Prediction, screening and characterization of novel bioactive tetrapeptide matrikines for skin rejuvenation.

BACKGROUND: Extracellular matrices play a critical role in tissue structure and function and aberrant remodelling of these matrices is a hallmark of many age-related diseases. In skin, loss of dermal collagens and disorganization of elastic fibre components are key features of photoageing. Although the application of some small matrix-derived peptides to aged skin has been shown to beneficially affect in vitro cell behaviour and, in vivo, molecular architecture and clinical appearance, the discovery of new peptides has lacked a guiding hypothesis. OBJECTIVES: To identify, using protease cleavage site prediction, novel putative matrikines with beneficial activities for skin composition and structure. METHODS: Here, we present an in silico (peptide cleavage prediction) to in vitro (proteomic and transcriptomic activity testing in cultured human dermal fibroblasts) to in vivo (short-term patch test and longer-term split-face clinical study) discovery pipeline, which enables the identification and characterization of peptides with differential activities. RESULTS: Using this pipeline we showed that cultured fibroblasts were responsive to all applied peptides, but their associated bioactivity was sequence-dependent. Based on bioactivity, toxicity and protein source, we further characterized a combination of two novel peptides, GPKG (glycine-proline-lysine-glycine) and LSVD (leucine-serine-valine-aspartate), that acted in vitro to enhance the transcription of matrix -organization and cell proliferation genes and in vivo (in a short-term patch test) to promote processes associated with epithelial and dermal maintenance and remodelling. Prolonged use of a formulation containing these peptides in a split-face clinical study led to significantly improved measures of crow's feet and firmness in a mixed population. CONCLUSIONS: This approach to peptide discovery and testing can identify new synthetic matrikines, providing insights into biological mechanisms of tissue homeostasis and repair and new pathways to clinical intervention.

Like other organs and tissues, the skin is composed of both cells and a complex network of molecules and proteins called an extracellular matrix. This matrix contains proteins such as collagen and elastin and undergoes many changes when the skin is damaged by the sun. We know from previous studies that small parts of matrix proteins (called peptide 'matrikines') can help to treat the signs of sun-related skin ageing. In this UK study, we show that new beneficial peptides (with matrikine activity) can be identified using machine learning (artificial intelligence) techniques that predict where common matrix proteins might be 'cut' by skin enzymes. Candidate peptides were first made in the laboratory and then applied to skin cells in culture. These cell culture screens demonstrated that, while all the peptides showed some matrikine activity, two were particularly promising. These two peptides were then tested in a short-term study on the forearm skin of volunteers and, in a longer-term study, on the face. We found that the combination of these two peptides can prompt forearm skin cells to express genes that are involved in many different aspect of skin health and, over the longer 6-month period, produce visible benefits in the appearance of fine lines and wrinkles and firmness on the face. Our findings suggest that this approach may be able to identify beneficial peptide treatments for not only skin ageing and diseases, but also unwanted changes in the extracellular matrix of other tissues and organs.

Peptide Location Fingerprinting Reveals Tissue Region-Specific Differences in Protein Structures in an Ageing Human Organ.

In ageing tissues, long-lived extracellular matrix (ECM) proteins are susceptible to the accumulation of structural damage due to diverse mechanisms including glycation, oxidation and protease cleavage. Peptide location fingerprinting (PLF) is a new mass spectrometry (MS) analysis technique capable of identifying proteins exhibiting structural differences in complex proteomes. PLF applied to published young and aged intervertebral disc (IVD) MS datasets (posterior, lateral and anterior regions of the annulus fibrosus) identified 268 proteins with age-associated structural differences. For several ECM assemblies (collagens I, II and V and aggrecan), these differences were markedly conserved between degeneration-prone (posterior and lateral) and -resistant (anterior) regions. Significant differences in peptide yields, observed within collagen I α2, collagen II α1 and collagen V α1, were located within their triple-helical regions and/or cleaved C-terminal propeptides, indicating potential accumulation of damage and impaired maintenance. Several proteins (collagen V α1, collagen II α1 and aggrecan) also exhibited tissue region (lateral)-specific differences in structure between aged and young samples, suggesting that some ageing mechanisms may act locally within tissues. This study not only reveals possible age-associated differences in ECM protein structures which are tissue-region specific, but also highlights the ability of PLF as a proteomic tool to aid in biomarker discovery.

