Investigation of Age Gelation in UHT Milk

The role of glycosylation in amyloid fibril formation of bovine κ-casein

In order to explore the functions of glycosylation of κ-Casein (κ-CN) in bovine milk, unglycosylated (UG) and twice glycosylated (2G) forms of κ-CN B were purified by selective precipitation followed by anion exchange chromatography from κ-CN BB milk and tested for their amyloid fibril formation and morphology, oligomerisation states and protein structure. The diameter of self-assembled κ-CN B aggregates of both glyco-form were shown for the first time to be in the same 26.0-28.7 nm range for a 1 mg mL^-1 solution. The presence of two bound glycans in the protein structure of 2G κ-CN B led to a greater increase in the maximum amyloid fibril formation rate with increasing protein concentration and a difference in both length (82.0 ± 29.9 vs 50.3 ± 13.7 nm) and width (8.6 ± 2.1 vs 13.9 ± 2.5 nm) for fibril morphology compared to UG κ-CN B. The present results suggest that amyloid fibril formation proceeds at a slow but steady rate via the self-assembly of dissociated, monomeric κ-CN B proteins at concentrations of 0.22-0.44 mg mL^-1. However amyloid fibril formation proceeds more rapidly via the assembly of either aggregated κ-CN present in a micelle-like form or dissociated monomeric κ-CN, packed into reorganised formational structures above the critical micellar concentration to form fibrils of differing width. The degree of glycosylation has no effect on the polarity of the adjacent environment, nor non-covalent and disulphide interactions between protein molecules when in the native form. Yet glycosylation can influence protein folding patterns of κ-CN B leading to a reduced tryptophan intrinsic fluorescence intensity for 2G compared to UG κ-CN B. These results demonstrate that glycosylation plays an important role in the modulation of aggregation states of κ-CN and contributes to a better understanding of the role of glycosylation in the formation of amyloid fibrils from intrinsically disordered proteins.

Mining the Wheat Grain Proteome

Bread wheat is the most widely cultivated crop worldwide, used in the production of food products and a feed source for animals. Selection tools that can be applied early in the breeding cycle are needed to accelerate genetic gain for increased wheat production while maintaining or improving grain quality if demand from human population growth is to be fulfilled. Proteomics screening assays of wheat flour can assist breeders to select the best performing breeding lines and discard the worst lines. In this study, we optimised a robust LC–MS shotgun quantitative proteomics method to screen thousands of wheat genotypes. Using 6 cultivars and 4 replicates, we tested 3 resuspension ratios (50, 25, and 17 µL/mg), 2 extraction buffers (with urea or guanidine-hydrochloride), 3 sets of proteases (chymotrypsin, Glu-C, and trypsin/Lys-C), and multiple LC settings. Protein identifications by LC–MS/MS were used to select the best parameters. A total 8738 wheat proteins were identified. The best method was validated on an independent set of 96 cultivars and peptides quantities were normalised using sample weights, an internal standard, and quality controls. Data mining tools found particularly useful to explore the flour proteome are presented (UniProt Retrieve/ID mapping tool, KEGG, AgriGO, REVIGO, and Pathway Tools).

Proteolytic Traits of Psychrotrophic Bacteria Potentially Causative of Sterilized Milk Instability: Genotypic, Phenotypic and Peptidomic Insight

The proteolytic traits of the psychrotrophic strains Pseudomonas poae LP5, Pseudomonas fluorescens LPF3, Chryseobacterium joostei LPR1, Pseudomonas fulva PS1, Citrobacter freundii PS37, Hafnia alvei PS46, and Serratia marcescens PS92 were initially investigated by phenotypic and genotypic approaches. Six strains elicited extracellular proteolytic activity, and five expressed the thermostable AprX or (likely) Ser1 enzymes. Then, the strains were inoculated (10⁴ CFU/mL) in microfiltered pasteurized milk and kept at 4 °C for five days. All of the strains reached 10⁸ CFU/mL at the end of storage and five produced thermostable extracellular proteolytic enzymes. The freshly inoculated samples and the corresponding samples at 10⁸ CFU/mL were batch-sterilized (131 °C, 30 s) and kept at 45 °C up to 100 days. The former samples did not gel until the end of incubation, whereas the latter, containing P. poae, P. fluorescens, C. joostei, C. freundii, and S. marcescens, gelled within a few days of incubation. The thermostable proteolytic activity of strains affected the peptidomic profile, and specific proteolyzed zones of β-CN were recognized in the gelled samples. Overall, the results confirm some proteolytic traits of psychrotrophic Pseudomonas spp. strains and provide additional insights on the proteolytic activity of psychrotrophic bacteria potentially responsible for sterilized milk destabilization.

