Redox proteomics analysis of hair shaft proteins upon hydrothermal and alkaline insult.

OBJECTIVE: Human hair is regularly subjected to chemical and physical insults, such as heat, UV-irradiation and alkaline hair care products. These insults result in molecular modifications at the hair protein level that underpin mechanical and sensory property changes in the fibres. These changes can manifest itself in reduced hair quality and performance attributes observable to the consumer. In this work, changes in protein modification as a result of heat and alkaline treatments are determined. METHODS: Redox proteomic profiling using high-resolution mass spectrometry was applied to map and evaluate amino acid residue modifications in human hair exposed to a combination of thermal treatments and alkali exposure with the aim to understand the underlying chemical processes. RESULTS: Our results show that an increase in redox-related modifications is associated with exposure to higher levels of hydrothermal and alkaline insult. Post-translational modification profiling at the protein primary structural level delivered some further insights into the site-specificity of these modifications, with a clear increase in the number of cysteic acid modifications noticed in samples subjected to more extreme insults. CONCLUSION: Pinpointing modification sides within proteins and the hair shaft proteome can be used as a basis for employing mitigation or repair strategies of hair protein damage caused by environmental or hair treatment-related insults.

OBJECTIF: Les cheveux humains sont sujet à de nombreuses agressions physiques et chimiques telles que la chaleur, les radiations ultra-violettes et les produits alcalins d'entretien des cheveux. Ces agressions entrainent des modifications moléculaires dans les protéines constituant les cheveux et elles conduisent aussi à des changements mécaniques et sensoriels des fibres capillaires. Les manifestations possibles de ces transformations sont une baisse, visible pour le consommateur, de la qualité et des indicateurs de performance des cheveux. Lors de cette étude, nous mettons en évidence les changements au niveau protéique liés à la chaleur et aux traitements alcalins. MÉTHODES: Les méthodes de profilage d'oxydoréduction protéomique utilisant des spectromètres de masses à haute résolution ont été utilisées afin d'évaluer les modifications des amino-acides dans les cheveux humains après exposition à plusieurs combinaisons de traitements thermiques et alcalins dans le but de comprendre les processus chimiques impliqués. RÉSULTATS: Nos résultats montrent que l'augmentation des modifications d'oxydoréduction est associée à des niveaux élevés d'exposition aux traitements thermiques et/ou alcalins. Le profilage des modifications post-translationnelles des structures primaires des protéines ont permis de mieux comprendre les spécificités de ces modifications ; notamment une augmentation nette du nombre des modifications des acides cystéiques liée aux traitements les plus agressifs. CONCLUSION: Ce travail d'identification des modifications engendrées par les agressions liées aux traitements capillaires ou environnementales peut désormais servir de base pour évaluer et mettre en place des techniques de réduction des risques, protection et de réparation des protéines des cheveux.

UV and visible light exposure to hair leads to widespread changes in the hair lipidome.

OBJECTIVE: Scalp hair is among the most exposed parts of the human body, yet the impact of visible and UV light on hair lipids, an important structural component of hair, is poorly researched. We have used lipidomics, a broad-based approach to measure lipids in samples, which has hitherto not been applied to UV-exposed hair in the published literature, and could allow for a wider understanding of how UV light impacts on specific hair lipids. METHODS: Mixed blonde Caucasian hair switches were divided into two groups of five, with half of the hair switches exposed to UV and visible light mimicking normal daytime exposure and half left unexposed. LC-MS lipidomics was used to profile the lipids in the hair samples. RESULTS: A total of 791 lipids and 32 lipid classes with tentative identifications were detected in the hair samples. Nineteen lipid classes and 397 lipids differed between UV-treated and non-treated hair. The main lipid classes that differed were vitamin A fatty acid esters, sterol esters, several ceramides, mono-, di- and triglycerides, phosphatidylethanolamines (all decreased in UV-exposed hair) and bismonoacylglycerolphosphates, acylcarnitines and acylglycines (all increased in UV-exposed hair). Most detected lipids were decreased in UV-exposed hair, supporting earlier work that has found that UV exposure causes oxidation of lipids which would result in a decrease in most lipid classes. CONCLUSION: Light exposure to hair has a widespread impact on the hair lipidome. This study also adds to the emerging literature on the hair lipidome, broadening the range of lipid classes reported in hair.

