610 nm longpass) were recorded on a GloMax Discover System using 0.5 s integration time.

Reagents, Linearity, Blotting, Imaging, and qPCR

Supporting Information

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The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acschembio.7b00549.

  • Figures s1–s11, Tables s1–10, and supporting methods (PDF)

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Most electronic Supporting Information files are available without a subscription to ACS Web Editions. Such files may be downloaded by article for research use (if there is a public use license linked to the relevant article, that license may permit other uses). Permission may be obtained from ACS for other uses through requests via the RightsLink permission system: http://pubs.acs.org/page/copyright/permissions.html.

Author Information

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  • Corresponding Author
  • Authors
    • Thomas Machleidt - Promega Corporation, Madison, Wisconsin 53711, United States
    • Kris Zimmerman - Promega Corporation, Madison, Wisconsin 53711, United States
    • Christopher T. Eggers - Promega Corporation, Madison, Wisconsin 53711, United States
    • Andrew S. Dixon - Department of Pharmaceutics and Pharmaceutical Chemistry, University of Utah, Salt Lake City, Utah 84112, United States
    • Robin Hurst - Promega Corporation, Madison, Wisconsin 53711, United States
    • Mary P. Hall - Promega Corporation, Madison, Wisconsin 53711, United States
    • Lance P. Encell - Promega Corporation, Madison, Wisconsin 53711, United States
    • Brock F. Binkowski - Promega Corporation, Madison, Wisconsin 53711, United States
    • Keith V. Wood - Promega Corporation, Madison, Wisconsin 53711, United States
  • Notes
    The authors declare no competing financial interest.

Acknowledgment

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The authors wish to thank J. Unch for the Nano-Glo Live Cell Ex-4377 substrate and P. Otto for assistance with the purification of LgBiT protein.

References

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This article references 31 other publications.

  1. 1
    Buuh, Z. Y., Lyu, Z., and Wang, R. E. (2017) Interrogating the Roles of Post-Translational Modifications of Non-Histone Proteins, J. Med. Chem., DOI:  DOI: 10.1021/acs.jmedchem.6b01817 .
  2. 2
    Harper, J. W. and Bennett, E. J. (2016) Proteome complexity and the forces that drive proteome imbalance Nature 537, 328 338 DOI: 10.1038/nature19947
  3. 3
    Beri, J., Rosenblatt, M. M., Strauss, E., Urh, M., and Bereman, M. S. (2015) Reagent for Evaluating Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) Performance in Bottom-Up Proteomic Experiments Anal. Chem. 87, 11635 11640 DOI: 10.1021/acs.analchem.5b04121
  4. 4
    McDonough, A. A., Veiras, L. C., Minas, J. N., and Ralph, D. L. (2015) Considerations when quantitating protein abundance by immunoblot Am. J. Physiol Cell Physiol 308, C426 433 DOI: 10.1152/ajpcell.00400.2014
  5. 5
    Moriya, H. (2015) Quantitative nature of overexpression experiments Mol. Biol. Cell 26, 3932 3939 DOI: 10.1091/mbc.E15-07-0512
  6. 6
    Lackner, D. H., Carre, A., Guzzardo, P. M., Banning, C., Mangena, R., Henley, T., Oberndorfer, S., Gapp, B. V., Nijman, S. M., Brummelkamp, T. R., and Burckstummer, T. (2015) A generic strategy for CRISPR-Cas9-mediated gene tagging Nat. Commun. 6, 10237 10244 DOI: 10.1038/ncomms10237
  7. 7
    Ratz, M., Testa, I., Hell, S. W., and Jakobs, S. (2015) CRISPR/Cas9-mediated endogenous protein tagging for RESOLFT super-resolution microscopy of living human cells Sci. Rep. 5, 9592 9598 DOI: 10.1038/srep09592
  8. 8
    Leonetti, M. D., Sekine, S., Kamiyama, D., Weissman, J. S., and Huang, B. (2016) A scalable strategy for high-throughput GFP tagging of endogenous human proteins Proc. Natl. Acad. Sci. U. S. A. 113, E3501 3508 DOI: 10.1073/pnas.1606731113
  9. 9
    Cabantous, S., Terwilliger, T. C., and Waldo, G. S. (2005) Protein tagging and detection with engineered self-assembling fragments of green fluorescent protein Nat. Biotechnol. 23, 102 107 DOI: 10.1038/nbt1044
  10. 10
    Fan, F. and Wood, K. V. (2007) Bioluminescent assays for high-throughput screening Assay Drug Dev. Technol. 5, 127 136 DOI: 10.1089/adt.2006.053
  11. 11
    Hall, M. P., Unch, J., Binkowski, B. F., Valley, M. P., Butler, B. L., Wood, M. G., Otto, P., Zimmerman, K., Vidugiris, G., Machleidt, T., Robers, M. B., Benink, H. A., Eggers, C. T., Slater, M. R., Meisenheimer, P. L., Klaubert, D. H., Fan, F., Encell, L. P., and Wood, K. V. (2012) Engineered luciferase reporter from a deep sea shrimp utilizing a novel imidazopyrazinone substrate ACS Chem. Biol. 7, 1848 1857 DOI: 10.1021/cb3002478
  12. 12
    Dixon, A. S., Schwinn, M. K., Hall, M. P., Zimmerman, K., Otto, P., Lubben, T. H., Butler, B. L., Binkowski, B. F., Machleidt, T., Kirkland, T. A., Wood, M. G., Eggers, C. T., Encell, L. P., and Wood, K. V. (2016) NanoLuc Complementation Reporter Optimized for Accurate Measurement of Protein Interactions in Cells ACS Chem. Biol. 11, 400 408 DOI: 10.1021/acschembio.5b00753
  13. 13
    Dengler, V. L., Galbraith, M. D., and Espinosa, J. M. (2014) Transcriptional regulation by hypoxia inducible factors Crit. Rev. Biochem. Mol. Biol. 49, 1 15 DOI: 10.3109/10409238.2013.838205
  14. 14
    Beltrao, P., Bork, P., Krogan, N. J., and van Noort, V. (2013) Evolution and functional cross-talk of protein post-translational modifications Mol. Syst. Biol. 9, 714 727 DOI: 10.1002/msb.201304521
  15. 15
    Machleidt, T., Woodroofe, C. C., Schwinn, M. K., Mendez, J., Robers, M. B., Zimmerman, K., Otto, P., Daniels, D. L., Kirkland, T. A., and Wood, K. V. (2015) NanoBRET--A Novel BRET Platform for the Analysis of Protein-Protein Interactions ACS Chem. Biol. 10, 1797 1804 DOI: 10.1021/acschembio.5b00143
  16. 16
    Masson, N. and Ratcliffe, P. J. (2014) Hypoxia signaling pathways in cancer metabolism: the importance of co-selecting interconnected physiological pathways Cancer Metab 2, 3 20 DOI: 10.1186/2049-3002-2-3
  17. 17
    Theriault, J. R., Felts, A. S., Bates, B. S., Perez, J. R., Palmer, M., Gilbert, S. R., Dawson, E. S., Engers, J. L., Lindsley, C. W., and Emmitte, K. A. (2012) Discovery of a new molecular probe ML228: an activator of the hypoxia inducible factor (HIF) pathway Bioorg. Med. Chem. Lett. 22, 76 81 DOI: 10.1016/j.bmcl.2011.11.077
  18. 18
    Xia, M., Huang, R., Sun, Y., Semenza, G. L., Aldred, S. F., Witt, K. L., Inglese, J., Tice, R. R., and Austin, C. P. (2009) Identification of chemical compounds that induce HIF-1alpha activity Toxicol. Sci. 112, 153 163 DOI: 10.1093/toxsci/kfp123
  19. 19
    Hong, Y. R., Kim, H. T., Lee, S. C., Ro, S., Cho, J. M., Kim, I. S., and Jung, Y. H. (2013) [(4-Hydroxyl-benzo[4,5]thieno[3,2-c]pyridine-3-carbonyl)-amino]-acetic acid derivatives; HIF prolyl 4-hydroxylase inhibitors as oral erythropoietin secretagogues Bioorg. Med. Chem. Lett. 23, 5953 5957 DOI: 10.1016/j.bmcl.2013.08.067
  20. 20
    Chan, M. C., Ilott, N. E., Schodel, J., Sims, D., Tumber, A., Lippl, K., Mole, D. R., Pugh, C. W., Ratcliffe, P. J., Ponting, C. P., and Schofield, C. J. (2016) Tuning the Transcriptional Response to Hypoxia by Inhibiting Hypoxia-inducible Factor (HIF) Prolyl and Asparaginyl Hydroxylases J. Biol. Chem. 291, 20661 20673 DOI: 10.1074/jbc.M116.749291
  21. 21
    Frost, J., Galdeano, C., Soares, P., Gadd, M. S., Grzes, K. M., Ellis, L., Epemolu, O., Shimamura, S., Bantscheff, M., Grandi, P., Read, K. D., Cantrell, D. A., Rocha, S., and Ciulli, A. (2016) Potent and selective chemical probe of hypoxic signalling downstream of HIF-alpha hydroxylation via VHL inhibition Nat. Commun. 7, 13312 13324 DOI: 10.1038/ncomms13312
  22. 22
    Zhao, Y., Xiong, X., Jia, L., and Sun, Y. (2012) Targeting Cullin-RING ligases by MLN4924 induces autophagy via modulating the HIF1-REDD1-TSC1-mTORC1-DEPTOR axis Cell Death Dis. 3, e386 DOI: 10.1038/cddis.2012.125
  23. 23
    Kallio, P. J., Okamoto, K., O’Brien, S., Carrero, P., Makino, Y., Tanaka, H., and Poellinger, L. (1998) Signal transduction in hypoxic cells: inducible nuclear translocation and recruitment of the CBP/p300 coactivator by the hypoxia-inducible factor-1alpha EMBO J. 17, 6573 6586 DOI: 10.1093/emboj/17.22.6573
  24. 24
    Benita, Y., Kikuchi, H., Smith, A. D., Zhang, M. Q., Chung, D. C., and Xavier, R. J. (2009) An integrative genomics approach identifies Hypoxia Inducible Factor-1 (HIF-1)-target genes that form the core response to hypoxia Nucleic Acids Res. 37, 4587 4602 DOI: 10.1093/nar/gkp425
  25. 25
    Daer, R. M., Cutts, J. P., Brafman, D. A., and Haynes, K. A. (2017) The Impact of Chromatin Dynamics on Cas9-Mediated Genome Editing in Human Cells ACS Synth. Biol. 6, 428 438 DOI: 10.1021/acssynbio.5b00299
  26. 26
    Nilsson, I., Shibuya, M., and Wennstrom, S. (2004) Differential activation of vascular genes by hypoxia in primary endothelial cells Exp. Cell Res. 299, 476 485 DOI: 10.1016/j.yexcr.2004.06.005
  27. 27
    D’Angelo, G., Duplan, E., Boyer, N., Vigne, P., and Frelin, C. (2003) Hypoxia up-regulates prolyl hydroxylase activity: a feedback mechanism that limits HIF-1 responses during reoxygenation J. Biol. Chem. 278, 38183 38187 DOI: 10.1074/jbc.M302244200
  28. 28
    Berra, E., Roux, D., Richard, D. E., and Pouyssegur, J. (2001) Hypoxia-inducible factor-1 alpha (HIF-1 alpha) escapes O(2)-driven proteasomal degradation irrespective of its subcellular localization: nucleus or cytoplasm EMBO Rep. 2, 615 620 DOI: 10.1093/embo-reports/kve130
  29. 29
    Brahimi-Horn, C., Mazure, N., and Pouyssegur, J. (2005) Signalling via the hypoxia-inducible factor-1alpha requires multiple posttranslational modifications Cell. Signalling 17, 1 9 DOI: 10.1016/j.cellsig.2004.04.010
  30. 30
    DeWitt, M. A., Corn, J. E., and Carroll, D. (2017) Genome editing via delivery of Cas9 ribonucleoprotein Methods 121–122, 9 15 DOI: 10.1016/j.ymeth.2017.04.003
  31. 31
    Klaubert, D. H., Meisenheimer, P., and Unch, J. (2014) Imidazo[1,2-α]pyrazine derivatives, Promega Corporation, United States of America.

