Next-Generation Sequencing (NGS) technologies and Genome-Wide Association Studies (GWAS) generate millions of reads and hundreds of datasets, and there is an urgent need for a better way to accurately interpret and distill such large amounts of data. Extensive pathway and network analysis allow for the discovery of highly significant pathways from a set of disease vs. healthy samples in the NGS and GWAS. Knowledge of activation of these processes will lead to elucidation of the complex biological pathways affected by drug treatment, to patient stratification studies of new and existing drug treatments, and to understanding the underlying anti-cancer drug effects. There are approximately 141 biological human pathway resources as of Jan 2012 according to the Pathguide database. However, most currently available resources do not contain disease, drug or organ specificity information such as disease-pathway, drug-pathway, and organ-pathway associations. Systematically integrating pathway, disease, drug and organ specificity together becomes increasingly crucial for understanding the interrelationships between signaling, metabolic and regulatory pathway, drug action, disease susceptibility, and organ specificity from high-throughput omics data (genomics, transcriptomics, proteomics and metabolomics).
Pre-eclampsia (PE), a severe pregnancy-specific disease characterized by the new onset of hypertension, proteinuria, edema, and a series of other systematic disorders, is a state of widespread mitochondrial dysfunction of the placenta.
In response to toxic stimuli, BCL2L11 (also known as BIM), a BH3-only protein, is released from its interaction with dynein light chain 1 (DYNLL1 also known as LC8) and can induce apoptosis by inactivating anti-apoptotic BCL2 proteins and by activating BAX-BAK1. Recently, we discovered that BCL2L11 interacts with BECN1 (Beclin 1), and that this interaction is facilitated by DYNLL1. BCL2L11 recruits BECN1 to microtubules by bridging BECN1 and DYNLL1, thereby inhibiting autophagy. In starvation conditions, BCL2L11 is phosphorylated by MAPK8/JNK and this phosphorylation abolishes the BCL2L11-DYNLL1 interaction, allowing dissociation of BCL2L11 and BECN1, thereby ameliorating autophagy inhibition. This finding demonstrates a novel function of BIM beyond its roles in apoptosis, highlighting the crosstalk between autophagy and apoptosis, and suggests that BCL2L11’s dual effects in inhibiting autophagy and promoting apoptosis may have important roles in disease pathogenesis.
Although bulk protein turnover has been measured with the use of stable isotope labeled tracers for over half a century, it is only recently that the same approach has become applicable to the level of the proteome, permitting analysis of the turnover of many proteins instead of single proteins or an aggregated protein pool. The optimal experimental design for turnover studies is dependent on the nature of the biological system under study, which dictates the choice of precursor label, protein pool sampling strategy, and treatment of data. In this review we discuss different approaches and, in particular, explore how complexity in experimental design and data processing increases as we shift from unicellular to multicellular systems, in particular animals.
ABSTRACT Microorganisms grow under a remarkable range of extreme conditions. Environmental transcriptomic and proteomic studies have highlighted metabolic pathways active in extremophilic communities. However, metabolites directly linked to their physiology are less well defined because metabolomics methods lag behind other omics technologies due to a wide range of experimental complexities often associated with the environmental matrix. We identified key metabolites associated with acidophilic and metal-tolerant microorganisms using stable isotope labeling coupled with untargeted, high-resolution mass spectrometry. We observed >3,500 metabolic features in biofilms growing in pH ~0.9 acid mine drainage solutions containing millimolar concentrations of iron, sulfate, zinc, copper, and arsenic. Stable isotope labeling improved chemical formula prediction by >50% for larger metabolites (>250 atomic mass units), many of which were unrepresented in metabolic databases and may represent novel compounds. Taurine and hydroxyectoine were identified and likely provide protection from osmotic stress in the biofilms. Community genomic, transcriptomic, and proteomic data implicate fungi in taurine metabolism. Leptospirillum group II bacteria decrease production of ectoine and hydroxyectoine as biofilms mature, suggesting that biofilm structure provides some resistance to high metal and proton concentrations. The combination of taurine, ectoine, and hydroxyectoine may also constitute a sulfur, nitrogen, and carbon currency in the communities. IMPORTANCE Microbial communities are central to many critical global processes and yet remain enigmatic largely due to their complex and distributed metabolic interactions. Metabolomics has the possibility of providing mechanistic insights into the function and ecology of microbial communities. However, our limited knowledge of microbial metabolites, the difficulty of identifying metabolites from complex samples, and the inability to link metabolites directly to community members have proven to be major limitations in developing advances in systems interactions. Here, we show that combining stable-isotope-enabled metabolomics with genomics, transcriptomics, and proteomics can illuminate the ecology of microorganisms at the community scale.
The nematocyst is a complex intracellular structure unique to Cnidaria. When triggered to discharge, the nematocyst explosively releases a long spiny, tubule that delivers an often highly venomous mixture of components. The box jellyfish, Chironex fleckeri, produces exceptionally potent and rapid-acting venom and its stings to humans cause severe localized and systemic effects that are potentially life-threatening. In an effort to identify toxins that could be responsible for the serious health effects caused by C. fleckeri and related species, we used a proteomic approach to profile the protein components of C. fleckeri venom. Collectively, 61 proteins were identified, including toxins and proteins important for nematocyte development and nematocyst formation (nematogenesis). The most abundant toxins identified were isoforms of a taxonomically restricted family of potent cnidarian proteins. These toxins are associated with cytolytic, nociceptive, inflammatory, dermonecrotic and lethal properties and expansion of this important protein family goes some way to explaining the destructive and potentially fatal effects of C. fleckeri venom. Venom proteins and their post-translational modifications (PTMs) were further characterized using toxin-specific antibodies and phosphoprotein/glycoprotein-specific stains. Results indicated that glycosylation is a common PTM of the toxin family while a lack of cross-reactivity by toxin-specific antibodies infers there is significant divergence in structure and possibly function among family members. This study provides insight into the depth and diversity of protein toxins produced by harmful box jellyfish and represents the first description of a cubozoan jellyfish venom proteome.
