Exploring the immune-inflammatory mechanism of Maxing Shigan Decoction in treating influenza virus A-induced pneumonia based on an integrated strategy of single-cell transcriptomics and systems biology.

BACKGROUND: Influenza is an acute respiratory infection caused by influenza virus. Maxing Shigan Decoction (MXSGD) is a commonly used traditional Chinese medicine prescription for the prevention and treatment of influenza. However, its mechanism remains unclear. METHOD: The mice model of influenza A virus pneumonia was established by nasal inoculation. After 3 days of intervention, the lung index was calculated, and the pathological changes of lung tissue were detected by HE staining. Firstly, transcriptomics technology was used to analyze the differential genes and important pathways in mouse lung tissue regulated by MXSGD. Then, real-time fluorescent quantitative PCR (RT-PCR) was used to verify the changes in mRNA expression in lung tissues. Finally, intestinal microbiome and intestinal metabolomics were performed to explore the effect of MXSGD on gut microbiota. RESULTS: The lung inflammatory cell infiltration in the MXSGD group was significantly reduced (p < 0.05). The results of bioinformatics analysis for transcriptomics results show that these genes are mainly involved in inflammatory factors and inflammation-related signal pathways mediated inflammation biological modules, etc. Intestinal microbiome showed that the intestinal flora Actinobacteriota level and Desulfobacterota level increased in MXSGD group, while Planctomycetota in MXSGD group decreased. Metabolites were mainly involved in primary bile acid biosynthesis, thiamine metabolism, etc. This suggests that MXSGD has a microbial-gut-lung axis regulation effect on mice with influenza A virus pneumonia. CONCLUSION: MXSGD may play an anti-inflammatory and immunoregulatory role by regulating intestinal microbiome and intestinal metabolic small molecules, and ultimately play a role in the treatment of influenza A virus pneumonia.

Mechanisms Involved in Therapeutic Effects of Scutellaria baicalensis Georgi in Oral Squamous Cell Carcinoma Based on Systems Biology and Structural Bioinformatics Approaches.

Objective: Oral squamous cell carcinoma (OSCC) is the most frequent oral cancer, constituting more than 90% of all oral carcinomas. The 5-year survival rate of OSCC patients is not satisfactory, and therefore, there is an urgent need for new practical therapeutic approaches besides the current therapies to overcome OSCC. Scutellaria baicalensis Georgi (SBG) is a plant of the family Lamiaceae with several pharmaceutical properties such as antioxidant, anti-inflammatory, and anticancer effects. Previous studies have demonstrated the curative effects of SBG in OSCC. Methods: A systems biology approach was conducted to identify differentially expressed miRNAs (DEMs) in OSCC patients with a dismal prognosis compared to OSCC patients with a favorable prognosis. A protein interaction map (PIM) was built based on DEMs targets, and the hub genes within the PIM were indicated. Subsequently, the prognostic role of the hubs was studied using Kaplan-Meier curves. Next, the binding affinity of SBG's main components, including baicalein, wogonin, oroxylin-A, salvigenin, and norwogonin, to the prognostic markers in OSCC was evaluated using molecular docking analysis. Results: Survival analysis showed that overexpression of CAV1, SERPINE1, ACTB, SMAD3, HMGA2, MYC, EIF2S1, HSPA4, HSPA5, and IL6 was significantly related to a poor prognosis in OSCC. Besides, molecular docking analysis demonstrated the ΔGbinding and inhibition constant values between SBG's main components and SERPINE1, ACTB, HMGA2, EIF2S1, HSPA4, and HSPA5 were as <-8.00 kcal/mol and nanomolar concentration, respectively. The most salient binding affinity was observed between wogonin and SERPINE1 with a criterion of ΔGbinding < -10.02 kcal/mol. Conclusion: The present results unraveled potential mechanisms involved in therapeutic effects of SBG in OSCC based on systems biology and structural bioinformatics analyses.

Veterinary systems biology for bridging the phenotype-genotype gap via computational modeling for disease epidemiology and animal welfare.