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  34. Igor Fijalkowski, Valdes Snauwaert, Petra Van Damme, , . Proteins à la carte: riboproteogenomic exploration of bacterial N-terminal proteoform expression. mBio 2024, 15 (4) https://doi.org/10.1128/mbio.00333-24
  35. Praveen Kumar Tiwari, Sai Reddy Doda, Raghu Vannam, Manish Hudlikar, Drew A. Harrison, Samuel Ojeda, Sumit Rai, Ann-Sophie Koglin, Angelique Nguyen Gilbert, Christopher J. Ott. Exploration of bromodomain ligand-linker conjugation sites for efficient CBP/p300 heterobifunctional degrader activity. Bioorganic & Medicinal Chemistry Letters 2024, 102 , 129676. https://doi.org/10.1016/j.bmcl.2024.129676
  36. Ekaterina S. Shakhova, Tatiana A. Karataeva, Nadezhda M. Markina, Tatiana Mitiouchkina, Kseniia A. Palkina, Maxim M. Perfilov, Monika G. Wood, Trish T. Hoang, Mary P. Hall, Liliia I. Fakhranurova, Anna E. Alekberova, Alena K. Malyshevskaia, Dmitry A. Gorbachev, Evgenia N. Bugaeva, Ludmila K. Pletneva, Vladislav V. Babenko, Daria I. Boldyreva, Andrey Y. Gorokhovatsky, Anastasia V. Balakireva, Feng Gao, Vladimir V. Choob, Lance P. Encell, Keith V. Wood, Ilia V. Yampolsky, Karen S. Sarkisyan, Alexander S. Mishin. An improved pathway for autonomous bioluminescence imaging in eukaryotes. Nature Methods 2024, 21 (3) , 406-410. https://doi.org/10.1038/s41592-023-02152-y
  37. Geoffrey A. Holdgate, Catherine Bardelle, Sophia K. Berry, Alice Lanne, Maria Emanuela Cuomo. Screening for molecular glues – Challenges and opportunities. SLAS Discovery 2024, 29 (2) , 100136. https://doi.org/10.1016/j.slasd.2023.12.008
  38. Xue Liu, Laurye Van Maele, Laura Matarazzo, Daphnée Soulard, Vinicius Alves Duarte da Silva, Vincent de Bakker, Julien Dénéréaz, Florian P. Bock, Michael Taschner, Jinzhao Ou, Stephan Gruber, Victor Nizet, Jean-Claude Sirard, Jan-Willem Veening. A conserved antigen induces respiratory Th17-mediated broad serotype protection against pneumococcal superinfection. Cell Host & Microbe 2024, 32 (3) , 304-314.e8. https://doi.org/10.1016/j.chom.2024.02.002
  39. Sayaka Shizukuishi, Michinaga Ogawa, Eisuke Kuroda, Shigeto Hamaguchi, Chisato Sakuma, Soichiro Kakuta, Isei Tanida, Yasuo Uchiyama, Yukihiro Akeda, Akihide Ryo, Makoto Ohnishi. Pneumococcal sialidase promotes bacterial survival by fine-tuning of pneumolysin-mediated membrane disruption. Cell Reports 2024, 43 (3) , 113962. https://doi.org/10.1016/j.celrep.2024.113962
  40. Qian M. Cao, Pakpoom Boonchuen, Tzu-Chun Chen, Shaohua Lei, Kunlaya Somboonwiwat, Peter Sarnow. Virus-derived circular RNAs populate hepatitis C virus–infected cells. Proceedings of the National Academy of Sciences 2024, 121 (7) https://doi.org/10.1073/pnas.2313002121
  41. Jeremy W. Mason, Yuen Ting Chow, Liam Hudson, Antonin Tutter, Gregory Michaud, Matthias V. Westphal, Wei Shu, Xiaolei Ma, Zher Yin Tan, Connor W. Coley, Paul A. Clemons, Simone Bonazzi, Frédéric Berst, Karin Briner, Shuang Liu, Frédéric J. Zécri, Stuart L. Schreiber. DNA-encoded library-enabled discovery of proximity-inducing small molecules. Nature Chemical Biology 2024, 20 (2) , 170-179. https://doi.org/10.1038/s41589-023-01458-4
  42. Min Hao, Xinyu Ling, Yi Sun, Xue Wang, Wenzhe Li, Liying Chang, Zhiying Zeng, Xiaomeng Shi, Mengxiao Niu, Liangyi Chen, Tao Liu. Tracking endogenous proteins based on RNA editing-mediated genetic code expansion. Nature Chemical Biology 2024, 41 https://doi.org/10.1038/s41589-023-01533-w
  43. Arianne Caudal, Michael P. Snyder, Joseph C. Wu. Harnessing human genetics and stem cells for precision cardiovascular medicine. Cell Genomics 2024, 4 (2) , 100445. https://doi.org/10.1016/j.xgen.2023.100445
  44. Martin Ondra, Lukas Lenart, Amanda Centorame, Daciana C Dumut, Alexander He, Syeda Sadaf Zehra Zaidi, John W Hanrahan, Juan Bautista De Sanctis, Danuta Radzioch, Marian Hajduch. CRISPR/Cas9 bioluminescence-based assay for monitoring CFTR trafficking to the plasma membrane. Life Science Alliance 2024, 7 (1) , e202302045. https://doi.org/10.26508/lsa.202302045
  45. Alexander Chan, Andrew Tsourkas. Intracellular Protein Delivery: Approaches, Challenges, and Clinical Applications. BME Frontiers 2024, 5 https://doi.org/10.34133/bmef.0035
  46. Robert G. Hawley, Teresa S. Hawley. CRISPR-Cas9-Mediated Bioluminescent Tagging of Endogenous Proteins by Fluorescent Protein-Assisted Cell Sorting. 2024, 273-286. https://doi.org/10.1007/978-1-0716-3738-8_12
  47. Yume MIMURA, Takahiro HIONO, Loc Tan HUYNH, Saho OGINO, Maya KOBAYASHI, Norikazu ISODA, Yoshihiro SAKODA. Establishment of a superinfection exclusion method for pestivirus titration using a recombinant reporter pestiviruses. Journal of Veterinary Medical Science 2024, 86 (4) , 389-395. https://doi.org/10.1292/jvms.24-0005
  48. Jia Wang, Qingpeng Xie, Haoyue Song, Xiaohang Chen, Xiaoxuan Zhang, Xiangyu Zhao, Yujia Hao, Yuan Zhang, Huifei Li, Na Li, Kelong Fan, Xing Wang. Utilizing nanozymes for combating COVID-19: advancements in diagnostics, treatments, and preventative measures. Journal of Nanobiotechnology 2023, 21 (1) https://doi.org/10.1186/s12951-023-01945-9
  49. Takenobu Katagiri, Sho Tsukamoto, Mai Kuratani, Shinnosuke Tsuji, Kensuke Nakamura, Satoshi Ohte, Yoshiro Kawaguchi, Kiyosumi Takaishi. A blocking monoclonal antibody reveals dimerization of intracellular domains of ALK2 associated with genetic disorders. Nature Communications 2023, 14 (1) https://doi.org/10.1038/s41467-023-38746-5
