Sep 2021, Volume 9 Issue 3

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  • The year 2021 is the 20th anniversary of the publication of the draft human genome. The sequencing of the human genome has brought life sciences into a new era, the era to understand the information systems of life in a quantitative manner. Quantitative Biology publishes a series of featured articles to celebrate the anniversary.

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    Wei Dong, Boqing Qiang, Huanming Yang
    Runsheng Chen

    This article records the author’s experience in participating in the early human genome and bioinformatics research in China, especially the non-coding sequence of the genome. It also introduced the beginning of human genome research in china, including the experts and teams involved in the International Human Genome Project. All the progress of bioinformatics originates from the inheritance of theoretical biology and the layout of philosophers in china.

    Andrew F. Neuwald
    Taoyu Chen, Qi Lei, Minglei Shi, Tingting Li

    Background: The concept of biomolecular condensate was put forward recently to emphasize the ability of certain cellular compartments to concentrate molecules and comprise proteins and nucleic acids with specific biological functions, from ribosome genesis to RNA splicing. Due to their unique role in biological processes, it is crucial to investigate their compositions, which is a primary determinant of condensate properties.

    Results: Since a wide range of macromolecules comprise biomolecular condensates, it is necessary for researchers to investigate them using high-throughput methodologies while low-throughput experiments are not efficient enough. These high-throughput methods usually purify interacting protein libraries from condensates before being scanned in mass spectrometry. It is possible to extract organelles as a whole for specific condensates for further analysis, however, most condensates do not have a distinguishable marker or are sensitive to shear force to be extracted as a whole. Affinity tagging allows a comprehensive view of interacting proteins of target molecule yet only proteins with strong bonds may be pulled down. Proximity labeling serves as a complementary method to label more dynamic proteins with weaker interactions, increasing sensitivity while decreasing specificity. Image-based fluorescent screening takes another path by scanning images automatically to illustrate the condensing state of biomolecules within membraneless organelles, which is a unique feature unlike the previous mass spectrometry-based methods.

    Conclusion: This review presents a rough glimpse into high-throughput methodologies for biomolecular condensate investigation to encourage usage of bioinformatic tools by researchers in relevant fields.

    Tianying Chen, Xue Zhang, Qiong Wu

    Background: The core concept of cell engineering is the use of synthetic biological methods to engineer and design genetically modified cells with specific functions, which has revolutionized the biotechnology industry and cell therapy. Implanted cells play an important role in the cell therapy, but the currently used implanted cells are unable to fully meet the needs of researchers and clinicians. Therefore, the construction of engineered implanted cells has become a new research area, with many groups exploring the working principles of implanted cells, allowing them to better exert their repair function.

    Results: Based on the existing cell engineering platforms, this paper summarizes the main types of chassis cells used in implanted cell engineering, progress in the development of gene editing tools and delivery systems, as well as strategies for the construction of engineered implanted cells.

    Conclusions: The rational use of synthetic biology methods to program and control the function of implanted cells with high spatiotemporal accuracy provides new ideas for the development of cell therapy, and opens up new possibilities for exploring the mechanism of implanted cell action to allow them to better exert their role in promoting the progress of repair.

    Lei Zhang, Ji Lv, Ming Xiao, Li Yang, Le Zhang

    Background: A traditional Chinese medicine formula, Youdujing (YDJ) ointment, is widely used for treatment of human papilloma virus-related diseases, such as cervical cancer. However, the underlying mechanisms by which active compounds of YDJ alleviates cervical cancer are still unclear.

    Methods: We applied a comprehensive network pharmacology approach to explore the key mechanisms of YDJ by integrating potential target identification, network analysis, and enrichment analysis into classical molecular docking procedures. First, we used network and enrichment analyses to identify potential therapeutic targets. Second, we performed molecular docking to investigate the potential active compounds of YDJ. Finally, we carried out a network-based analysis to unravel potentially effective drug combinations.

    Results: Network analysis yielded four potential therapeutic targets: ESR1, NFKB1, TNF, and AKT1. Molecular docking highlighted that these proteins may interact with four potential active compounds of YDJ: E4, Y2, Y20, and Y21. Finally, we found that Y2 or Y21 can act alone or together with E4 to trigger apoptotic cascades via the mitochondrial apoptotic pathway and estrogen receptors.

    Conclusion: Our study not only explained why YDJ is effective for cervical cancer treatment, but also lays a strong foundation for future clinical studies based on this traditional medicine.

    Shilei Zhao, Tong Sha, Chung-I Wu, Yongbiao Xue, Hua Chen

    Background: The availability of vaccines provides a promising solution to contain the COVID-19 pandemic. However, it remains unclear whether the large-scale vaccination can succeed in containing the COVID-19 pandemic and how soon. We developed an epidemiological model named SUVQC (Suceptible-Unquarantined-Vaccined-Quarantined-Confirmed) to quantitatively analyze and predict the epidemic dynamics of COVID-19 under vaccination.

    Methods: In addition to the impact of non-pharmaceutical interventions (NPIs), our model explicitly parameterizes key factors related to vaccination, including the duration of immunity, vaccine efficacy, and daily vaccination rate etc. The model was applied to the daily reported numbers of confirmed cases of Israel and the USA to explore and predict trends under vaccination based on their current epidemic statuses and intervention measures. We further provided a formula for designing a practical vaccination strategy, which simultaneously considers the effects of the basic reproductive number of COVID-19, intensity of NPIs, duration of immunological memory after vaccination, vaccine efficacy and daily vaccination rate.

