Modelling and analysis of the complement system signalling pathways: roles of C3, C5a and pro-inflammatory cytokines in SARS-CoV-2 infection.

The complement system is an essential part of innate immunity. It is activated by invading pathogens causing inflammation, opsonization, and lysis via complement anaphylatoxins, complement opsonin's and membrane attack complex (MAC), respectively. However, in SARS-CoV-2 infection overactivation of complement system is causing cytokine storm leading to multiple organs damage. In this study, the René Thomas kinetic logic approach was used for the development of biological regulatory network (BRN) to model SARS-CoV-2 mediated complement system signalling pathways. Betweenness centrality analysis in cytoscape was adopted for the selection of the most biologically plausible states in state graph. Among the model results, in strongly connected components (SCCs) pro-inflammatory cytokines (PICyts) oscillatory behaviour between recurrent generation and downregulation was found as the main feature of SARS-CoV-2 infection. Diversion of trajectories from the SCCs leading toward hyper-inflammatory response was found in agreement with in vivo studies that overactive innate immunity response caused PICyts storm during SARS-CoV-2 infection. The complex of negative regulators FI, CR1 and DAF in the inhibition of complement peptide (C5a) and PICyts was found desirable to increase immune responses. In modelling role of MAC and PICyts in lowering of SARS-CoV-2 titre was found coherent with experimental studies. Intervention in upregulation of C5a and PICyts by C3 was found helpful in back-and-forth variation of signalling pattern linked with the levels of PICyts. Moreover, intervention in upregulation of PICyts by C5a was found productive in downregulation of all activating factors in the normal SCCs. However, the computational model predictions require experimental studies to be validated by exploring the activation role of C3 and C5a which could change levels of PICyts at various phases of SARS-CoV-2 infection.

Decoding the Role of Epigenetics in Breast Cancer Using Formal Modeling and Machine-Learning Methods.

Breast carcinogenesis is known to be instigated by genetic and epigenetic modifications impacting multiple cellular signaling cascades, thus making its prevention and treatments a challenging endeavor. However, epigenetic modification, particularly DNA methylation-mediated silencing of key TSGs, is a hallmark of cancer progression. One such tumor suppressor gene (TSG) RUNX3 (Runt-related transcription factor 3) has been a new insight in breast cancer known to be suppressed due to local promoter hypermethylation mediated by DNA methyltransferase 1 (DNMT1). However, the precise mechanism of epigenetic-influenced silencing of the RUNX3 signaling resulting in cancer invasion and metastasis remains inadequately characterized. In this study, a biological regulatory network (BRN) has been designed to model the dynamics of the DNMT1-RUNX3 network augmented by other regulators such as p21, c-myc, and p53. For this purpose, the René Thomas qualitative modeling was applied to compute the unknown parameters and the subsequent trajectories signified important behaviors of the DNMT1-RUNX3 network (i.e., recovery cycle, homeostasis, and bifurcation state). As a result, the biological system was observed to invade cancer metastasis due to persistent activation of oncogene c-myc accompanied by consistent downregulation of TSG RUNX3. Conversely, homeostasis was achieved in the absence of c-myc and activated TSG RUNX3. Furthermore, DNMT1 was endorsed as a potential epigenetic drug target to be subjected to the implementation of machine-learning techniques for the classification of the active and inactive DNMT1 modulators. The best-performing ML model successfully classified the active and least-active DNMT1 inhibitors exhibiting 97% classification accuracy. Collectively, this study reveals the underlined epigenetic events responsible for RUNX3-implicated breast cancer metastasis along with the classification of DNMT1 modulators that can potentially drive the perception of epigenetic-based tumor therapy.

Genomic Investigation of Methicillin-Resistant Staphylococcus aureus ST113 Strains Isolated from Tertiary Care Hospitals in Pakistan.

Methicillin-resistant Staphylococcus aureus (MRSA) is a multi-drug resistant and opportunistic pathogen. The emergence of new clones of MRSA in both healthcare settings and the community warrants serious attention and epidemiological surveillance. However, epidemiological data of MRSA isolates from Pakistan are limited. We performed a whole-genome-based comparative analysis of two (P10 and R46) MRSA strains isolated from two provinces of Pakistan to understand the genetic diversity, sequence type (ST), and distribution of virulence and antibiotic-resistance genes. The strains belong to ST113 and harbor the SCCmec type IV encoding mecA gene. Both the strains contain two plasmids, and three and two complete prophage sequences are present in P10 and R46, respectively. The specific antibiotic resistance determinants in P10 include two aminoglycoside-resistance genes, aph(3')-IIIa and aad(6), a streptothrin-resistance gene sat-4, a tetracycline-resistance gene tet(K), a mupirocin-resistance gene mupA, a point mutation in fusA conferring resistance to fusidic acid, and in strain R46 a specific plasmid associated gene ant(4')-Ib. The strains harbor many virulence factors common to MRSA. However, no Panton-Valentine leucocidin (lukF-PV/lukS-PV) or toxic shock syndrome toxin (tsst) genes were detected in any of the genomes. The phylogenetic relationship of P10 and R46 with other prevailing MRSA strains suggests that ST113 strains are closely related to ST8 strains and ST113 strains are a single-locus variant of ST8. These findings provide important information concerning the emerging MRSA clone ST113 in Pakistan and the sequenced strains can be used as reference strains for the comparative genomic analysis of other MRSA strains in Pakistan and ST113 strains globally.