  50. Sandra Wimberger, Nina Akrap, Mike Firth, Johan Brengdahl, Susanna Engberg, Marie K. Schwinn, Michael R. Slater, Anders Lundin, Pei-Pei Hsieh, Songyuan Li, Silvia Cerboni, Jonathan Sumner, Burcu Bestas, Bastian Schiffthaler, Björn Magnusson, Silvio Di Castro, Preeti Iyer, Mohammad Bohlooly-Y, Thomas Machleidt, Steve Rees, Ola Engkvist, Tyrell Norris, Elaine B. Cadogan, Josep V. Forment, Saša Šviković, Pinar Akcakaya, Amir Taheri-Ghahfarokhi, Marcello Maresca. Simultaneous inhibition of DNA-PK and Polϴ improves integration efficiency and precision of genome editing. Nature Communications 2023, 14 (1) https://doi.org/10.1038/s41467-023-40344-4
  51. Michael A. Erb. Small-molecule tools for YEATS domain proteins. Current Opinion in Chemical Biology 2023, 77 , 102404. https://doi.org/10.1016/j.cbpa.2023.102404
  52. Catherine S. Hansel, Alice Lanne, Hannah Rowlands, Joseph Shaw, Matthew J. Collier, Helen Plant. High-throughput differential scanning fluorimetry (DSF) and cellular thermal shift assays (CETSA): Shifting from manual to automated screening. SLAS Technology 2023, 28 (6) , 411-415. https://doi.org/10.1016/j.slast.2023.08.004
  53. Elizabeth A. Phillips, Adam D. Silverman, Aric Joneja, Michael Liu, Carl Brown, Paul Carlson, Christine Coticchia, Kristen Shytle, Alex Larsen, Nadish Goyal, Vincent Cai, Jason Huang, Jennifer E. Hickey, Emily Ryan, Joycelynn Acheampong, Pradeep Ramesh, James J. Collins, William J. Blake. Detection of viral RNAs at ambient temperature via reporter proteins produced through the target-splinted ligation of DNA probes. Nature Biomedical Engineering 2023, 7 (12) , 1571-1582. https://doi.org/10.1038/s41551-023-01028-y
  54. Gabriele Colozza, Heetak Lee, Alessandra Merenda, Szu-Hsien Sam Wu, Andrea Català-Bordes, Tomasz W. Radaszkiewicz, Ingrid Jordens, Ji-Hyun Lee, Aileen-Diane Bamford, Fiona Farnhammer, Teck Yew Low, Madelon M. Maurice, Vítězslav Bryja, Jihoon Kim, Bon-Kyoung Koo. Intestinal Paneth cell differentiation relies on asymmetric regulation of Wnt signaling by Daam1/2. Science Advances 2023, 9 (47) https://doi.org/10.1126/sciadv.adh9673
  55. Rebecca R. Florke Gee, Andrew D. Huber, Jing Wu, Richa Bajpai, Allister J. Loughran, Shondra M. Pruett-Miller, Taosheng Chen. The F-box-only protein 44 regulates pregnane X receptor protein level by ubiquitination and degradation. Acta Pharmaceutica Sinica B 2023, 13 (11) , 4523-4534. https://doi.org/10.1016/j.apsb.2023.07.014
  56. Laure Simoens, Igor Fijalkowski, Petra Van Damme. Exposing the small protein load of bacterial life. FEMS Microbiology Reviews 2023, 47 (6) https://doi.org/10.1093/femsre/fuad063
  57. Younghoon Kim, Pooreum Seo, Eunhye Jeon, Inchul You, Kyubin Hwang, Namkyoung Kim, Jason Tse, Juhyeon Bae, Ha-Soon Choi, Stephen M. Hinshaw, Nathanael S. Gray, Taebo Sim. Targeted kinase degradation via the KLHDC2 ubiquitin E3 ligase. Cell Chemical Biology 2023, 30 (11) , 1414-1420.e5. https://doi.org/10.1016/j.chembiol.2023.07.008
  58. Koya Miura, Youichi Suzuki, Kotaro Ishida, Masashi Arakawa, Hong Wu, Yoshihiko Fujioka, Akino Emi, Koki Maeda, Ryusei Hamajima, Takashi Nakano, Takeshi Tenno, Hidekazu Hiroaki, Eiji Morita, . Distinct motifs in the E protein are required for SARS-CoV-2 virus particle formation and lysosomal deacidification in host cells. Journal of Virology 2023, 97 (10) https://doi.org/10.1128/jvi.00426-23
  59. In Young Choi, Jee-Hwan Oh, Zhiying Wang, Jan-Peter van Pijkeren, . Bioluminescent monitoring of recombinant lactic acid bacteria and their products. mBio 2023, 14 (5) https://doi.org/10.1128/mbio.01197-23
  60. Habib Bouguenina, Andrea Scarpino, Jack A. O'Hanlon, Justin Warne, Hannah Z. Wang, Laura Chan Wah Hak, Amine Sadok, P. Craig McAndrew, Mark Stubbs, Olivier A. Pierrat, Tamas Hahner, Marc P. Cabry, Yann‐Vaï Le Bihan, Costas Mitsopoulos, Fernando J. Sialana, Theodoros I. Roumeliotis, Rosemary Burke, Rob L. M. van Montfort, Jyoti Choudhari, Rajesh Chopra, John J. Caldwell, Ian Collins. A Degron Blocking Strategy Towards Improved CRL4 CRBN Recruiting PROTAC Selectivity**. ChemBioChem 2023, 13 https://doi.org/10.1002/cbic.202300351
  61. Sofia Guzzetti, Pablo Morentin Gutierrez. An integrated modelling approach for targeted degradation: insights on optimization, data requirements and PKPD predictions from semi- or fully-mechanistic models and exact steady state solutions. Journal of Pharmacokinetics and Pharmacodynamics 2023, 50 (5) , 327-349. https://doi.org/10.1007/s10928-023-09857-9
  62. Manabu Kawata, Daniel B. McClatchy, Jolene K. Diedrich, Merissa Olmer, Kristen A. Johnson, John R. Yates, Martin K. Lotz. Mocetinostat activates Krüppel-like factor 4 and protects against tissue destruction and inflammation in osteoarthritis. JCI Insight 2023, 8 (17) https://doi.org/10.1172/jci.insight.170513
  63. Tianyi Ma, Kunlun Huang, Nan Cheng. Recent Advances in Nanozyme-Mediated Strategies for Pathogen Detection and Control. International Journal of Molecular Sciences 2023, 24 (17) , 13342. https://doi.org/10.3390/ijms241713342
  64. Shuo Huang, Rui Dai, Zhiqi Zhang, Han Zhang, Meng Zhang, Zhangjun Li, Kangrui Zhao, Wenjun Xiong, Siyu Cheng, Buhua Wang, Yi Wan. CRISPR/Cas-Based Techniques for Live-Cell Imaging and Bioanalysis. International Journal of Molecular Sciences 2023, 24 (17) , 13447. https://doi.org/10.3390/ijms241713447
  65. Adam B. Schroer, Patrick B. Ventura, Juliana Sucharov, Rhea Misra, M. K. Kirsten Chui, Gregor Bieri, Alana M. Horowitz, Lucas K. Smith, Katriel Encabo, Imelda Tenggara, Julien Couthouis, Joshua D. Gross, June M. Chan, Anthony Luke, Saul A. Villeda. Platelet factors attenuate inflammation and rescue cognition in ageing. Nature 2023, 620 (7976) , 1071-1079. https://doi.org/10.1038/s41586-023-06436-3
  66. Mina Oliayi, Rahman Emamzadeh, Mojgan Rastegar, Mahboobeh Nazari. Tri-part NanoLuc as a new split technology with potential applications in chemical biology: a mini-review. Analytical Methods 2023, 15 (32) , 3924-3931. https://doi.org/10.1039/D3AY00512G