    Results: In Israel, 53.83% of the population is fully vaccinated, and under the current NPI intensity and vaccination scheme, the pandemic is predicted to end between May 14, 2021, and May 16, 2021, assuming immunity persists for 180 days to 365 days. If NPIs are not implemented after March 24, 2021, the pandemic will end later, between July 4, 2021, and August 26, 2021. For the USA, if we assume the current vaccination rate (0.268% per day) and intensity of NPIs, the pandemic will end between January 20, 2022, and October 19, 2024, assuming immunity persists for 180 days to 365 days. However, assuming immunity persists for 180 days and no NPIs are implemented, the pandemic will not end and instead reach an equilibrium state, with a proportion of the population remaining actively infected.

    Conclusions: Overall, the daily vaccination rate should be decided according to vaccine efficacy and immunity duration to achieve herd immunity. In some situations, vaccination alone cannot stop the pandemic, and NPIs are necessary to supplement vaccination and accelerate the end of the pandemic. Considering that vaccine efficacy and duration of immunity may be reduced for new mutant strains, it is necessary to remain cautiously optimistic about the prospect of ending the pandemic under vaccination.

    Rudra Banerjee, Srijit Bhattacharjee, Pritish Kumar Varadwaj

    Background: The coronavirus pandemic (COVID-19) is causing a havoc globally, exacerbated by the newly discovered SARS-CoV-2 virus. Due to its high population density, India is one of the most badly effected countries from the first wave of COVID-19. Therefore, it is extremely necessary to accurately predict the state-wise and overall dynamics of COVID-19 to get the effective and efficient organization of resources across India.

    Methods: In this study, the dynamics of COVID-19 in India and several of its selected states with different demographic structures were analyzed using the SEIRD epidemiological model. The basic reproductive ratio R 0 was systemically estimated to predict the dynamics of the temporal progression of COVID-19 in India and eight of its states, Andhra Pradesh, Chhattisgarh, Delhi, Gujarat, Madhya Pradesh, Maharashtra, Tamil Nadu, and Uttar Pradesh.

    Results: For India, the SEIRD model calculations show that the peak of infection is expected to appear around the middle of October, 2020. Furthermore, we compared the model scenario to a Gaussian fit of the daily infected cases and obtained similar results. The early imposition of a nation-wide lockdown has reduced the number of infected cases but delayed the appearance of the infection peak significantly.

    Conclusion: After comparing our calculations using India’s data to the real life dynamics observed in Italy and Russia, we can conclude that the SEIRD model can predict the dynamics of COVID-19 with sufficient accuracy.

    Zongwei Guo, Fangkui Yin, Peiran Wang, Ting Song, Zhichao Zhang

    Background: Inhibitors of B-cell CLL/lymphoma 2 (Bcl-2) family proteins have shown hope as antitumor drugs. While the notion that it is efficient to coordinate, balance, and neutralize both arms of the anti-apoptotic Bcl-2 family has been validated in many cancer cells, the weights of the two arms contributing to apoptosis inhibition have not been explored. This study analyzed the best combination ratio for different Bcl-2 selective inhibitors.

    Methods: We used a previously established mathematical model to study the weights of Bcl-2 (representing both Bcl-2 and Bcl-xL in this study) and myeloid cell leukemia-1 (Mcl-1). Correlation and single-parameter sensitivity analysis were used to find the major molecular determinants for Bcl-2 and Mcl-1 dependency, as well as their weights. Biological experiments were used to verify the mathematical model.

    Results: Bcl-2 protein level and Mcl-1 protein level, production, and degradation rates were the major molecular determinants for Bcl-2 and Mcl-1 dependency. The model gained agreement with the experimental assays for ABT-737/A-1210477 and ABT-737/compound 5 combination effect in MCF-7 and MDA-MB-231. Two sets of equations composed of Bcl-2 and Mcl-1 levels were obtained to predict the best combination ratio for Bcl-2 inhibitors with Mcl-1 inhibitors that stabilize and downregulate Mcl-1, respectively.

    Conclusions: The two sets of equations can be used as tools to bypass time-consuming and laborious experimental screening to predict the best drug combination ratio for treatment.

    Eric Durandau, Serge Pelet

    Background: Commitment to a new cell cycle is controlled by a number of cellular signals. Mitogen-activated protein kinase (MAPK) pathways, which transduce multiple extracellular cues, have been shown to be interconnected with the cell cycle and can modulate its progression.

    Methods: In budding yeast, we have introduced fluorescent biosensors that monitor in real time the signaling activity of the MAPKs Fus3 and Kss1 and the cyclin-dependent kinase (CDK) in individual cells. We have quantified in hundreds of live single cells the interplay between the MAPKs regulating the mating response and the CDK controlling cell cycle progression.

    Results: Different patterns of MAPK activity dynamics could be identified by clustering cells based on their CDK activity, denoting the tight relationship between these two cellular signals. Our data suggest that beyond the already well-established mechanisms of regulation between the MAPK and the CDK, additional mechanisms remain to be identified.

    Conclusion: A tight interplay between MAPK pathways and the cell cycle is essential to control cellular proliferation and cell fate decisions.