Comparative assessment regarding antioxidative and nutrition potential of Moringa oleifera leaves by bacterial fermentation.

Moringa is considered as a miraculous plant because of its outstanding health-promoting properties. Moringa leaves are used in various forms for various purposes owing to its potential against that purpose. This experiment was performed to utilize the hidden potential of Moringa leaves. The Moringa leaves were fermented by Bacillus subtilis KCTC 13,241 for 24, 48, 72 and 96 h to identify the best time duration of fermentation. The antioxidant potential of fermented Moringa leaves was estimated by measuring the total phenolic content (TPC), total isoflavones content (TIFC), DPPH and ABTS free radical scavenging activity and SOD-like activity. In addition to these parameters, the concentration of various total amino acids (TAA) and fatty acids were also determined. The best treatment was 48 h fermented Moringa leaves because of the best results in all measured parameters except in fatty acids concentration. The highest fatty acids concentration was recorded in 24 h fermented leaves. The results of 48 h fermented Moringa leaves regarding TAA, TPC, TIFC, DPPH and ABTS radical scavenging potential and SOD-like activity were 121.95 ± 3.74 mg/g, 310.25 ± 3.77 µg GAE/g, 1083.38 ± 5.92 µg/g, 63.12 ± 2.38%, 78.45 ± 3.32%, and 34.55 ± 1.05% respectively. The palmitic, stearic, oleic, linoleic and linolenic acid concentration in 24 h fermented Moringa leaves was 55.32 ± 1.93, 56.02 ± 2.12, 53.82 ± 2.54, 55.95 ± 1.62 and 56.41 ± 1.43% respectively. In conclusion, the present results disclose that fermented Moringa leaves are the source of natural antioxidants and nutrients.

Biological Regulatory Network (BRN) Analysis and Molecular Docking Simulations to Probe the Modulation of IP3R Mediated Ca2+ Signaling in Cancer.

Inositol trisphosphate receptor (IP3R) mediated Ca+2 signaling is essential in determining the cell fate by regulating numerous cellular processes, including cell division and cell death. Despite extensive studies about the characterization of IP3R in cancer, the underlying molecular mechanism initiating the cell proliferation and apoptosis remained enigmatic. Moreover, in cancer, the modulation of IP3R in downstream signaling pathways, which control oncogenesis and cancer progression, is not well characterized. Here, we constructed a biological regulatory network (BRN), and describe the remodeling of IP3R mediated Ca2+ signaling as a central key that controls the cellular processes in cancer. Moreover, we summarize how the inhibition of IP3R affects the deregulated cell proliferation and cell death in cancer cells and results in the initiation of pro-survival responses in resistance of cell death in normal cells. Further, we also investigated the role of stereo-specificity of IP3 molecule and its analogs in binding with the IP3 receptor. Molecular docking simulations showed that the hydroxyl group at R6 position along with the phosphate group at R5 position in 'R' conformation is more favorable for IP3 interactions. Additionally, Arg-266 and Arg-510 showed π-π and hydrogen bond interactions and Ser-278 forms hydrogen bond interactions with the IP3 binding site. Thus, they are identified as crucial for the binding of antagonists.

Isolation and characterization of exopolysaccharide-producing strains of Lactobacillus bulgaricus from curd.

Curd is the most widespread traditional fermented milk product used by a large population and is a good source of vitamin B, protein, and calcium. In this study, the isolation of exopolysaccharide (EPS)-producing strains of Lactobacillus delbrueckii subsp. bulgaricus from curd samples was carried out. Identification of EPS-producing strains was done by Gram staining, catalase activity, sugar fermentation test, API 50 CHL, and PCR analysis. These EPS-producing strains were subjected for the estimation of technological properties such as titratable acidity, curdling time, acidification rate, and texture. The strains best in their technological properties were selected for the production of yogurt in combination with EPS- or non-EPS-producing strains of Streptococcus thermophilus. The EPS concentration range was from 41 to 268 mg/L in the yogurt. The highest value of EPS concentration was detected in S. thermophilus and non-EPS-producing Lb. bulgaricus after 14 days of storage.

Parameter estimation of qualitative biological regulatory networks on high performance computing hardware.

