Algorithms for integrated analysis of glycomics and glycoproteomics by LC-MS/MS

The glycoproteome is an intricate and diverse component of a cell, and it plays a key role in the definition of the interface between that cell and the rest of its world. Methods for studying the glycoproteome have been developed for released glycan glycomics and site-localized bottom-up glycoproteomics using liquid chromatography-coupled mass spectrometry and tandem mass spectrometry (LC-MS/MS), which is itself a complex problem. Algorithms for interpreting these data are necessary to be able to extract biologically meaningful information in a high throughput, automated context. Several existing solutions have been proposed but may be found lacking for larger glycopeptides, for complex samples, different experimental conditions, different instrument vendors, or even because they simply ignore fundamentals of glycobiology. I present a series of open algorithms that approach the problem from an instrument vendor neutral, cross-platform fashion to address these challenges, and integrate key concepts from the underlying biochemical context into the interpretation process. In this work, I created a suite of deisotoping and charge state deconvolution algorithms for processing raw mass spectra at an LC scale from a variety of instrument types. These tools performed better than previously published algorithms by enforcing the underlying chemical model more strictly, while maintaining a higher degree of signal fidelity. From this summarized, vendor-normalized data, I composed a set of algorithms for interpreting glycan profiling experiments that can be used to quantify glycan expression. From this I constructed a graphical method to model the active biosynthetic pathways of the sample glycome and dig deeper into those signals than would be possible from the raw data alone. Lastly, I created a glycopeptide database search engine from these components which is capable of identifying the widest array of glycosylation types available, and demonstrate a learning algorithm which can be used to tune the model to better understand the process of glycopeptide fragmentation under specific experimental conditions to outperform a simpler model by between 10% and 15%. This approach can be further augmented with sample-wide or site-specific glycome models to increase depth-of-coverage for glycoforms consistent with prior beliefs

PLecDom: a program for identification and analysis of plant lectin domains

PLecDom is a program for detection of Plant Lectin Domains in a polypeptide or EST sequence, followed by a classification of the identified domains into known families. The web server is a collection of plant lectin domain families represented by alignments and profile Hidden Markov Models. PLecDom was developed after a rigorous analysis of evolutionary relationships between available sequences of lectin domains with known specificities. Users can test their sequences for potential lectin domains, catalog the identified domains into broad substrate classes, estimate the extent of divergence of new domains with existing homologs, extract domain boundaries and examine flanking sequences for further analysis. The high prediction accuracy of PLecDom combined with the ease with which it handles large scale input, enabled us to apply the program to protein and EST data from 48 plant genome-sequencing projects in various stages of completion. Our results represent a significant enrichment of the currently annotated plant lectins, and highlight potential targets for biochemical characterization. The search algorithm requires input in fasta format and is designed to process simultaneous connection requests from multiple users, such that huge sets of input sequences can be scanned in a matter of seconds. PLecDom is available at http://www.nipgr.res.in/plecdom.html

Computational Biology and Chemistry

The use of computers and software tools in biochemistry (biology) has led to a deep revolution in basic sciences and medicine. Bioinformatics and systems biology are the direct results of this revolution. With the involvement of computers, software tools, and internet services in scientific disciplines comprising biology and chemistry, new terms, technologies, and methodologies appeared and established. Bioinformatic software tools, versatile databases, and easy internet access resulted in the occurrence of computational biology and chemistry. Today, we have new types of surveys and laboratories including “in silico studies” and “dry labs” in which bioinformaticians conduct their investigations to gain invaluable outcomes. These features have led to 3-dimensioned illustrations of different molecules and complexes to get a better understanding of nature

