Discordant signaling and autophagy response to fasting in hearts of obese mice: Implications for ischemia tolerance.

Autophagy is regulated by nutrient and energy status and plays an adaptive role during nutrient deprivation and ischemic stress. Metabolic syndrome (MetS) is a hypernutritive state characterized by obesity, dyslipidemia, elevated fasting blood glucose levels, and insulin resistance. It has also been associated with impaired autophagic flux and larger-sized infarcts. We hypothesized that diet-induced obesity (DIO) affects nutrient sensing, explaining the observed cardiac impaired autophagy. We subjected male friend virus B NIH (FVBN) mice to a high-fat diet, which resulted in increased weight gain, fat deposition, hyperglycemia, insulin resistance, and larger infarcts after myocardial ischemia-reperfusion. Autophagic flux was impaired after 4 wk on a high-fat diet. To interrogate nutrient-sensing pathways, DIO mice were subjected to overnight fasting, and hearts were processed for biochemical and proteomic analysis. Obese mice failed to upregulate LC3-II or to clear p62/SQSTM1 after fasting, although mRNA for LC3B and p62/SQSTM1 were appropriately upregulated in both groups, demonstrating an intact transcriptional response to fasting. Energy- and nutrient-sensing signal transduction pathways [AMPK and mammalian target of rapamycin (mTOR)] also responded appropriately to fasting, although mTOR was more profoundly suppressed in obese mice. Proteomic quantitative analysis of the hearts under fed and fasted conditions revealed broad changes in protein networks involved in oxidative phosphorylation, autophagy, oxidative stress, protein homeostasis, and contractile machinery. In many instances, the fasting response was quite discordant between lean and DIO mice. Network analysis implicated the peroxisome proliferator-activated receptor and mTOR regulatory nodes. Hearts of obese mice exhibited impaired autophagy, altered proteome, and discordant response to nutrient deprivation.

Metaproteomic analysis using the Galaxy framework.

Metaproteomics characterizes proteins expressed by microorganism communities (microbiome) present in environmental samples or a host organism (e.g. human), revealing insights into the molecular functions conferred by these communities. Compared to conventional proteomics, metaproteomics presents unique data analysis challenges, including the use of large protein databases derived from hundreds or thousands of organisms, as well as numerous processing steps to ensure high data quality. These challenges limit the use of metaproteomics for many researchers. In response, we have developed an accessible and flexible metaproteomics workflow within the Galaxy bioinformatics framework. Via analysis of human oral tissue exudate samples, we have established a modular Galaxy-based workflow that automates a reduction method for searching large sequence databases, enabling comprehensive identification of host proteins (human) as well as "meta-proteins" from the nonhost organisms. Downstream, automated processing steps enable basic local alignment search tool analysis and evaluation/visualization of peptide sequence match quality, maximizing confidence in results. Outputted results are compatible with tools for taxonomic and functional characterization (e.g. Unipept, MEGAN5). Galaxy also allows for the sharing of complete workflows with others, promoting reproducibility and also providing a template for further modification and enhancement. Our results provide a blueprint for establishing Galaxy as a solution for metaproteomic data analysis. All MS data have been deposited in the ProteomeXchange with identifier PXD001655 (http://proteomecentral.proteomexchange.org/dataset/PXD001655).

A two-step database search method improves sensitivity in peptide sequence matches for metaproteomics and proteogenomics studies.

Large databases (>10(6) sequences) used in metaproteomic and proteogenomic studies present challenges in matching peptide sequences to MS/MS data using database-search programs. Most notably, strict filtering to avoid false-positive matches leads to more false negatives, thus constraining the number of peptide matches. To address this challenge, we developed a two-step method wherein matches derived from a primary search against a large database were used to create a smaller subset database. The second search was performed against a target-decoy version of this subset database merged with a host database. High confidence peptide sequence matches were then used to infer protein identities. Applying our two-step method for both metaproteomic and proteogenomic analysis resulted in twice the number of high confidence peptide sequence matches in each case, as compared to the conventional one-step method. The two-step method captured almost all of the same peptides matched by the one-step method, with a majority of the additional matches being false negatives from the one-step method. Furthermore, the two-step method improved results regardless of the database search program used. Our results show that our two-step method maximizes the peptide matching sensitivity for applications requiring large databases, especially valuable for proteogenomics and metaproteomics studies.

Energetic rationale for an unexpected and abrupt reversal of guanidinium chloride-induced unfolding of peptide deformylase.

Peptide deformylase (PDF) catalyzes the removal of formyl group from the N-terminal methionine residues of nascent proteins in prokaryotes, and this enzyme is a high priority target for antibiotic design. In pursuit of delineating the structural-functional features of Escherichia coli PDF (EcPDF), we investigated the mechanistic pathway for the guanidinium chloride (GdmCl)-induced unfolding of the enzyme by monitoring the secondary structural changes via CD spectroscopy. The experimental data revealed that EcPDF is a highly stable enzyme, and it undergoes slow denaturation in the presence of varying concentrations of GdmCl. The most interesting aspect of these studies has been the abrupt reversal of the unfolding pathway at low to moderate concentrations of the denaturant, but not at high concentration. An energetic rationale for such an unprecedented feature in protein chemistry is offered.