Veterinary systems biology is an innovative approach that integrates biological data at the molecular and cellular levels, allowing for a more extensive understanding of the interactions and functions of complex biological systems in livestock and veterinary science. It has tremendous potential to integrate multi-omics data with the support of vetinformatics resources for bridging the phenotype-genotype gap via computational modeling. To understand the dynamic behaviors of complex systems, computational models are frequently used. It facilitates a comprehensive understanding of how a host system defends itself against a pathogen attack or operates when the pathogen compromises the host's immune system. In this context, various approaches, such as systems immunology, network pharmacology, vaccinology and immunoinformatics, can be employed to effectively investigate vaccines and drugs. By utilizing this approach, we can ensure the health of livestock. This is beneficial not only for animal welfare but also for human health and environmental well-being. Therefore, the current review offers a detailed summary of systems biology advancements utilized in veterinary sciences, demonstrating the potential of the holistic approach in disease epidemiology, animal welfare and productivity.

Sistemas Computacionais para Auxílio na Cicatrização de Feridas: Revisão de Escopo / Computer Systems to Aid in Wound Healing: Scope Review / Sistemas Informáticos para Ayudar en la Cicatrización de Heridas: Revisión del Alcance

Objetivo:Investigar estudos que apresentem sistemas computacionais de auxílio à cicatrização de feridas e quais sistemas se referem ao uso de laser de baixa intensidade. Método: Revisão de escopo que visou responder à questão de pesquisa: Quais sistemas computacionais auxiliam na cicatrização de feridas? Uma subquestão foi: quais sistemas computacionais se referem ao uso do laser de baixa intensidade? Resultados: A partir da busca, aplicando os critérios de elegibilidade, 49 artigos compuseram a amostra final. Os sistemas apresentaram várias finalidades de apoio à cicatrização de feridas, em que a maioria apresentou como usuário do sistema o profissional de saúde, sendo a medicina a área profissional mais mencionada, embora a enfermagem esteja envolvida com o manejo do cuidado às pessoas com feridas. Foi relatada com frequência a inovação na assistência a partir do uso do sistema computacional, o que demonstra a importância desse tipo de ferramenta para a prática clínica. Verificou-se com frequência o uso de plataforma mobile, como tendência da atualidade. Conclusão: Os sistemas computacionais têm sido utilizados como ferramentas para apoiar pacientes e principalmente profissionais na cicatrização de feridas. Quanto ao laser de baixa intensidade, houve escassez de sistemas computacionais com essa finalidade, com apenas um estudo.

Objective:To investigate studies that present computational systems to aid healing and systems which refer to the use of low-level laser. Method: Scope review that aimed to answer the question: Which computer systems help in wound healing? A subquestion was: Which of the computer systems refer to the use of low-level laser? Results: From the search, applying the eligibility criteria, 49 articles made up the final sample. The systems served multiple purposes in support of wound healing; the majority presented the health professional as a user of the system; medicine was the most mentioned professional area despite nursing being involved in the management of care for people with wounds. Innovation in care using the computer system was frequently reported, demonstrating the importance of this type of tool for clinical practice. There was a high frequency of the mobile platform, showing that this is a current trend. Conclusion: Computer systems have been used as tools to support patients and especially professionals in wound healing. Regarding the systems aimed at the low intensity laser, there was a shortage of computer systems for this purpose, with a study.

