Proteomes

Background: Acetification is a complex process driven by acetic acid bacteria (AAB), in which high ethanol and acidity levels require strong microbial metabolic adaptation. Although the microbiota involved in vinegar production has been described, the functional mechanisms that enable these bacteria to maintain metabolic activity remain poorly understood. In this study, the functional dynamics of AAB during Verdejo vinegar acetification were analyzed using a quantitative metaproteomic approach. Methods: Acetification was performed in submerged culture under semi-continuous conditions, and samples were collected at four stages of the cycle (S1–S4). Results: LC-MS/MS analysis led to the identification of 1626 proteins, of which 1409 were assigned to the Acetobacteraceae family. Komagataeibacter europaeus was the dominant species (73.7%). Hierarchical clustering revealed four protein abundance patterns, and differential analysis identified 350 proteins with increased abundance and 169 with decreased abundance, with the greatest changes observed between S1 and S4. Functional annotation and protein–protein interaction analyses indicated that the main metabolic adaptations involve pathways related to energy metabolism, amino acid biosynthesis, membrane-associated functions, cellular homeostasis, and acid stress response. Conclusions: Overall, the results show that K. europaeus concentrates most of the metabolic activity during acetification and that proteome reorganization reflects key molecular strategies for adaptation and survival under high-acidity conditions.

Single-cell proteomics (SCP) is an exciting new field of study with developments in the areas of sample preparation, instrumentation and informatics. SCP has captured the imagination of biologists and clinicians and the critical interest of both academic and commercial mass-spectrometry groups. Currently (i.e., at the time this manuscript was written), SCP is still difficult and slow relative to competing single-cell technologies. What SCP may lose in relative throughput, it trades for direct analysis of protein and proteoforms, albeit with biases toward those of the highest relative concentration in each cell. These strengths may not make SCP the technology of choice for every study. This perspective is intended to identify current and future biological or clinical areas where SCP has or could have the greatest potential to advance human health and knowledge. I will also discuss applications where SCP would be less impactful than other technologies and where SCP, when mature, could play a true role in clinical diagnostics.

Background: Maize is a vital crop, supporting 19.5% of global calorie intake. However, maize is vulnerable to even brief periods of drought which substantially reduces seed set and therefore yield. Methods: To identify proteins involved in responses of maize to drought, soluble proteins were extracted from leaf and silk tissues of Zea mays and protein abundance and phosphorylation status were quantified relative to well-watered controls. Label-free quantification and phosphopeptide enrichment were applied to the same biological samples and over 300 proteins were identified with significantly different changes. Results: Proteins known to be involved in drought responses were identified, such as the abscisic acid pathway and transcription factors. Of particular interest is a group of dehydrins quantified at both total protein and phosphopeptide levels, permitting insight into stoichiometry. The biological function of dehydrins in the model plant Arabidopsis thaliana is known to be regulated by phosphorylation. Conclusions: Translation of protein function from model plant to crops remains highly challenging because genome duplication has created complex sets of orthologous and homologous proteins. By focusing on proteomic changes during crop stress responses, this work enables the identification of known and novel proteins, substantially aiding the transfer of knowledge from model plants to crops.