A strategy for designing "multi-prong" enzyme inhibitors by incorporating selective ligands to the liposomal surface.

We offer a novel strategy for designing "multi-prong" inhibitors of enzymes by incorporating selective ligands on the liposomal surface.

Evaluating the potential of a novel oral lesion exudate collection method coupled with mass spectrometry-based proteomics for oral cancer biomarker discovery.

INTRODUCTION: Early diagnosis of Oral Squamous Cell Carcinoma (OSCC) increases the survival rate of oral cancer. For early diagnosis, molecular biomarkers contained in samples collected non-invasively and directly from at-risk oral premalignant lesions (OPMLs) would be ideal. METHODS: In this pilot study we evaluated the potential of a novel method using commercial PerioPaper absorbent strips for non-invasive collection of oral lesion exudate material coupled with mass spectrometry-based proteomics for oral cancer biomarker discovery. RESULTS: Our evaluation focused on three core issues. First, using an "on-strip" processing method, we found that protein can be isolated from exudate samples in amounts compatible with large-scale mass spectrometry-based proteomic analysis. Second, we found that the OPML exudate proteome was distinct from that of whole saliva, while being similar to the OPML epithelial cell proteome, demonstrating the fidelity of our exudate collection method. Third, in a proof-of-principle study, we identified numerous, inflammation-associated proteins showing an expected increase in abundance in OPML exudates compared to healthy oral tissue exudates. These results demonstrate the feasibility of identifying differentially abundant proteins from exudate samples, which is essential for biomarker discovery studies. CONCLUSIONS: Collectively, our findings demonstrate that our exudate collection method coupled with mass spectrometry-based proteomics has great potential for transforming OSCC biomarker discovery and clinical diagnostics assay development.

Quantitative proteomics reveals myosin and actin as promising saliva biomarkers for distinguishing pre-malignant and malignant oral lesions.

BACKGROUND: Oral cancer survival rates increase significantly when it is detected and treated early. Unfortunately, clinicians now lack tests which easily and reliably distinguish pre-malignant oral lesions from those already transitioned to malignancy. A test for proteins, ones found in non-invasively-collected whole saliva and whose abundances distinguish these lesion types, would meet this critical need. METHODOLOGY/PRINCIPAL FINDINGS: To discover such proteins, in a first-of-its-kind study we used advanced mass spectrometry-based quantitative proteomics analysis of the pooled soluble fraction of whole saliva from four subjects with pre-malignant lesions and four with malignant lesions. We prioritized candidate biomarkers via bioinformatics and validated selected proteins by western blotting. Bioinformatic analysis of differentially abundant proteins and initial western blotting revealed increased abundance of myosin and actin in patients with malignant lesions. We validated those results by additional western blotting of individual whole saliva samples from twelve other subjects with pre-malignant oral lesions and twelve with malignant oral lesions. Sensitivity/specificity values for distinguishing between different lesion types were 100%/75% (p = 0.002) for actin, and 67%/83% (p<0.00001) for myosin in soluble saliva. Exfoliated epithelial cells from subjects' saliva also showed increased myosin and actin abundance in those with malignant lesions, linking our observations in soluble saliva to abundance differences between pre-malignant and malignant cells. CONCLUSIONS/SIGNIFICANCE: Salivary actin and myosin abundances distinguish oral lesion types with sensitivity and specificity rivaling other non-invasive oral cancer tests. Our findings provide a promising starting point for the development of non-invasive and inexpensive salivary tests to reliably detect oral cancer early.

Structural analysis of charge discrimination in the binding of inhibitors to human carbonic anhydrases I and II.

Despite the similarity in the active site pockets of carbonic anhydrase (CA) isozymes I and II, the binding affinities of benzenesulfonamide inhibitors are invariably higher with CA II as compared to CA I. To explore the structural basis of this molecular recognition phenomenon, we have designed and synthesized simple benzenesulfonamide inhibitors substituted at the para position with positively charged, negatively charged, and neutral functional groups, and we have determined the affinities and X-ray crystal structures of their enzyme complexes. The para-substituents are designed to bind in the midsection of the 15 A deep active site cleft, where interactions with enzyme residues and solvent molecules are possible. We find that a para-substituted positively charged amino group is more poorly tolerated in the active site of CA I compared with CA II. In contrast, a para-substituted negatively charged carboxylate substituent is tolerated equally well in the active sites of both CA isozymes. Notably, enzyme-inhibitor affinity increases upon neutralization of inhibitor charged groups by amidation or esterification. These results inform the design of short molecular linkers connecting the benzenesulfonamide group and a para-substituted tail group in "two-prong" CA inhibitors: an optimal linker segment will be electronically neutral, yet capable of engaging in at least some hydrogen bond interactions with protein residues and/or solvent. Microcalorimetric data reveal that inhibitor binding to CA I is enthalpically less favorable and entropically more favorable than inhibitor binding to CA II. This contrasting behavior may arise in part from differences in active site desolvation and the conformational entropy of inhibitor binding to each isozyme active site.