Objetivo:Investigar estudios que presenten sistemas computacionales de ayuda a la cicatrización y sistemas que se refieran al uso de láser de bajo nivel. Método: Revisión de alcance que tuvo como objetivo responder a la pregunta: ¿Qué sistemas informáticos ayudan en la cicatrización de heridas? Una subpregunta fue: ¿Cuál de los sistemas informáticos se refieren al uso de láser de bajo nivel? Resultados: A partir de la búsqueda, aplicando los criterios de elegibilidad, 49 artículos conformaron la muestra final. Los sistemas sirvieron para múltiples propósitos en apoyo de la cicatrización de heridas; la mayoría presentó al profesional de la salud como usuario del sistema; la medicina fue el área profesional más mencionadas, a pesar de que la enfermería está involucrada en la gestión del cuidado de las personas con heridas. La innovación en la atención basada en el uso del sistema informático fue relatada con frecuencia, demostrando la importancia de este tipo de herramienta para la práctica clínica. Hubo una alta frecuencia de la plataforma móvil, lo que demuestra que esta es una tendencia actual. Conclusión: Los sistemas informáticos se han utilizado como herramientas de apoyo a los pacientes y especialmente a los profesionales en la cicatrización de heridas. En cuanto a los sistemas dirigidos al láser de baja intensidad, hubo escasez de sistemas informáticos para este fin, con un estudio.

Mechanisms of action underlying Shentong Zhuyu decoction based treatment of rheumatoid arthritis using systems biology and computer-aided drug design.

Rheumatoid arthritis is an autoimmune disease characterized by chronic polyarticular pain, for which no cure currently exists. In Chinese medicine, rheumatoid arthritis (RA) is believed to be caused by phlegm and blood stagnation. Shentong Zhuyu decoction can be used to treat RA, as it promotes blood circulation, resolves blood stasis, and relieves pain. In our study, we used network pharmacology and computer-aided drug design to evaluate the components, active compounds, and targets of Shentong Zhuyu decoction (STZY). Our results suggest that STZY contains active compounds such as quercetin, luteolin, and formononetin that regulate immune network targets. RA associated genes are enriched in pathways including those associated with nuclear factor kappa B, phosphatidylinositol-3-kinase/AKT, and hypoxia inducible factor 1 signaling. The main active compounds in STZY (quercetin and luteolin) were derived from Achyranthis Bidentatae Radix, Carthami Flos, licorice, Cyperi Rhizoma, and Myrrha and targeted the pro-inflammatory cytokines interleukin 2, interleukin 1 alpha, interleukin 1 beta, and interleukin 6. In addition, the compounds quercetin, luteolin, and formononetin in these herbs can target the anti-inflammatory cytokines interleukin 4 and interleukin 10. Our results suggest that STZY can balance the immune network, promote an anti-inflammatory environment, and reduce the clinical symptoms of RA. Based on the close relationship between inflammatory response and osteoclast formation, we hypothesized that STZY may inhibit inflammation and alleviate bone destruction in RA. Our findings indicate that STZY can treat RA through multiple components, targets, and pathways. This study may provide a reference for the clinical application of STZY in RA treatment.

Attenuation of Aging-Related Oxidative Stress Pathways by Phytonutrients: A Computational Systems Biology Analysis.

Aging results from gradual accumulation of damage to the cellular functions caused by biochemical processes such as oxidative stress, inflammation-driven prolonged cellular senescence state, immune system malfunction, psychological stress, and epigenetic changes due to exposure to environmental toxins. Plant-derived bioactive molecules have been shown to ameliorate the damage from oxidative stress. This research seeks to uncover the mechanisms of action of how phytochemicals from fruit/berry/vegetable (FBV) juice powder mitigate oxidative stress. The study uses a computational systems biology approach to (1) identify biomolecular pathways of oxidative stress; (2) identify phytochemicals from FBV juice powder and their specific action on oxidative stress mechanisms; and (3) quantitatively estimate the effects of FBV juice powder bioactive compounds on oxidative stress. The compounds in FBV affected two oxidative stress molecular pathways: (1) reactive oxygen species (ROS) production and (2) antioxidant enzyme production. Six bioactive compounds including cyanidin, delphinidin, ellagic acid, kaempherol, malvidin, and rutin in FBV significantly lowered production of ROS and increased the production of antioxidant enzymes such as catalase, heme oxygenase-1, superoxide dismutase, and glutathione peroxidase. FBV juice powder provides a combination of bioactive compounds that attenuate aging by affecting multiple pathways of oxidative stress.

