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- Teusink,B et al. Can yeast glycolysis be understood in terms of in vitro kinetics of the constituent enzymes? Testing biochemistry. Eur J Biochem 2000 Sep;267(17):5313-29.
- Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.
- Prof. Henry Jakubowski (College of St. Benedict/St. John's University)
Structural basis for the inhibition of SARS-CoV-2 main protease by antineoplastic drug carmofur
The antineoplastic drug carmofur is shown to inhibit the SARS-CoV-2 main protease (M pro ). Here, the X-ray crystal structure of M pro in complex with carmofur reveals that the carbonyl reactive group of carmofur is covalently bound to catalytic Cys145, whereas its fatty acid tail occupies the hydrophobic S2 subsite. Carmofur inhibits viral replication in cells (EC50 = 24.30 μM) and is a promising lead compound to develop new antiviral treatment for COVID-19.
COVID-19, a highly infectious viral disease caused by coronavirus SARS-CoV-2, has spread worldwide since its appearance in December 2019, causing an unprecedented pandemic. The number of confirmed cases worldwide continues to grow at a rapid rate, but, at this time, there are no specific drugs or vaccines available to control the symptoms or the spread of this disease.
30,000 nt RNA genome. The first open reading frame encodes two translational products, polyproteins 1a and 1ab (pp1a and pp1ab) 1,2 , which are processed into mature non-structural proteins by the main protease (M pro ) and a papain-like protease 3 . M pro has been proposed as a therapeutic target for anti-coronavirus drug development 4,5,6 . We previously screened over 10,000 compounds and identified carmofur as a compound that can inhibit M pro in vitro, with a half-maximum inhibitory concentration (IC50) of 1.82 μM (ref. 7 ).
Carmofur (1-hexylcarbamoyl-5-fluorouracil) is a derivative of 5-fluorouracil (5-FU Fig. 1a) and an approved antineoplastic agent. Carmofur has been used to treat colorectal cancer since the 1980s 8 and has shown clinical benefits for breast, gastric and bladder cancers 9,10,11 . The target for carmofur is believed to be thymidylate synthase 12,13 , but it has also been shown to inhibit human acid ceramidase (AC) 14 through covalent modification of its catalytic cysteine 15 .
a, The chemical structure of carmofur. b, The binding mode of carmofur to SARS-CoV-2 M pro . The red curve represents the SARS-CoV-2 M pro polypeptide with the side chain of Cys145 protruding. c, The structure of a single protomer. The three domains are shown in three different colors. The catalytic center is located within the dashed square. d, Magnified view of the catalytic center. The residues that participate in carmofur binding are shown as stick models. Carmofur is shown as a ball-and-stick model with the carbons in magenta. A water molecule is presented as a red sphere. e, A rotated view of the binding site, but with the surface removed. The red dashed circle highlights the C-S covalent bond.
The molecular details of how carmofur inhibits M pro activity have remained unresolved. Here, we now present a 1.6 Å X-ray crystal structure of SARS-CoV-2 M pro in complex with carmofur (Fig. 1b,c and Supplementary Table 1). In agreement with previous studies 4,5,16,17,18 , M pro forms a homodimer (protomers A and B) related by crystallographic symmetry (Extended Data Fig. 1a,b). All of the residues (1–306) in the polypeptide can be traced in the electron density map. Each protomer is composed of three domains (Fig. 1c)—domains I (residues 10–99), II (residues 100–184) and III (residues 201–303)—and a long loop region (residues 185–200) that connects domains II and III. The substrate-binding pocket lies in the cleft between domains I and II, and features the catalytic dyad residues Cys145 and His41 (Fig. 1c,d). The substrate-binding pocket is divided into a series of subsites (including S1, S2, S4 and S1′), each accommodating a single but consecutive amino acid residue in the substrate. Ser1 in each one protomer interacts with Phe140 and Glu166 of the other protomer to stabilize the S1 subsite (Extended Data Fig. 1c), a structural feature that is essential for catalysis 7 .
The electron density map unambiguously shows that the fatty acid moiety (C7H14NO) of carmofur is linked to the Sγ atom of Cys145 through a 1.8 Å covalent bond, whereas the fatty acid tail is inserted into the S2 subsite (Fig. 1d,e). This observation suggests that the sulfhydryl group of Cys145 attacks the electrophilic carbonyl group of carmofur, resulting in covalent modification of Cys145 and release of the 5-FU moiety (Fig. 1b and Extended Data Fig. 2a). In addition to the C-S covalent bond, the inhibitor is stabilized by numerous hydrogen bonds and hydrophobic interactions (Fig. 1e and Extended Data Fig. 2b). The carbonyl oxygen of carmofur occupies the oxyanion hole and forms hydrogen bonds (3.0 Å) with the backbone amides of Gly143 and Cys145, mimicking the tetrahedral oxyanion intermediate formed during protease cleavage (Fig. 1e). The fatty acid tail, which appears in an extended conformation, inserts into the bulky hydrophobic S2 subsite (composed of the side chains of His41, Met49, Tyr54 and Met165 and the alkyl portion of the side chain of Asp187 Fig. 1d,e). The hydrophobic interactions are mainly contributed by the side chains of His41, Met49 and Met165, all of which run parallel to the alkyl part of the fatty acid tail of the inhibitor (Fig. 1e and Extended Data Fig. 2b).