  67. Jitesh Kumar, Si Nian Char, Trevor Weiss, Hua Liu, Bo Liu, Bing Yang, Feng Zhang. Efficient protein tagging and cis -regulatory element engineering via precise and directional oligonucleotide-based targeted insertion in plants. The Plant Cell 2023, 35 (8) , 2722-2735. https://doi.org/10.1093/plcell/koad139
  68. Lingyun Wang, Guojin Wu, Ji-Bin Peng. Identification of a novel KLHL3-interacting motif in the C-terminal region of WNK4. Biochemical and Biophysical Research Communications 2023, 670 , 87-93. https://doi.org/10.1016/j.bbrc.2023.05.105
  69. Takahiro Yamakawa, Guoxiang Zhang, Liza Bengrine Najjar, Chun Li, Keiichi Itakura. The uncharacterized transcript KIAA0930 confers a cachexic phenotype on cancer cells. Oncotarget 2023, 14 (1) , 723-737. https://doi.org/10.18632/oncotarget.28476
  70. Martin P. Schwalm, Andreas Krämer, Anja Dölle, Janik Weckesser, Xufen Yu, Jian Jin, Krishna Saxena, Stefan Knapp. Tracking the PROTAC degradation pathway in living cells highlights the importance of ternary complex measurement for PROTAC optimization. Cell Chemical Biology 2023, 30 (7) , 753-765.e8. https://doi.org/10.1016/j.chembiol.2023.06.002
  71. Ajay Gupta, Bo Liu, Qi‐Jun Chen, Bing Yang. High‐efficiency prime editing enables new strategies for broad‐spectrum resistance to bacterial blight of rice. Plant Biotechnology Journal 2023, 21 (7) , 1454-1464. https://doi.org/10.1111/pbi.14049
  72. Kevin Munoz Navarrete, Ladislav Bumba, Tatyana Prudnikova, Ivana Malcova, Tania Romero Allsop, Peter Sebo, Jana Kamanova, . BopN is a Gatekeeper of the Bordetella Type III Secretion System. Microbiology Spectrum 2023, 11 (3) https://doi.org/10.1128/spectrum.04112-22
  73. Shrusti S. Patel, Ella N. Hoogenboezem, Fang Yu, Carlisle R. DeJulius, R. Brock Fletcher, Alex G. Sorets, Fiona K. Cherry, Justin H. Lo, Mariah G. Bezold, Nora Francini, Richard d’Arcy, Jordan E. Brasuell, Rebecca S. Cook, Craig L. Duvall. Core polymer optimization of ternary siRNA nanoparticles enhances in vivo safety, pharmacokinetics, and tumor gene silencing. Biomaterials 2023, 297 , 122098. https://doi.org/10.1016/j.biomaterials.2023.122098
  74. Ke Li, Junwei Zheng, Leyi Yu, Bin Wang, Li Pan. Exploration of the Strategy for Improving the Expression of Heterologous Sweet Protein Monellin in Aspergillus niger. Journal of Fungi 2023, 9 (5) , 528. https://doi.org/10.3390/jof9050528
  75. Brandon E. K. Tan, Michael R. Beard, Nicholas S. Eyre. Identification of Key Residues in Dengue Virus NS1 Protein That Are Essential for Its Secretion. Viruses 2023, 15 (5) , 1102. https://doi.org/10.3390/v15051102
  76. Matthew T. N. Yarnall, Eleonora I. Ioannidi, Cian Schmitt-Ulms, Rohan N. Krajeski, Justin Lim, Lukas Villiger, Wenyuan Zhou, Kaiyi Jiang, Sofya K. Garushyants, Nathaniel Roberts, Liyang Zhang, Christopher A. Vakulskas, John A. Walker, Anastasia P. Kadina, Adrianna E. Zepeda, Kevin Holden, Hong Ma, Jun Xie, Guangping Gao, Lander Foquet, Greg Bial, Sara K. Donnelly, Yoshinari Miyata, Daniel R. Radiloff, Jordana M. Henderson, Andrew Ujita, Omar O. Abudayyeh, Jonathan S. Gootenberg. Drag-and-drop genome insertion of large sequences without double-strand DNA cleavage using CRISPR-directed integrases. Nature Biotechnology 2023, 41 (4) , 500-512. https://doi.org/10.1038/s41587-022-01527-4
  77. Simone Bonazzi, Eva d’Hennezel, Rohan E.J. Beckwith, Lei Xu, Aleem Fazal, Anna Magracheva, Radha Ramesh, Artiom Cernijenko, Brandon Antonakos, Hyo-eun C. Bhang, Roxana García Caro, Jennifer S. Cobb, Elizabeth Ornelas, Xiaolei Ma, Charles A. Wartchow, Matthew C. Clifton, Ry R. Forseth, Bethany Hughes Fortnam, Hongbo Lu, Alfredo Csibi, Jennifer Tullai, Seth Carbonneau, Noel M. Thomsen, Jay Larrow, Barbara Chie-Leon, Dominik Hainzl, Yi Gu, Darlene Lu, Matthew J. Meyer, Dylan Alexander, Jacqueline Kinyamu-Akunda, Catherine A. Sabatos-Peyton, Natalie A. Dales, Frédéric J. Zécri, Rishi K. Jain, Janine Shulok, Y. Karen Wang, Karin Briner, Jeffery A. Porter, John A. Tallarico, Jeffrey A. Engelman, Glenn Dranoff, James E. Bradner, Michael Visser, Jonathan M. Solomon. Discovery and characterization of a selective IKZF2 glue degrader for cancer immunotherapy. Cell Chemical Biology 2023, 30 (3) , 235-247.e12. https://doi.org/10.1016/j.chembiol.2023.02.005
  78. Jing Zhang, Maarten van Dinther, Midory Thorikay, Babak Mousavi Gourabi, Boudewijn P. T. Kruithof, Peter ten Dijke. Opposing USP19 splice variants in TGF-β signaling and TGF-β-induced epithelial–mesenchymal transition of breast cancer cells. Cellular and Molecular Life Sciences 2023, 80 (2) https://doi.org/10.1007/s00018-022-04672-w
  79. Elizabeth Thomas, Retheesh S. Thankan, Puranik Purushottamachar, David J. Weber, Vincent C. O. Njar. Targeted Degradation of Androgen Receptor by VNPP433-3β in Castration-Resistant Prostate Cancer Cells Implicates Interaction with E3 Ligase MDM2 Resulting in Ubiquitin-Proteasomal Degradation. Cancers 2023, 15 (4) , 1198. https://doi.org/10.3390/cancers15041198
  80. Jing Zhang, Gerard van der Zon, Jin Ma, Hailiang Mei, Birol Cabukusta, Cedrick C Agaser, Katarina Madunić, Manfred Wuhrer, Tao Zhang, Peter ten Dijke. ST3GAL5 ‐catalyzed gangliosides inhibit TGF ‐β‐induced epithelial‐mesenchymal transition via TβRI degradation. The EMBO Journal 2023, 42 (2) https://doi.org/10.15252/embj.2021110553
  81. Bo Cai, Amol B. Mhetre, Casey J. Krusemark. Selection methods for proximity-dependent enrichment of ligands from DNA-encoded libraries using enzymatic fusion proteins. Chemical Science 2023, 14 (2) , 245-250. https://doi.org/10.1039/D2SC05495G
