Protein identification by spectral networks analysis

Antibiotic drug discovery

Due to the threat posed by the increase of highly resistant pathogenic bacteria, there is an urgent need for new antibiotics; all the more so since in the last 20 years, the approval for new antibacterial agents had decreased. The field of natural product discovery has undergone a tremendous development over the past few years. This has been the consequence of several new and revolutionizing drug discovery and development techniques, which is initiating a ‘New Age of Antibiotic Discovery’. In this review, we concentrate on the most significant discovery approaches during the last and present years and comment on the challenges facing the community in the coming years.

SweetNET: A Bioinformatics Workflow for Glycopeptide MS/MS Spectral Analysis

Glycoproteomics has rapidly become an independent analytical platform bridging the fields of glycomics and proteomics to address site-specific protein glycosylation and its impact in biology. Current glycopeptide characterization relies on time-consuming manual interpretations and demands high levels of personal expertise. Efficient data interpretation constitutes one of the major challenges to be overcome before true high-throughput glycopeptide analysis can be achieved. The development of new glyco-related bioinformatics tools is thus of crucial importance to fulfill this goal. Here we present SweetNET: a data-oriented bioinformatics workflow for efficient analysis of hundreds of thousands of glycopeptide MS/MS-spectra. We have analyzed MS data sets from two separate glycopeptide enrichment protocols targeting sialylated glycopeptides and chondroitin sulfate linkage region glycopeptides, respectively. Molecular networking was performed to organize the glycopeptide MS/MS data based on spectral similarities. The combination of spectral clustering, oxonium ion intensity profiles, and precursor ion m/z shift distributions provided typical signatures for the initial assignment of different N-, O- and CS-glycopeptide classes and their respective glycoforms. These signatures were further used to guide database searches leading to the identification and validation of a large number of glycopeptide variants including novel deoxyhexose (fucose) modifications in the linkage region of chondroitin sulfate proteoglycans.

Emerging mass spectrometry techniques for the direct analysis of microbial colonies

One of the emerging areas in microbiology is detecting specialized metabolites produced by microbial colonies and communities with mass spectrometry. In this review/perspective, we illustrate the emerging mass spectrometry methodologies that enable the interrogation of specialized metabolites directly from microbial colonies. Mass spectrometry techniques such as imaging mass spectrometry and real-time mass spectrometry allow two and three-dimensional visualization of the distribution of metabolites, often with minimal sample pretreatment. The speed in which molecules are captured using these methods requires the development of new molecular visualization tools such as molecular networking. Together, these tools are beginning to provide unprecedented insight into the chemical world that microbes experience.

Proteomic studies related to genetic determinants of variability in protein concentrations

Genetic variation has multiple effects on the proteome. It may influence the expression level of proteins, modify their sequences through single nucleotide polymorphisms, the occurrence of allelic variants, or alternative splicing (ASP) events. This perspective paper summarizes the major effects of genetic variability on protein expression and isoforms and provides an overview of proteomics techniques and methods that allow studying the effects of genetic variability at different levels of the proteome. The paper provides an overview of recent quantitative trait loci studies performed to explore the effect of genetic variation on protein expression (pQTL). Finally it gives a perspective view on advances in proteomics technology and the role of the Chromosome-Centric Human Proteome Project (C-HPP) by creating large-scale resources that may facilitate performing more comprehensive pQTL experiments in the future.

Advancing formaldehyde cross-linking towards quantitative proteomic applications

Formaldehyde is a key fixation reagent. This review explores its application in combination with qualitative and quantitative mass spectrometry (MS). Formalin-fixed and paraffin-embedded (FFPE) tissues form a large reservoir of biologically valuable samples and their investigation by MS has only recently started. Furthermore, formaldehyde can be used to stabilise protein-protein interactions in living cells. Because formaldehyde is able to modify proteins, performing MS analysis on these samples can pose a challenge. Here we discuss the chemistry of formaldehyde cross-linking, describe the problems of and progress in these two applications and their common aspects, and evaluate the potential of these methods for the future.

Nano-enabled biomarker discovery and detection

The completion of the human genome project has led to intensified efforts toward comprehensive analysis of proteomes. New possibilities exist for efficient proteomic technologies. However, primary attention is given to the discovery of new predictive biomarker patterns. Understanding proteomes and, in particular, protein-mediated interactions underlying their complexity and diversity, is critical for the development of more reliable and robust diagnostic platforms, which are anticipated to enable personalized medicine. Of immediate relevance in this respect are those approaches that capitalize on the application of nanotechnology, which is seen as a powerful tool for the diagnosis of early-stage diseases. Here we highlight the current state of the field exemplified by recent nano-enabled technologies for biomarker discovery.