Predicting Proteolysis in Complex Proteomes Using Deep Learning.

Both protease- and reactive oxygen species (ROS)-mediated proteolysis are thought to be key effectors of tissue remodeling. We have previously shown that comparison of amino acid composition can predict the differential susceptibilities of proteins to photo-oxidation. However, predicting protein susceptibility to endogenous proteases remains challenging. Here, we aim to develop bioinformatics tools to (i) predict cleavage site locations (and hence putative protein susceptibilities) and (ii) compare the predicted vulnerabilities of skin proteins to protease- and ROS-mediated proteolysis. The first goal of this study was to experimentally evaluate the ability of existing protease cleavage site prediction models (PROSPER and DeepCleave) to identify experimentally determined MMP9 cleavage sites in two purified proteins and in a complex human dermal fibroblast-derived extracellular matrix (ECM) proteome. We subsequently developed deep bidirectional recurrent neural network (BRNN) models to predict cleavage sites for 14 tissue proteases. The predictions of the new models were tested against experimental datasets and combined with amino acid composition analysis (to predict ultraviolet radiation (UVR)/ROS susceptibility) in a new web app: the Manchester proteome susceptibility calculator (MPSC). The BRNN models performed better in predicting cleavage sites in native dermal ECM proteins than existing models (DeepCleave and PROSPER), and application of MPSC to the skin proteome suggests that: compared with the elastic fiber network, fibrillar collagens may be susceptible primarily to protease-mediated proteolysis. We also identify additional putative targets of oxidative damage (dermatopontin, fibulins and defensins) and protease action (laminins and nidogen). MPSC has the potential to identify potential targets of proteolysis in disparate tissues and disease states.

hadge: a comprehensive pipeline for donor deconvolution in single-cell studies.

Single-cell multiplexing techniques (cell hashing and genetic multiplexing) combine multiple samples, optimizing sample processing and reducing costs. Cell hashing conjugates antibody-tags or chemical-oligonucleotides to cell membranes, while genetic multiplexing allows to mix genetically diverse samples and relies on aggregation of RNA reads at known genomic coordinates. We develop hadge (hashing deconvolution combined with genotype information), a Nextflow pipeline that combines 12 methods to perform both hashing- and genotype-based deconvolution. We propose a joint deconvolution strategy combining best-performing methods and demonstrate how this approach leads to the recovery of previously discarded cells in a nuclei hashing of fresh-frozen brain tissue.

Oxidative DNA damage promotes vascular aging associated with changes in extracellular matrix-regulating proteins.

AIMS: Vascular aging is characterized by vessel stiffening, with increased deposition of extracellular matrix (ECM) proteins including collagens. Oxidative DNA damage occurs in vascular aging, but how it regulates ECM proteins and vascular stiffening is unknown. We sought to determine the relationship between oxidative DNA damage and ECM regulatory proteins in vascular aging. METHODS AND RESULTS: We examined oxidative DNA damage, the major base excision repair (BER) enzyme 8-Oxoguanine DNA Glycosylase (Ogg1) and its regulators, multiple physiological markers of aging, and ECM proteomics in mice from 22-72w. Vascular aging was associated with increased oxidative DNA damage, and decreased expression of Ogg1, its active acetylated form, its acetylation regulatory proteins P300 and CBP, and the transcription factor Foxo3a. Vascular stiffness was examined in vivo in control, Ogg1-/-, or mice with vascular smooth muscle cell-specific expression of Ogg1+ (Ogg1) or an inactive mutation (Ogg1KR). Ogg1-/- and Ogg1KR mice showed reduced arterial compliance and distensibility, and increased stiffness and pulse pressure, whereas Ogg1 expression normalised all parameters to 72w. ECM proteomics identified major changes in collagens with aging, and downregulation of the ECM regulatory proteins Protein 6-lysyl oxidase (LOX) and WNT1-inducible-signaling pathway protein 2 (WISP2). Ogg1 overexpression upregulated LOX and WISP2 both in vitro and in vivo, and downregulated Transforming growth factor ß1 (TGFb1) and Collagen 4α1 in vivo compared with Ogg1KR. Foxo3a activation induced Lox, while Wnt3 induction of Wisp2 also upregulated LOX and Foxo3a, and downregulated TGFß1 and fibronectin 1. In humans, 8-oxo-G increased with vascular stiffness, while active OGG1 reduced with both age and stiffness. CONCLUSIONS: Vascular aging is associated with oxidative DNA damage, downregulation of major BER proteins, and changes in multiple ECM structural and regulatory proteins. Ogg1 protects against vascular aging, associated with changes in ECM regulatory proteins including LOX and WISP2.