A Q-marker screening strategy based on ADME studies and systems biology for Chinese herbal medicine, taking Qianghuo Shengshi decoction in treating rheumatoid arthritis as an example.

Chinese herbal medicine (CHM) exhibits a broad spectrum of clinical applications and demonstrates favorable therapeutic efficacy. Nonetheless, elucidating the underlying mechanism of action (MOA) of CHM in disease treatment remains a formidable task due to its inherent characteristics of multi-level, multi-linked, and multi-dimensional non-linear synergistic actions. In recent years, the concept of a Quality marker (Q-marker) proposed by Liu et al. has significantly contributed to the monitoring and evaluation of CHM products, thereby fostering the advancement of CHM research. Within this study, a Q-marker screening strategy for CHM formulas has been introduced, particularly emphasising efficacy and biological activities, integrating absorption, distribution, metabolism, and excretion (ADME) studies, systems biology, and experimental verification. As an illustrative case, the Q-marker screening of Qianghuo Shengshi decoction (QHSSD) for treating rheumatoid arthritis (RA) has been conducted. Consequently, from a pool of 159 compounds within QHSSD, five Q-markers exhibiting significant in vitro anti-inflammatory effects have been identified. These Q-markers encompass notopterol, isoliquiritin, imperatorin, cimifugin, and glycyrrhizic acid. Furthermore, by employing an integrated analysis of network pharmacology and metabolomics, several instructive insights into pharmacological mechanisms have been gleaned. This includes the identification of key targets and pathways through which QHSSD exerts its crucial roles in the treatment of RA. Notably, the inhibitory effect of QHSSD on AKT1 and MAPK3 activation has been validated through western blot analysis, underscoring its potential to mitigate RA-related inflammatory responses. In summary, this research demonstrates the proposed strategy's feasibility and provides a practical reference model for the systematic investigation of CHM formulas.

Systems biology strategy through integrating metabolomics and network pharmacology to reveal the mechanisms of Xiaopi Hewei Capsule improves functional dyspepsia.

Functional dyspepsia (FD) is one of the more common functional disorders, with a prevalence of 20-25 %. It seriously affects the quality life of patients. Xiaopi Hewei Capsule (XPHC) is a classic formula originated from the Chinese Miao minority. Clinical studies have demonstrated that XPHC can effectively alleviate the symptoms of FD, but the molecular mechanism has not been elucidated. The purpose of this work is to investigate the mechanism of XPHC on FD by integrating metabolomics and network pharmacology. The mice models of FD were established, and gastric emptying rate, small intestine propulsion rate, serum level of motilin and gastrin were evaluate to study the interventional effect of XPHC on FD. Next, a metabolomics strategy has been developed to screen differential metabolites and related metabolic pathways induced by XPHC. Then, prediction of active compounds, targets and pathways of XPHC in treating FD were carried out by commonly used network pharmacological method. Finally, two parts of the results were integrated to investigate therapeutic mechanism of XPHC on FD, which were preliminary validated based on molecular docking. Thus, twenty representative different metabolites and thirteen related pathways of XPHC in treating FD were identified. Most of these metabolites were restored using modulation after XPHC treatment. The results of the network pharmacology analysis showed ten crucial compounds and nine hub genes related to the treatment of FD with XPHC. The further integrated analysis focused on four key targets, such as albumin (ALB), epidermal growth factor receptor (EGFR), tumor necrosis factor (TNF) and roto-oncogene tyrosine-protein kinase Src (SRC), and three representative biomarkers such as citric acid, L-leucine and eicosapentaenoic acid. Furthermore, molecular docking results showed that ten bioactive compounds from XPHC have good binding interactions with the four key genes. The functional enrichment analysis indicated that the potential mechanism of XPHC in treating FD was mainly associated with energy metabolism, amino acid metabolism, lipid metabolism, inflammatory reactions and mucosal repair. Our work confirms that network pharmacology-integrated metabolomics strategyis a powerful means to reveal the therapeutic mechanisms of XPHC improves FD, which contribute its further scientific research.

