On the structure differences of short fragments and amino acids in proteins with and without disulfide bonds

Of the 20 standard amino acids, cysteines are the only amino acids that have a reactive sulphur atom, thus enabling two cysteines to form strong covalent bonds known as disulfide bonds. Even though almost all proteins have cysteines, not all of them have disulfide bonds. Disulfide bonds provide structural stability to proteins and hence are an important constraint in determining the structure of a protein. As a result, disulfide bonds are used to study various protein properties, one of them being protein folding. Protein structure prediction is the problem of predicting the three-dimensional structure of a protein from its one-dimensional amino acid sequence. Ab initio methods are a group of methods that attempt to solve this problem from first principles, using only basic physico-chemical properties of proteins. These methods use structure libraries of short amino acid fragments in the process of predicting the structure of a protein. The protein structures from which these structure libraries are created are not classified in any other way apart from being non-redundant. In this thesis, we investigate the structural dissimilarities of short amino acid fragments when occurring in proteins with disulfide bonds and when occurring in those proteins without disulfide bonds. We are interested in this because, as mentioned earlier, the protein structures from which the structure libraries of ab initio methods are created, are not classified in any form. This means that any significant structural difference in amino acids and short fragments when occurring in proteins with and without disulfide bonds would remain unnoticed as these structure libraries have both fragments from proteins with disulfide bonds and without disulfide bonds together. Our investigation of structural dissimilarities of amino acids and short fragments is done in four phases. In phase one, by statistically analysing the phi and psi backbone dihedral angle distributions we show that these fragments have significantly different structures in terms of dihedral angles when occurring in proteins with and without disulfide bonds. In phase two, using directional statistics we investigate how structurally different are the 20 different amino acids and the short fragments when occurring in proteins with and without disulfide bonds. In phase three of our work, we investigate the differences in secondary structure preference of the 20 amino acids in proteins with and without disulfide bonds. In phase four, we further investigate and show that there are significant differences within the same secondary structure region of amino acids when they occur in proteins with and without disulfide bonds. Finally, we present the design and implementation details of a dihedral angle and secondary structure database of short amino acid fragments (DASSD) that is publicly available. Thus, in this thesis we show previously unknown significant structure differences in terms of backbone dihedral angles and secondary structures in amino acids and short fragments when they occur in proteins with and without disulfide bonds

A study on maternal and perinatal outcome of oligohydramnios in term low risk pregnancy

Background: Oligohydramnios is a frequent complication of pregnancy that is associated with increased perinatal morbidity and mortality. Once diagnosed; oligohydramnios should further lead to intensive fetal surveillance including ultrasound evaluation. The aim of the study was to determine obstetric outcome in term low risk pregnancy with AFI less than or equal to 5 and to assess whether antepartum oligohydramnios is associated with adverse perinatal outcome.Methods: 200 patients in third trimester in the hospital with evidence of oligohydramnios (AFI less than or equal to 5) were selected after satisfying inclusion and exclusion criteria and studied prospectively. Observations regarding the outcome of labour in form of maternal and perinatal parameters including AFI value, CTG features, mode of delivery, LSCS rate, meconium stained, APGAR score, birth weight and NICU admission were made.Results: Overall perinatal outcome with respect to CTG, 128 (64%) out of 200 patients had non-reactive CTG and only 72 (36%) had reactive CTG. 128 (64%) of non-reactive CTG delivered by LSCS, 72 (36%) delivered by labour natural. Nil labour natural in the subset of AFI 1 to 2, birth weight (2.5 kg-92%), Apgar score (<7 at 1-5 mins:18%), still birth (1%), meconium (58.5%), NICU admission (6%) and perinatal mortality (2%).Conclusions: AFI measurement of less than 5 cm detected after 37 completed weeks of gestation with a low risk pregnancy is found to be an indicator of adverse pregnancy outcome with higher fetal distress, meconium stained liquor and higher caesarean section rate. AFI assessment serves as an important tool and remains as an effective screening test in predicting fetal distress in labour that requires caesarean section

Lipidomic profiling of adipose tissue reveals an inflammatory signature in cancer-related and primary Lymphedema

© 2016 Sedger et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Cancer-related and primary lymphedema (LE) are associated with the production of adipose tissue (AT). Nothing is known, however, about the lipid-based molecules that comprise LE AT. We therefore analyzed lipid molecules in lipoaspirates and serum obtained from LE patients, and compared them to lipoaspirates from cosmetic surgery patients and healthy control cohort serum. LE patient serum analysis demonstrated that triglycerides, HDL- and LDL-cholesterol and lipid transport molecules remained within the normal range, with no alterations in individual fatty acids. The lipidomic analysis also identified 275 lipid-based molecules, including triacylglycerides, diacylglycerides, fatty acids and phospholipids in AT oil and fat. Although the majority of lipid molecules were present in a similar abundance in LE and non-LE samples, there were several small changes: increased C20:5-containing triacylglycerides, reduced C10:0 caprinic and C24:1 nervonic acids. LE AT oil also contained a signature of increased cyclopropane-type fatty acids and inflammatory mediators arachidonic acid and ceramides. Interestingly C20:5 and C22:6 omega-3-type lipids are increased in LE AT, correlating with LE years. Hence, LE AT has a normal lipid profile containing a signature of inflammation and omega-3-lipids. It remains unclear, however, whether these differences reflect a small-scale global metabolic disturbance or effects within localised inflammatory foci

MASTR-MS: A web-based collaborative laboratory information management system (LIMS) for metabolomics