  82. Anna K. Duell, Daniel J. Sanderson, Michael S. Cohen. Quantification of PARP7 Protein Levels and PARP7 Inhibitor Target Engagement in Cells Using a Split Nanoluciferase System. 2023, 387-395. https://doi.org/10.1007/978-1-0716-2891-1_24
  83. Jian Wang, Emily Griffiths, Omar Tounekti, Martin Nemec, Eric Deneault, Jessie R. Lavoie, Anthony Ridgway. Canadian Regulatory Framework and Regulatory Requirements for Cell and Gene Therapy Products. 2023, 91-116. https://doi.org/10.1007/978-3-031-34567-8_6
  84. Neha Masarkar, Suman Kumar Ray, Pragati Raghuwanshi, Ashish K. Yadav, Sukhes Mukherjee. CRISPR/Cas9-Editing-Based Modeling of Tumor Hypoxia. 2023, 275-295. https://doi.org/10.1007/978-981-99-0313-9_13
  85. Xingjuan Chen, Hui Yao, Da Song, Jianhui Lin, Hua Zhou, Weifang Yuan, Ping Song, Guoping Sun, Meiying Xu. A novel antimony-selective ArsR transcriptional repressor and its specific detection of antimony trioxide in environmental samples via bacterial biosensor. Biosensors and Bioelectronics 2023, 220 , 114838. https://doi.org/10.1016/j.bios.2022.114838
  86. Duygu Sari-Ak, Omar Alomari, Raghad Shomali, Jackwee Lim, Deepak Thimiri Govinda Raj. Advances in CRISPR-Cas9 for the Baculovirus Vector System: A Systematic Review. Viruses 2023, 15 (1) , 54. https://doi.org/10.3390/v15010054
  87. Daniel J. Sanderson, Kelsie M. Rodriguez, Daniel S. Bejan, Ninni E. Olafsen, Inga D. Bohn, Ana Kojic, Sunil Sundalam, Ivan R. Siordia, Anna K. Duell, Nancy Deng, Carsten Schultz, Denis M. Grant, Jason Matthews, Michael S. Cohen. Structurally distinct PARP7 inhibitors provide new insights into the function of PARP7 in regulating nucleic acid-sensing and IFN-β signaling. Cell Chemical Biology 2023, 30 (1) , 43-54.e8. https://doi.org/10.1016/j.chembiol.2022.11.012
  88. Dinesh Kankanamge, Mithila Tennakoon, Ajith Karunarathne, N. Gautam. G protein gamma subunit, a hidden master regulator of GPCR signaling. Journal of Biological Chemistry 2022, 298 (12) , 102618. https://doi.org/10.1016/j.jbc.2022.102618
  89. Wakana Sato, Melanie Rasmussen, Christopher Deich, Aaron E. Engelhart, Katarzyna P. Adamala. Expanding luciferase reporter systems for cell-free protein expression. Scientific Reports 2022, 12 (1) https://doi.org/10.1038/s41598-022-15624-6
  90. Shi Min Tan, Wei-Guang Seetoh. Construction of a bioluminescence-based assay for bitter taste receptors (TAS2Rs). Scientific Reports 2022, 12 (1) https://doi.org/10.1038/s41598-022-21678-3
  91. Natasha C. Dale, Carl W. White, Elizabeth K.M. Johnstone, Kevin D.G. Pfleger. Bioluminescence Resonance Energy Transfer ( BRET ) Technologies to Study GPCRs. 2022, 841-873. https://doi.org/10.1002/9781119564782.ch23
  92. N. Connor Payne, Ralph Mazitschek. Tiny Titans: Nanobodies as Powerful Tools for TR‐FRET Assay Development. Analysis & Sensing 2022, 2 (6) https://doi.org/10.1002/anse.202200020
  93. Sylvaine Boissinot, Marie Ducousso, Véronique Brault, Martin Drucker. Bioluminescence Production by Turnip Yellows Virus Infectious Clones: A New Way to Monitor Plant Virus Infection. International Journal of Molecular Sciences 2022, 23 (22) , 13685. https://doi.org/10.3390/ijms232213685
  94. Emily A. Torio, Valerie T. Ressler, Virginia A. Kincaid, Robin Hurst, Mary P. Hall, Lance P. Encell, Kristopher Zimmerman, Stuart K. Forsyth, William M. Rehrauer, Molly A. Accola, Chia-Chang Hsu, Thomas Machleidt, Melanie L. Dart. Development of a rapid, simple, and sensitive point-of-care technology platform utilizing ternary NanoLuc. Frontiers in Microbiology 2022, 13 https://doi.org/10.3389/fmicb.2022.970233
  95. Luke M. Simpson, Lorraine Glennie, Abigail Brewer, Jin-Feng Zhao, Jennifer Crooks, Natalia Shpiro, Gopal P. Sapkota. Target protein localization and its impact on PROTAC-mediated degradation. Cell Chemical Biology 2022, 29 (10) , 1482-1504.e7. https://doi.org/10.1016/j.chembiol.2022.08.004
  96. Václav Němec, Martin P. Schwalm, Susanne Müller, Stefan Knapp. PROTAC degraders as chemical probes for studying target biology and target validation. Chemical Society Reviews 2022, 51 (18) , 7971-7993. https://doi.org/10.1039/D2CS00478J
  97. Ariunaa Sumiyadorj, Kazuhisa Murai, Tetsuro Shimakami, Kazuyuki Kuroki, Tomoki Nishikawa, Masaki Kakuya, Atsumu Yamada, Ying Wang, Atsuya Ishida, Takayoshi Shirasaki, Shotaro Kawase, Ying‐Yi Li, Hikari Okada, Kouki Nio, Kazunori Kawaguchi, Taro Yamashita, Yoshio Sakai, Davaadorj Duger, Eishiro Mizukoshi, Masao Honda, Shuichi Kaneko. A single hepatitis B virus genome with a reporter allows the entire viral life cycle to be monitored in primary human hepatocytes. Hepatology Communications 2022, 6 (9) , 2441-2454. https://doi.org/10.1002/hep4.2018
  98. Mari ISOBE, Yumika SUZUKI, Hideshi SUGIURA, Masahiro SHIBATA, Yuki OHSAKI, Satoshi KAMETAKA. Novel cell-based system to assay cell-cell fusion during myotube formation. Biomedical Research 2022, 43 (4) , 107-114. https://doi.org/10.2220/biomedres.43.107
  99. Sundararaj Stanleyraj Jeremiah, Kei Miyakawa, Akihide Ryo, . Detecting SARS-CoV-2 neutralizing immunity: highlighting the potential of split nanoluciferase technology. Journal of Molecular Cell Biology 2022, 14 (4) https://doi.org/10.1093/jmcb/mjac023
  100. Laura Van Moortel, Jonathan Thommis, Brecht Maertens, An Staes, Dorien Clarisse, Delphine De Sutter, Claude Libert, Onno C. Meijer, Sven Eyckerman, Kris Gevaert, Karolien De Bosscher. Novel assays monitoring direct glucocorticoid receptor protein activity exhibit high predictive power for ligand activity on endogenous gene targets. Biomedicine & Pharmacotherapy 2022, 152 , 113218. https://doi.org/10.1016/j.biopha.2022.113218
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  • Abstract