[Application and development of systems biology in computer-aided drug design].

With the advances in medicine, people have deeply understood the complex pathogenesis of diseases. Revealing the mechanism of action and therapeutic effect of drugs from an overall perspective has become the top priority of drug design. However, the traditional drug design methods cannot meet the current needs. In recent years, with the rapid development of systems biology, a variety of new technologies including metabolomics, genomics, and proteomics have been used in drug research and development. As a bridge between traditional pharmaceutical theory and modern science, computer-aided drug design(CADD) can shorten the drug development cycle and improve the success rate of drug design. The application of systems biology and CADD provides a methodological basis and direction for revealing the mechanism and action of drugs from an overall perspective. This paper introduces the research and application of systems biology in CADD from different perspectives and proposes the development direction, providing reference for promoting the application.

Network pharmacology, a promising approach to reveal the pharmacology mechanism of Chinese medicine formula.

ETHNOPHARMACOLOGICAL RELEVANCE: Network pharmacology is a new discipline based on systems biology theory, biological system network analysis, and multi-target drug molecule design specific signal node selection. The mechanism of action of TCM formula has the characteristics of multiple targets and levels. The mechanism is similar to the integrity, systematization and comprehensiveness of network pharmacology, so network pharmacology is suitable for the study of the pharmacological mechanism of Chinese medicine compounds. AIM OF THE STUDY: The paper summarizes the present application status and existing problems of network pharmacology in the field of Chinese medicine formula, and formulates the research ideas, up-to-date key technology and application method and strategy of network pharmacology. Its purpose is to provide guidance and reference for using network pharmacology to reveal the modern scientific connotation of Chinese medicine. MATERIALS AND METHODS: Literatures in this review were searched in PubMed, China National Knowledge Infrastructure (CNKI), Web of Science, ScienceDirect and Google Scholar using the keywords "traditional Chinese medicine", "Chinese herb medicine" and "network pharmacology". The literature cited in this review dates from 2002 to 2022. RESULTS: Using network pharmacology methods to predict the basis and mechanism of pharmacodynamic substances of traditional Chinese medicines has become a trend. CONCLUSION: Network pharmacology is a promising approach to reveal the pharmacology mechanism of Chinese medicine formula.

Neurodegenerative disorders: From clinicopathology convergence to systems biology divergence.

Neurodegenerative diseases are multifactorial. This means that several genetic, epigenetic, and environmental factors contribute to their emergence. Therefore, for the future management of these highly prevalent diseases, it is necessary to change perspective. If a holistic viewpoint is assumed, the phenotype (the clinicopathological convergence) emerges from the perturbation of a complex system of functional interactions among proteins (systems biology divergence). The systems biology top-down approach starts with the unbiased collection of sets of data generated through one or more -omics techniques and has the aim to identify the networks and the components that participate in the generation of a phenotype (disease), often without any available a priori knowledge. The principle behind the top-down method is that the molecular components that respond similarly to experimental perturbations are somehow functionally related. This allows the study of complex and relatively poorly characterized diseases without requiring extensive knowledge of the processes under investigation. In this chapter, the use of a global approach will be applied to the comprehension of neurodegeneration, with a particular focus on the two most prevalent ones, Alzheimer's and Parkinson's diseases. The final purpose is to distinguish disease subtypes (even with similar clinical manifestations) to launch a future of precision medicine for patients with these disorders.

Mechanistic Understanding of D-Glucaric Acid to Support Liver Detoxification Essential to Muscle Health Using a Computational Systems Biology Approach.