BACKGROUND: Pseudomonas putida exerts a filamentous phenotype in response to environmental stress conditions that are encountered during its natural life cycle. This study assessed whether P. putida filamentation could confer survival advantages. Filamentation of P. putida was induced through culturing at low shaking speed and was compared to culturing in high shaking speed conditions, after which whole proteomic analysis and stress exposure assays were performed. RESULTS: P. putida grown in filament-inducing conditions showed increased resistance to heat and saline stressors compared to non-filamented cultures. Proteomic analysis showed a significant metabolic change and a pronounced induction of the heat shock protein IbpA and recombinase RecA in filament-inducing conditions. Our data further indicated that the associated heat shock resistance, but not filamentation, was dependent of RecA. CONCLUSIONS: This study provides insights into the altered metabolism of P. putida in filament-inducing conditions, and indicates that the formation of filaments could potentially be utilized by P. putida as a survival strategy in its hostile, recurrently changing habitat.
Extracellular vesicles are emerging as a potent mechanism of intercellular communication since they can systemically exchange genetic and protein material between cells. Tetraspanin molecules are commonly used as protein markers of extracellular vesicles, although their role in the unexplored mechanisms of cargo selection into exosomes has not been addressed. For that purpose, we have characterized the intracellular TEM interactome by high-throughput mass-spectrometry, in both human lymphoblasts and their derived exosomes, revealing a clear pattern of interaction networks. Proteins interacting with TEM receptors cytoplasmic regions presented a considerable degree of overlap, although some highly specific CD81 tetraspanin ligands, such as Rac GTPase, were detected. Quantitative proteomics showed that TEM ligands account for a great proportion of the exosome proteome and that a selective repertoire of CD81-associated molecules, including Rac, is not correctly routed to exosomes in cells from CD81-deficient animals. Our data provide evidence that insertion into TEMs may be necessary for protein inclusion into the exosome structure.
Alzheimer’s disease is a worldwide metabolic disease and an economically costly diseases to society, so more medicines need to be developed to treat this disease. Huperzine A, a novel lycopodium alkaloid isolated from tranditional Chinese medicine Huperzia serrata (Qian Ceng Ta), has been shown to possess multiple neuroprotective effects for Alzheimer’s disease, but the precise pharmacological mechanism of huperzine A is unclear and need to be further investigated. In this study, proteins from untreated N2a cells (Con group), cells pre-incubated with huperzine A followed by Aβ (1-42) oligomers treatment (HupA group) and cells treated with Aβ (1-42) oligomers (Aβ group) with 5 biological replicates in each cohort, were processed in centrifugal proteomic reactor and quantified by label-free quantitation. A total of 2860 proteins were quantified with high confidence, and 198 proteins were significantly changed (with P-value <0.05) between HupA and Aβ cohorts. The pathway and direct protein-protein interaction network analysis showed that huperzine A protects N2a cells against Aβ oligomer-induced cell death by down-regulation of cellular tumor antigen p53 (Trp53) expression.
BACKGROUND: MultiAlign is a free software tool that aligns multiple liquid chromatography-mass spectrometry datasets to one another by clustering mass and chromatographic elution features across datasets. Applicable to both label-free proteomics and metabolomics comparative analyses, the software can be operated in several modes. For example, clustered features can be matched to a reference database to identify analytes, used to generate abundance profiles, linked to tandem mass spectra based on parent precursor masses, and culled for targeted liquid chromatography-tandem mass spectrometric analysis. MultiAlign is also capable of tandem mass spectral clustering to describe proteome structure and find similarity in subsequent sample runs. RESULTS: MultiAlign was applied to two large proteomics datasets obtained from liquid chromatography-mass spectrometry analyses of environmental samples. Peptides in the datasets for a microbial community that had a known metagenome were identified by matching mass and elution time features to those in an established reference peptide database. Results compared favorably with those obtained using existing tools such as VIPER, but with the added benefit of being able to trace clusters of peptides across conditions to existing tandem mass spectra. MultiAlign was further applied to detect clusters across experimental samples derived from a reactor biomass community for which no metagenome was available. Several clusters were culled for further analysis to explore changes in the community structure. Lastly, MultiAlign was applied to liquid chromatography-mass spectrometry-based datasets obtained from a previously published study of wild type and mitochondrial fatty acid oxidation enzyme knockdown mutants of human hepatocarcinoma to demonstrate its utility for analyzing metabolomics datasets. CONCLUSION: MultiAlign is an efficient software package for finding similar analytes across multiple liquid chromatography-mass spectrometry feature maps, as demonstrated here for both proteomics and metabolomics experiments. The software is particularly useful for proteomic studies where little or no genomic context is known, such as with environmental proteomics.