Peptide location fingerprinting identifies structural alterations within basement membrane components in ageing kidney.

During ageing, the glomerular and tubular basement membranes (BM) of the kidney undergo a progressive decline in function that is underpinned by histological changes, including glomerulosclerosis and tubular interstitial fibrosis and atrophy. This BM-specific ageing is thought to result from damage accumulation to long-lived extracellular matrix (ECM) protein structures. Determining which BM proteins are susceptible to these structure-associated changes, and the possible mechanisms and downstream consequences, is critical to understand age-related kidney degeneration and to identify markers for therapeutic intervention. Peptide location fingerprinting (PLF) is an emerging proteomic mass spectrometry analysis technique capable of identifying ECM proteins with structure-associated differences that may occur by damage modifications in ageing. Here, we apply PLF as a bioinformatic screening tool to identify BM proteins with structure-associated differences between young and aged human glomerular and tubulointerstitial compartments. Several functional regions within key BM components displayed alterations in tryptic peptide yield, reflecting potential age-dependent shifts in molecular (e.g. laminin-binding regions in agrin) and cellular (e.g. integrin-binding regions in laminins 521 and 511) interactions, oxidation (e.g. collagen IV) and the fragmentation and release of matrikines (e.g. canstatin and endostatin from collagens IV and XVIII). Furthermore, we found that periostin and the collagen IV α2 chain exhibited structure-associated differences in ageing that were conserved between human kidney and previously analysed mouse lung, revealing BM components that harbour shared susceptibilities across species and organs.

Defining the Protease and Protease Inhibitor (P/PI) Proteomes of Healthy and Diseased Human Skin by Modified Systematic Review.

Proteases and protease inhibitors (P/PIs) are involved in many biological processes in human skin, yet often only specific families or related groups of P/PIs are investigated. Proteomics approaches, such as mass spectrometry, can define proteome signatures (including P/PIs) in tissues; however, they struggle to detect low-abundance proteins. To overcome these issues, we aimed to produce a comprehensive proteome of all P/PIs present in normal and diseased human skin, in vivo, by carrying out a modified systematic review using a list of P/PIs from MEROPS and combining this with key search terms in Web of Science. Resulting articles were manually reviewed against inclusion/exclusion criteria and a dataset constructed. This study identified 111 proteases and 77 protease inhibitors in human skin, comprising the serine, metallo-, cysteine and aspartic acid catalytic families of proteases. P/PIs showing no evidence of catalytic activity or protease inhibition, were designated non-peptidase homologs (NPH), and no reported protease inhibitory activity (NRPIA), respectively. MMP9 and TIMP1 were the most frequently published P/PIs and were reported in normal skin and most skin disease groups. Normal skin and diseased skin showed significant overlap with respect to P/PI profile; however, MMP23 was identified in several skin disease groups, but was absent in normal skin. The catalytic profile of P/PIs in wounds, scars and solar elastosis was distinct from normal skin, suggesting that a different group of P/PIs is responsible for disease progression. In conclusion, this study uses a novel approach to provide a comprehensive inventory of P/PIs in normal and diseased human skin reported in our database. The database may be used to determine either which P/PIs are present in specific diseases or which diseases individual P/PIs may influence.

Matrikines as mediators of tissue remodelling.

Extracellular matrix (ECM) proteins confer biomechanical properties, maintain cell phenotype and mediate tissue repair (via release of sequestered cytokines and proteases). In contrast to intracellular proteomes, where proteins are monitored and replaced over short time periods, many ECM proteins function for years (decades in humans) without replacement. The longevity of abundant ECM proteins, such as collagen I and elastin, leaves them vulnerable to damage accumulation and their host organs prone to chronic, age-related diseases. However, ECM protein fragmentation can potentially produce peptide cytokines (matrikines) which may exacerbate and/or ameliorate age- and disease-related ECM remodelling. In this review, we discuss ECM composition, function and degradation and highlight examples of endogenous matrikines. We then critically and comprehensively analyse published studies of matrix-derived peptides used as topical skin treatments, before considering the potential for improvements in the discovery and delivery of novel matrix-derived peptides to skin and internal organs. From this, we conclude that while the translational impact of matrix-derived peptide therapeutics is evident, the mechanisms of action of these peptides are poorly defined. Further, well-designed, multimodal studies are required.