Liver and muscle health are intimately connected. Nutritional strategies that support liver detoxification are beneficial to muscle recovery. Computational-in silico-molecular systems' biology analysis of supplementation of calcium and potassium glucarate salts and their metabolite D-glucaric acid (GA) reveals their positive effect on mitigation of liver detoxification via four specific molecular pathways: (1) ROS production, (2) deconjugation, (3) apoptosis of hepatocytes, and (4) ß-glucuronidase synthesis. GA improves liver detoxification by downregulating hepatocyte apoptosis, reducing glucuronide deconjugates levels, reducing ROS production, and inhibiting ß-Glucuronidase enzyme that reduces re-absorption of toxins in hepatocytes. Results from this in silico study provide an integrative molecular mechanistic systems explanation for the mitigation of liver toxicity by GA.

Systems biology strategy and experimental validation to uncover the pharmacological mechanism of Xihuang Pill in treating non-small cell lung cancer.

BACKGROUND: Non-small cell lung cancer (NSCLC) accounts for almost 85% of lung cancer-related deaths worldwide. Xihuang Pill (XHP) is a representative anticancer Chinese patented medicine used to treat NSCLC in China. However, to date, a systematic analysis of XHP's antitumour effects and its impact on the immune microenvironment has not been performed. PURPOSE: Based on the systems biology strategy and experimental validation, the present study aimed to investigate the pharmacological mechanisms involved in treating NSCLC with XHP. METHODS: A subcutaneous tumour model was established to evaluate XHP's tumour-inhibitory effect in BALB/c nude mice. RNA sequencing (RNA-seq) and bioinformatics analysis were conducted to identify differentially expressed genes (DEGs) and signalling pathways related to XHP treatment. Network analysis based on network pharmacology and protein-to-protein networks was applied to identify the compounds and genes targeted by XHP. External data from the TCGA-NSCLC cohort were used to verify the clinical significance of XHP-targeted genes in NSCLC. The expression of survival-related candidate genes after XHP treatment was verified via qPCR. The protein expression of calcium voltage-gated channel subunit alpha 1C (CACNA1C) in different NSCLC cell lines was analysed in the Human Protein Atlas database (HPA) and DepMap Portal. Using the Estimation of STromal and Immune cells in MAlignant Tumour tissues using Expression data (ESTIMATE) algorithm and the single-sample gene set enrichment analysis (ssGSEA) algorithm uncovered the role of CACNA1C in the NSCLC tumour microenvironment (TME). RESULTS: XHP (2 g/kg/d) significantly inhibited the growth of transplanted A549 tumours. RNA-seq identified a total of 529 DEGs (189 upregulated and 340 downregulated). In addition, 542 GO terms, 41 significant KEGG pathways, 9 upregulated hallmarks pathways, and 18 downregulated hallmark pathways were enriched. These GO terms and signalling pathways were closely related to cell proliferation, immunity, energy metabolism, and the inflammatory response of NSCLC. In addition, XHP's network pharmacology analysis identified 301 compounds and 1,432 target genes. A comprehensive strategic analysis identified CACNA1C as a promising gene by which XHP targets and regulates the TME of NSCLC, benefiting patient survival. CACNA1C expression was positively correlated with both the immune score and stromal score but negatively correlated with the tumour purity score. Additionally, CACNA1C expression was significantly correlated with the infiltration levels of 15 types of immune cells and the expression levels of 6 well-known checkpoint genes. CONCLUSIONS: Our results show that by regulating the pathways associated with cell proliferation and immunity, XHP can suppress cancer cell growth in NSCLC. Additionally, XHP may increase the expression of CACNA1C to suppress immune cell infiltration and regulate the expression of checkpoint-related genes, thereby improving the overall survival of NSCLC patients.

Review on the systems biology research of Yin-deficiency-heat syndrome in traditional Chinese medicine.