The mechanism of covalent modification by carmofur is different from that of the inhibitor N3 7,19 , which covalently modifies Cys145 through Michael addition of the vinyl group. The structures of M pro –carmofur and M pro –N3 are similar overall (r.m.s. deviation (r.m.s.d.) of 0.286 Å for all Cα atoms). The largest conformational differences occur in the substrate-binding pocket, with the backbone surrounding carmofur in a slightly more outward position compared with the M pro –N3 complex structure (Extended Data Fig. 3a). Another difference is that carmofur only occupies the S2 subsite (Fig. 1d), whereas N3 occupies four subsites (S1, S2, S4 and S1′ Extended Data Fig. 3b,c). The lactam ring of N3 is located in the S1 subsite, which is filled by a DMSO molecule in the M pro –carmofur structure (Extended Data Fig. 3b,c). These observations demonstrate the potential for structural elaboration of carmofur and will be useful for the design of more potent derivatives against the M pro of SARS-CoV-2.
We previously showed that treatment with 10 μM ebselen (half-maximum effective concentration, EC50 = 4.67 μM) inhibited infection of Vero cells with SARS-CoV-2, whereas carmofur did not show detectable antiviral activity at this concentration 7 . Here, we have determined the inhibitory effect of carmofur against SARS-CoV-2 infection on Vero E6 cells, as previously described in ref. 20 (Fig. 2). By measuring viral RNA in the cellular supernatant, we determined the EC50 value for carmofur as 24.30 μM (Fig. 2a). To verify this result, we fixed infected cells and stained them using anti-sera against viral nucleocapsid protein (NP), observing a decrease in NP levels after carmofur treatment (Fig. 2b). We also performed cytotoxicity assays for carmofur in Vero E6 cells and determined a half-maximum cytotoxic concentration (CC50) value of 133.4 μM (Fig. 2c). Thus, carmofur has a favorable selectivity index (SI) of 5.36, but further optimization will be required to develop an effective drug.
Vero E6 cells infected with SARS-CoV-2 at a multiplicity of infection (MOI) of 0.05 were treated with different concentrations of carmofur. a, Quantitative polymerase chain reaction with reverse transcription (qRT-PCR) assays were performed to measure the viral copy number in cellular supernatant. The y axis indicates percentage inhibition of virus relative to sample treated with DMSO (vehicle). Data are shown as mean ± s.e.m., n = 6 biological replicates. b, Immunofluorescence images for intracellular NP. At 24 h post-infection, cells were fixed, and intracellular NP levels were monitored by immunofluorescence. Chloroquine (CQ, 10 μM) was used as a positive control 20 . The results are representative of three biological replicates. Scale bars, 400 μm. c, Cell viability assay. The y axis represents the percentage of cell viability relative to sample treated with DMSO (vehicle). Data are shown as mean ± s.e.m., n = 3 biological replicates. Data for graphs in a and c are available as source data.
In conclusion, the crystal structure of M pro in complex with carmofur shows that the compound directly modifies the catalytic Cys145 of SARS-CoV-2 M pro . Our study also provides a basis for rational design of carmofur analogs with enhanced inhibitory efficacy to treat COVID-19. Because M pro is highly conserved among all coronaviruses, carmofur and its analogs may be effective against a broader spectrum of these viruses.
Human papillomaviruses (HPVs) are associated with a variety of epithelial lesions, including benign genital warts and cervical intraepithelial neoplasia . To date, more than 250 HPV types have been identified and each of these genotypes are associated with infection at particular anatomical sites. HPV6 may be the most prevalent low risk alpha-papillomavirus type and is commonly associated with genital warts . For example, anogenital warts are primarily caused by HPV6 (family Papillomaviridae, genus Alphapapillomavirus, species 10) , which brings a significant burden to both the healthcare system and patients. Similarly, one third of Dutch primary school children have cutaneous warts, of which approximately 20% seek medical treatment each year . Generally speaking, these infections are classified as “not carcinogenic” or “low risk”, they often attract negative attention, and thereby cause significant psychological distress . However, some HPV6 variants are classified as “carcinogenic”, because they cause infections that lead to potentially fatal conditions, such as tonsillar, and malignant laryngeal carcinoma and/or malignant laryngeal papilloma [6,7,8,9].