A Multiple Protease Strategy to Optimise the Shotgun Proteomics of Mature Medicinal Cannabis Buds

Earlier this year we published a method article aimed at optimising protein extraction from mature buds of medicinal cannabis for trypsin-based shotgun proteomics (Vincent, D., et al. Molecules2019, 24, 659). We then developed a top-down proteomics (TDP) method (Vincent, D., et al. Proteomes2019, 7, 33). This follow-up study aims at optimising the digestion of medicinal cannabis proteins for identification purposes by bottom-up and middle-down proteomics (BUP and MDP). Four proteases, namely a mixture of trypsin/LysC, GluC, and chymotrypsin, which target different amino acids (AAs) and therefore are orthogonal and cleave proteins more or less frequently, were tested both on their own as well as sequentially or pooled, followed by nLC-MS/MS analyses of the peptide digests. Bovine serum albumin (BSA, 66 kDa) was used as a control of digestion efficiency. With this multiple protease strategy, BSA was reproducibly 97% sequenced, with peptides ranging from 0.7 to 6.4 kD containing 5 to 54 AA residues with 0 to 6 miscleavages. The proteome of mature apical buds from medicinal cannabis was explored more in depth with the identification of 27,123 peptides matching 494 unique accessions corresponding to 229 unique proteins from Cannabis sativa and close relatives, including 130 (57%) additional annotations when the list is compared to that of our previous BUP study (Vincent, D., et al. Molecules2019, 24, 659). Almost half of the medicinal cannabis proteins were identified with 100% sequence coverage, with peptides composed of 7 to 91 AA residues with up to 9 miscleavages and ranging from 0.6 to 10 kDa, thus falling into the MDP domain. Many post-translational modifications (PTMs) were identified, such as oxidation, phosphorylations, and N-terminus acetylations. This method will pave the way for deeper proteome exploration of the reproductive organs of medicinal cannabis, and therefore for molecular phenotyping within breeding programs.

Top-Down Proteomics of Medicinal Cannabis

The revised legislation on medicinal cannabis has triggered a surge of research studies in this space. Yet, cannabis proteomics is lagging. In a previous study, we optimised the protein extraction of mature buds for bottom-up proteomics. In this follow-up study, we developed a top-down mass spectrometry (MS) proteomics strategy to identify intact denatured protein from cannabis apical buds. After testing different source-induced dissociation (SID), collision-induced dissociation (CID), higher-energy collisional dissociation (HCD), and electron transfer dissociation (ETD) parameters on infused known protein standards, we devised three LC-MS/MS methods for top-down sequencing of cannabis proteins. Different MS/MS modes produced distinct spectra, albeit greatly overlapping between SID, CID, and HCD. The number of fragments increased with the energy applied; however, this did not necessarily translate into greater sequence coverage. Some precursors were more amenable to fragmentation than others. Sequence coverage decreased as the mass of the protein increased. Combining all MS/MS data maximised amino acid (AA) sequence coverage, achieving 73% for myoglobin. In this experiment, most cannabis proteins were smaller than 30 kD. A total of 46 cannabis proteins were identified with 136 proteoforms bearing different post-translational modifications (PTMs), including the excision of N-terminal M, the N-terminal acetylation, methylation, and acetylation of K resides, and phosphorylation. Most identified proteins are involved in photosynthesis, translation, and ATP production. Only one protein belongs to the phytocannabinoid biosynthesis, olivetolic acid cyclase.

Optimisation of Protein Extraction from Medicinal Cannabis Mature Buds for Bottom-Up Proteomics

Medicinal cannabis is used to relieve the symptoms of certain medical conditions, such as epilepsy. Cannabis is a controlled substance and until recently was illegal in many jurisdictions. Consequently, the study of this plant has been restricted. Proteomics studies on Cannabis sativa reported so far have been primarily based on plant organs and tissues other than buds, such as roots, hypocotyl, leaves, hempseeds and flour. As far as we know, no optimisation of protein extraction from cannabis reproductive tissues has been attempted. Therefore, we set out to assess different protein extraction methods followed by mass spectrometry-based proteomics to recover, separate and identify the proteins of the reproductive organs of medicinal cannabis, apical buds and isolated trichomes. Database search following shotgun proteomics was limited to protein sequences from C. sativa and closely related species available from UniprotKB. Our results demonstrate that a buffer containing the chaotrope reagent guanidine hydrochloride recovers many more proteins than a urea-based buffer. In combination with a precipitation with trichloroacetic acid, such buffer proved optimum to identify proteins using a trypsin digestion followed by nano-liquid chromatography tandem mass spectrometry (nLC-MS/MS) analyses. This is validated by focusing on enzymes involved in the phytocannabinoid pathway.

Optimisation of Milk Protein Top-Down Sequencing Using In-Source Collision-Induced Dissociation in the Maxis Quadrupole Time-of-Flight Mass Spectrometer

Top-down sequencing in proteomics has come of age owing to continuous progress in LC-MS. With their high resolution and broad mass range, Quadrupole Time-of-Flight (Q-ToF) hybrid mass spectrometers equipped with electrospray ionisation source and tandem MS capability by collision-induced dissociation (CID) can be employed to analyse intact proteins and retrieve primary sequence information. To our knowledge, top-down proteomics methods with Q-ToF have only been evaluated using samples of relatively low complexity. Furthermore, the in-source CID (IS-CID) capability of Q-ToF instruments has been under-utilised. This study aimed at optimising top-down sequencing of intact milk proteins to achieve the greatest sequence coverage possible from samples of increasing complexity, assessed using nine known proteins. Eleven MS/MS methods varying in their IS-CID and conventional CID parameters were tested on individual and mixed protein standards as well as raw milk samples. Top-down sequencing results from the nine most abundant proteoforms of caseins, alpha-lactalbumin and beta-lactoglubulins were compared. Nine MS/MS methods achieved more than 70% sequence coverage overall to distinguish between allelic proteoforms, varying only by one or two amino acids. The optimal methods utilised IS-CID at low energy. This experiment demonstrates the utility of Q-ToF systems for top-down proteomics and that IS-CID could be more frequently employed.