Middle-down proteomics (MDP) is an analytical approach in which protein samples are digested with proteases such as Glu-C to generate large peptides (>3 kDa) that are analyzed by mass spectrometry (MS). This method is useful for characterizing high-molecular-weight proteins that are difficult to detect by top-down proteomics (TDP), in which intact proteins are analyzed by MS. In this study, we applied GeLC-FAIMS-MS, a multidimensional separation workflow that combines gel-based prefractionation with LC-FAIMS MS, for deep MDP. Middle-down peptides generated by optimized limited Glu-C digestion conditions were first size-fractionated by polyacrylamide gel electrophoresis, followed by C4 reversed-phase liquid chromatography separation and additional ion mobility fractionation, resulting in a significant increase in peptide length detectable by MS. In addition to global analysis, the GeLC-FAIMS-MS concept can also be applied to targeted MDP, where only proteins in the desired molecular weight range are gel-fractionated and their Glu-C digestion products are analyzed, as demonstrated by targeted analysis of integrins in exosomes. In-depth MDP achieved by global and targeted GeLC-FAIMS-MS supports the exploration of proteoform information not covered by conventional TDP by increasing the number of detectable protein groups or post-translational modifications (PTMs) and improving the sequence coverage.

Metaproteomics can be used to study functionally active biofilm-based bacterial populations in reclaimed water distribution systems, which in turn result in bacterial regrowth that impacts the water quality. However, existing protein extraction methods have differences in their protein recovery and have not been evaluated for their efficacies in reclaimed water biofilm samples. In this study, we first evaluated six different protein extraction methods with diverse chemical and physical properties on a mixture of bacterial cell culture. Based on a weighting scores-based evaluation, the extraction protocols in order of decreasing performance are listed as B-PER > RIPA > PreOmics > SDS > AllPrep > Urea. The highest four optimal methods on cell culture were further tested against treated wastewater non-chlorinated and chlorinated effluent biofilms. In terms of protein yield, our findings showed that RIPA performed the best; however, the highest number of proteins were extracted from SDS and PreOmics. Furthermore, SDS and PreOmics worked best to rupture gram-positive and gram-negative bacterial cell walls. Considering the five evaluation factors, PreOmics obtained highest weighted score, indicating its potential effectiveness in extracting proteins from biofilms. This study provides the first insight into evaluating protein extraction methods to facilitate metaproteomics for complex reclaimed water matrices.

Parkinson's disease (PD) is a complex neurodegenerative disease with motor and non-motor symptoms. Diagnosis is complicated by lack of reliable biomarkers. To individuate peptides and/or proteins with diagnostic potential for early diagnosis, severity and discrimination from similar pathologies, the salivary proteome in 36 PD patients was investigated in comparison with 36 healthy controls (HC) and 35 Alzheimer's disease (AD) patients. A top-down platform based on HPLC-ESI-IT-MS allowed characterizing and quantifying intact peptides, small proteins and their PTMs (overall 51). The three groups showed significantly different protein profiles, PD showed the highest levels of cystatin SA and antileukoproteinase and the lowest of cystatin SN and some statherin proteoforms. HC exhibited the lowest abundance of thymosin β4, short S100A9, cystatin A, and dimeric cystatin B. AD patients showed the highest abundance of α-defensins and short oxidized S100A9. Moreover, different proteoforms of the same protein, as S-cysteinylated and S-glutathionylated cystatin B, showed opposite trends in the two pathological groups. Statherin, cystatins SA and SN classified accurately PD from HC and AD subjects. α-defensins, histatin 1, oxidized S100A9, and P-B fragments were the best classifying factors between PD and AD patients. Interestingly statherin and thymosin β4 correlated with defective olfactory functions in PD patients. All these outcomes highlighted implications of specific proteoforms involved in the innate-immune response and inflammation regulation at oral and systemic level, suggesting a possible panel of molecular and clinical markers suitable to recognize subjects affected by PD.