BACKGROUND: Biological Regulatory Networks (BRNs) are responsible for developmental and maintenance related functions in organisms. These functions are implemented by the dynamics of BRNs and are sensitive to regulations enforced by specific activators and inhibitors. The logical modeling formalism by René Thomas incorporates this sensitivity with a set of logical parameters modulated by available regulators, varying with time. With the increase in complexity of BRNs in terms of number of entities and their interactions, the task of parameters estimation becomes computationally expensive with existing sequential SMBioNET tool. We extend the existing sequential implementation of SMBioNET by using a data decomposition approach using a Java messaging library called MPJ Express. The approach divides the parameters space into different regions and each region is then explored in parallel on High Performance Computing (HPC) hardware. RESULTS: The performance of the parallel approach is evaluated on BRNs of different sizes, and experimental results on multicore and cluster computers showed almost linear speed-up. This parallel code can be executed on a wide range of concurrent hardware including laptops equipped with multicore processors, and specialized distributed memory computer systems. To demonstrate the application of parallel implementation, we selected a case study of Hexosamine Biosynthetic Pathway (HBP) in cancer progression to identify potential therapeutic targets against cancer. A set of logical parameters were computed for HBP model that directs the biological system to a state of recovery. Furthermore, the parameters also suggest a potential therapeutic intervention that restores homeostasis. Additionally, the performance of parallel application was also evaluated on a network (comprising of 23 entities) of Fibroblast Growth Factor Signalling in Drosophila melanogaster. CONCLUSIONS: Qualitative modeling framework is widely used for investigating dynamics of biological regulatory networks. However, computation of model parameters in qualitative modeling is computationally intensive. In this work, we presented results of our Java based parallel implementation that provides almost linear speed-up on both multicore and cluster platforms. The parallel implementation is available at https://psmbionet.github.io .

Effects of Bacterial Fermentation on the Biochemical Constituents and Antioxidant Potential of Fermented and Unfermented Soybeans Using Probiotic Bacillus subtilis (KCTC 13241).

Fermented soybeans, cheonggukjang (CKJ), are considered to be more wholesome than soybeans in Korea. To select the best soybean cultivar for making functional CKJ, a comparison was made between the biological activities of four soybean cultivars in their unfermented soybean (UFS) and CKJ states. Changes in 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical-scavenging activity, 2,2'-azino-bis (3-ethylbenzothiazoline-6-sulphonic acid) (ABTS) assays, superoxide dismutase (SOD)-like activity, total phenolic compounds, total amino acids, and isoflavones were investigated. The levels of DPPH, ABTS, SOD-like activity, and total phenolic compounds increased in CKJ among all cultivars. The isoflavone aglycone and total amino acids showed the highest amount in CKJ prepared from soybean cultivar Aga 3. These results suggest that the improved antioxidant activity of CKJ in all cultivars might occur because of the higher levels of aglycones and total phenolic compounds achieved during fermentation. Moreover, CKJ prepared from soybean cultivar Aga 3 showed higher antioxidant activity than the other cultivars and so can be considered for the commercial production of functional foods in the future.

Formal modeling and analysis of the hexosamine biosynthetic pathway: role of O-linked N-acetylglucosamine transferase in oncogenesis and cancer progression.

The alteration of glucose metabolism, through increased uptake of glucose and glutamine addiction, is essential to cancer cell growth and invasion. Increased flux of glucose through the Hexosamine Biosynthetic Pathway (HBP) drives increased cellular O-GlcNAcylation (hyper-O-GlcNAcylation) and contributes to cancer progression by regulating key oncogenes. However, the association between hyper-O-GlcNAcylation and activation of these oncogenes remains poorly characterized. Here, we implement a qualitative modeling framework to analyze the role of the Biological Regulatory Network in HBP activation and its potential effects on key oncogenes. Experimental observations are encoded in a temporal language format and model checking is applied to infer the model parameters and qualitative model construction. Using this model, we discover step-wise genetic alterations that promote cancer development and invasion due to an increase in glycolytic flux, and reveal critical trajectories involved in cancer progression. We compute delay constraints to reveal important associations between the production and degradation rates of proteins. O-linked N-acetylglucosamine transferase (OGT), an enzyme used for addition of O-GlcNAc during O-GlcNAcylation, is identified as a key regulator to promote oncogenesis in a feedback mechanism through the stabilization of c-Myc. Silencing of the OGT and c-Myc loop decreases glycolytic flux and leads to programmed cell death. Results of network analyses also identify a significant cycle that highlights the role of p53-Mdm2 circuit oscillations in cancer recovery and homeostasis. Together, our findings suggest that the OGT and c-Myc feedback loop is critical in tumor progression, and targeting these mediators may provide a mechanism-based therapeutic approach to regulate hyper-O-GlcNAcylation in human cancer.