Background An increasing number of research laboratories and core analytical facilities around the world are developing high throughput metabolomic analytical and data processing pipelines that are capable of handling hundreds to thousands of individual samples per year, often over multiple projects, collaborations and sample types. At present, there are no Laboratory Information Management Systems (LIMS) that are specifically tailored for metabolomics laboratories that are capable of tracking samples and associated metadata from the beginning to the end of an experiment, including data processing and archiving, and which are also suitable for use in large institutional core facilities or multi-laboratory consortia as well as single laboratory environments. Results Here we present MASTR-MS, a downloadable and installable LIMS solution that can be deployed either within a single laboratory or used to link workflows across a multisite network. It comprises a Node Management System that can be used to link and manage projects across one or multiple collaborating laboratories; a User Management System which defines different user groups and privileges of users; a Quote Management System where client quotes are managed; a Project Management System in which metadata is stored and all aspects of project management, including experimental setup, sample tracking and instrument analysis, are defined, and a Data Management System that allows the automatic capture and storage of raw and processed data from the analytical instruments to the LIMS. Conclusion MASTR-MS is a comprehensive LIMS solution specifically designed for metabolomics. It captures the entire lifecycle of a sample starting from project and experiment design to sample analysis, data capture and storage. It acts as an electronic notebook, facilitating project management within a single laboratory or a multi-node collaborative environment. This software is being developed in close consultation with members of the metabolomics research community

The stress-responsive kinase DYRK2 activates heat shock factor 1 promoting resistance to proteotoxic stress

To survive proteotoxic stress, cancer cells activate the proteotoxic-stress response pathway, which is controlled by the transcription factor heat shock factor 1 (HSF1). This pathway supports cancer initiation, cancer progression and chemoresistance and thus is an attractive therapeutic target. As developing inhibitors against transcriptional regulators, such as HSF1 is challenging, the identification and targeting of upstream regulators of HSF1 present a tractable alternative strategy. Here we demonstrate that in triple-negative breast cancer (TNBC) cells, the dual specificity tyrosine-regulated kinase 2 (DYRK2) phosphorylates HSF1, promoting its nuclear stability and transcriptional activity. DYRK2 depletion reduces HSF1 activity and sensitises TNBC cells to proteotoxic stress. Importantly, in tumours from TNBC patients, DYRK2 levels positively correlate with active HSF1 and associates with poor prognosis, suggesting that DYRK2 could be promoting TNBC. These findings identify DYRK2 as a key modulator of the HSF1 transcriptional programme and a potential therapeutic target

Best practice data life cycle approaches for the life sciences

Throughout history, the life sciences have been revolutionised by technological advances; in our era this is manifested by advances in instrumentation for data generation, and consequently researchers now routinely handle large amounts of heterogeneous data in digital formats. The simultaneous transitions towards biology as a data science and towards a ‘life cycle’ view of research data pose new challenges. Researchers face a bewildering landscape of data management requirements, recommendations and regulations, without necessarily being able to access data management training or possessing a clear understanding of practical approaches that can assist in data management in their particular research domain. Here we provide an overview of best practice data life cycle approaches for researchers in the life sciences/bioinformatics space with a particular focus on ‘omics’ datasets and computer-based data processing and analysis. We discuss the different stages of the data life cycle and provide practical suggestions for useful tools and resources to improve data management practices.Philippa C. Griffin, Jyoti Khadake, Kate S. LeMay, Suzanna E. Lewis, Sandra Orchard ... Nathan S. Watson-Haigh ... et al

KEAP1-modifying small molecule reveals muted NRF2 signaling responses in neural stem cells from Huntington's disease patients

The activity of the transcription factor nuclear factor-erythroid 2 p45-derived factor 2 (NRF2) is orchestrated and amplified through enhanced transcription of antioxidant and antiinflammatory target genes. The present study has characterized a triazole-containing inducer of NRF2 and elucidated the mechanism by which this molecule activates NRF2 signaling. In a highly selective manner, the compound covalently modifies a critical stress-sensor cysteine (C151) of the E3 ligase substrate adaptor protein Kelch-like ECH-associated protein 1 (KEAP1), the primary negative regulator of NRF2. We further used this inducer to probe the functional consequences of selective activation of NRF2 signaling in Huntington's disease (HD) mouse and human model systems. Surprisingly, we discovered a muted NRF2 activation response in human HD neural stem cells, which was restored by genetic correction of the disease-causing mutation. In contrast, selective activation of NRF2 signaling potently repressed the release of the proinflammatory cytokine IL-6 in primary mouse HD and WT microglia and astrocytes. Moreover, in primary monocytes from HD patients and healthy subjects, NRF2 induction repressed expression of the proinflammatory cytokines IL-1, IL-6, IL-8, and TNFα. Together, our results demonstrate a multifaceted protective potential of NRF2 signaling in key cell types relevant to HD pathology

Integrative omics identifies conserved and pathogen-specific responses of sepsis-causing bacteria

Even in the setting of optimal resuscitation in high-income countries severe sepsis and septic shock have a mortality of 20–40%, with antibiotic resistance dramatically increasing this mortality risk. To develop a reference dataset enabling the identification of common bacterial targets for therapeutic intervention, we applied a standardized genomic, transcriptomic, proteomic and metabolomic technological framework to multiple clinical isolates of four sepsis-causing pathogens: Escherichia coli, Klebsiella pneumoniae species complex, Staphylococcus aureus and Streptococcus pyogenes. Exposure to human serum generated a sepsis molecular signature containing global increases in fatty acid and lipid biosynthesis and metabolism, consistent with cell envelope remodelling and nutrient adaptation for osmoprotection. In addition, acquisition of cholesterol was identified across the bacterial species. This detailed reference dataset has been established as an open resource to support discovery and translational research