Peptide location fingerprinting identifies species- and tissue-conserved structural remodelling of proteins as a consequence of ageing and disease.

Extracellular matrices (ECMs) in the intervertebral disc (IVD), lung and artery are thought to undergo age-dependant accumulation of damage by chronic exposure to mechanisms such as reactive oxygen species, proteases and glycation. It is unknown whether this damage accumulation is species-dependant (via differing lifespans and hence cumulative exposures) or whether it can influence the progression of age-related diseases such as atherosclerosis. Peptide location fingerprinting (PLF) is a new proteomic analysis method, capable of the non-targeted identification of structure-associated changes within proteins. Here we applied PLF to publicly available ageing human IVD (outer annulus fibrosus), ageing mouse lung and human arterial atherosclerosis datasets and bioinformatically identified novel target proteins alongside common age-associated differences within protein structures which were conserved between three ECM-rich organs, two species, three IVD tissue regions, sexes and in an age-related disease. We identify peptide yield differences across protein structures which coincide with biological regions, potentially reflecting the functional consequences of ageing or atherosclerosis for macromolecular assemblies (collagen VI), enzyme/inhibitor activity (alpha-2 macroglobulin), activation states (complement C3) and interaction states (laminins, perlecan, fibronectin, filamin-A, collagen XIV and apolipoprotein-B). Furthermore, we show that alpha-2 macroglobulin and collagen XIV exhibit possible shared structural consequences in IVD ageing and arterial atherosclerosis, providing novel links between an age-related disease and intrinsic ageing. Crucially, we also demonstrate that fibronectin, laminin beta chains and filamin-A all exhibit conserved age-associated structural differences between mouse lung and human IVD, providing evidence that ECM, and their associating proteins, may be subjected to potentially similar mechanisms or consequences of ageing across both species, irrespective of differences in lifespan and tissue function.

Assessing Trustworthy AI in Times of COVID-19: Deep Learning for Predicting a Multiregional Score Conveying the Degree of Lung Compromise in COVID-19 Patients.

This article's main contributions are twofold: 1) to demonstrate how to apply the general European Union's High-Level Expert Group's (EU HLEG) guidelines for trustworthy AI in practice for the domain of healthcare and 2) to investigate the research question of what does "trustworthy AI" mean at the time of the COVID-19 pandemic. To this end, we present the results of a post-hoc self-assessment to evaluate the trustworthiness of an AI system for predicting a multiregional score conveying the degree of lung compromise in COVID-19 patients, developed and verified by an interdisciplinary team with members from academia, public hospitals, and industry in time of pandemic. The AI system aims to help radiologists to estimate and communicate the severity of damage in a patient's lung from Chest X-rays. It has been experimentally deployed in the radiology department of the ASST Spedali Civili clinic in Brescia, Italy, since December 2020 during pandemic time. The methodology we have applied for our post-hoc assessment, called Z-Inspection®, uses sociotechnical scenarios to identify ethical, technical, and domain-specific issues in the use of the AI system in the context of the pandemic.

Peptide location fingerprinting reveals modification-associated biomarker candidates of ageing in human tissue proteomes.

Although dysfunctional protein homeostasis (proteostasis) is a key factor in many age-related diseases, the untargeted identification of structurally modified proteins remains challenging. Peptide location fingerprinting is a proteomic analysis technique capable of identifying structural modification-associated differences in mass spectrometry (MS) data sets of complex biological samples. A new webtool (Manchester Peptide Location Fingerprinter), applied to photoaged and intrinsically aged skin proteomes, can relatively quantify peptides and map statistically significant differences to regions within protein structures. New photoageing biomarker candidates were identified in multiple pathways including extracellular matrix organisation (collagens and proteoglycans), protein synthesis and folding (ribosomal proteins and TRiC complex subunits), cornification (keratins) and hemidesmosome assembly (plectin and integrin α6ß4). Crucially, peptide location fingerprinting uniquely identified 120 protein biomarker candidates in the dermis and 71 in the epidermis which were modified as a consequence of photoageing but did not differ significantly in relative abundance (measured by MS1 ion intensity). By applying peptide location fingerprinting to published MS data sets, (identifying biomarker candidates including collagen V and versican in ageing tendon) we demonstrate the potential of the MPLF webtool for biomarker discovery.