The Automation of Glycopeptide Discovery in High Throughput MS/MS Data

Glycosylation, the addition of one or more carbohydrates molecules to a protein, is crucial for many cellular processes. Aberrant glycosylation is a key marker for various diseases such as cancer and rheumatoid arthritis. It has also recently been discovered that glycosylation is important in the ability of the Human Immunodeficiency Virus (HIV) to evade recognition by the immune system. Given the importance of glycosylation in disease, major efforts are underway in life science research to investigate the glycome, the entire glycosylation profile of an organelle, cell or tissue type. To date, little bioinformatics research has been performed in glycomics due to the complexity of glycan structures and the low throughput of carbohydrate analysis. Recent advances in mass spectrometry (MS) have greatly facilitated the analysis of the glycome. Increasingly, this technology is preferred over traditional methods of carbohydrate analysis which are often laborious and unsuitable for low abundance glycoproteins. When subject to mass spectrometry with collision-induced dissociation, glycopeptides produce characteristic MS/MS spectra that can be detected by visual inspection. However, given the high volume of data output from proteome studies today, manually searching for glycopeptides is an impractical task. In this thesis, we present a tool to automate the identification of glycopeptide spectra from MS/MS data. Further, we discuss some methodologies to automate the elucidation of the structure of the carbohydrate moiety of glycopeptides by adapting traditional MS/MS ion searching techniques employed in peptide sequence determination. MS/MS ion searching, a common technique in proteomics, aims to interpret MS/MS spectra by correlating structures from a database to the patterns represented in the spectrum. The tool was tested on high throughput proteomics data and was shown to identify 97% of all glycopeptides present in the test data. Further, the tool assigned correct carbohydrate structures to many of these glycopeptide MS/MS spectra. Applications of the tool in a proteomics environment for the analysis of glycopeptide expression in cancer tissue are also be presented

The unique glycoproteins of Cryptosporidium parvum and Toxoplasma gondii

Cryptosporidium parvum and Toxoplasma gondii are obligate intracellular parasites transmitted by ingestion of resilient walled structures called oocysts. Infection is self-limiting in adults with normal immune systems. However, severe disease can occur in immunocompromised individuals, or those without cellular immunity. Cryptosporidium is a leading cause of infant mortality in developing countries, due to diarrhea. There are no human vaccines and no broad effective drug treatments. Several vaccine candidates have been described: the glycoproteins Gp900, Gp40, and Gp15 and the protein Cp23, the immuno-dominant-antigen. Details about modifications to these proteins have not previously been reported. Using mass spectrometry, we identified 16 Cryptosporidium N-glycosylated proteins, including Gp900 and a possible oocyst wall protein. The observed N-glycan structures exhibited only two compositions: HexNAc2Hex5 and HexNAc2Hex6; these glycoforms had a single extended arm. The simplicity of Cryptosporidium N-glycans contrasts with the complexity of host N-glycans. Four heavily O-glycosylated proteins included Gp900, Gp40, Gp15, and a novel mucin-like protein, Gp20. Single O-HexNAc residues modified Ser/Thr in low density regions of Gp15 and Gp900, while attachment of O-HexNAc residues on tandem Ser/Thr repeats of Gp20 and Gp40 approached saturation. Identification of N-acetylgalactosamine (GalNAc) as the HexNAc released from proteins suggests that most Cryptosporidium O-glycans resemble the immunogenic Tn antigen (O-GalNAc). The immunodominant antigen Cp23, while not glycosylated, was discovered to be N-myristoylated and S-palmitoylated on the first and second residues, respectively. This is the first identification in Cryptosporidium of these modifications. Information about the N-glycans, O-glycans, and lipid modifications may be useful for design of better serodiagnostic reagents and more effective vaccines. To date, there are no vaccines against Toxoplasma infection, and the only available pharmaceutical therapies are expensive. In the second study, a novel O-fucose modification was discovered on nuclear pore-associated proteins including nucleoporins. This observation has profound implications on how the organism may regulate trafficking in/out of the nucleus by employing a system parallel to that described for O- linked N-acetylglucosamine in other organisms. In summary, the new details regarding the vaccine candidates of Cryptosporidium and the discovery of the novel O-fucose modifications in T. gondii provide information that could prove useful for development of effective drugs and vaccines.2018-11-01T00:00:00

Program and abstracts

We are pleased that the program in 2022 will be more interesting than ever and it will include the following topics: Mathematical Modeling in Cancer Therapy, Gene Therapy, Archaeological Genetics, New perspectives in Human Forensic Molecular Biology, Genomics in Medicine, Pharmacogenomics and Drug Development, Stem Cells in Medicine, Regenerative Medicine, Ribosomes in Medicine, Epigenomics, Crime Scene Investigation, Forensic Genetics, and Mass Catastrophes Managements. This year, the third "Nobel Spirit" will provide a forum to the three Nobel laureates to stimulate public discussion on the role of science in solving global health issues, acute regional problems such as brain drain, demographic decline, as well as cultural and social change. In addition, we are organizing a very stimulating Session on Bioanthropology and global health in the times of crisis, as well as Joint Event ISABS and Ministry of the Interior - Crime Scene Investigation Training Course: Mystery on the ship —Investigation of the water-related crime scene