Miniprep assisted proteomics (MAP) for rapid proteomics sample preparation

Quenching Trypsin Is Unnecessary in Filter-Based Bottom-Up Proteomics

Quenching digestions in proteomics prior to analysis is routine in order to eliminate residual protease activity. Residual activity leads to overdigestion, nonspecific star-activity, and back-exchange in isotopic 18O quantitation. Chemical and isobaric labeling (e.g., TMT/iTRAQ) of proteins or peptides for mass spectrometry-based proteomics is generally incompatible with ubiquitous postdigestion acidification. This necessitates buffer exchange and pH adjustments. We demonstrate that quenching is unnecessary with peptides generated from protein filter-traps, as trypsin activity and intact trypsin are negligible in the eluate from these preparations. Labeling can be directly performed on enzymatic digests from these methods, improving recovery, throughput, and ease of automation.

Lytic transglycosylase Slt of Pseudomonas aeruginosa as a periplasmic hub protein

Peptidoglycan is a major constituent of the bacterial cell wall. Its integrity as a polymeric edifice is critical for bacterial survival and, as such, it is a preeminent target for antibiotics. The peptidoglycan is a dynamic crosslinked polymer that undergoes constant biosynthesis and turnover. The soluble lytic transglycosylase (Slt) of Pseudomonas aeruginosa is a periplasmic enzyme involved in this dynamic turnover. Using amber-codon-suppression methodology in live bacteria, we incorporated a fluorescent chromophore into the structure of Slt. Fluorescent microscopy shows that Slt populates the length of the periplasmic space and concentrates at the sites of septation in daughter cells. This concentration persists after separation of the cells. Amber-codon-suppression methodology was also used to incorporate a photoaffinity amino acid for the capture of partner proteins. Mass-spectrometry-based proteomics identified 12 partners for Slt in vivo. These proteomics experiments were complemented with in vitro pulldown analyses. Twenty additional partners were identified. We cloned the genes and purified to homogeneity 22 identified partners. Biophysical characterization confirmed all as bona fide Slt binders. The identities of the protein partners of Slt span disparate periplasmic protein families, inclusive of several proteins known to be present in the divisome. Notable periplasmic partners (KD < 0.5 μM) include PBPs (PBP1a, KD = 0.07 μM; PBP5 = 0.4 μM); other lytic transglycosylases (SltB2, KD = 0.09 μM; RlpA, KD = 0.4 μM); a type VI secretion system effector (Tse5, KD = 0.3 μM); and a regulatory protease for alginate biosynthesis (AlgO, KD < 0.4 μM). In light of the functional breadth of its interactome, Slt is conceptualized as a hub protein within the periplasm.

Benchmarking low- and high-throughput protein cleanup and digestion methods for human fecal metaproteomics

The application of fecal metaproteomics to large-scale studies of the gut microbiota requires high-throughput analysis and standardized experimental protocols. Although high-throughput protein cleanup and digestion methods are increasingly used in shotgun proteomics, no studies have yet critically compared such protocols using human fecal samples. In this study, human fecal protein extracts were processed using several different protocols based on three main approaches: filter-aided sample preparation (FASP), solid-phase-enhanced sample preparation (SP3), and suspension trapping (S-Trap). These protocols were applied in both low-throughput (i.e., microtube-based) and high-throughput (i.e., microplate-based) formats, and the final peptide mixtures were analyzed by liquid chromatography coupled to high-resolution tandem mass spectrometry. The FASP-based methods and the combination of SP3 with in-StageTips (iST) yielded the best results in terms of the number of peptides identified through a database search against gut microbiome and human sequences. The efficiency of protein digestion, the ability to preserve hydrophobic peptides and high molecular weight proteins, and the reproducibility of the methods were also evaluated for the different protocols. Other relevant variables, including interindividual variability of stool, duration of protocols, and total costs, were considered and discussed. In conclusion, the data presented here can significantly contribute to the optimization and standardization of sample preparation protocols in human fecal metaproteomics. Furthermore, the promising results obtained with the high-throughput methods are expected to encourage the development of automated workflows and their application to large-scale gut microbiome studies.IMPORTANCEFecal metaproteomics is an experimental approach that allows the investigation of gut microbial functions, which are involved in many different physiological and pathological processes. Standardization and automation of sample preparation protocols in fecal metaproteomics are essential for its application in large-scale studies. Here, we comparatively evaluated different methods, available also in a high-throughput format, enabling two key steps of the metaproteomics analytical workflow (namely, protein cleanup and digestion). The results of our study provide critical information that may be useful for the optimization of metaproteomics experimental pipelines and their implementation in laboratory automation systems.

