Differential proteomics of circulating extracellular vesicles of placental origin isolated from women with early-onset preeclampsia reveal aberrant innate immune and hemostasis processes.

PROBLEM: Early-onset preeclampsia (EOPE) is a severe gestational hypertensive disorder with significant feto-maternal morbidity and mortality due to uteroplacental insufficiency. Circulating extracellular vesicles of placental origin (EV-P) are known to be involved in the pathophysiology of EOPE and might serve as an ideal reservoir for its specific biomarkers. Therefore, we aimed to characterize and perform comparative proteomics of circulating EV-P from healthy pregnant and EOPE women before delivery. METHOD OF STUDY: The EV-P from both groups were isolated using immunoaffinity and were characterized using transmission electron microscopy, dynamic light scattering, nanoparticle tracking analysis, and immunoblotting. Following IgG albumin depletion, the pooled proteins that were isolated from EV-P of both groups were subjected to quantitative TMT proteomics. RESULTS: Circulating term EV-P isolated from both groups revealed ∼150 nm spherical vesicles containing CD9 and CD63 along with placental PLAP and HLA-G proteins. Additionally, the concentration of EOPE-derived EV-P was significantly increased. A total of 208 proteins were identified, with 26 among them being differentially abundant in EV-P of EOPE women. This study linked the pathophysiology of EOPE to 19 known and seven novel proteins associated with innate immune responses such as complement and TLR signaling along with hemostasis and oxygen homeostasis. CONCLUSION: The theory suggesting circulating EVs of placental origin could mimic molecular information from the parent organ-"the placenta"-is strengthened by this study. The findings pave the way for possible discovery of novel prognostic and predictive biomarkers as well as provide insight into the mechanisms driving the pathogenesis of EOPE.

A Recombinant Fragment of Human Surfactant Protein D Binds Spike Protein and Inhibits Infectivity and Replication of SARS-CoV-2 in Clinical Samples.

Coronavirus disease (COVID-19) is an acute infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Human SP-D (surfactant protein D) is known to interact with the spike protein of SARS-CoV, but its immune surveillance against SARS-CoV-2 is not known. The current study aimed to examine the potential of a recombinant fragment of human SP-D (rfhSP-D) as an inhibitor of replication and infection of SARS-CoV-2. The interaction of rfhSP-D with the spike protein of SARS-CoV-2 and human ACE-2 (angiotensin-converting enzyme 2) receptor was predicted via docking analysis. The inhibition of interaction between the spike protein and ACE-2 by rfhSP-D was confirmed using direct and indirect ELISA. The effect of rfhSP-D on replication and infectivity of SARS-CoV-2 from clinical samples was assessed by measuring the expression of RdRp gene of the virus using quantitative PCR. In silico interaction studies indicated that three amino acid residues in the receptor-binding domain of spike protein of SARS-CoV-2 were commonly involved in interacting with rfhSP-D and ACE-2. Studies using clinical samples of SARS-CoV-2-positive cases (asymptomatic, n = 7; symptomatic, n = 8) and negative control samples (n = 15) demonstrated that treatment with 1.67 µM rfhSP-D inhibited viral replication by ∼5.5-fold and was more efficient than remdesivir (100 µM) in Vero cells. An approximately two-fold reduction in viral infectivity was also observed after treatment with 1.67 µM rfhSP-D. These results conclusively demonstrate that the rfhSP-D mediated calcium independent interaction between the receptor-binding domain of the S1 subunit of the SARS-CoV-2 spike protein and human ACE-2, its host cell receptor, and significantly reduced SARS-CoV-2 infection and replication in vitro.

Enrichment analyses of diseases and pathways associated with precocious puberty using PrecocityDB.

Precocious puberty (PP) is an important endocrine disorder affecting children globally. Several genes, SNPs and comorbidities are reported to be associated with PP; however, this data is scattered across scientific literature and has not been systematically collated and analysed. In this study, we present PrecocityDB as the first manually curated online database on genes and their ontology terms, SNPs, and pathways associated with PP. A tool for visualizing SNP coordinates and allelic variation on each chromosome, for genes associated with PP is also incorporated in PrecocityDB. Pathway enrichment analysis of PP-associated genes revealed that endocrine and cancer-related pathways are highly enriched. Disease enrichment analysis indicated that individuals with PP seem to be highly likely to suffer from reproductive and metabolic disorders such as PCOS, hypogonadism, and insulin resistance. PrecocityDB is a useful resource for identification of comorbid conditions and disease risks due to shared genes in PP. PrecocityDB is freely accessible at http://www.precocity.bicnirrh.res.in . The database source code and content can be downloaded through GitHub ( https://github.com/bic-nirrh/precocity ).

