Metabolic and proteomic signatures of type 2 diabetes subtypes in an Arab population.

Type 2 diabetes (T2D) has a heterogeneous etiology influencing its progression, treatment, and complications. A data driven cluster analysis in European individuals with T2D previously identified four subtypes: severe insulin deficient (SIDD), severe insulin resistant (SIRD), mild obesity-related (MOD), and mild age-related (MARD) diabetes. Here, the clustering approach was applied to individuals with T2D from the Qatar Biobank and validated in an independent set. Cluster-specific signatures of circulating metabolites and proteins were established, revealing subtype-specific molecular mechanisms, including activation of the complement system with features of autoimmune diabetes and reduced 1,5-anhydroglucitol in SIDD, impaired insulin signaling in SIRD, and elevated leptin and fatty acid binding protein levels in MOD. The MARD cluster was the healthiest with metabolomic and proteomic profiles most similar to the controls. We have translated the T2D subtypes to an Arab population and identified distinct molecular signatures to further our understanding of the etiology of these subtypes.

Genome-wide association analyses highlight etiological differences underlying newly defined subtypes of diabetes.

Type 2 diabetes has been reproducibly clustered into five subtypes with different disease progression and risk of complications; however, etiological differences are unknown. We used genome-wide association and genetic risk score (GRS) analysis to compare the underlying genetic drivers. Individuals from the Swedish ANDIS (All New Diabetics In Scania) study were compared to individuals without diabetes; the Finnish DIREVA (Diabetes register in Vasa) and Botnia studies were used for replication. We show that subtypes differ with regard to family history of diabetes and association with GRS for diabetes-related traits. The severe insulin-resistant subtype was uniquely associated with GRS for fasting insulin but not with variants in the TCF7L2 locus or GRS reflecting insulin secretion. Further, an SNP (rs10824307) near LRMDA was uniquely associated with mild obesity-related diabetes. Therefore, we conclude that the subtypes have partially distinct genetic backgrounds indicating etiological differences.

Wild-Type MIC Distribution for Re-evaluating the Critical Concentration of Anti-TB Drugs and Pharmacodynamics Among Tuberculosis Patients From South India.

The World Health Organization (WHO) has developed specific guidelines for critical concentrations (CCs) of antibiotics used for tuberculosis (TB) treatment, which is universally followed for drug susceptibility testing (DST) of clinical specimens. However, the CC of drugs can differ significantly among the mycobacterial species based on the population, geographic location, and the prevalence of the infecting strain in a particular area. The association between CC and the minimal inhibitory concentration (MIC) of anti-TB drugs is poorly understood. In this study, we assessed the MICs of anti-TB drugs, including isoniazid (INH), rifampicin (RMP), moxifloxacin (MXF), ethambutol (ETH), and p-aminosalicylic acid (PAS) on drug-sensitive Mtb isolates from pulmonary TB patients in South India. The MIC assays performed using solid- and liquid-growth media showed changes in the CC of a few of the tested antibiotics compared with the WHO-recommended levels. Our observation suggests that the WHO guidelines could potentially lead to overdiagnosis of drug-resistant cases, which can result in inappropriate therapeutic decisions. To evaluate the correlation between drug-resistance and CC, we performed the whole-genome sequencing for 16 mycobacterial isolates, including two wild-type and 14 resistant isolates. Our results showed that two of the isolates belonged to the W-Beijing lineage, while the rest were of the East-African-Indian type. We identified a total of 74 mutations, including five novel mutations, which are known to be associated with resistance to anti-TB drugs in these isolates. In our previous study, we determined the serum levels of INH and RMP among the same patients recruited in the current study and estimated the MICs of the corresponding infected isolates in these cases. Using these data and the CCs for INH and RMP from the present study, we performed pharmacodynamics (PD) evaluation. The results show that the PD of RMP was subtherapeutic. Together, these observations emphasize the need for optimizing the drug dosage based on the PD of large-scale studies conducted in different geographical settings.

Exploring the conformational landscapes of HIV protease structural ensembles using principal component analysis.

HIV protease, an essential enzyme for viral particle maturation, is an important drug target of HIV. Its structural conformation is a key determinant of both biological function as well as efficient binding of protease inhibitor molecules. In the present study we analyzed 471 crystal structures of HIV-1 protease to understand the conformational changes induced by mutations or binding of various ligands and substrates. We performed principal component analysis on the ensembles of the HIV-1 protease structures to explore the conformational landscapes. The study identified structural differences between drug resistant and drug sensitive protease structures. Conformational changes were identified in the A and B chains of homo-dimeric HIV protease structures having different combinations of mutations, and also rigidity in the binding conformation of HIV drugs within the active site of the protein.© 2018 Wiley Periodicals, Inc.

CRCDA--Comprehensive resources for cancer NGS data analysis.

Next generation sequencing (NGS) innovations put a compelling landmark in life science and changed the direction of research in clinical oncology with its productivity to diagnose and treat cancer. The aim of our portal comprehensive resources for cancer NGS data analysis (CRCDA) is to provide a collection of different NGS tools and pipelines under diverse classes with cancer pathways and databases and furthermore, literature information from PubMed. The literature data was constrained to 18 most common cancer types such as breast cancer, colon cancer and other cancers that exhibit in worldwide population. NGS-cancer tools for the convenience have been categorized into cancer genomics, cancer transcriptomics, cancer epigenomics, quality control and visualization. Pipelines for variant detection, quality control and data analysis were listed to provide out-of-the box solution for NGS data analysis, which may help researchers to overcome challenges in selecting and configuring individual tools for analysing exome, whole genome and transcriptome data. An extensive search page was developed that can be queried by using (i) type of data [literature, gene data and sequence read archive (SRA) data] and (ii) type of cancer (selected based on global incidence and accessibility of data). For each category of analysis, variety of tools are available and the biggest challenge is in searching and using the right tool for the right application. The objective of the work is collecting tools in each category available at various places and arranging the tools and other data in a simple and user-friendly manner for biologists and oncologists to find information easier. To the best of our knowledge, we have collected and presented a comprehensive package of most of the resources available in cancer for NGS data analysis. Given these factors, we believe that this website will be an useful resource to the NGS research community working on cancer. Database URL: http://bioinfo.au-kbc.org.in/ngs/ngshome.html.

A user-friendly web portal for analyzing conformational changes in structures of Mycobacterium tuberculosis.

Initiation of the Tuberculosis Structural Consortium has resulted in the expansion of the Mycobacterium tuberculosis (MTB) protein structural database. Currently, 969 experimentally solved structures are available for 354 MTB proteins. This includes multiple crystal structures for a given protein under different functional conditions, such as the presence of different ligands or mutations. In depth analysis of the multiple structures reveal that subtle differences exist in conformations of a given protein under varied conditions. Therefore, it is immensely important to understand the conformational differences between the multiple structures of a given protein in order to select the most suitable structure for molecular docking and structure-based drug designing. Here, we introduce a web portal ( http://bmi.icmr.org.in/mtbsd/torsion.php ) that we developed to provide comparative data on the ensemble of available structures of MTB proteins, such as Cα root means square deviation (RMSD), sequence identity, presence of mutations and torsion angles. Additionally, torsion angles were used to perform principal component analysis (PCA) to identify the conformational differences between the structures. Additionally, we present a few case studies to demonstrate this database. Graphical Abstract Conformational changes seen in the structures of the enoyl-ACP reductase protein encoded by the Mycobacterial gene inhA.