To date, extensive research has been conducted to investigate sequence variation among carcinogenic HPV types nevertheless, only limited data is available regarding HPV6 variants, despite their significant impact on human health. Structurally, the HPV is a double-stranded, circular DNA virus that encodes E1, E2, E4, E5, E6, E7, L1 and L2 proteins . HPVs infect cells via the basal layer of the stratified epithelium, and viral gene expression is closely linked to the endogenous differentiation program of the host cells . Of the HPV-encoded proteins, E6 and E7 have been shown to be the most important pathogenic HPV proteins. They have been previously shown to function as oncoproteins that critically regulate HPV-induced tumorigenesis . Furthermore, they have also been demonstrated to be essential to maintain the extrachromosomal forms of HPV in undifferentiated basal cells .
Genetic variability analyses have proven essential to facilitate an improved understanding of the evolution of the papillomavirus. A number of carcinogenic variants have been identified in HPV variants isolated from populations in Southwest China however, only limited research has been conducted to identify low risk HPV variants. Thus, the present study aimed to analyze E6 and E7 sequence variability among HPV6 isolated from cervical papilloma samples collected from patients in Southwest China. Phylogenetic analyses were conducted to compare the identified nucleotide sequences with those previously described in other ethnic populations. In addition, the secondary structure of the identified sequences were predicted to assess the probably impact of the low risk variants on overall viral function. The results of the study could provide important data for the research on HPV6 prevention, diagnostic, therapeutic and even the design of therapeutic vaccines based on proteins E6 and E7 in Southwest China.
USING THE HISTORY OF BIOLOGY TO HIGHLIGHT SOCIAL CONTEXT
To help students understand that biological research can be influenced by people within the scientific community as well as outside of it, instructors can use the history of biology to provide context for the development of key principles, methods, and concepts. By tracing the steps of discovery through time, students see that biological knowledge is the result of human activity with each researcher building on the other's work through communication, competition, and collaboration. Though students might struggle to embrace a lengthy and nonlinear path of biological discovery, they may also be comforted by the fact that each discovery was not achieved alone. By sharing the history of biology with students, we present a more realistic view of the construction of biological knowledge: Opposing hypotheses or conflicting results are common the paths of discovery can involve technological limitations, experimental challenges, missteps, and wrong turns and culture and politics can influence the direction of research. By sharing historical tales of discovery, we promote the development of critical thinking through the creation of learning environments in which students feel comfortable airing misconceptions of their own, taking risks, and asking questions.
The History of Evolutionary Theory
A careful selection of topics from the historical record can be used to enhance student learning, but since time and space are limited in our courses, we must be judicious in our choices. In 2003, a working group of biologists was asked to define four or five central biological concepts that should be taught in every undergraduate biology course for the Steering Committee on Criteria and Benchmarks for Increased Learning from Undergraduate STEM Instruction (NRC, 2003). After many hours of deliberation, the group reported that evolution was the only concept common to all biology courses, and that other concepts (i.e., germ theory, cell theory, energetics, the central dogma) should be taught in courses that specifically require this knowledge. Given this outcome, it seems that it would be wise to teach the historical development of evolutionary theory, as this theory is the foundation of all of biology.
Though most biology educators have no formal training in the history of biology, we are fortunate to have access to many resources that highlight the significant events and people that have shaped evolutionary thought. Excellent sources that critically evaluate the contributions of scholars to the theory of evolution include “Evolution for Teachers” produced by PBS, the “Understanding Evolution” project hosted by The University of California (UC) at Berkeley, and Robert Young's online book Darwin's Metaphor: Nature's Place in Victorian Culture (Table 3). These resources acknowledge that ideas from other disciplines were essential to the development of evolutionary theory. The UC Berkeley site offers a concept map superimposed over a timeline that demonstrates the four disciplinary areas that contributed to our current understanding of evolution. In Young's book, excerpts from Darwin's Origin of the Species, Charles Lyell's Principles of Geology, and Thomas Malthus' An Essay on the Principle of Population are analyzed for commonalities. By viewing these excerpts together in one text, students learn that though Darwin was focused on the process of animal speciation, it was Malthus' work on economics and the social condition that ultimately propelled Darwin to make the leap from artificial selection to natural selection. Social philosopher Herbert Spencer then adapted the concept and coined the phrase “survival of the fittest” in Principles of Biology published in 1864. These resources naturally lead to conversations about “Social Darwinism” and the subsequent development of social eugenics practices in the United States, which can be illustrated by images from the “Eugenics Image Archive” hosted by the Dolan DNA Learning Center (Table 3). As evolution is the one guiding principle of all of biology, it is important that students be aware of the historical underpinnings of this theory, and recognize that even today there is debate about which biological phenomena contribute the most to speciation. The latter topic is brought to view more directly in a recent book that focuses on the contributions of horizontal gene transfer (Margulis and Sagan, 2003).
