AMPK Is a Negative Regulator of the Warburg Effect and Suppresses Tumor Growth In Vivo

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Highlights? Loss of AMPKα1 cooperates with the Myc oncogene to accelerate lymphomagenesis ? AMPKα dysfunction enhances aerobic glycolysis (Warburg effect) ? Inhibiting HIF-1α reverses the metabolic effects of AMPKα loss ? HIF-1α mediates the growth advantage of tumors with reduced AMPK signaling     

Metformin Antagonizes Cancer Cell Proliferation by Suppressing Mitochondrial-Dependent Biosynthesis

Metformin is a biguanide widely prescribed to treat Type II diabetes that has gained interest as an antineoplastic agent. Recent work suggests that metformin directly antagonizes cancer cell growth through its actions on complex I of the mitochondrial electron transport chain (ETC). However, the mechanisms by which metformin arrests cancer cell proliferation remain poorly defined. Here we demonstrate that the metabolic checkpoint kinases AMP-activated protein kinase (AMPK) and LKB1 are not required for the antiproliferative effects of metformin. Rather, metformin inhibits cancer cell proliferation by suppressing mitochondrial-dependent biosynthetic activity. We show that in vitro metformin decreases the flow of glucose- and glutamine-derived metabolic intermediates into the Tricarboxylic Acid (TCA) cycle, leading to reduced citrate production and de novo lipid biosynthesis. Tumor cells lacking functional mitochondria maintain lipid biosynthesis in the presence of metformin via glutamine-dependent reductive carboxylation, and display reduced sensitivity to metformin-induced proliferative arrest. Our data indicate that metformin inhibits cancer cell proliferation by suppressing the production of mitochondrial-dependent metabolic intermediates required for cell growth, and that metabolic adaptations that bypass mitochondrial-dependent biosynthesis may provide a mechanism of tumor cell resistance to biguanide activity.     

HPTLC and GC/MS Study of Amaryllidaceae Alkaloids of Two Narcissus Species

In this article, we report on the alkaloid profile and dynamic of alkaloid content and diversity in two Narcissus plants at different stages of development. The alkaloid profile of the two Narcissus species was investigated by GC/MS and HPTLC. Fifty eight Amaryllidaceae alkaloids were detected, and 25 of them were identified in the different organs of N. tazetta and N. papyraceus. The alkaloid 3‐O‐methyl‐9‐O‐demethylmaritidine is tentatively identified here for the first time from the Amaryllidaceae family, and four alkaloids (tazettamide, sternbergine, 1‐O‐acetyllycorine, 2,11‐didehydro‐2‐dehydroxylycorine) are tentatively identified for the first time in the genus Narcissus. The different organs of the two species analyzed showed remarkable differences in their alkaloid pattern, type of biosynthesis, main alkaloid and number of alkaloids. Lycorine‐type alkaloids dominated the alkaloid, metabolism in N. papyraceus, while alkaloids of narciclasine‐, galanthamine‐ and homolycorine‐types were found only in the species N. tazetta L.     

Analysis of the tryptic search space in UniProt databases

In this article, we provide a comprehensive study of the content of the Universal Protein Resource (UniProt) protein data sets for human and mouse. The tryptic search spaces of the UniProtKB (UniProt knowledgebase) complete proteome sets were compared with other data sets from UniProtKB and with the corresponding International Protein Index, reference sequence, Ensembl, and UniRef100 (where UniRef is UniProt reference clusters) organism‐specific data sets. All protein forms annotated in UniProtKB (both the canonical sequences and isoforms) were evaluated in this study. In addition, natural and disease‐associated amino acid variants annotated in UniProtKB were included in the evaluation. The peptide unicity was also evaluated for each data set. Furthermore, the peptide information in the UniProtKB data sets was also compared against the available peptide‐level identifications in the main MS‐based proteomics repositories. Identifying the peptides observed in these repositories is an important resource of information for protein databases as they provide supporting evidence for the existence of otherwise predicted proteins. Likewise, the repositories could use the information available in UniProtKB to direct reprocessing efforts on specific sets of peptides/proteins of interest. In summary, we provide comprehensive information about the different organism‐specific sequence data sets available from UniProt, together with the pros and cons for each, in terms of search space for MS‐based bottom‐up proteomics workflows. The aim of the analysis is to provide a clear view of the tryptic search space of UniProt and other protein databases to enable scientists to select those most appropriate for their purposes.     

