Polymerisation of α 1 -antitrypsin within hepatocytes is considered central to the pathogenesis of α 1 -antitrypsin deficiency-associated liver fibrosis, most commonly in homozygotes for the Z (p.Glu342Lys) allele. Polymerisation proceeds via self-association of monomeric intermediate states. In parallel, >50% of synthesised Z α 1 -antitrypsin is instead recognized as terminally-misfolded and degraded. It is unclear whether this contributes to Z α 1 -antitrypsin deficiency-associated liver disease. We characterised the relationships between polymer formation, terminal misfolding and their cellular consequences, using label-free proteomics mass spectrometry (MS), light and electron microscopy, and cellular assays. Proteomic analyses of well-established CHO cell models of hepatocyte handling of α 1 -antitrypsin variants indicated that cellular responses to the Z mutation were surprisingly similar to those seen with the Null HongKong variant (NHK), which can only misfold terminally and cannot polymerise. A minor set of proteins showed increases associated with Z and not NHK α 1 -antitrypsin expression, consistent with a polymer-specific response, characterized by association with increased organellar organization and vesicle-mediated transport. Conversely, proteostatic and pro-fibrotic integrin-associated pathways increased with the degree of terminal misfolding of the expressed α 1 -antitrypsin variant. Bioenergetic pathway changes indicated concomitant switching from oxidative to glycolytic metabolism. Cell studies further correlated fibrosis-associated behaviours with terminal misfolding rather than polymerisation. Terminal misfolding, as well as polymerisation behaviour, may therefore be important for pro-fibrotic responses including metabolic reprogramming and senescence in Z α 1 -antitrypsin deficiency. Molecular therapies may prove most efficacious for associated liver disease if they address terminal misfolding as well as polymerisation.

Polymerisation of α1-antitrypsin within hepatocytes is considered central to pathogenesis in α1-antitrypsin deficiency-associated liver fibrosis, most commonly seen in homozygotes for the Z (p.Glu342Lys) allele. Polymerisation proceeds via self-association of monomeric intermediate states. In parallel, >50% of synthesised Z α1-antitrypsin is instead recognized as terminally-misfolded and degraded. It is unclear whether this contributes to Z α1-antitrypsin deficiency-associated liver disease. We characterised the relationships between polymer formation, terminal misfolding and their cellular consequences, using ion-mobility and label-free proteomics mass spectrometry, light and electron microscopy, and cellular assays. IM-MS findings supported the relationship between polymerisation propensity of different variants and expansion of the protein consistent with opening of its β-sheet A. Proteomic analyses of well-established CHO cell models of hepatocyte handling of α1-antitrypsin variants indicated that cellular responses to the Z mutation were surprisingly similar to those seen with the NullHongKong variant (NHK), which can only misfold terminally and cannot polymerise. A minor set of proteins showed increases associated with Z and not NHK α1-antitrypsin expression, consistent with a polymer-specific response, characterized by association with increased organellar organization and vesicle-mediated transport. Conversely, proteostatic and pro-fibrotic integrin-associated pathways increased with terminal misfolding tendency of the expressed α1-antitrypsin variant. Bioenergetic pathway changes indicated concomitant switching from oxidative to glycolytic metabolism. Cell studies further correlated fibrosis-associated behaviours with terminal misfolding rather than polymerisation. Terminal misfolding, as well as polymerisation behaviour, may therefore be important for pro-fibrotic responses including metabolic reprogramming and senescence in Z α1-antitrypsin deficiency. Molecular therapies may prove most efficacious for associated liver disease if they address terminal misfolding as well as polymerisation consequences. ### Competing Interest Statement The authors have declared no competing interest.

An SI traceable primary calibrator was used for the development of a reference measurement procedure for α-synuclein. A targeted proteomics workflow allowed for the SI traceable quantification of α-synuclein in cerebrospinal fluid.