    Figure 1

    Figure 1. Linearity of luminescence generated by HiBiT. (a) Luminescent signal generated either by full-length recombinant NanoLuc or by Halo-Tag HiBiT incubated with saturating LgBiT. (b) Luminescent signal in live cells and cell lysates. HEK293 cells stably expressing LgBiT were transfected with varying concentrations of an expression plasmid for HaloTag-HiBiT, and luminescence was measured before (live cell) or after (lytic) lysis. For both panels, data represent luminescence after subtraction of the background caused by reagent (panel a) or untransfected cells (panel b). Shown are mean values, n = 4, with variability expressed as SD.

    Figure 2

    Figure 2. Quantification of endogenous HIF1α-HiBiT abundance. HIF1α-HiBiT levels in edited HeLa cells were measured in lytic format following 6 h treatment with (a) hypoxia (1% O2) or (b) the following compounds: Phenanthroline (Phen, 20 μM), ML228 (2 μM), DFO (300 μM), IOX2 (100 μM), FG2216 (100 μM), FG4592 (50 μM), DMOG (250 μM), MG132 (10 μM), and MLN4924 (1 μM). (c) HIF1α-HiBiT abundance measured in lytic format following treatment with different concentrations of compound. For panels a–c, shown are mean luminescence values (after subtraction of reagent background) from four independent experiments (at least five replicates per experiment) with variability expressed as SEM. Dashed line (panel b) denotes luminescence generated by untreated HIF1α-HiBiT-expressing HeLa cells.

