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Metaproteomics has substantially grown over the past years and supplements other omics approaches by bringing valuable functional information, enabling genotype- phenotype linkages and connections to metabolic outputs. Currently, a wide variety of metaproteomic workflows is available, yet their impact on the results remains to be thoroughly assessed.
Here, we carried out the first community-driven, multi-lab comparison in metaproteomics: the critical assessment of metaproteome investigation (CAMPI) study. Based on well-established workflows, we evaluated the influence of sample preparation, mass spectrometry acquisition, and bioinformatic analysis using two samples: a simplified, lab-assembled human intestinal model and a human fecal sample.
Although bioinformatic pipelines contributed to variability in peptide identification, wet-lab workflows were the most important source of differences between analyses. Overall, these peptide-level differences largely disappeared at the protein group level. Differences were observed between peptide- and protein-centric approaches for the predicted community composition but similar functional profiles were found across workflows.
The CAMPI findings demonstrate the robustness of current metaproteomics research and provide a perspective for future benchmarking studies.
The use of inorganic lanthanide-doped upconversion nanoparticles (UCNP) in bioimaging and cellular studies requires biocompatible particles. One possible cause of UCNP toxicity is the release of potentially harmful fluoride and lanthanide ions as revealed by dilution studies in aqueous environments, particularly under high dilution conditions. To address this issue, suitable surface coatings preventing such effects in combination with fast screening methods suited for online monitoring and in situ analyses are desired.
Here we present systematic studies of differently sized β-NaYF4:Yb,Er UCNP stabilized with different surface coatings and hydrophilic ligands varying in binding strength to the particle surface in various aqueous environments at different temperatures and UCNP concentrations. The concentration of the fluoride and lanthanide ions released upon particle dissolution was quantified electrochemically with a fluoride ion-sensitive electrode and inductively coupled plasma optical emission spectrometry (ICP-OES) and monitored fluorometrically, thereby exploiting the sensitivity of the upconversion luminescence to changes in size and surface chemistry. Moreover, changes in surface chemistry were determined with X-Ray photoelectron spectroscopy (XPS). Based upon our results, we could derive optimum screening parameters for UCNP stability studies and determine conditions and coating procedures and ligands for enhancing UCNP stability in aqueous environments.
The climate and energy crisis are extreme challenges. One possible solution could be hydrogen technology. Safety is a big concern. Steel used for pipelines and storage is under permanent stress from low temperatures and high pressures. The content of different alloyed metals determines the performance of the steel. Nitrogen microwave inductively coupled atmosphere pressure plasma mass spectrometry (N2-MICAP-MS) is a promising method for trace metal analysis in steel. Nitrogen is cheap and can be generated on site. It has fewer interferences than argon. Additionally, MICAP-MS is very matrix tolerant, proving the matrix-matched calibration expendable. Safety in technology and chemistry is the mission of BAM. Providing reference methods and materials can create trust in future technologies like hydrogen.
Driven by recent technological advances and the need for improved viral diagnostic applications, mass spectrometry-based proteomics comes into play for detecting viral pathogens accurately and efficiently. However, the lack of specific algorithms and software tools presents a major bottleneck for analyzing data from host-virus samples. For example, accurate species- and strain-level classification of a priori unidentified organisms remains a very challenging task in the setting of large search databases. Another prominent issue is that many existing solutions suffer from the protein inference issue, aggravated because many homologous proteins are present across multiple species. One of the contributing factors is that existing bioinformatic algorithms have been developed mainly for single-species proteomics applications for model organisms or human samples. In addition, a statistically sound framework was lacking to accurately assign peptide identifications to viral taxa. In this presentation, an overview is given on current bioinformatics developments that aim to overcome the above-mentioned issues using algorithmic and statistical methods. The presented methods and software tools aim to provide tailored solutions for both discovery-driven and targeted proteomics for viral diagnostics and taxonomic sample profiling. Furthermore, an outlook is provided on how the bioinformatic developments might serve as a generic toolbox, which can be transferred to other research questions, such as metaproteomics for profiling microbiomes and identifying bacterial pathogens.
Isotope Ratio Analysis
(2023)