Table 3. Resources for the history of biology
The History of Cell Biology, Embryology and Genetics
Sources that trace the history of cell biology, developmental biology, and genetics often juxtapose excerpts from original historical texts with critical analysis, summarize history through the use of timelines, or reconstruct history through biographies, oral history projects, and interviews. The “Discovery of the Cell” (DoTC) project reflects contributions from historians of science and includes excerpts from historical texts, giving special attention to “the significance and conceptual value of a particular discovery” using a color coding scheme throughout the website that goes back as far as the 1500s (Table 3). GarlandScience has published a DVD titled “Exploring the Living Cell,” which contains a historical section that uses drawings and text to illustrate the work of early cell biologists (Table 3). Another interesting project, “The Embryo Project Encyclopedia,” is searchable by place, person, or object, and provides results in the form of a map that depicts the historical and relational links of these objects (Arizona State University, Table 3). Whose View of Life contains a rich and detailed history of early stem cell biology that serves as a foundation for current day stem cell research (Maienschein, Table 3). UC Berkeley has created an oral histories project around the same topic, using Proposition 71 in California as a case study to document the relationship between science and society through interviews with stem cell biologists and policy makers (Table 3). Though the Berkeley project does not use historical texts, its construction illustrates the need to preserve history in the making—something also observed in interviews from the “Program in Bioscience and Biotechnology Studies,” which capture the experiences, passions, and relationships of biologists who were poised to take biotechnology in a new direction. Similar shifts in biological research are reflected upon in “Language and Science,” which is the first of three chapters in Refiguring Life (Table 3). Here, Keller traces the emergence of genetics as a new field of biology and suggests that through its associated language, genetics led to the marginalization of the long-standing field of embryology. This kind of tracing back reminds students that as biologists continue to make discoveries, new fields will develop and old ideas may fade only to re-emerge in a new context. For example, some Larmarckian forms of inheritance are recognized today as the consequence of epigenetic programming events, which can be responsive to the environment (Jablonka et al., 1998).
A Word of Caution in Using the History of Biology to Teach Discovery
A paper titled “How Not to Teach History of Science,” cautions educators from using history as a tool to view science as “triumphant discovery” or “pathological error” (Allchin, 2000). To suggest that some scientists in the past are “losers” rather than contributors to a larger field of study results in three negative outcomes: It suggests that there is a “right answer,” that any results that don't move the investigator closer to this predicted and defined answer are useless, and that biology is static. One of the most famous “losers” depicted in biology textbooks is Jean-Baptiste Lamarck. A biased representation of Lamarck is strengthened when he is pitted against Charles Darwin. However, Lamarck and Darwin did not see their theories of evolution as mutually exclusive, and more recently Lamarck's work has been resurrected by a better understanding of how environmental factors can impact epigenetic modification of the genome. By using these theories together rather than in opposition, instructors can emphasize the importance of context in determining when, and how, these theories explain various biological phenomena. A multiplicity of approaches in addressing the same problem is useful because it gives students permission to be more courageous in putting forth new ideas.
One will also want to refrain from teaching “cookbook history,” presenting biological research or discoveries outside of their historical contexts (Allchin, 2000). When students read “historical” texts, they might criticize the experimental approach of a biologist, but use present day knowledge to do so. To help students place themselves back in time, one can use an excellent set of historical biographies in Microbe Hunters, originally published in 1928 (Table 3). The author uses language that was appropriate for the time, and though he may embellish here and there, he captures the personalities as well as the political and national alliances of various cell biologists (Summers, 1998). One important characteristic of these narratives is that they are not shy about highlighting the “pathological error” associated with a need to be “right,” and the frustrations that accompany experimentation that did not go as planned (see Koch and Metchnikoff chapters). When asking students to reflect on how these historical figures could have improved their experimental models, they must be reminded to stay true to the technologies and knowledge available at that point in time. These stories can be further contextualized using other articles that delve deeper into the social context. In the case of Louis Pasteur and Robert Koch, case studies show how the politics of war ignited animosity between individuals and competing schools of thought with respect to public health practices (Ullmann, 2007). Collectively these perspectives illustrate that technology is an important tool, and can be a driver or limiting factor in biological discovery.
Lastly, we recommend moving away from using history to showcase biological discoveries as products of serendipity, as it may convince students that biology is not about good experimentation but rather dumb luck. If we make a conscious effort to demonstrate that knowledge is built over time by multiple researchers who take years to acquire their expertise, students may be less inclined to rush toward finding the answers to problems, and spend time on meaningful observations and analysis. Timelines that display the contributions of multiple disciplines to one major discovery, such as DNA being the molecule of heredity, illustrate the power of integration and the vast amount of expertise needed to arrive at this finding (Figure 1, class-constructed timeline Figure 2, student-constructed timeline). Historical sources and timelines highlight one of the most influential factors of biological discovery, which is not serendipity, but sagacity—the ability through experience to distinguish meaningful deviations from experimental noise or human error (Gest, 1997).