Exploring the druggable proteome of Candida species through comprehensive computational analysis.

Candida albicans and non-albicans Candida spp. are major cause of systemic mycoses. Antifungal drugs such as azoles and polyenes are not efficient to successfully eradicate Candida infection owing to their fungistatic nature or low bioavailability. Here, we have adopted a comprehensive computational workflow for identification, prioritization and validation of targets from proteomes of Candida albicans and Candida tropicalis. The protocol involves identification of essential drug-target candidates using subtractive genomics, protein-protein interaction network properties and systems biology based methods. The essentiality of the novel metabolic and non-metabolic targets was established by performing in silico gene knockouts, under aerobic as well as anaerobic conditions, and in vitro drug inhibition assays respectively. Deletion of twelve genes that are involved in amino acid, secondary metabolite, and carbon metabolism showed zero growth in metabolic model under simulated conditions. The algorithm, used in this study, can be downloaded from http://pbit.bicnirrh.res.in/offline.php and executed locally.

PCOSKBR2: a database of genes, diseases, pathways, and networks associated with polycystic ovary syndrome.

PolyCystic Ovary Syndrome KnowledgeBase (PCOSKBR2) is a manually curated database with information on 533 genes, 145 SNPs, 29 miRNAs, 1,150 pathways, and 1,237 diseases associated with PCOS. This data has been retrieved based on evidence gleaned by critically reviewing literature and related records available for PCOS in databases such as KEGG, DisGeNET, OMIM, GO, Reactome, STRING, and dbSNP. Since PCOS is associated with multiple genes and comorbidities, data mining algorithms for comorbidity prediction and identification of enriched pathways and hub genes are integrated in PCOSKBR2, making it an ideal research platform for PCOS. PCOSKBR2 is freely accessible at http://www.pcoskb.bicnirrh.res.in/ .

Membrane Interactome of a Recombinant Fragment of Human Surfactant Protein D Reveals GRP78 as a Novel Binding Partner in PC3, a Metastatic Prostate Cancer Cell Line.

Surfactant protein-D (SP-D), a member of the collectin family has been shown to induce apoptosis in cancer cells. SP-D is composed of an N-terminal collagen-like domain and a calcium-dependent carbohydrate recognition domain (CRD). Recently, we reported that a recombinant fragment of human SP-D (rfhSP-D), composed of homotrimeric CRD region, induced intrinsic apoptotic pathway in prostate cancer cells. Here, we analyzed the membrane interactome of rfhSP-D in an androgen-independent prostate cancer cell line, PC3, by high resolution mass spectrometry and identified 347 proteins. Computational analysis of PPI network of this interactome in the context of prostate cancer metastasis and apoptosis revealed Glucose Regulated Protein of 78 kDa (GRP78) as an important binding partner of rfhSP-D. Docking studies suggested that rfhSP-D (CRD) bound to the substrate-binding domain of glycosylated GRP78. This was further supported by the observations that human recombinant GRP78 interfered with the binding of rfhSP-D to anti-SP-D polyclonal antibodies; GRP78 also significantly inhibited the binding of recombinant full-length human SP-D with a monoclonal antibody specific to the CRD in a dose-dependent manner. We conclude that the interaction with rfhSP-D is likely to interfere with the pro-survival signaling of GRP78.

A machine learning approach towards the prediction of protein-ligand binding affinity based on fundamental molecular properties.

There is an exigency of transformation of the enormous amount of biological data available in various forms into some significant knowledge. We have tried to implement Machine Learning (ML) algorithm models on the protein-ligand binding affinity data already available to predict the binding affinity of the unknown. ML methods are appreciably faster and cheaper as compared to traditional experimental methods or computational scoring approaches. The prerequisites of this prediction are sufficient and unbiased features of training data and a prediction model which can fit the data well. In our study, we have applied Random forest and Gaussian process regression algorithms from the Weka package on protein-ligand binding affinity, which encompasses protein and ligand binding information from PdbBind database. The models are trained on the basis of selective fundamental information of both proteins and ligand, which can be effortlessly fetched from online databases or can be calculated with the availability of structure. The assessment of the models was made on the basis of correlation coefficient (R 2) and root mean square error (RMSE). The Random forest model gave R 2 and RMSE of 0.76 and 1.31 respectively. We have also used our features and prediction models on the dataset used by others and found that our model with our features outperformed the existing ones.

Giant fibrolipoma of the oral cavity.

Firbolipomas are rat e tumors of oral cavity Here, we present a case of giant fibrolipoma of the oral cavity.

Fibrous dysplasia of ethmoid - a rare presentation.

Monostatic fibrous dysplasia involving th ethmoid is one of the rarest lesions. The clinico-pathologhical featutres and management are described.