AbstractObjectivesα-synuclein aggregation is an indicator of neurodegenerative diseases such as Parkinson’s disease (PD) and recent advances have suggested that this protein could serve as a potential biomarker. It has been indicated that soluble and oligomeric α-synuclein in biological fluids could have diagnostic applications for PD. Clinical laboratories currently rely on antibody-based assays to detect α-synuclein. These assays have limited specificity, low sensitivity and poor inter-lab reproducibility, which prevents the validation of α-synuclein as a biomarkers. This study aims to fill the unmet need for the standardisation of clinical measurements for α-synuclein.MethodsWe report the first candidate reference method for α-synuclein, using an SI traceable primary calibrator for α-synuclein and isotope dilution mass spectrometry. The primary calibrator was traceably quantified utilising a combination of amino acid analysis and nuclear magnetic resonance. A targeted sample clean-up procedure involving a non-denaturing Lys-C digestion and solid-phase extraction allowed for the sensitive detection of multiple proteotypic α-synuclein peptides in cerebrospinal fluid (CSF) samples.ResultsThe candidate reference method procedure showed linearity across three orders of magnitude, covering the physiological levels of α-synuclein in CSF (LOQ = 0.1 ng/g). The method was used to quantify a cohort of CSF samples and the measurements were correlated with immunoassay-based quantifications.ConclusionsThe SI traceable quantification of α-synuclein in complex biological matrices means that the role of this protein can be further elucidated in synucleinopathies. This candidate reference method would lead to the harmonisation of α-synuclein measurements, which may allow for development of high throughput clinical tests.

In an adult human body, only a minority (~1%) of cells are dividing; all others are either quiescent, senescent or terminally differentiated. Cellular quiescence, also called G0, is a reversible non-proliferative state in which cells, such as adult stem cells, exist until stimuli trigger their re-entry into the cell cycle. Quiescent cells are known to reside within microenvironment niches of specific extracellular matrix (ECM) composition, but the molecular mechanisms that control their entry and maintenance into G0 and their long-term survival are poorly understood. Here, using a reproducible and homogenous in vitro model of quiescence, ex vivo tissue histology, phosphoproteomics, and molecular cell biological assays, we revealed that Laminin 111 was sufficient to trigger i) reversible cell cycle exit into G0; ii) sustained and elevated MAPK/ERK signaling; and iii) long-term survival. We found that ERK was activated through the Rap1-BRAF-MEK arm underneath Laminin-binding Integrin alpha3beta1. Activated pERK was scaffolded into the cytoplasm by IQGAP1, thereby blocking its translocation into the nucleus and the activation of proliferative transcription factors. Instead, cytoplasmic pERK inhibited pro-apoptotic protein BAD, which mediated the survival of quiescent cells even in absence of mitogen stimuli. Importantly, we confirmed that pERK was elevated and retained in the cytoplasm of Lgr5+ stem cells when they were located within Laminin alpha1-positive niches in porcine intestine. These findings uncovered a molecular mechanism that may explain how quiescent cell pools, such as dormant adult stem cells, can survive many years despite low mitogen stimuli and be resistant to apoptotic challenges, including chemotherapy. ### Competing Interest Statement The authors have declared no competing interest.