Figure 1. Example of a class-constructed genetics timeline. This image was constructed in one class session of an introductory genetics course in which students were asked to integrate the people, history, and experiments that led to an understanding of DNA as the transforming material. Events and publications from physics, chemistry, and biology are woven together common techniques of the time are highlighted, including the use of radioactivity to trace molecules undergoing various molecular processes. The nod to “Bill and Doug” refers to a parable that helps students discern the differences between biochemical and genetic approaches and the merits of both in solving problems (Kellogg, 1994 Sullivan, 1993). There is a strong emphasis on the social ills of the time that drove discovery including infectious diseases (Griffiths, Hershey-Chase, Koch's Postulates), and attention is given to less-known figures such as Meischer, Franklin, and Wallace.
Figure 2. Example of student-constructed metagenomics and obesity timeline. When asked to submit a written summary of readings, which included research and review articles, this student spontaneously provided an additional timeline. This submission came midway through an intermediate-level course on the Human Genome Project and illustrates multiple approaches and methods to understanding the genetic and environmental contributions to the contemporary interdisciplinary problem of obesity.
Interaction of HPV16 E6 and Daxx in C33A cells
The positive controls (complexes of E6 with anti-E6 antibody or Daxx with anti-Daxx antibody) could be detected from the lytic supernatant of C33A cells transfected with pcDNA3.1(+)/HPV16 E6 or pcDNA3.1(+)/Daxx. Anti-E6 antibody could detect a complex precipitated out by anti-Daxx antibody or anti-E6 antibody. Similarly, anti-Daxx antibody could detect a complex precipitated out through anti-Daxx antibody or anti-E6 antibody (Fig. 1A).
Interaction of HPV16 E6 and Daxx in C33A cells. A Binding of HPV16 E6 and Daxx assessed using western blotting. Photo shows representative blots for: (a) the cell lytic supernatant with anti-Daxx antibody (positive control for Daxx) (b) the complex of Daxx pulled down by the anti-Daxx antibody with anti-Daxx antibody (c) the complex of Daxx pulled down by the anti-E6 antibody with anti-Daxx antibody (d) the complex pulled down by the IgG antibody with anti-Daxx antibody (negative control of Daxx) (e) the cell lytic supernatant with anti-E6 antibody (positive control of HPV16 E6) (f) the complex pulled down by the anti-Daxx antibody with anti-E6 antibody (g) the complex pulled down by the anti-E6 antibody with anti-E6 antibody (h) the complex pulled down by the IgG antibody with anti-E6 antibody (negative control of HPV16 E6). B Localization of HPV16 E6 and Daxx via indirect immunofluorescence. (a) C33A cells with mouse anti-E6 antibodies visualized with TRITC-conjugated goat anti-mouse IgG (red) (b) C33A cells with rabbit anti-Daxx antibodies visualized with FITC -conjugated goat anti-rabbit IgG (green) (c) C33A cells with DNA dye (blue) (d) a and c overlapped (e) b and c overlapped (f) a and b overlapped, showing yellow fluorescence (h) a, b and c overlapped
Blue fluorescence was assigned to the nucleus. The red fluorescence of HPV16 E6 was distributed in the nucleus and cytoplasm. The green fluorescence of Daxx was mainly in the nucleus. However, in the cells expressing HPV16 E6, the green fluorescence was distributed in the nucleus and cytoplasm too. Superimposition of the images revealed the yellow fluorescence (Fig. 1B).
Effects of HPV16 E6 on Daxx expression
As shown in Fig. 2A, there was not much statistical difference in the relative quantification for Daxx RNA between the Negative and Blank groups (p > 0.05), but there was a significant difference between the Daxx and Negative groups, as expected (p < 0.01). There was not much statistical difference between the E6 and Negative groups (p > 0.05). However, there was a clear decrease from the single Daxx transfection to the co-transfection group, and the differences between the Daxx+E6 and Daxx groups was statistically significant (p < 0.05). This suggests that HPV16 E6 may have some influence on the function of Daxx.
Effects of HPV16 E6 on Daxx expression. A Relative quantification of Daxx RNA via quantitative PCR. Relative quantification of Daxx was evaluated using the double delta Ct (ΔΔCt) method. ★ , p < 0.05. B Daxx protein expression evaluated via western blotting. (a) C33A cells without transfection (b) C33A cells with empty vector transfection (c) C33A cells with Daxx transfection (d) C33A cells with E6 and Daxx co-transfection (e) C33A cells with E6 transfection. C Integrated density values based on western blotting results. IntDen TP/IR describes the ratio of the integrated density of the internal reference to that of the target protein (IntDen IR/TP). ★ ★ , p < 0.01
As shown in Fig. 2B and C, the differences in protein expression of Daxx between the Negative and Blank groups (p > 0.05) and the Daxx and Negative groups (p < 0.01) were similar to those for the relative quantification of Daxx RNA, showing that pCDNA3.1(+)/Daxx was successfully transfected into C33A cells.
