Antimycobacterial, antimicrobial activity, experimental (FT-IR, FT-Raman, NMR, UV-Vis, DSC) and DFT (transition state, chemical reactivity, NBO, NLO) studies on pyrrole-isonicotinyl hydrazine.

As part of a study of pyrrole hydrazone, we have investigated quantum chemical calculations, molecular geometry, relative energy, vibrational properties and antimycobacterial/antimicrobial activity of pyrrole-2-carboxaldehyde isonicotinyl hydrazone (PCINH), by applying the density functional theory (DFT) and Hartree Fock (HF). Good reproduction of experimental values is obtained and with small percentage error in majority of the cases in comparison to theoretical result (DFT). The experimental FT-IR and Raman wavenumbers were compared with the respective theoretical values obtained from DFT calculations and found to agree well. In crystal structure studies the hydrated PCINH (syn-syn conformer) shows different conformation than from anhydrous form (syn-anti conformer). The rotational barrier between syn-syn and syn-anti conformers of PCINH is 12.7kcal/mol in the gas phase. In this work, use of FT-IR, FT-Raman, 1H NMR, 13C NMR and UV-Vis spectroscopies has been made for full characterization of PCINH. A detailed interpretation of the vibrational spectrum was carried out with the aid of normal coordinate analysis using single scaling factor. Our results support the hydrogen bonding pattern proposed by reported crystalline structure. The calculated nature of electronic transitions within molecule found to be π→π*. The electronic descriptors study indicates that PCINH can be used as robust synthon for synthesis of new heterocyclic compounds. The first static hyperpolarizability (ß0) of PCINH is calculated as 33.89×10-30esu, (gas phase); 68.79×10-30 (CHCl3), esu; 76.76×10-30esu (CH2Cl2), 85.16×10-30esu (DMSO). The solvent induced effects on the first static hyperpolarizability were studied and found to increase as dielectric constants of the solvents increases. Investigated molecule shows better NLO value than Para nitroaniline (PNA). The compound PCINH shows good antifungal and antibacterial activity against Aspergillus niger and gram-positive bacteria Bacillus subtilis, respectively. The compound also shows good antituberculosis activity against Mycobacterium tuberculosis H37Rv using the microplate alamar blue assay (MABA).

A draft map of the human proteome.

The availability of human genome sequence has transformed biomedical research over the past decade. However, an equivalent map for the human proteome with direct measurements of proteins and peptides does not exist yet. Here we present a draft map of the human proteome using high-resolution Fourier-transform mass spectrometry. In-depth proteomic profiling of 30 histologically normal human samples, including 17 adult tissues, 7 fetal tissues and 6 purified primary haematopoietic cells, resulted in identification of proteins encoded by 17,294 genes accounting for approximately 84% of the total annotated protein-coding genes in humans. A unique and comprehensive strategy for proteogenomic analysis enabled us to discover a number of novel protein-coding regions, which includes translated pseudogenes, non-coding RNAs and upstream open reading frames. This large human proteome catalogue (available as an interactive web-based resource at http://www.humanproteomemap.org) will complement available human genome and transcriptome data to accelerate biomedical research in health and disease.

Regulation of PPAR-alpha pathway by Dicer revealed through proteomic analysis.