BackgroundGlobal healthcare systems continue to be challenged by the COVID-19 pandemic, and there is a need for clinical assays that can help optimise resource allocation, support treatment decisions, and accelerate the development and evaluation of new therapies.MethodsWe developed a multiplexed proteomics assay for determining disease severity and prognosis in COVID-19. The assay quantifies up to 50 peptides, derived from 30 known and newly introduced COVID-19-related protein markers, in a single measurement using routine-lab compatible analytical flow rate liquid chromatography and multiple reaction monitoring (LC-MRM). We conducted two observational studies in patients with COVID-19 hospitalised at Charité – Universitätsmedizin Berlin, Germany before (from March 1 to 26, 2020, n=30) and after (from April 4 to November 19, 2020, n=164) dexamethasone became standard of care. The study is registered in the German and the WHO International Clinical Trials Registry (DRKS00021688).FindingsThe assay produces reproducible (median inter-batch CV of 10.9%) absolute quantification of 47 peptides with high sensitivity (median LLOQ of 143 ng/ml) and accuracy (median 96.8%). In both studies, the assay reproducibly captured hallmarks of COVID-19 infection and severity, as it distinguished healthy individuals, mild, moderate, and severe COVID-19. In the post-dexamethasone cohort, the assay predicted survival with an accuracy of 0.83 (108/130), and death with an accuracy of 0.76 (26/34) in the median 2.5 weeks before the outcome, thereby outperforming compound clinical risk assessments such as SOFA, APACHE II, and ABCS scores.InterpretationDisease severity and clinical outcomes of patients with COVID-19 can be stratified and predicted by the routine-applicable panel assay that combines known and novel COVID-19 biomarkers. The prognostic value of this assay should be prospectively assessed in larger patient cohorts for future support of clinical decisions, including evaluation of sample flow in routine setting. The possibility to objectively classify COVID-19 severity can be helpful for monitoring of novel therapies, especially in early clinical trials.FundingThis research was funded in part by the European Research Council (ERC) under grant agreement ERC-SyG-2020 951475 (to M.R) and by the Wellcome Trust (IA 200829/Z/16/Z to M.R.). The work was further supported by the Ministry of Education and Research (BMBF) as part of the National Research Node ‘Mass Spectrometry in Systems Medicine (MSCoresys)', under grant agreements 031L0220 and 161L0221. J.H. was supported by a Swiss National Science Foundation (SNSF) Postdoc Mobility fellowship (project number 191052). This study was further supported by the BMBF grant NaFoUniMedCOVID-19 – NUM-NAPKON, FKZ: 01KX2021. The study was co-funded by the UK's innovation agency, Innovate UK, under project numbers 75594 and 56328.

Global healthcare systems continue to be challenged by the COVID-19 pandemic, and there is a need for clinical assays that can both help to optimize resource allocation and accelerate the development and evaluation of new therapies. Here, we present a multiplex proteomic panel assay for the assessment of disease severity and outcome prediction in COVID-19. The assay quantifies 50 peptides derived from 30 COVID-19 severity markers in a single measurement using analytical flow rate liquid chromatography and multiple reaction monitoring (LC-MRM), on equipment that is broadly available in routine and regulated analytical laboratories. We demonstrate accurate classification of COVID-19 severity in patients from two cohorts. Furthermore, the assay outperforms established risk assessments such as SOFA and APACHE II in predicting survival in a longitudinal COVID-19 cohort. The prognostic value implies its use for support of clinical decisions in settings with overstrained healthcare resources e.g. to optimally allocate resources to severely ill individuals with high chance of survival. It can furthermore be helpful for monitoring of novel therapies in clinical trials.

Accumulation of amyloid beta peptides is thought to initiate the pathogenesis of Alzheimer's disease. However, the precise mechanisms mediating their neurotoxicity are unclear. Our microarray analyses show that, in Drosophila models of amyloid beta 42 toxicity, genes involved in the unfolded protein response and metabolic processes are upregulated in brain. Comparison with the brain transcriptome of early-stage Alzheimer's patients revealed a common transcriptional signature, but with generally opposing directions of gene expression changes between flies and humans. Among these differentially regulated genes, lactate dehydrogenase (Ldh) was up-regulated by the greatest degree in amyloid beta 42 flies and the human orthologues (LDHA and LDHB) were down-regulated in patients. Functional analyses revealed that either over-expression or inhibition of Ldh by RNA interference (RNAi) slightly exacerbated climbing defects in both healthy and amyloid beta 42-induced Drosophila. This suggests that metabolic responses to lactate dehydrogenase must be finely-tuned, and that its observed upregulation following amyloid beta 42 production could potentially represent a compensatory protection to maintain pathway homeostasis in this model, with further manipulation leading to detrimental effects. The increased Ldh expression in amyloid beta 42 flies was regulated partially by unfolded protein response signalling, as ATF4 RNAi diminished the transcriptional response and enhanced amyloid beta 42-induced climbing phenotypes. Further functional studies are required to determine whether Ldh upregulation provides compensatory neuroprotection against amyloid beta 42-induced loss of activating transcription factor 4 activity and endoplasmatic reticulum stress. Our study thus reveals dysregulation of lactate dehydrogenase signalling in Drosophila models and patients with Alzheimer's disease, which may lead to a detrimental loss of metabolic homeostasis. Importantly, we observed that down-regulation of ATF4-dependent endoplasmic reticulum-stress signalling in this context appears to prevent Ldh compensation and to exacerbate amyloid beta 42-dependent neuronal toxicity. Our findings, therefore, suggest caution in the use of therapeutic strategies focussed on down-regulation of this pathway for the treatment of Alzheimer's disease, since its natural response to the toxic peptide may induce beneficial neuroprotective effects.