Lipids play a significant role in maintaining central nervous system (CNS) structure and function, and the dysregulation of lipid metabolism is known to occur in many neurological disorders, including Alzheimer's disease. Here we review what is currently known about lipid dyshomeostasis in Alzheimer's disease. We propose that small extracellular vesicle (sEV) lipids may provide insight into the pathophysiology and progression of Alzheimer's disease. This stems from the recognition that sEV likely contributes to disease pathogenesis, but also an understanding that sEV can serve as a source of potential biomarkers. While the protein and RNA content of sEV in the CNS diseases have been studied extensively, our understanding of the lipidome of sEV in the CNS is still in its infancy.

Organophosphorus compounds (OPs) such as chemical agents and pesticides are posing critical threats to civilians due to their irreversible phosphonylation of diverse amino acids residues forming different protein adducts. However, traditional analytical approaches are quite limited in capturing the myriad of post-translational events that affect protein functions, especially in identifying the low-abundance OP adducts. Herein a systematic proteomic strategy based on a typical click-enrich-release-identify bioorthogonal operation was firstly developed by employing an alkynyl-tagged V-type agent probe (AVP) and a biotin-based azido-enrichment linker (BTP-N3 ). AVP targeting peptides from human serum albumin (HSA) or plasma were captured by BTP-N3 via CuAAC click reaction, enriched by streptavidin beads, released by selective alkaline hydrolysis of phenacyl ester bond, and subsequently sequenced by LC-MS/MS. This strategy has helped identifying 1115 unique OP adduction sites on 163 proteins in human plasma, and covers lots of OP adducts that cannot be achieved by traditional detection methods. The comprehensive coverage of novel OP substrates provided a general and sensitive approach to retrospective verification and/or dose assessment of toxic OPs.

Proteins with up to 100 amino acids have been largely overlooked due to the challenges associated with predicting and identifying them using traditional methods. Recent advances in bioinformatics and machine learning, DNA sequencing, RNA and Ribo-seq technologies, and mass spectrometry (MS) have greatly facilitated the detection and characterisation of these elusive proteins in recent years. This has revealed their crucial role in various cellular processes including regulation, signalling and transport, as toxins and as folding helpers for protein complexes. Consequently, the systematic identification and characterisation of these proteins in bacteria have emerged as a prominent field of interest within the microbial research community. This review provides an overview of different strategies for predicting and identifying these proteins on a large scale, leveraging the power of these advanced technologies. Furthermore, the review offers insights into the future developments that may be expected in this field.

Advances in proteogenomic technologies have revealed hundreds to thousands of translated small open reading frames (sORFs) that encode microproteins in genomes across evolutionary space. While many microproteins have now been shown to play critical roles in biology and human disease, a majority of recently identified microproteins have little or no experimental evidence regarding their functionality. Computational tools have some limitations for analysis of short, poorly conserved microprotein sequences, so additional approaches are needed to determine the role of each member of this recently discovered polypeptide class. A currently underexplored avenue in the study of microproteins is structure prediction and determination, which delivers a depth of functional information. In this review, we provide a brief overview of microprotein discovery methods, then examine examples of microprotein structures (and, conversely, intrinsic disorder) that have been experimentally determined using crystallography, cryo-electron microscopy, and NMR, which provide insight into their molecular functions and mechanisms. Additionally, we discuss examples of predicted microprotein structures that have provided insight or context regarding their function. Analysis of microprotein structure at the angstrom level, and confirmation of predicted structures, therefore, has potential to identify translated microproteins that are of biological importance and to provide molecular mechanism for their in vivo roles.

Ochrogaster lunifer (Lepidoptera: Notodontidae) is an Australian processionary caterpillar with detachable urticating setae that have a defensive function. These true setae induce inflammation when they contact human skin, and equine foetal loss syndrome if they are accidentally ingested by gravid horses. We used transcriptomics and proteomics to identify proteins and peptides present in and on urticating setae, which may include toxins that contribute to inflammation and/or foetal loss syndromes. This process identified 37 putative toxins, including multiple homologues of the honeybee venom peptide secapin, and proteins with similarity to odorant binding proteins, arylphorins, and the insect immune modulator Diedel. This work identifies candidate molecules that may contribute to the adverse effects of processionary caterpillar setae on human and animal health.