Protein Identification in Latex Gloves for Bio-compatibility using Maximum Minimal Variation Test

Author(s):  
Kok Swee Sim ◽  
F. S. Chin ◽  
C. P. Tso ◽  
L. W. Thong
Author(s):  
Rocco J. Rotello ◽  
Timothy D. Veenstra

: In the current omics-age of research, major developments have been made in technologies that attempt to survey the entire repertoire of genes, transcripts, proteins, and metabolites present within a cell. While genomics has led to a dramatic increase in our understanding of such things as disease morphology and how organisms respond to medications, it is critical to obtain information at the proteome level since proteins carry out most of the functions within the cell. The primary tool for obtaining proteome-wide information on proteins within the cell is mass spectrometry (MS). While it has historically been associated with the protein identification, developments over the past couple of decades have made MS a robust technology for protein quantitation as well. Identifying quantitative changes in proteomes is complicated by its dynamic nature and the inability of any technique to guarantee complete coverage of every protein within a proteome sample. Fortunately, the combined development of sample preparation and MS methods have made it capable to quantitatively compare many thousands of proteins obtained from cells and organisms.


2020 ◽  
Vol 15 ◽  
Author(s):  
Affan Alim ◽  
Abdul Rafay ◽  
Imran Naseem

Background: Proteins contribute significantly in every task of cellular life. Their functions encompass the building and repairing of tissues in human bodies and other organisms. Hence they are the building blocks of bones, muscles, cartilage, skin, and blood. Similarly, antifreeze proteins are of prime significance for organisms that live in very cold areas. With the help of these proteins, the cold water organisms can survive below zero temperature and resist the water crystallization process which may cause the rupture in the internal cells and tissues. AFP’s have attracted attention and interest in food industries and cryopreservation. Objective: With the increase in the availability of genomic sequence data of protein, an automated and sophisticated tool for AFP recognition and identification is in dire need. The sequence and structures of AFP are highly distinct, therefore, most of the proposed methods fail to show promising results on different structures. A consolidated method is proposed to produce the competitive performance on highly distinct AFP structure. Methods: In this study, we propose to use machine learning-based algorithms Principal Component Analysis (PCA) followed by Gradient Boosting (GB) for antifreeze protein identification. To analyze the performance and validation of the proposed model, various combinations of two segments composition of amino acid and dipeptide are used. PCA, in particular, is proposed to dimension reduction and high variance retaining of data which is followed by an ensemble method named gradient boosting for modelling and classification. Results: The proposed method obtained the superfluous performance on PDB, Pfam and Uniprot dataset as compared with the RAFP-Pred method. In experiment-3, by utilizing only 150 PCA components a high accuracy of 89.63 was achieved which is superior to the 87.41 utilizing 300 significant features reported for the RAFP-Pred method. Experiment-2 is conducted using two different dataset such that non-AFP from the PISCES server and AFPs from Protein data bank. In this experiment-2, our proposed method attained high sensitivity of 79.16 which is 12.50 better than state-of-the-art the RAFP-pred method. Conclusion: AFPs have a common function with distinct structure. Therefore, the development of a single model for different sequences often fails to AFPs. A robust results have been shown by our proposed model on the diversity of training and testing dataset. The results of the proposed model outperformed compared to the previous AFPs prediction method such as RAFP-Pred. Our model consists of PCA for dimension reduction followed by gradient boosting for classification. Due to simplicity, scalability properties and high performance result our model can be easily extended for analyzing the proteomic and genomic dataset.


Nanomaterials ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1922
Author(s):  
Ramila Mammadova ◽  
Immacolata Fiume ◽  
Ramesh Bokka ◽  
Veronika Kralj-Iglič ◽  
Darja Božič ◽  
...  