Alzheimer’s disease (AD), the most prevalent form of dementia, is a progressive and devastating neurodegenerative condition for which there are no effective treatments. Understanding the molecular pathology of AD during disease progression may identify new ways to reduce neuronal damage. Here, we present a longitudinal study tracking dynamic proteomic alterations in the brains of an inducible Drosophila melanogaster model of AD expressing the Arctic mutant Aβ42 gene. We identified 3093 proteins from flies that were induced to express Aβ42 and age-matched healthy controls using label-free quantitative ion-mobility data independent analysis mass spectrometry. Of these, 228 proteins were significantly altered by Aβ42 accumulation and were enriched for AD-associated processes. Network analyses further revealed that these proteins have distinct hub and bottleneck properties in the brain protein interaction network, suggesting that several may have significant effects on brain function. Our unbiased analysis provides useful insights into the key processes governing the progression of amyloid toxicity and forms a basis for further functional analyses in model organisms and translation to mammalian systems.

Assuring the stability of therapeutic proteins is a major challenge in the biopharmaceutical industry, and a better molecular understanding of the mechanisms through which formulations influence their stability is an ongoing priority. While the preferential exclusion effects of excipients are well known, the additional presence and impact of specific protein-excipient interactions have proven to be more elusive to identify and characterize. We have taken a combined approach of in silico molecular docking and hydrogen deuterium exchange-mass spectrometry (HDX-MS) to characterize the interactions between granulocyte colony-stimulating factor (G-CSF), and some common excipients. These interactions were related to their influence on the thermal-melting temperatures (Tm) for the nonreversible unfolding of G-CSF in liquid formulations. The residue-level interaction sites predicted in silico correlated well with those identified experimentally and highlighted the potential impact of specific excipient interactions on the Tm of G-CSF.

As monoclonal antibodies (mAbs) rapidly emerge as a dominant class of therapeutics, so does the need for suitable analytical technologies to monitor for changes in protein higher order structure (HOS) of these biomolecules. Reference materials (RM) serve a key analytical purpose of benchmarking the suitability and robustness of both established and emerging analytical procedures for both drug producers and regulators. Here, two simple enzymatic protocols for generating Fc-glycan variants from the NISTmAb RM are described and both global and localized changes in HOS between the RM and these Fc-glycan variants are characterized using hydrogen deuterium exchange-mass spectrometry (HDX-MS) and ion mobility spectrometry-mass spectrometry (IMS-MS) measurements. An alternative statistical approach is described where measurement thresholds that differentiate between measurement variability and significant structural changes were established on the basis of experimental data. Measurements revealed decreases in structural stability correlating with the degree of Fc-glycan structure loss, especially at the CH2/CH3 domain interface. These data promote the use of this RM and these Fc-glycan variants for establishing the sensitivity of and validating analytical methods for the detection of HOS measurements of mAbs.

Cross-linking mass spectrometry is an emerging structural biology technique. Almost exclusively, the analyzer of choice for such an experiment has been the Orbitrap. We present an optimized protocol for the use of a Synapt G2-Si for the analysis of cross-linked peptides. We first tested six different energy ramps and analyzed the fragmentation behavior of cross-linked peptides identified by xQuest. By combining the most successful energy ramps, cross-link yield can be increased by up to 40%. When compared to previously published Orbitrap data, the Synapt G2-Si also offers improved fragmentation of the β peptide. In order to improve cross-link quality control we have also developed ValidateXL, a programmatic solution that works with existing cross-linking software to improve cross-link quality control.

