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Proteins are the primary effectors of function in biology, and thus, complete knowledge of their structure and properties is fundamental to deciphering function in basic and translational research. The chemical diversity of proteins is expressed in their many proteoforms, which result from combinations of genetic polymorphisms, RNA splice variants, and posttranslational modifications. This knowledge is foundational for the biological complexes and networks that control biology yet remains largely unknown. We propose here an ambitious initiative to define the human proteome, that is, to generate a definitive reference set of the proteoforms produced from the genome. Several examples of the power and importance of proteoform-level knowledge in disease-based research are presented along with a call for improved technologies in a two-pronged strategy to the Human Proteoform Project.

The Consortium for Top-Down Proteomics (www.topdownproteomics.org) launched the present study to assess the current state of top-down mass spectrometry (TD MS) and middle-down mass spectrometry (MD MS) for characterizing monoclonal antibody (mAb) primary structures, including their modifications. To meet the needs of the rapidly growing therapeutic antibody market, it is important to develop analytical strategies to characterize the heterogeneity of a therapeutic product's primary structure accurately and reproducibly. The major objective of the present study is to determine whether current TD/MD MS technologies and protocols can add value to the more commonly employed bottom-up (BU) approaches with regard to confirming protein integrity, sequencing variable domains, avoiding artifacts, and revealing modifications and their locations. We also aim to gather information on the common TD/MD MS methods and practices in the field. A panel of three mAbs was selected and centrally provided to 20 laboratories worldwide for the analysis: Sigma mAb standard (SiLuLite), NIST mAb standard, and the therapeutic mAb Herceptin (trastuzumab). Various MS instrument platforms and ion dissociation techniques were employed. The present study confirms that TD/MD MS tools are available in laboratories worldwide and provide complementary information to the BU approach that can be crucial for comprehensive mAb characterization. The current limitations, as well as possible solutions to overcome them, are also outlined. A primary limitation revealed by the results of the present study is that the expert knowledge in both experiment and data analysis is indispensable to practice TD/MD MS.

One gene can give rise to many functionally distinct proteoforms, each of which has a characteristic molecular mass. Top-down mass spectrometry enables the analysis of intact proteins and proteoforms. Here members of the Consortium for Top-Down Proteomics provide a decision tree that guides researchers to robust protocols for mass analysis of intact proteins (antibodies, membrane proteins and others) from mixtures of varying complexity. We also present cross-platform analytical benchmarks using a protein standard sample, to allow users to gauge their proficiency.

The Consortium for Top-Down Proteomics (CTDP) proposes a standardized notation, ProForma, for writing the sequence of fully characterized proteoforms. ProForma provides a means to communicate any proteoform by writing the amino acid sequence using standard one-letter notation and specifying modifications or unidentified mass shifts within brackets following certain amino acids. The notation is unambiguous, human-readable, and can easily be parsed and written by bioinformatic tools. This system uses seven rules and supports a wide range of possible use cases, ensuring compatibility and reproducibility of proteoform annotations. Standardizing proteoform sequences will simplify storage, comparison, and reanalysis of proteomic studies, and the Consortium welcomes input and contributions from the research community on the continued design and maintenance of this standard.

Despite decades of accumulated knowledge about proteins and their post-translational modifications (PTMs), numerous questions remain regarding their molecular composition and biological function. One of the most fundamental queries is the extent to which the combinations of DNA-, RNA- and PTM-level variations explode the complexity of the human proteome. Here, we outline what we know from current databases and measurement strategies including mass spectrometry-based proteomics. In doing so, we examine prevailing notions about the number of modifications displayed on human proteins and how they combine to generate the protein diversity underlying health and disease. We frame central issues regarding determination of protein-level variation and PTMs, including some paradoxes present in the field today. We use this framework to assess existing data and to ask the question, "How many distinct primary structures of proteins (proteoforms) are created from the 20,300 human genes?" We also explore prospects for improving measurements to better regularize protein-level biology and efficiently associate PTMs to function and phenotype.

Often considered benign, meningiomas represent 32% of intracranial tumors with three grades of malignancy defined by the World Health Organization (WHO) histology based classification. Malignant meningiomas are associated with less than 2 years median survival. The inability to predict recurrence and progression of meningiomas induces significant anxiety for patients and limits physicians in implementing prophylactic treatment approaches. This report presents an analytical approach to tissue characterization based on matrix-assisted laser desorption ionization time-of-flight (MALDI TOF) mass spectrometry imaging (MSI) which is introduced in an attempt to develop a reference database for predictive classification of brain tumors. This pilot study was designed to evaluate the potential of such an approach and to begin to address limitations of the current methodology. Five recurrent and progressive meningiomas for which surgical specimens were available from the original and progressed grades were selected and tested against nonprogressive high-grade meningiomas, high-grade gliomas, and nontumor brain specimens. The common profiling approach of data acquisition was compared to imaging and revealed significant benefits in spatially resolved acquisition for improved spectral definition. A preliminary classifier based on the support vector machine showed the ability to distinguish meningioma image spectra from the nontumor brain and from gliomas, a different type of brain tumor, and to enable class imaging of surgical tissue. Although the development of classifiers was shown to be sensitive to data preparation parameters such as recalibration and peak picking criteria, it 'also suggested the potential for maturing into a predictive algorithm if provided with a larger series of well-defined cases. 10.1021/ac100113w

Mass spectrometry imaging (MSI) acquires a grid of spatially resolved mass spectra and provides a molecular landscape of a tissue. This can have a myriad of uses: from basic tissue characterization to a comprehensive pathological diagnosis. We have developed a fast, inexpensive, histology-compatible tissue preparation method for matrix-assisted laser desorption/ionization (MALDI)-MSI, which overcomes current sample preparation-imposed limitations in image resolution. Tissue sections are prepared via simultaneous fixation and matrix deposition. This is accomplished by incorporating the MALDI matrix into solvents that preserve tissue integrity when applied according to standard histology procedures. This concept was expanded to include multiple histology protocols, thereby enabling analysis to be tailored to a variety of biomolecules and tissue types.

A spectroscopic investigation of the time course and products of NifS-mediated cluster assembly on wild-type NifU, wild-type and D37A NifU-1 and wild-type NifU-2 plus C-terminal domain fragments is reported. The assembly and transfer of clusters on NifU are compared with results reported for U- and Nfu-type scaffold proteins, and the need for two functional Fe-S cluster scaffolding domains on NifU is discussed.

Results demonstrate the ability of Isc homologue (sup)Nif IscA of Azotobacter vinelandii to bind iron and assemble iron-sulfur clusters through a NifS-directed pathway. Data indicate that (sup)Nif IscA lends itself as an alternative scaffold to NifU for the NifS-directed sequential assembly of iron-sulfur clusters.