Plant-derived nanovesicles (NVs) have attracted interest due to their anti-inflammatory, anticancer and antioxidative properties and their efficient uptake by human intestinal epithelial cells. Previously we showed that tomato (Solanum lycopersicum L.) fruit is one of the interesting plant resources from which NVs can be obtained at a high yield. In the course of the isolation of NVs from different batches of tomatoes, using the established differential ultracentrifugation or size-exclusion chromatography methods, we occasionally observed the co-isolation of viral particles. Density gradient ultracentrifugation (gUC), using sucrose or iodixanol gradient materials, turned out to be efficient in the separation of NVs from the viral particles. We applied cryogenic transmission electron microscopy (cryo-TEM), scanning electron microscopy (SEM) for the morphological assessment and LC–MS/MS-based proteomics for the protein identification of the gradient fractions. Cryo-TEM showed that a low-density gUC fraction was enriched in membrane-enclosed NVs, while the high-density fractions were rich in rod-shaped objects. Mass spectrometry–based proteomic analysis identified capsid proteins of tomato brown rugose fruit virus, tomato mosaic virus and tomato mottle mosaic virus. In another batch of tomatoes, we isolated tomato spotted wilt virus, potato virus Y and southern tomato virus in the vesicle sample. Our results show the frequent co-isolation of plant viruses with NVs and the utility of the combination of cryo-TEM, SEM and proteomics in the detection of possible viral contamination.


2021 ◽  
Vol 22 (5) ◽  
pp. 2244
Author(s):  
Anton E. Shikov ◽  
Yury V. Malovichko ◽  
Arseniy A. Lobov ◽  
Maria E. Belousova ◽  
Anton A. Nizhnikov ◽  
...  

Bacillus thuringiensis, commonly referred to as Bt, is an object of the lasting interest of microbiologists due to its highly effective insecticidal properties, which make Bt a prominent source of biologicals. To categorize the exuberance of Bt strains discovered, serotyping assays are utilized in which flagellin serves as a primary seroreactive molecule. Despite its convenience, this approach is not indicative of Bt strains’ phenotypes, neither it reflects actual phylogenetic relationships within the species. In this respect, comparative genomic and proteomic techniques appear more informative, but their use in Bt strain classification remains limited. In the present work, we used a bottom-up proteomic approach based on fluorescent two-dimensional difference gel electrophoresis (2D-DIGE) coupled with liquid chromatography/tandem mass spectrometry(LC-MS/MS) protein identification to assess which stage of Bt culture, vegetative or spore, would be more informative for strain characterization. To this end, the proteomic differences for the israelensis-attributed strains were assessed to compare sporulating cultures of the virulent derivative to the avirulent one as well as to the vegetative stage virulent bacteria. Using the same approach, virulent spores of the israelensis strain were also compared to the spores of strains belonging to two other major Bt serovars, namely darmstadiensis and thuringiensis. The identified proteins were analyzed regarding the presence of the respective genes in the 104 Bt genome assemblies available at open access with serovar attributions specified. Of 21 proteins identified, 15 were found to be encoded in all the present assemblies at 67% identity threshold, including several virulence factors. Notable, individual phylogenies of these core genes conferred neither the serotyping nor the flagellin-based phylogeny but corroborated the reconstruction based on phylogenomics approaches in terms of tree topology similarity. In its turn, the distribution of accessory protein genes was not confined to the existing serovars. The obtained results indicate that neither gene presence nor the core gene sequence may serve as distinctive bases for the serovar attribution, undermining the notion that the serotyping system reflects strains’ phenotypic or genetic similarity. We also provide a set of loci, which fit in with the phylogenomics data plausibly and thus may serve for draft phylogeny estimation of the novel strains.


2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Lei Xiang ◽  
Wenguo Cui

Abstract During the past decades, photo-crosslinked gelatin hydrogel (methacrylated gelatin, GelMA) has gained a lot of attention due to its remarkable application in the biomedical field. It has been widely used in cell transplantation, cell culture and drug delivery, based on its crosslinking to form hydrogels with tunable mechanical properties and excellent bio-compatibility when exposed to light irradiation to mimic the micro-environment of native extracellular matrix (ECM). Because of its unique biofunctionality and mechanical tenability, it has also been widely applied in the repair and regeneration of bone, heart, cornea, epidermal tissue, cartilage, vascular, peripheral nerve, oral mucosa, and skeletal muscle et al. The purpose of this review is to summarize the recent application of GelMA in drug delivery and tissue engineering field. Moreover, this review article will briefly introduce both the development of GelMA and the characterization of GelMA. Finally, we discuss the challenges and future development prospects of GelMA as a tissue engineering material and drug or gene delivery carrier, hoping to contribute to accelerating the development of GelMA in the biomedical field. Graphical abstract


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