Effects of HPV16 E6 on the proliferation of C33A cells
As shown from the cell count results (Fig. 3a), the differences in total cell number, dead cell number or viable cell number between the Daxx-transfected group and the negative control were statistically significant (p < 0.05). However, the differences between the HPV16 E6-transfected group and negative group were not statistically significant (p > 0.05). Moreover, the difference in viable cell number for the Daxx-transfected group was clearly lower than that for the HPV16 E6 and Daxx co-transfected group (p < 0.05).
Effects of HPV16 E6 on cell proliferation. a Cell count results for all groups. The cell counting unit was 10 6 , i.e., E+ 06. b Proliferation inhibition ratios for all groups. The proliferation inhibition (PI) ratio represents the inhibition of cell proliferation. ★ , p < 0.05 ★ ★ , p < 0.01
The MTT tests (Fig. 3b) showed that the cell proliferation in the Daxx-transfected group was clearly lower than that in the negative control group (p < 0.01). The PI ratio for the Daxx-transfected group was higher than that for the other groups and these differences were also statistically significant (p < 0.01). The difference between the HPV16 E6-transfected and negative groups was not statistically significant (p > 0.05). Importantly, the difference between the Daxx-transfected group and HPV16 E6 and Daxx co-transfected group was also not statistically significant (p > 0.05), indicating that HPV16 E6 may be not enough to inhibit the negative regulation of Daxx on cell proliferation.
Effects of HPV16 E6 on the apoptosis of C33A cells
The apoptotic cells were observed intuitively under a fluorescence microscope (Fig. 4A). It was clear that the groups with Daxx transfection had more apoptotic cells than the other groups. The characteristic morphological changes of apoptosis were observed in cells that had undergone Daxx treatment.
Effect of HPV16 E6 on apoptosis of C33A cells. A Observation of representative apoptotic cells. The groups with Daxx transfection had more apoptotic cells than the other groups. (a) C33A cells without transfection (b) C33A cells with empty vector transfection (c) C33A cells with Daxx transfection (d) C33A cells with E6 and Daxx co-transfection (e) C33A cells with E6 transfection. B Representative flow cytometry data. (a) C33A cells without transfection (b) C33A cells with empty vector transfection (c) C33A cells with Daxx transfection (d) C33A cells with E6 and Daxx co-transfection (e) C33A cells with E6 transfection. C Apoptosis rate. The mean apoptosis rate of each group came from the flow cytometry data. ★ ★ , p < 0.01
As expected, the results of the FCM tests (Fig. 4B and C) showed that there was not much difference between the groups with empty plasmid transfection and non-transfection statistically (p > 0.05). Similarly, the difference between the HPV16 E6-transfected group and the empty plasmid-transfected group was not statistically significant (p > 0.05), indicating that HPV16 E6 had little effect on the apoptosis of C33A cells. There was considerable difference between the groups with Daxx transfection and with empty plasmid transfection (p < 0.01), showing that Daxx transfection caused more apoptosis. However, it was found that there was a significant difference between the Daxx and HPV16 E6 co-transfected group and the Daxx-transfected group (p < 0.01).
Summing up, there was no obvious decrease or increase in apoptosis of C33A cells after HPV16 E6 transfection (p > 0.05). It was also evident that the apoptosis of C33A cells with Daxx and E6 co-transfection was low compared with that of cells with Daxx transfection alone. It is thus unknown whether HPV16 E6 can inhibit or promote cell apoptosis, but it can clearly affect the apoptosis caused by Daxx. This may be related to the interaction of HPV16 E6 and Daxx.
Impact of HPV16 E6 on caspase-8 activity in C33A cells
As shown in Fig. 5, the caspase-8 activity of the Daxx-transfected group was higher than that of the empty plasmid-transfected group, and this difference had statistical significance (p < 0.01). However, there was no difference between the HPV16 E6-transfected group and the negative control group (p > 0.05). Moreover, the caspase-8 activity of the co-transfected group was statistically significantly higher than that of the HPV16 E6-transfected group (p < 0.01). However, the differences between the Daxx-transfected group and co-transfected group were not statistically significant (p > 0.05).
Effects of HPV16 E6 on caspase-8 activity. The A405 value represents the relative activity of caspase-8. ★ ★ , p < 0.01
E6(R2) Good Clinical Practice: Integrated Addendum to ICH E6(R1) March 2018
Good Clinical Practice (GCP) is an international ethical and scientific quality standard for designing, conducting, recording and reporting trials that involve the participation of human subjects. Compliance with this standard provides public assurance that the rights, safety, and well-being of trial subjects are protected, consistent with the principles that have their origin in the Declaration of Helsinki, and that the clinical trial data are credible.
The objective of this ICH GCP guidance is to provide a unified standard for the European Union, Japan, and the United States to facilitate the mutual acceptance of clinical data by the regulatory authorities in these jurisdictions.
Eight adult patients (7 males and 1 female) ranging in age from 51 to 72 years were included in this study. The anatomical locations of their biopsy-proven squamous cell carcinomas included palatine tonsil in five and tongue base in three.