    Figure 3

    Figure 3. Hypoxia response of HIF1α target proteins. Levels of endogenous (a) BNIP3-, (b) ANKRD37-, (c) HILPDA-, and (d) KLF10-HiBiT in HeLa cells following 20 h of hypoxia treatment. Shown are mean luminescence values (after subtraction of background) from five independent experiments (at least five replicates per experiment), with variability expressed as SEM.

    Figure 4

    Figure 4. Response of HIF1α target proteins to hypoxia mimetics. Levels of endogenous (a) BNIP3-, (b) ANKRD37-, (c) HILPDA-, and (d) KLF10-HiBiT in HeLa cells following 24 h treatment with the following compounds: Phenanthroline (Phen, 20 μM), ML228 (2 μM), DFO (300 μM), IOX2 (100 μM), FG2216 (100 μM), FG4592 (50 μM), DMOG (250 μM), MG132 (10 μM), and MLN4924 (1 μM). Data represent luminescence acquired in lytic format after background subtraction from five independent experiments, with variability expressed as SEM. Dashed line denotes luminescence generated by untreated HiBiT-edited cells.

    Figure 5

    Figure 5. Dose response of HIF1α target proteins. Compound-induced accumulation of endogenous (a) BNIP3-, (b) ANKRD37-, (c) HILPDA-, and (d) KLF10-HiBiT in edited HeLa cells treated for 20 h with hypoxia mimetics. Shown are mean luminescence values (after subtraction of reagent background) from five independent experiments (at least five replicates per experiment), with variability expressed as SEM. Dashed line denotes luminescence generated by untreated HiBiT-edited HeLa cells.

    Figure 6

    Figure 6. Quantification of HiBiT-tagged proteins in primary cells. Levels of endogenous (a) HIF1α-, (b) BNIP3-, and (c) VEGFA-HiBiT in edited HUVEC cells. Cells were treated for 6 h with phenanthroline (Phen, 20 μM), ML228 (2 μM), DFO (300 μM), MG132 (10 μM), and MLN4924 (1 μM) and then analyzed for luminescence in lytic format. Data are represented as luminescence with background subtracted, n = 4, with variation expressed as SD. Dashed line indicates luminescence generated by untreated HiBiT-edited HUVEC cells.

    Figure 7

    Figure 7. Real-time measurement of induced changes in protein abundance. (a) HeLa cells expressing HiBiT-edited HIF1α and downstream target proteins were transduced with BacMam-LgBiT, and luminescence was monitored following phenanthroline addition. Signal-to-background (S/B) ratios were derived using the formula: (RLUphenanthroline – RLUbackground)/(RLUuntreated – RLUbackground), where background is determined from parental HeLa cells. (b) Edited HeLa cells were transduced with BacMam-LgBiT and incubated for 20 h under hypoxia. Luminescence was measured immediately following release from the hypoxia chamber. Shown are mean relative responses, n = 3, with variability represented as SD.

    Figure 8

    Figure 8. Simultaneous quantification of HIF1α hydroxylation at proline 564 and protein abundance. HeLa cells expressing HIF1α-HiBiT were treated for 6 h with phenanthroline in the presence of MG132. HIF1α proline hydroxylation levels are represented as BRET ratio (acceptor emission 610 nm/donor emission 460 nm; red circles). HIF1α abundance is represented as luminescence (blue circles). Shown are the mean values, n = 3, with variability represented as SD.

  • References

    ARTICLE SECTIONS
    Jump To

    This article references 31 other publications.