Electrospun poly-l-lactide nanofibres as scaffolds for tissue engineering]

Tissue engineering is a promising tool for treating structural and functional defects in bone and cartilage. To provide optimal conditions for three-dimensional cell growth the use of a scaffold is necessary. The aim of the study was to test the potential application of an electrospun poly (l-lactide)-nanostructured scaffold as a matrix for tissue engineering. Matrices were seeded with human osteosarcoma MG-63 cells and cultivated for 14 days. Cells showed a clear preference for growth along the nanofibres, and demonstrated no signs of degeneration or apoptosis. The fine structure of electrospun nanofibres makes them an ideal scaffold for tissue engineering, in particular for cartilage repair. They can be "doped" with growth factors, medications, etc., and are both biocompatible and biodegradable.     

Validation data for periprosthetic bone remodelling theories

Periprosthetic adaptive bone remodelling after total hip arthroplasty (THA) has been frequently simulated in computer models, combining bone remodelling theory with finite element analysis. Unfortunately, there still subsist a lack of clinical data, which are necessary for validation of these simulation results. Therefore, the objective of the current project is to collect prospective volumetric bone density data with a clinical computerized tomography study in seven patients after THA. A retrospective study 12 years after implantation in 11 patients was added. A data set of about 100 000 bone voxels for each femur was collected. In all prospective cases, the predominant change is seen during the first year. The average density reduction in the horizontal slices was between 50 and 150 Hounsfield units (HU) (approx. 10%; p<0.001) after 2 years. Loss of density is particularly strong distal of the minor trochanter and decreases from proximal to distal.

For the 12 years retrospective study, the contralateral femur provided the control. Similar trends comparable to the prospective 2-year follow-up CT density values were seen in most cases with density reductions of up to 400 HU (30%). However, in one of these cases there was no difference between the operated and the control density.

As far as we are aware, this is the first collection of fully prospective 3D validation data in vivo for periprosthetic adaptive bone remodelling theories. The data are also unique as they are suitable for direct patient-specific 3D finite element meshing and individual weight-related loading.     

Published and Perished? The Influence of the Searched Protein Database on the Long-Term Storage of Proteomics Data

In proteomics, protein identifications are reported and stored using an unstable reference system: protein identifiers. These proprietary identifiers are created individually by every protein database and can change or may even be deleted over time. To estimate the effect of the searched protein sequence database on the long-term storage of proteomics data we analyzed the changes of reported protein identifiers from all public experiments in the Proteomics Identifications (PRIDE) database by November 2010. To map the submitted protein identifier to a currently active entry, two distinct approaches were used. The first approach used the Protein Identifier Cross Referencing (PICR) service at the EBI, which maps protein identifiers based on 100% sequence identity. The second one (called logical mapping algorithm) accessed the source databases and retrieved the current status of the reported identifier. Our analysis showed the differences between the main protein databases (International Protein Index (IPI), UniProt Knowledgebase (UniProtKB), National Center for Biotechnological Information nr database (NCBI nr), and Ensembl) in respect to identifier stability. For example, whereas 20% of submitted IPI entries were deleted after two years, virtually all UniProtKB entries remained either active or replaced. Furthermore, the two mapping algorithms produced markedly different results. For example, the PICR service reported 10% more IPI entries deleted compared with the logical mapping algorithm. We found several cases where experiments contained more than 10% deleted identifiers already at the time of publication. We also assessed the proportion of peptide identifications in these data sets that still fitted the originally identified protein sequences. Finally, we performed the same overall analysis on all records from IPI, Ensembl, and UniProtKB: two releases per year were used, from 2005. This analysis showed for the first time the true effect of changing protein identifiers on proteomics data. Based on these findings, UniProtKB seems the best database for applications that rely on the long-term storage of proteomics data.     

The mzTab Data Exchange Format: Communicating Mass-spectrometry-based Proteomics and Metabolomics Experimental Results to a Wider Audience