Traditional Chinese medicine (TCM) is a systematic medical method that has existed for more than 3,000 years. Unlike Western medicine, the disease diagnosis in TCM is carried out by inspection, auscultation, olfaction, interrogation, and palpation. The patient is then treated according to the disease and corresponding TCM syndrome. However, the development of Chinese medicine is stagnated, partially because it can be influenced by subjective factors, such as the experience and knowledge of TCM practitioners, and there is a lack of relevant biological research on TCM syndromes. Yin-deficiency-heat (YDH) syndrome in TCM is characterized by a series of pathological changes caused by the insufficiency of Yin-fluid, inability to moisturize, and the failure to suppress Yang. In recent years, systems biology research on TCM syndromes has gradually become the focus of TCM research, including syndrome differentiation and functional research using systems biology methodologies such as proteomics, transcriptomics, and metabolomics. This journal aims to publish a series of issues on the systems biology research of TCM syndromes that can provide biological indicators for the syndrome differentiation of YDH syndrome and can provide perspectives on the biological research of YDH syndrome.

The Yin-Yang Dynamics in Cancer Pharmacogenomics and Personalized Medicine.

The enormous heterogeneity of cancer systems has made it very challenging to overcome drug resistance and adverse reactions to achieve personalized therapies. Recent developments in systems biology, especially the perception of cancer as the complex adaptive system (CAS), may help meet the challenges by deciphering the interactions at various levels from the molecular, cellular, tissue-organ, to the whole organism. The ubiquitous Yin-Yang interactions among the coevolving components, including the genes and proteins, decide their spatiotemporal features at various stages from cancer initiation to metastasis. The Yin-Yang imbalances across different systems levels, from genetic mutations to tumor cells adaptation, have been related to the intra- and inter-tumoral heterogeneity in the micro- and macro-environments. At the molecular and cellular levels, dysfunctional Yin-Yang dynamics in the cytokine networks, mitochondrial activities, redox systems, apoptosis, and metabolism can contribute to tumor cell growth and escape of immune surveillance. Up to the organism and system levels, the Yin-Yang imbalances in the cancer microenvironments can lead to different phenotypes from breast cancer to leukemia. These factors may be considered the systems-based biomarkers and treatment targets. The features of adaptation and nonlinearity in Yin-Yang dynamical interactions should be addressed by individualized drug combinations, dosages, intensities, timing, and frequencies at different cancer stages. The comprehensive "Yin-Yang dynamics" framework would enable powerful approaches for personalized and systems medicine strategies.

A comprehensive review on genomics, systems biology and structural biology approaches for combating antimicrobial resistance in ESKAPE pathogens: computational tools and recent advancements.

In recent decades, antimicrobial resistance has been augmented as a global concern to public health owing to the global spread of multidrug-resistant strains from different ESKAPE pathogens. This alarming trend and the lack of new antibiotics with novel modes of action in the pipeline necessitate the development of non-antibiotic ways to treat illnesses caused by these isolates. In molecular biology, computational approaches have become crucial tools, particularly in one of the most challenging areas of multidrug resistance. The rapid advancements in bioinformatics have led to a plethora of computational approaches involving genomics, systems biology, and structural biology currently gaining momentum among molecular biologists since they can be useful and provide valuable information on the complex mechanisms of AMR research in ESKAPE pathogens. These computational approaches would be helpful in elucidating the AMR mechanisms, identifying important hub genes/proteins, and their promising targets together with their interactions with important drug targets, which is a crucial step in drug discovery. Therefore, the present review aims to provide holistic information on currently employed bioinformatic tools and their application in the discovery of multifunctional novel therapeutic drugs to combat the current problem of AMR in ESKAPE pathogens. The review also summarizes the recent advancement in the AMR research in ESKAPE pathogens utilizing the in silico approaches.

Attenuation of low-grade chronic inflammation by phytonutrients: A computational systems biology analysis.