Proteomic fingerprints of damage in extracellular matrix assemblies.

In contrast to the dynamic intracellular environment, structural extracellular matrix (ECM) proteins with half-lives measured in decades, are susceptible to accumulating damage. Whilst conventional approaches such as histology, immunohistochemistry and mass spectrometry are able to identify age- and disease-related changes in protein abundance or distribution, these techniques are poorly suited to characterising molecular damage. We have previously shown that mass spectrometry can detect tissue-specific differences in the proteolytic susceptibility of protein regions within fibrillin-1 and collagen VI alpha-3. Here, we present a novel proteomic approach to detect damage-induced "peptide fingerprints" within complex multi-component ECM assemblies (fibrillin and collagen VI microfibrils) following their exposure to ultraviolet radiation (UVR) by broadband UVB or solar simulated radiation (SSR). These assemblies were chosen because, in chronically photoaged skin, fibrillin and collagen VI microfibril architectures are differentially susceptible to UVR. In this study, atomic force microscopy revealed that fibrillin microfibril ultrastructure was significantly altered by UVR exposure whereas the ultrastructure of collagen VI microfibrils was resistant. UVR-induced molecular damage was further characterised by proteolytic peptide generation with elastase followed by liquid chromatography tandem mass spectrometry (LC-MS/MS). Peptide mapping revealed that UVR exposure increased regional proteolytic susceptibility within the protein structures of fibrillin-1 and collagen VI alpha-3. This allowed the identification of UVR-induced molecular changes within these two key ECM assemblies. Additionally, similar changes were observed within protein regions of co-purifying, microfibril-associated receptors integrins αv and ß1. This study demonstrates that LC-MS/MS mapping of peptides enables the characterisation of molecular post-translational damage (via direct irradiation and radiation-induced oxidative mechanisms) within a complex in vitro model system. This peptide fingerprinting approach reliably allows both the identification of UVR-induced molecular damage in and between proteins and the identification of specific protein domains with increased proteolytic susceptibility as a result of photo-denaturation. This has the potential to serve as a sensitive method of identifying accumulated molecular damage in vivo using conventional mass spectrometry data-sets.

Circadian rhythms in skin and other elastic tissues.

Circadian rhythms are daily oscillations that, in mammals, are driven by both a master clock, located in the brain, and peripheral clocks in cells and tissues. Approximately 10% of the transcriptome, including extracellular matrix components, is estimated to be under circadian control. Whilst it has been established that certain collagens and extracellular matrix proteases are diurnally regulated (for example in tendon, cartilage and intervertebral disc) the role played by circadian rhythms in mediating elastic fiber homeostasis is poorly understood. Skin, arteries and lungs are dynamic, resilient, elastic fiber-rich organs and tissues. In skin, circadian rhythms influence cell migration and proliferation, wound healing and susceptibility of the tissues to damage (from protease activity, oxidative stress and ultraviolet radiation). In the cardiovascular system, blood pressure and heart rate also follow age-dependent circadian rhythms whilst the lungs exhibit diurnal variations in immune response. In order to better understand these processes it will be necessary to characterise diurnal changes in extracellular matrix biology. In particular, given the sensitivity of peripheral clocks to external factors, the timed delivery of interventions (chronotherapy) has the potential to significantly improve the efficacy of treatments designed to repair and regenerate damaged cutaneous, vascular and pulmonary tissues.

Defining tissue proteomes by systematic literature review.

Defining protein composition is a key step in understanding the function of both healthy and diseased biological systems. There is currently little consensus between existing published proteomes in tissues such as the aorta, cartilage and organs such as skin. Lack of agreement as to both the number and identity of proteins may be due to issues in protein extraction, sensitivity/specificity of detection and the use of disparate tissue/cell sources. Here, we developed a method combining bioinformatics and systematic review to screen >32M articles from the Web of Science for evidence of proteins in healthy human skin. The resulting Manchester Proteome ( www.manchesterproteome.manchester.ac.uk ) collates existing evidence which characterises 2,948 skin proteins, 437 unique to our database and 2011 evidenced by both mass spectrometry and immune-based techniques. This approach circumvents the limitations of individual proteomics studies and can be applied to other species, organs, cells or disease-states. Accurate tissue proteomes will aid development of engineered constructs and offer insight into disease treatments by highlighting differences in proteomic composition.