The HUPO Proteomics Standards Initiative has developed several standardized data formats to facilitate data sharing in mass spectrometry (MS)-based proteomics. These allow researchers to report their complete results in a unified way. However, at present, there is no format to describe the final qualitative and quantitative results for proteomics and metabolomics experiments in a simple tabular format. Many downstream analysis use cases are only concerned with the final results of an experiment and require an easily accessible format, compatible with tools such as Microsoft Excel or R.We developed the mzTab file format for MS-based proteomics and metabolomics results to meet this need. mzTab is intended as a lightweight supplement to the existing standard XML-based file formats (mzML, mzIdentML, mzQuantML), providing a comprehensive summary, similar in concept to the supplemental material of a scientific publication. mzTab files can contain protein, peptide, and small molecule identifications together with experimental metadata and basic quantitative information. The format is not intended to store the complete experimental evidence but provides mechanisms to report results at different levels of detail. These range from a simple summary of the final results to a representation of the results including the experimental design. This format is ideally suited to make MS-based proteomics and metabolomics results available to a wider biological community outside the field of MS. Several software tools for proteomics and metabolomics have already adapted the format as an output format. The comprehensive mzTab specification document and extensive additional documentation can be found online.Mass spectrometry (MS)¹ has become a major analysis tool in the life sciences (1). It is currently used in different modes for several “omics” approaches, proteomics and metabolomics being the most prominent. In both disciplines, one major burden in the exchange, communication, and large-scale (re-) analysis of MS-based data is the significant number of software pipelines and, consequently, heterogeneous file formats used to process, analyze, and store these experimental results, including both identification and quantification data. Publication guidelines from scientific journals and funding agencies'' requirements for public data availability have led to an increasing amount of MS-based proteomics and metabolomics data being submitted to public repositories, such as those of the ProteomeXchange consortium (2) or, in the case of metabolomics, the resources from the nascent COSMOS (Coordination of Standards in Metabolomics) initiative (3).In the past few years, the Human Proteome Organization Proteomics Standards Initiative (PSI) has developed several vendor-neutral standard data formats to overcome the representation heterogeneity. The Human Proteome Organization PSI promotes the usage of three XML file formats to fully report the data coming from MS-based proteomics experiments (including related metadata): mzML (4) to store the “primary” MS data (the spectra and chromatograms), mzIdentML (5) to report peptide identifications and inferred protein identifications, and mzQuantML (6) to store quantitative information associated with these results.Even though the existence of the PSI standard data formats represents a huge step forward, these formats cannot address all use cases related to proteomics and metabolomics data exchange and sharing equally well. During the development of mzML, mzIdentML, and mzQuantML, the main focus lay on providing an exact and comprehensive representation of the gathered results. All three formats can be used within analysis pipelines and as interchange formats between independent analysis tools. It is thus vital that these formats be capable of storing the full data and analysis that led to the results. Therefore, all three formats result in relatively complex schemas, a clear necessity for adequate representation of the complexity found in MS-based data.An inevitable drawback of this approach is that data consumers can find it difficult to quickly retrieve the required information. Several application programming interfaces (APIs) have been developed to simplify software development based on these formats (7–9), but profound proteomics and bioinformatics knowledge still is required in order to use them efficiently and take full advantage of the comprehensive information contained.The new file format presented here, mzTab, aims to describe the qualitative and quantitative results for MS-based proteomics and metabolomics experiments in a consistent, simpler tabular format, abstracting from the mass spectrometry details. The format contains identifications, basic quantitative information, and related metadata. With mzTab''s flexible design, it is possible to report results at different levels ranging from a simple summary or subset of the complete information (e.g. the final results) to fairly comprehensive representation of the results including the experimental design. Many downstream analysis use cases are only concerned with the final results of an experiment in an easily accessible format that is compatible with tools such as Microsoft Excel® or R (10) and can easily be adapted by existing bioinformatics tools. Therefore, mzTab is ideally suited to make MS proteomics and metabolomics results available to the wider biological community, beyond the field of MS.mzTab follows a similar philosophy as the other tab-delimited format recently developed by the PSI to represent molecular interaction data, MITAB (11). MITAB is a simpler tab-delimited format, whereas PSI-MI XML (12), the more detailed XML-based format, holds the complete evidence. The microarray community makes wide use of the format MAGE-TAB (13), another example of such a solution that can cover the main use cases and, for the sake of simplicity, is often preferred to the XML standard format MAGE-ML (14). Additionally, in MS-based proteomics, several software packages, such as Mascot (15), OMSSA (16), MaxQuant (17), OpenMS/TOPP (18, 19), and SpectraST (20), also support the export of their results in a tab-delimited format next to a more complete and complex default format. These simple formats do not contain the complete information but are nevertheless sufficient for the most frequent use cases.mzTab has been designed with the same purpose in mind. It can be used alone or in conjunction with mzML (or other related MS data formats such as mzXML (21) or text-based peak list formats such as MGF), mzIdentML, and/or mzQuantML. Several highly successful concepts taken from the development process of mzIdentML and mzQuantML were adapted to the text-based nature of mzTab.In addition, there is a trend to perform more integrated experimental workflows involving both proteomics and metabolomics data. Thus, we developed a standard format that can represent both types of information in a single file.