BACKGROUND: Low-grade chronic inflammation (LGCI) is a strong and independent risk factor for many chronic diseases, like cardiovascular, musculoskeletal, metabolic, and neurological conditions. Dietary intervention studies have reported evidence for the role of plant-derived flavonoids in modulation of LGCI. This research explores the efficacy of Fruit/Berry/Vegetable (FBV) juice powder on LGCI. METHODS: The study employs computational systems biology: 1) to identify biomolecular mechanisms of LGCI; 2) to identify the bioactive compounds of FBV juice powder and their specific effects on mechanisms of LGCI; and, 3) to predict the quantitative effects of those bioactive compounds on LGCI. RESULTS: Four molecular pathways that are affected by the compounds of FBV include: 1) TNF-α production; 2) CCL2 production; 3) IL-1ß production; and 4) reactive oxygen species production. The bioactive compounds including luteolin, epicatechin, epigallocatechin gallate, lycopene, quercetin, vitamin A, vitamin C and vitamin E in FBV significantly lowered TNF-α production, CCL2 production, IL-1ß production, and reactive oxygen species production. CONCLUSION: FBV provides a combination of active ingredients that synergistically affect multiple modalities of low grade chronic inflammation to help improve blood circulation and energy levels, and lower muscle soreness.

Personal Dense Dynamic Data Clouds Connect Systems Biomedicine to Scientific Wellness.

The dramatic convergence of molecular biology, genomics, proteomics, metabolomics, bioinformatics, and artificial intelligence has provided a substrate for deep understanding of the biological basis of health and disease. Systems biology is a holistic, dynamic, integrative, cross-disciplinary approach to biological complexity that embraces experimentation, technology, computation, and clinical translation. Systems Medicine integrates genome analyses and longitudinal deep phenotyping with biological pathways and networks to understand mechanisms of disease, identify relevant blood biomarkers, define druggable molecular targets, and enhance the maintenance or restoration of wellness. Two programs initiated our understanding of data-driven population-based wellness. The Pioneer 100 Study of Scientific Wellness and the much larger Arivale commercial program that followed had two spectacular results: demonstrating the feasibility and utility of collecting longitudinal multiomic data, and then generating dense, dynamic data clouds for each individual to utilize actionable metrics for promoting health and preventing disease when combined with personalized coaching. Future developments in these domains will enable better population health and personal, preventive, predictive, participatory (P4) health care.

The Systems and Synthetic Biology of Auxin.

Auxin biology as a field has been at the forefront of advances in delineating the structures, dynamics, and control of plant growth networks. Advances have been enabled by combining the complementary fields of top-down, holistic systems biology and bottom-up, build-to-understand synthetic biology. Continued collaboration between these approaches will facilitate our understanding of and ability to engineer auxin's control of plant growth, development, and physiology. There is a need for the application of similar complementary approaches to improving equity and justice through analysis and redesign of the human systems in which this research is undertaken.

Systems biology and machine learning approaches identify drug targets in diabetic nephropathy.

Diabetic nephropathy (DN), the leading cause of end-stage renal disease, has become a massive global health burden. Despite considerable efforts, the underlying mechanisms have not yet been comprehensively understood. In this study, a systematic approach was utilized to identify the microRNA signature in DN and to introduce novel drug targets (DTs) in DN. Using microarray profiling followed by qPCR confirmation, 13 and 6 differentially expressed (DE) microRNAs were identified in the kidney cortex and medulla, respectively. The microRNA-target interaction networks for each anatomical compartment were constructed and central nodes were identified. Moreover, enrichment analysis was performed to identify key signaling pathways. To develop a strategy for DT prediction, the human proteome was annotated with 65 biochemical characteristics and 23 network topology parameters. Furthermore, all proteins targeted by at least one FDA-approved drug were identified. Next, mGMDH-AFS, a high-performance machine learning algorithm capable of tolerating massive imbalanced size of the classes, was developed to classify DT and non-DT proteins. The sensitivity, specificity, accuracy, and precision of the proposed method were 90%, 86%, 88%, and 89%, respectively. Moreover, it significantly outperformed the state-of-the-art (P-value ≤ 0.05) and showed very good diagnostic accuracy and high agreement between predicted and observed class labels. The cortex and medulla networks were then analyzed with this validated machine to identify potential DTs. Among the high-rank DT candidates are Egfr, Prkce, clic5, Kit, and Agtr1a which is a current well-known target in DN. In conclusion, a combination of experimental and computational approaches was exploited to provide a holistic insight into the disorder for introducing novel therapeutic targets.