Assessing the precision of a detergent-assisted cartridge precipitation workflow for non-targeted quantitative proteomics

Detergent-based workflows incorporating sodium dodecyl sulfate (SDS) necessitate additional steps for detergent removal ahead of mass spectrometry (MS). These steps may lead to variable protein recovery, inconsistent enzyme digestion efficiency, and unreliable MS signals. To validate a detergent-based workflow for quantitative proteomics, we herein evaluate the precision of a bottom-up sample preparation strategy incorporating cartridge-based protein precipitation with organic solvent to deplete SDS. The variance of data-independent acquisition (SWATH-MS) data was isolated from sample preparation error by modelling the variance as a function of peptide signal intensity. Our SDS-assisted cartridge workflow yield a coefficient of variance (CV) of 13%-14%. By comparison, conventional (detergent-free) in-solution digestion increased the CV to 50%; in-gel digestion provided lower CVs between 14% and 20%. By filtering peptides predicting to display lower precision, we further enhance the validity of data in global comparative proteomics. These results demonstrate the detergent-based precipitation workflow is a reliable approach for in depth, label-free quantitative proteome analysis.

Amber-codon suppression for spatial localization and in vivo photoaffinity capture of the interactome of the Pseudomonas aeruginosa rare lipoprotein A lytic transglycosylase

The 11 lytic transglycosylases of Pseudomonas aeruginosa have overlapping activities in the turnover of the cell-wall peptidoglycan. Rare lipoprotein A (RlpA) is distinct among the 11 by its use of only peptidoglycan lacking peptide stems. The spatial localization of RlpA and its interactome within P. aeruginosa are unknown. We employed suppression of introduced amber codons at sites in the rlpA gene for the introduction of the unnatural-amino-acids Νζ -[(2-azidoethoxy)carbonyl]-l-lysine (compound 1) and Nζ -[[[3-(3-methyl-3H-diazirin-3-yl)propyl]amino]carbonyl]-l-lysine (compound 2). In live P. aeruginosa, full-length RlpA incorporating compound 1 into its sequence was fluorescently tagged using strained-promoted alkyne-azide cycloaddition and examined by fluorescence microscopy. RlpA is present at low levels along the sidewall length of the bacterium, and at higher levels at the nascent septa of replicating bacteria. In intact P. aeruginosa, UV photolysis of full-length RlpA having compound 2 within its sequence generated a transient reactive carbene, which engaged in photoaffinity capture of neighboring proteins. Thirteen proteins were identified. Three of these proteins-PBP1a, PBP5, and MreB-are members of the bacterial divisome. The use of the complementary methodologies of non-canonical amino-acid incorporation, photoaffinity proximity analysis, and fluorescent microscopy confirm a dominant septal location for the RlpA enzyme of P. aeruginosa, as a divisome-associated activity. This accomplishment adds to the emerging recognition of the value of these methodologies for identification of the intracellular localization of bacterial proteins.

The BR-body proteome contains a complex network of protein-protein and protein-RNA interactions

Bacterial RNP bodies (BR-bodies) are non-membrane-bound structures that facilitate mRNA decay by concentrating mRNA substrates with RNase E and the associated RNA degradosome machinery. However, the full complement of proteins enriched in BR-bodies has not been defined. Here we define the protein components of BR-bodies through enrichment of the bodies followed by mass spectrometry-based proteomic analysis. We found 111 BR-body enriched proteins, including several RNA binding proteins, many of which are also recruited directly to in vitro reconstituted RNase E droplets, showing BR-bodies are more complex than previously assumed. While most BR-body enriched proteins that were tested cannot phase separate, we identified five that undergo RNA-dependent phase separation in vitro, showing other RNP condensates interface with BR-bodies. RNA degradosome protein clients are recruited more strongly to RNase E droplets than droplets of other RNP condensates, implying that client specificity is largely achieved through direct protein-protein interactions. We observe that some RNP condensates assemble with preferred directionally, suggesting that RNA may be trafficked through RNP condensates in an ordered manner to facilitate mRNA processing/decay, and that some BR-body associated proteins have the capacity to dissolve the condensate. Finally, we find that RNA dramatically stimulates the rate of RNase E phase separation in vitro, explaining the dissolution of BR-bodies after cellular mRNA depletion observed previously. Altogether, these results suggest that a complex network of protein-protein and protein-RNA interactions controls BR-body phase separation and RNA processing.