Subcellular Localization and Prediction of Chloroplast Proteins

Chloroplast proteins phave different functions and play important roles in different biological processes. Furthermore, the function of a protein is closely related to its own structure and subcellular localization. Only when proteins are transported to specific subcellular locations can they exert their functions and participate in cellular life activities. Therefore, first identifying the subcellular localization of a protein can help to understand the biological function of the protein, as well as to explain the relationship between the protein and other biomolecules. There are two common methods of chloroplast protein localization: experimental localization and bioinformatics prediction. With the advent of the post-genome era and the continuous development of bioinformatics analysis technology, the means of using computer system theory to predict the subcellular localization of proteins have become more and more mature, and a large number of prediction methods and online prediction websites have emerged.

Fig. 1. Summary of representative prediction approaches of different subcellular localization. (Lehtimäki N, et al., 2015)

Services

The rise of subcellular omics and advances in mass spectrometry have made possible the subcellular localization, functional annotation, and large-scale protein sorting of chloroplast proteins, as well as the basis for optimizing prediction software for chloroplast proteins. Over the years, the team at Lifeasible has extensive experience in chloroplast protein subcellular omics research. We are committed to providing professional chloroplast protein subcellular localization and prediction services for global customers to perform large-scale subcellular localization prediction of newly discovered chloroplast proteins. In addition, our scientists have successfully used a variety of experimental localization and bioinformatics methods to predict the intrinsic information present in protein sequences, including amino acid composition or fixed length, sequence profiles, hydrophobicity, charged residues, and more within a polypeptide sequence. Peptide sequence composition of physicochemical parameters such as electric point, etc.

The workflow for predicting subcellular localization using a computer is as follows:

(1) Collecting sequence information from multiple databases and establish a database for subcellular localization.
(2) Extracting protein characteristic parameters according to amino acid composition, N-terminal signal peptide of amino acid sequence, amino acid residue properties, sequence homology similarity and protein functional domain.
(3) Correctly and efficiently using prediction algorithms to predict the subcellular locations of different proteins.
(4) Detecting and evaluating the prediction results.

In the study of protein subcellular localization, the results of bioinformatics prediction have certain reference value, but the subcellular localization of protein cannot be completely determined. Finally, the specific localization of protein needs to be determined experimentally. The experimental positioning and computational prediction methods we can provide include:

• Immunocolloidal gold labeling.
• Immunofluorescence technique.
• Fusion reporter gene mapping.
• Hidden Markov Model (HMM).
• Neural Network (NN).
• Support Vector Machines (SVM).

Competitive Advantages

• A team with extensive experience in chloroplast protein subcytomics.
• Experimental positioning method and computer bioinformatics prediction method, the measurement results are accurate and fast.
• Combining subjectivity and objectivity, the detection cost is low.
• Online prediction of protein subcellular localization using a variety of Internet.
• High-efficiency analysis of chloroplast protein subcellular localization and function.

Lifeasible can meet the needs of customers on time and on budget through a wide range of strategies for analyzing chloroplast proteome. Our aim is to be customer-centric and to provide the highest quality service to customers around the world. Our skilled and dedicated scientific researchers ensure that the most appropriate methods and techniques are selected for each specialized chloroplast project. Our customer service representatives are enthusiastic and trustworthy 24 hours a day, 7 days a week. If you are interested in our services, please feel free to contact us for more information or a detailed discussion.

References

1. Imai K, Nakai K. (2020) Tools for the recognition of sorting signals and the prediction of subcellular localization of proteins from their amino acid sequences[J]. Frontiers in Genetics. 1491.
2. Wang Y, Na J. (2020) Progress on Methods of Subcellular Localization of Chloroplast Protein in Plant Cells[J].