α-Synuclein is a major constituent of Lewy bodies in a number of neurodegenerative diseases including Parkinson's disease. As such the protein is seen as a valuable target for therapeutics and its potential use as biomarker has been topic of several studies. Measurements of α-synuclein in clinical and pharmaceutical settings are limited by the high measurement variability of current analytical assays. The objective of this work is to develop a reference method procedure to underpin standardisation of α-synuclein measurements and ultimately improve patient outcomes. Recombinant α-Synuclein was purified and subsequently characterised by liquid chromatography high resolution mass spectrometry. A α-Synuclein solution was then prepared, aliquoted and quantified traceably to the International System of Units by amino acid certified reference materials and SI traceably quantified peptides as internal standards. A two steps sample clean-up mass spectrometry based method (nano-liquid chromatography coupled with a triple quadrupole mass spectrometer) was then developed for quantification of α-Synuclein in cerebrospinal fluid by using a recombinant isotopically labelled protein as internal standard. Pooled CSF samples were quantified by using the potential reference method, an independent mass spectrometry based method and immunoassay measurements. The results were compared together with the results obtained from the measurement of clinical samples to define the potential of using the method here developed as reference method. An SI traceable mass spectrometry-based candidate reference method for α-synuclein quantification has been developed and validated.

Ion mobility mass spectrometry (IM-MS) is a fast and sample-efficient method for analysing the gas phase conformation of proteins and protein complexes. Subjecting proteins to increased collision energies prior to ion mobility separation can directly probe their unfolding behaviour. Recent work in the field has utilised this approach to evaluate the effect of small ligand binding upon protein stability, and to screen compounds for drug discovery. Its general applicability for high-throughput screening will, however, depend upon new analytical methods to make the approach scalable. Here we describe a fully automated program, called Benthesikyme, for summarising the ion mobility results from such experiments. The program automatically creates collision induced unfolding (CIU) fingerprints and summary plots that capture the increase in collision cross section and the increase in conformational flexibility of proteins during unfolding. We also describe a program, based on a genetic algorithm, for the deconvolution of arrival time distributions from the CIU data. This multicomponent analysis method was developed to require as little user input as possible. Aside from the IM-MS data, the only input required is an estimate of the number of conformational families to be fitted to the data. In cases where the appropriate number of conformational families is unclear, the automated procedure means it is straightforward to repeat the analysis for several values and optimize the quality of the fit. We have employed our new methodology to study the effects of peptide binding to alpha(1)-antitrypsin, an abundant human plasma protein whose misfolding exemplifies a group of conformational diseases termed the serpinopathies. Our analysis shows that interaction with the peptide stabilises the protein and reduces its conformational flexibility. The previously unresolved patterns of unfolding detected by the deconvolution algorithm will allow us to set up a fully automated screen for new ligand molecules with similar properties. (C) 2018 Elsevier B.V. All rights reserved.

The development of novel therapies for Alzheimer's Disease (AD) is constrained by the lack of available methods for preclinical diagnosis, despite extensive research on biomarker identification. Here, we present an update of progress from EMPIR NeuroMET, a project combining diverse expertise from five National Measurement Institutes (NMIs), with clinicians and academics, to overcome limitations in measurement methods in neurodegenerative disease diagnosis and treatment. We provide an overview of our latest research focusing on: liquid chromatography; mass spectrometry (triple quadrupole and high resolution); immunoassays (MSD); digital PCR; magnetic resonance imaging (MRI); spectroscopy (7 Tesla); psychometric; and multivariate analyses. We will report on: (1) Our initial assessment of the uncertainty of immunoassays for quantification of Alzheimer's biomarkers in plasma including Aβ, tau and neurofilaments and its application on a number of platforms commercially available, together with the development of a novel approach to immunoassay quantification. (2) The development of primary calibrators for tau and alpha synuclein, to be used for reference method development alongside liquid chromatography mass spectrometry methods in biological fluids. (3) Protocols for high resolution magnetic resonance imaging of the whole brain were developed on three healthy individuals and the preliminary results of the application of those protocols on a patient cohort (currently >50). (4) The potential relationships between structural volumes and metabolite concentrations with measured memory function. (5) Improved cognitive assessment protocols currently being developed, distinct in their emphasis on: a) improved, metrological evaluation of cognitive performance scores; and b) the development of construct specification equations for various cognitive protocols and biomarkers. Our mid-term NeuroMet project is already providing a better understanding of how to improve, combine and analyse measurements in AD diagnosis and treatment. Measurement comparability through SI (System of International Units) traceability and uncertainty analysis is an, as yet, unmet requirement for regulatory approval of biomarkers, patient centred outcome measures, clinical thresholds and new therapeutic drugs. Therefore, in the case of neurodegenerative disease, we believe the development of reference methods to underpin the production of calibrators and improve measurement comparability of established biomarkers has the potential to significantly move the field forward.