Data collection protocols
Data collection and molecular analyses were performed in accordance with the guidelines of the University of Texas McGovern Medical School Committee for the Protection of Human Subjects Institutional Review Board (IRB).
Molecular analyses included in-situ hybridization for the expression of HPV-HR18 E6/E7 mRNA using the RNAscope® technology from Advanced Cell Diagnostics (https://acdbio.com/). Morphoproteomic analysis and biomedical analytics were also performed as part of the molecular analysis in our CLIA and CAP certified Consultative Proteomics Laboratory in order to define the biology of the patients’ tumors, to provide correlative expressions, and to ascertain targeted therapeutic options designed to reduce the progression or recurrence of the HPV-associated oropharyngeal carcinomas.
RNAscope® 2.5HD Red Assay was performed to evaluate expression in all 8 tissue specimens. The test assayed 18 high-risk HPV serotypes: HPV-HR18 HPV 16, 18, 26, 31, 33, 35, 39, 45, 51, 52, 53, 56, 58, 59, 66, 68, 73 and 82, E6/E7 mRNA. Hs-PPIB was used as a positive control marker for sample quality control (QC) and to evaluate RNA quality in all the tissue samples. Bacterial gene dapB was used as a negative control. Standard pretreatment assay conditions were determined to be optimal for the samples in the study set. All the samples in the study passed QC with strong PPIB expression and no/negligible dapB background. A semi-quantitative scoring system of 0-4 was utilized.
Morphoproteomic analysis applies bright field microscopy and immunohistochemistry directed against various protein analytes to define the biology of a neoplastic process. The analysis uncovers etiopathogenetic occurrences that might be responsible for the process development and the propensity for it to recur [5, 6]. Immunohistochemical probes were applied against the following protein analytes in unstained sections of the patients’ oropharyngeal carcinomas: Ki-67 (G1, S, G2 and M phases of the cell cycle DakoCytomation, Carpinteria, California, lot #20001030) and enhancer of zeste homolog 2 (EZH2 Cell Signaling Technology, Inc., lot #7). The level of expression of the analytes was graded on a 0 to 3+ scale based on signal intensity indicated by a 3,3′- tetrahydrochloride (DAB) chromogenic (brown) signal, the nuclear estimation of Ki-67 and EZH2 percentages, and mitotic index based on mitotic figures/10 high power fields. The details of the morphoproteomic staining procedure have been previously described [5, 6].
To gain insights into HPV-associated oropharyngeal carcinoma, a standard IPA oropharyngeal pathway network (“ORO”) was constructed from key molecules associated with oropharyngeal carcinoma in the Ingenuity Knowledge Base (www.ingenuity.com). Since IPA does not include viral species, E6/E7 and their interactions associated with HPV (hsa05203) (“HPV” network) were extracted from the KEGG pathway database (http://www.genome.jp/kegg/pathway.html) and manually added to the ORO network. A “patient” pathway network was also constructed from the median patient scores and linked to ORO-HPV. From these graphs and additional data mining of the National Library of Medicine’s MEDLINE database, a single ORO-HPV network model was constructed using IPA Pathway Designer to represent the key modulation and adaptive responses in the signal transduction processes. Therapies were then linked to the ORO-HPV network model to assess potential benefits.
The IHC workup had established the expression of p16INK4a protein in all cases (Fig. 1, Table 1).
Patient 8 biopsy specimen with non-keratinizing oropharyngeal carcinoma compared with concurrent non-neoplastic mucosa. H&E and p16INK4a stained sections of non-keratininzing squamous cell carcinoma versus non-neoplastic squamous epithelium (Frames a and c and b and d, respectively note strong DAB brown chromogenic signal for p16INK4a in oropharyngeal carcinoma [Frame c] versus absence of expression in non-neoplastic squamous mucosa [Frame d] original magnification ×200 Frames a-d)
HPV-HR18 E6/E7 was detected at high levels across most samples (score 4) with the exception of patient specimens 5 and 6 that scored at 2 and 3, respectively (see Table 2 and Fig. 2).
Patient 8 biopsy specimen with non-keratinizing oropharyngeal carcinoma compared with adjacent non-neoplastic mucosa. Red RNAscope® 2.5 HD in-situ hybridization (ISH) assay for HPV-HR18 E6/E7 mRNA performed on the non-keratinizing squamous cell carcinoma revealed strong red chromogenic cytoplasmic expression (4+ semi-quantitative score, see Table 2) in the tumor (lower right and middle, Frame a) and no expression in the adjacent non-neoplastic (upper left, Frame a). Contrast with the dapβ negative control in Frame b. (original magnification ×200 for Frames a and b)
Nuclear expressions of EZH2 (enhancer of zeste homolog 2) and Ki-67 (G1, S, G2 and M phases of the cell cycle) and mitotic indices (mitotic figures/10 high power fields) by visual estimation on each case revealed a median of 90% and 70% for EZH2 and Ki-67, respectively and a range of 16 to 105 for the mitotic indices (Table 1 and Fig. 3, frames a and b, c and d, and e and f, respectively for EZH2, Ki-67 expression, and mitotic progression).