Dicer is a crucial RNase III enzyme in miRNA biogenesis pathway. Although numerous studies have been carried out to investigate the role of miRNAs and Dicer in the regulation of biological processes, few studies have examined proteomic alterations upon knockout of Dicer. We employed a Cre-loxP-based inducible knockout mouse system to investigate the proteome regulated by Dicer-dependent miRNAs. We utilized spiked liver lysates from metabolically labeled mice to quantify the subtle changes in the liver proteome upon deletion of Dicer. We identified 2137 proteins using high resolution tandem mass spectrometry analysis. The upregulated proteins included several enzymes involved in peroxisomal ß-oxidation of fatty acids and a large majority of the upregulated proteins involved in lipid metabolism were known PPARα targets. MRM-based assays were carried out to confirm the upregulation of enzymes including peroxisomal bifunctional enzyme, phosphoenolpyruvate carboxykinase 1, cytochrome P450 3A13, cytochrome P450 3A41 and myristoylated alanine-rich protein kinase C substrate. Further, miRNA-124 which is predicted to regulate expression of peroxisomal bifunctional enzyme was confirmed to be downregulated in the Dicer knockout mice. Our study demonstrates the strength of coupling knockout mouse models and quantitative proteomic strategies to investigate functions of individual proteins in vivo. BIOLOGICAL SIGNIFICANCE: Dicer dependent miRNA biogenesis is the major pathway for generation of mature miRNAs. We developed SILAC mouse-based proteomics screen to identify protein targets of Dicer-dependent miRNAs in liver of Dicer knockout mice. We spiked liver lysates of induced and uninduced Dicer knockout mice with liver lysate of SILAC labeled mice for identification of dysregulated proteome. We quantitated 1217 proteins of which 257 were upregulated in induced Dicer knockout mice. We observed enrichment of PPAR-α targets and proteins involved in lipid metabolism among upregulated proteins. We further carried out MRM-based validation of peroxisomal bifunctional enzyme, phosphoenolpyruvate carboxykinase 1, Cyp3A13, Cyp3A41 and myristoylated alanine-rich protein kinase C substrate. We further validated upregulation of peroxisomal bifunctional enzyme using Western blot analysis and downregulation of its predicted upstream miRNA, miR-124 using qRT-PCR. Our study demonstrates that upon ablation of Dicer, certain Dicer-dependent miRNAs are dysregulated which result in dysregulation of their target proteins such as proteins associated with lipid metabolism. Our study illustrates the use of SILAC strategy for quantitative proteomic investigations of animal model systems.

Proteomic analysis of human osteoarthritis synovial fluid.

BACKGROUND: Osteoarthritis is a chronic musculoskeletal disorder characterized mainly by progressive degradation of the hyaline cartilage. Patients with osteoarthritis often postpone seeking medical help, which results in the diagnosis being made at an advanced stage of cartilage destruction. Sustained efforts are needed to identify specific markers that might help in early diagnosis, monitoring disease progression and in improving therapeutic outcomes. We employed a multipronged proteomic approach, which included multiple fractionation strategies followed by high resolution mass spectrometry analysis to explore the proteome of synovial fluid obtained from osteoarthritis patients. In addition to the total proteome, we also enriched glycoproteins from synovial fluid using lectin affinity chromatography. RESULTS: We identified 677 proteins from synovial fluid of patients with osteoarthritis of which 545 proteins have not been previously reported. These novel proteins included ADAM-like decysin 1 (ADAMDEC1), alanyl (membrane) aminopeptidase (ANPEP), CD84, fibulin 1 (FBLN1), matrix remodelling associated 5 (MXRA5), secreted phosphoprotein 2 (SPP2) and spondin 2 (SPON2). We identified 300 proteins using lectin affinity chromatography, including the glycoproteins afamin (AFM), attractin (ATRN), fibrillin 1 (FBN1), transferrin (TF), tissue inhibitor of metalloproteinase 1 (TIMP1) and vasorin (VSN). Gene ontology analysis confirmed that a majority of the identified proteins were extracellular and are mostly involved in cell communication and signaling. We also confirmed the expression of ANPEP, dickkopf WNT signaling pathway inhibitor 3 (DKK3) and osteoglycin (OGN) by multiple reaction monitoring (MRM) analysis of osteoarthritis synovial fluid samples. CONCLUSIONS: We present an in-depth analysis of the synovial fluid proteome from patients with osteoarthritis. We believe that the catalog of proteins generated in this study will further enhance our knowledge regarding the pathophysiology of osteoarthritis and should assist in identifying better biomarkers for early diagnosis.

Proteogenomic analysis of pathogenic yeast Cryptococcus neoformans using high resolution mass spectrometry.

BACKGROUND: Cryptococcus neoformans, a basidiomycetous fungus of universal occurrence, is a significant opportunistic human pathogen causing meningitis. Owing to an increase in the number of immunosuppressed individuals along with emergence of drug-resistant strains, C. neoformans is gaining importance as a pathogen. Although, whole genome sequencing of three varieties of C. neoformans has been completed recently, no global proteomic studies have yet been reported. RESULTS: We performed a comprehensive proteomic analysis of C. neoformans var. grubii (Serotype A), which is the most virulent variety, in order to provide protein-level evidence for computationally predicted gene models and to refine the existing annotations. We confirmed the protein-coding potential of 3,674 genes from a total of 6,980 predicted protein-coding genes. We also identified 4 novel genes and corrected 104 predicted gene models. In addition, our studies led to the correction of translational start site, splice junctions and reading frame used for translation in a number of proteins. Finally, we validated a subset of our novel findings by RT-PCR and sequencing. CONCLUSIONS: Proteogenomic investigation described here facilitated the validation and refinement of computationally derived gene models in the intron-rich genome of C. neoformans, an important fungal pathogen in humans.