    1. 1
      Buuh, Z. Y., Lyu, Z., and Wang, R. E. (2017) Interrogating the Roles of Post-Translational Modifications of Non-Histone Proteins, J. Med. Chem., DOI:  DOI: 10.1021/acs.jmedchem.6b01817 .
    2. 2
      Harper, J. W. and Bennett, E. J. (2016) Proteome complexity and the forces that drive proteome imbalance Nature 537, 328 338 DOI: 10.1038/nature19947
    3. 3
      Beri, J., Rosenblatt, M. M., Strauss, E., Urh, M., and Bereman, M. S. (2015) Reagent for Evaluating Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) Performance in Bottom-Up Proteomic Experiments Anal. Chem. 87, 11635 11640 DOI: 10.1021/acs.analchem.5b04121
    4. 4
      McDonough, A. A., Veiras, L. C., Minas, J. N., and Ralph, D. L. (2015) Considerations when quantitating protein abundance by immunoblot Am. J. Physiol Cell Physiol 308, C426 433 DOI: 10.1152/ajpcell.00400.2014
    5. 5
      Moriya, H. (2015) Quantitative nature of overexpression experiments Mol. Biol. Cell 26, 3932 3939 DOI: 10.1091/mbc.E15-07-0512
    6. 6
      Lackner, D. H., Carre, A., Guzzardo, P. M., Banning, C., Mangena, R., Henley, T., Oberndorfer, S., Gapp, B. V., Nijman, S. M., Brummelkamp, T. R., and Burckstummer, T. (2015) A generic strategy for CRISPR-Cas9-mediated gene tagging Nat. Commun. 6, 10237 10244 DOI: 10.1038/ncomms10237
    7. 7
      Ratz, M., Testa, I., Hell, S. W., and Jakobs, S. (2015) CRISPR/Cas9-mediated endogenous protein tagging for RESOLFT super-resolution microscopy of living human cells Sci. Rep. 5, 9592 9598 DOI: 10.1038/srep09592
    8. 8
      Leonetti, M. D., Sekine, S., Kamiyama, D., Weissman, J. S., and Huang, B. (2016) A scalable strategy for high-throughput GFP tagging of endogenous human proteins Proc. Natl. Acad. Sci. U. S. A. 113, E3501 3508 DOI: 10.1073/pnas.1606731113
    9. 9
      Cabantous, S., Terwilliger, T. C., and Waldo, G. S. (2005) Protein tagging and detection with engineered self-assembling fragments of green fluorescent protein Nat. Biotechnol. 23, 102 107 DOI: 10.1038/nbt1044
    10. 10
      Fan, F. and Wood, K. V. (2007) Bioluminescent assays for high-throughput screening Assay Drug Dev. Technol. 5, 127 136 DOI: 10.1089/adt.2006.053
    11. 11
      Hall, M. P., Unch, J., Binkowski, B. F., Valley, M. P., Butler, B. L., Wood, M. G., Otto, P., Zimmerman, K., Vidugiris, G., Machleidt, T., Robers, M. B., Benink, H. A., Eggers, C. T., Slater, M. R., Meisenheimer, P. L., Klaubert, D. H., Fan, F., Encell, L. P., and Wood, K. V. (2012) Engineered luciferase reporter from a deep sea shrimp utilizing a novel imidazopyrazinone substrate ACS Chem. Biol. 7, 1848 1857 DOI: 10.1021/cb3002478
    12. 12
      Dixon, A. S., Schwinn, M. K., Hall, M. P., Zimmerman, K., Otto, P., Lubben, T. H., Butler, B. L., Binkowski, B. F., Machleidt, T., Kirkland, T. A., Wood, M. G., Eggers, C. T., Encell, L. P., and Wood, K. V. (2016) NanoLuc Complementation Reporter Optimized for Accurate Measurement of Protein Interactions in Cells ACS Chem. Biol. 11, 400 408 DOI: 10.1021/acschembio.5b00753
    13. 13
      Dengler, V. L., Galbraith, M. D., and Espinosa, J. M. (2014) Transcriptional regulation by hypoxia inducible factors Crit. Rev. Biochem. Mol. Biol. 49, 1 15 DOI: 10.3109/10409238.2013.838205
    14. 14
      Beltrao, P., Bork, P., Krogan, N. J., and van Noort, V. (2013) Evolution and functional cross-talk of protein post-translational modifications Mol. Syst. Biol. 9, 714 727 DOI: 10.1002/msb.201304521
    15. 15
      Machleidt, T., Woodroofe, C. C., Schwinn, M. K., Mendez, J., Robers, M. B., Zimmerman, K., Otto, P., Daniels, D. L., Kirkland, T. A., and Wood, K. V. (2015) NanoBRET--A Novel BRET Platform for the Analysis of Protein-Protein Interactions ACS Chem. Biol. 10, 1797 1804 DOI: 10.1021/acschembio.5b00143
    16. 16
      Masson, N. and Ratcliffe, P. J. (2014) Hypoxia signaling pathways in cancer metabolism: the importance of co-selecting interconnected physiological pathways Cancer Metab 2, 3 20 DOI: 10.1186/2049-3002-2-3
    17. 17
      Theriault, J. R., Felts, A. S., Bates, B. S., Perez, J. R., Palmer, M., Gilbert, S. R., Dawson, E. S., Engers, J. L., Lindsley, C. W., and Emmitte, K. A. (2012) Discovery of a new molecular probe ML228: an activator of the hypoxia inducible factor (HIF) pathway Bioorg. Med. Chem. Lett. 22, 76 81 DOI: 10.1016/j.bmcl.2011.11.077
    18. 18
      Xia, M., Huang, R., Sun, Y., Semenza, G. L., Aldred, S. F., Witt, K. L., Inglese, J., Tice, R. R., and Austin, C. P. (2009) Identification of chemical compounds that induce HIF-1alpha activity Toxicol. Sci. 112, 153 163 DOI: 10.1093/toxsci/kfp123
    19. 19
      Hong, Y. R., Kim, H. T., Lee, S. C., Ro, S., Cho, J. M., Kim, I. S., and Jung, Y. H. (2013) [(4-Hydroxyl-benzo[4,5]thieno[3,2-c]pyridine-3-carbonyl)-amino]-acetic acid derivatives; HIF prolyl 4-hydroxylase inhibitors as oral erythropoietin secretagogues Bioorg. Med. Chem. Lett. 23, 5953 5957 DOI: 10.1016/j.bmcl.2013.08.067
    20. 20
      Chan, M. C., Ilott, N. E., Schodel, J., Sims, D., Tumber, A., Lippl, K., Mole, D. R., Pugh, C. W., Ratcliffe, P. J., Ponting, C. P., and Schofield, C. J. (2016) Tuning the Transcriptional Response to Hypoxia by Inhibiting Hypoxia-inducible Factor (HIF) Prolyl and Asparaginyl Hydroxylases J. Biol. Chem. 291, 20661 20673 DOI: 10.1074/jbc.M116.749291
    21. 21
      Frost, J., Galdeano, C., Soares, P., Gadd, M. S., Grzes, K. M., Ellis, L., Epemolu, O., Shimamura, S., Bantscheff, M., Grandi, P., Read, K. D., Cantrell, D. A., Rocha, S., and Ciulli, A. (2016) Potent and selective chemical probe of hypoxic signalling downstream of HIF-alpha hydroxylation via VHL inhibition Nat. Commun. 7, 13312 13324 DOI: 10.1038/ncomms13312
    22. 22
      Zhao, Y., Xiong, X., Jia, L., and Sun, Y. (2012) Targeting Cullin-RING ligases by MLN4924 induces autophagy via modulating the HIF1-REDD1-TSC1-mTORC1-DEPTOR axis Cell Death Dis. 3, e386 DOI: 10.1038/cddis.2012.125
    23. 23
      Kallio, P. J., Okamoto, K., O’Brien, S., Carrero, P., Makino, Y., Tanaka, H., and Poellinger, L. (1998) Signal transduction in hypoxic cells: inducible nuclear translocation and recruitment of the CBP/p300 coactivator by the hypoxia-inducible factor-1alpha EMBO J. 17, 6573 6586 DOI: 10.1093/emboj/17.22.6573
    24. 24
      Benita, Y., Kikuchi, H., Smith, A. D., Zhang, M. Q., Chung, D. C., and Xavier, R. J. (2009) An integrative genomics approach identifies Hypoxia Inducible Factor-1 (HIF-1)-target genes that form the core response to hypoxia Nucleic Acids Res. 37, 4587 4602 DOI: 10.1093/nar/gkp425
    25. 25
      Daer, R. M., Cutts, J. P., Brafman, D. A., and Haynes, K. A. (2017) The Impact of Chromatin Dynamics on Cas9-Mediated Genome Editing in Human Cells ACS Synth. Biol. 6, 428 438 DOI: 10.1021/acssynbio.5b00299
    26. 26
      Nilsson, I., Shibuya, M., and Wennstrom, S. (2004) Differential activation of vascular genes by hypoxia in primary endothelial cells Exp. Cell Res. 299, 476 485 DOI: 10.1016/j.yexcr.2004.06.005
    27. 27
      D’Angelo, G., Duplan, E., Boyer, N., Vigne, P., and Frelin, C. (2003) Hypoxia up-regulates prolyl hydroxylase activity: a feedback mechanism that limits HIF-1 responses during reoxygenation J. Biol. Chem. 278, 38183 38187 DOI: 10.1074/jbc.M302244200
    28. 28
      Berra, E., Roux, D., Richard, D. E., and Pouyssegur, J. (2001) Hypoxia-inducible factor-1 alpha (HIF-1 alpha) escapes O(2)-driven proteasomal degradation irrespective of its subcellular localization: nucleus or cytoplasm EMBO Rep. 2, 615 620 DOI: 10.1093/embo-reports/kve130
    29. 29
      Brahimi-Horn, C., Mazure, N., and Pouyssegur, J. (2005) Signalling via the hypoxia-inducible factor-1alpha requires multiple posttranslational modifications Cell. Signalling 17, 1 9 DOI: 10.1016/j.cellsig.2004.04.010
    30. 30
      DeWitt, M. A., Corn, J. E., and Carroll, D. (2017) Genome editing via delivery of Cas9 ribonucleoprotein Methods 121–122, 9 15 DOI: 10.1016/j.ymeth.2017.04.003
    31. 31
      Klaubert, D. H., Meisenheimer, P., and Unch, J. (2014) Imidazo[1,2-α]pyrazine derivatives, Promega Corporation, United States of America.
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