Patient 8 biopsy specimen with non-keratinizing oropharyngeal carcinoma compared with concurrent non-neoplastic mucosa. Enhancer of zeste homolog 2 (EZH2) and Ki-67 (G1, S, G2 and M phases of the cell cycle) show strong (3+ on a scale of 0-3+) nuclear expression in a majority of the non-keratinizing squamous cell carcinoma (NKSCC) versus similar expression primarily limited to the basal and suprabasal cells of the non-neoplastic squamous mucosa (Frames a and c versus b and d, respectively). Mitotic progression in the corresponding H&E coincides with the EZH2 and Ki-67 expression with multiple mitotic figures evident in the NKSCC (Frame e) with no mitotic figures in the adjacent non-neoplastic squamous mucosa (Frame f). (DAB brown chromogenic signal for frames a-d original magnifications ×200 for frames a-d and ×400 for Frames e and f)
In order to provide a visual comparison, biomedical analytics generated a normalized score by patient of the comparative analytes for Ki67, mitotic index, p16INK4a, EZH2 and E6/E7 mRNA. This is illustrated in the bar chart (Fig. 4).
Bar chart of normalized (median) score by patient of the comparative analytes for Ki67, mitotic index, p16INK4a,EZH2 and E6/E7 mRNA. Comparison of normalized scores. Note that patient #5 has the lowest E6/E7 score (assessed as moderate, 2+), and also the lowest mitotic index (see Tables 1 and 2)
ORO-HPV network model
There were extensive crossover interactions between the HPV pathway and the ORO pathway. Three molecules of interest - EZH2, MKI67 (Ki67) and CDKN2A (p16 INK4a) were present – and affected – in the combined pathway network (not shown.) This combined ORO-HPV network model contained 1086 molecular interactions, or links, in the 3 linked pathways of ORO, HPV, and median patient. Of the 1086 links, 513 bridged between the ORO network and the HPV network. For the patient, the level of CDKN2A affected more molecules associated with HPV than with ORO. In return, more molecules from HPV than ORO affected the patient network, with TP53 and RB1 being the major influencers. 174 molecules from ORO affected HPV and patients whereas 224 molecules from HPV affected ORO and patient.
The complex ORO-HPV network model was edited to focus on the key molecules: E6/E7 mRNA, EZH2, Ki-67 (MK167) plus related interactions from the National Library of Medicine’s MEDLINE Database. The potential efficacy of sulforaphane and the metformin and curcumin therapies – the latter in part through the upregulation of microRNAs – were graphically demonstrated (Fig. 5). EZH2 was identified as a possible therapeutic target. It can be seen from the networks that EZH2 (Fig. 5, upper left) is a key network point that is activated by E6/E7. Mir-26A can be seen in the upper right hand corner of Fig. 5 it needs to be upregulated to decrease EZH2.
Potential therapies for ORO-HPV combined pathway. Celecoxib, curcumin, metformin, sulforaphane (right, yellow). Scored molecules: CDKN2A, EZH2, MKI67 (left, light orange). E6, E7 (lower right, blue, viral †). microRNAs: miR-26a, MIR101, miR-101 (top, pink)
Create an external reference between cells in different workbooks
Open the workbook that will contain the external reference (the destination workbook, also called the formula workbook) and the workbook that contains the data that you want to link to (the source workbook, also called the data workbook).
In the source workbook, select the cell or cells you want to link.
Press Ctrl+C or go to Home > Clipboard > Copy.
Switch to the destination workbook, and then click the worksheet where you want the linked data to be placed.
Select the cell where you want to place the linked data, then go to Home > Clipboard > Paste > Paste Link.
Excel will return the data you copied from the source workbook. If you change it, it will automatically change in the destination workbook when you refresh your browser window.
To use the link in a formula, type = in front of the link, choose a function, type (, and then type ) after the link.
Human Papillomavirus Type 16 Variant Analysis of E6, E7, and L1 Genes and Long Control Region in Biopsy Samples from Cervical Cancer Patients in North IndiaFIG. 1 . Sequencing electropherogram showing frequently detected nucleotide variations in different genomic segments of HPV-16. (a) E6 T350G (b) E7 T789C (c) L1 A6695C and (d) LCR G7521A. The upper panel shows prototype sequences, while the lower panel shows variant sequences (indicated by arrows). FIG. 2 . Nucleotide sequence variations among the HPV-16 isolates. The nucleotide positions of E6, E7, the LCR, and L1 at which variations were observed are written across the top. The identification codes of the samples are indicated on the left. REF, the HPV-16 reference DNA sequence. For each variant sequence, positions that do not vary from those of the HPV reference sequence are marked with dashes.
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