Differential proteomic analysis of synovial fluid from rheumatoid arthritis and osteoarthritis patients.

BACKGROUND: Rheumatoid arthritis and osteoarthritis are two common musculoskeletal disorders that affect the joints. Despite high prevalence rates, etiological factors involved in these disorders remain largely unknown. Dissecting the molecular aspects of these disorders will significantly contribute to improving their diagnosis and clinical management. In order to identify proteins that are differentially expressed between these two conditions, a quantitative proteomic profiling of synovial fluid obtained from rheumatoid arthritis and osteoarthritis patients was carried out by using iTRAQ labeling followed by high resolution mass spectrometry analysis. RESULTS: We have identified 575 proteins out of which 135 proteins were found to be differentially expressed by ≥3-fold in the synovial fluid of rheumatoid arthritis and osteoarthritis patients. Proteins not previously reported to be associated with rheumatoid arthritis including, coronin-1A (CORO1A), fibrinogen like-2 (FGL2), and macrophage capping protein (CAPG) were found to be upregulated in rheumatoid arthritis. Proteins such as CD5 molecule-like protein (CD5L), soluble scavenger receptor cysteine-rich domain-containing protein (SSC5D), and TTK protein kinase (TTK) were found to be upregulated in the synovial fluid of osteoarthritis patients. We confirmed the upregulation of CAPG in rheumatoid arthritis synovial fluid by multiple reaction monitoring assay as well as by Western blot. Pathway analysis of differentially expressed proteins revealed a significant enrichment of genes involved in glycolytic pathway in rheumatoid arthritis. CONCLUSIONS: We report here the largest identification of proteins from the synovial fluid of rheumatoid arthritis and osteoarthritis patients using a quantitative proteomics approach. The novel proteins identified from our study needs to be explored further for their role in the disease pathogenesis of rheumatoid arthritis and osteoarthritis.Sartaj Ahmad and Raja Sekhar Nirujogi contributed equally to this article.

Identification of head and neck squamous cell carcinoma biomarker candidates through proteomic analysis of cancer cell secretome.

Protein biomarker discovery for early detection of head and neck squamous cell carcinoma (HNSCC) is a crucial unmet need to improve patient outcomes. Mass spectrometry-based proteomics has emerged as a promising tool for identification of biomarkers in different cancer types. Proteins secreted from cancer cells can serve as potential biomarkers for early diagnosis. In the current study, we have used isobaric tag for relative and absolute quantitation (iTRAQ) labeling methodology coupled with high resolution mass spectrometry to identify and quantitate secreted proteins from a panel of head and neck carcinoma cell lines. In all, we identified 2,472 proteins, of which 225 proteins were secreted at higher or lower abundance in HNSCC-derived cell lines. Of these, 148 were present in higher abundance and 77 were present in lower abundance in the cancer-cell derived secretome. We detected a higher abundance of some previously known markers for HNSCC including insulin like growth factor binding protein 3, IGFBP3 (11-fold) and opioid growth factor receptor, OGFR (10-fold) demonstrating the validity of our approach. We also identified several novel secreted proteins in HNSCC including olfactomedin-4, OLFM4 (12-fold) and hepatocyte growth factor activator, HGFA (5-fold). IHC-based validation was conducted in HNSCC using tissue microarrays which revealed overexpression of IGFBP3 and OLFM4 in 70% and 75% of the tested cases, respectively. Our study illustrates quantitative proteomics of secretome as a robust approach for identification of potential HNSCC biomarkers. This article is part of a Special Issue entitled: An Updated Secretome.

NetSlim: high-confidence curated signaling maps.

We previously developed NetPath as a resource for comprehensive manually curated signal transduction pathways. The pathways in NetPath contain a large number of molecules and reactions which can sometimes be difficult to visualize or interpret given their complexity. To overcome this potential limitation, we have developed a set of more stringent curation and inclusion criteria for pathway reactions to generate high-confidence signaling maps. NetSlim is a new resource that contains this 'core' subset of reactions for each pathway for easy visualization and manipulation. The pathways in NetSlim are freely available at http://www.netpath.org/netslim.