Type IV secretion (T4S) systems are versatile bacterial secretion systems mediating transport of protein and/or DNA T4S systems are generally composed of 11 VirB proteins and 1 VirD protein (VirD4). The VirB1-11 proteins assemble to form a secretion machinery and a pilus while the VirD4 protein is responsible for substrate recruitment. The structure of VirD4 in isolation is known; however, its structure bound to the VirB1-11 apparatus has not been determined. Here, we purify a T4S system with VirD4 bound, define the biochemical requirements for complex formation and describe the protein-protein interaction network in which VirD4 is involved. We also solve the structure of this complex by negative stain electron microscopy, demonstrating that two copies of VirD4 dimers locate on both sides of the apparatus, in between the VirB4 ATPases. Given the central role of VirD4 in type IV secretion, our study provides mechanistic insights on a process that mediates the dangerous spread of antibiotic resistance genes among bacterial populations.

Spider venom toxins, such as Protoxin-II (ProTx-II), have recently received much attention as selective Nav1.7 channel blockers, with potential to be developed as leads for the treatment of chronic nocioceptive pain. ProTx-II is a 30-amino acid peptide with three disulfide bonds that has been reported to adopt a well-defined inhibitory cystine knot (ICK) scaffold structure. Potential drawbacks with such peptides include poor pharmacodynamics and potential scrambling of the disulfide bonds in vivo. In order to address these issues, in the present study we report the solid-phase synthesis of lanthionine-bridged analogues of ProTx-II, in which one of the three disulfide bridges is replaced with a thioether linkage, and evaluate the biological properties of these analogues. We have also investigated the folding and disulfide bridging patterns arising from different methods of oxidation of the linear peptide precursor. Finally, we report the X-ray crystal structure of ProTx-II to atomic resolution; to our knowledge this is the first crystal structure of an ICK spider venom peptide not bound to a substrate.

Hydrogen-deuterium exchange mass spectrometry (HDX-MS) is an important tool for measuring and monitoring protein structure. A bottom-up approach to HDX-MS provides peptide level deuterium uptake values and a more refined localization of deuterium incorporation compared with global HDX-MS measurements. The degree of localization provided by HDX-MS is proportional to the number of peptides that can be identified and monitored across an exchange experiment. Ion mobility spectrometry (IMS) has been shown to improve MS-based peptide analysis of biological samples through increased separation capacity. The integration of IMS within HDX-MS workflows has been commercialized but presently its adoption has not been widespread. The potential benefits of IMS, therefore, have not yet been fully explored. We herein describe a comprehensive evaluation of traveling wave ion mobility integrated within an online-HDX-MS system and present the first reported example of UDMSE acquisition for HDX analysis. Instrument settings required for optimal peptide identifications are described and the effects of detector saturation due to peak compression are discussed. A model system is utilized to confirm the comparability of HDX-IM-MS and HDX-MS uptake values prior to an evaluation of the benefits of IMS at increasing sample complexity. Interestingly, MS and IM-MS acquisitions were found to identify distinct populations of peptides that were unique to the respective methods, a property that can be utilized to increase the spatial resolution of HDX-MS experiments by > 60%.

Assessing the recovery of food allergens from solid processed matrixes is one of the most difficult steps that needs to be overcome to enable the accurate quantification of protein allergens by immunoassay and MS. A feasibility study is described herein applying International System of Units (SI)-traceably quantified milk protein solutions to assess recovery by an improved extraction method. Untargeted MS analysis suggests that this novel extraction method can be further developed to provide high recoveries for a broad range of food allergens. A solution of α-casein was traceably quantified to the SI for the content of α-S1 casein. Cookie dough was prepared by spiking a known amount of the SI-traceable quantified solution into a mixture of flour, sugar, and soya spread, followed by baking. A novel method for the extraction of protein food allergens from solid matrixes based on proteolytic digestion was developed, and its performance was compared with the performance of methods reported in the literature.