OBJECTIF: Le cuir chevelu est l'une des parties les plus exposées de l'organisme. Cependant, l'impact de la lumière visible et des UV sur les lipides capillaires, un composant structurel important des cheveux, reste mal étudié. Nous avons utilisé la lipidomique, une approche large pour mesurer les lipides présents dans les échantillons de cheveux, qui n'a jusqu'ici pas été appliquée aux cheveux exposés aux UV dans la littérature publiée. Cette approche pourrait permettre de mieux comprendre l'impact de la lumière UV sur des lipides spécifiques des cheveux. MÉTHODES: Les mèches de cheveux caucasiens blonds mélangés ont été divisées en deux groupes de cinq, la moitié des mèches de cheveux étant exposées aux UV et à une lumière visible imitant l'exposition diurne normale tandis que l'autre moitié est restée non exposée. Le profil lipidique des échantillons de cheveux a été établi grâce à la lipidomique de la LC-MS. RÉSULTATS: Au total, 791 lipides et 32 classes de lipides avec des identifications provisoires ont été détectés dans les échantillons de cheveux. Entre les cheveux traités par UV et les cheveux non traités, dix-neuf classes de lipides et 397 lipides se sont avérés différents. Les principales classes de lipides qui différaient étaient les esters d'acides gras de la vitamine A, les esters de stérols, plusieurs céramides, les monoglycérides, diglycérides et triglycérides, les phosphatidyléthanolamines (tous diminués dans les cheveux exposés aux UV) et les bismonoacylglycérolphosphates, acylcarnitines et acylglycines (tous augmentés dans les cheveux exposés aux UV). La plupart des lipides détectés dans les cheveux exposés aux UV n'étaient présents qu'à taux réduit, soit un résultat cohérent avec une étude antérieure ayant montré que l'exposition aux UV provoque l'oxydation des lipides, ce qui entraînerait une diminution de la plupart des classes de lipides. CONCLUSION: L'exposition des cheveux à la lumière entraîne un impact généralisé sur leur lipidome. Cette étude vient également compléter la littérature émergente sur le lipidome capillaire, élargissant ainsi la gamme de classes lipidiques rapportées dans les cheveux.

Proteomic determinants of uterine receptivity for pregnancy in early and mid-postpartum dairy cows†.

Dairy cow subfertility is a worldwide issue arising from multiple factors. It manifests in >30% early pregnancy losses in seasonal pasture-grazed herds, especially when cows are inseminated in the early post-partum period. Most losses occur before implantation, when embryo growth depends on factors present in maternal tract fluids. Here we examined the proteomic composition of early and mid-postpartum uterine luminal fluid (ULF) in crossbred lactating dairy cows to identify molecular determinants of fertility. We also explored changes in ULF from first to third estrus cycles postpartum in individual cows, linking those changes with divergent embryo development. For this, we flushed uteri of 87 cows at Day 7 of pregnancy at first and third estrus postpartum, recovering, and grading their embryos. Out of 1563 proteins detected, 472 had not been previously reported in this fluid, and 408 were predicted to be actively secreted by bioinformatic analysis. The abundance of 18 proteins with roles in immune regulation and metabolic function (e.g. cystatin B, pyruvate kinase M2) was associated with contrasting embryo quality. Matched-paired pathway analysis indicated that, from first to third estrus postpartum, upregulation of metabolic (e.g. creatine and carbohydrate) and immune (e.g. complement regulation, antiviral defense) processes were related to poorer quality embryos in the third estrus cycle postpartum. Conversely, upregulated signal transduction and protein trafficking appeared related to improved embryo quality in third estrus. These results advance the characterization of the molecular environment of bovine ULF and may aid understanding fertility issues in other mammals, including humans.

Insights in Human Hair Curvature by Proteome Analysis of Two Distinct Hair Shapes.

Scalp hair is a universal human characteristic, and a wide range of hair shape and color variations exists. Although differences in human scalp hair shape are visually apparent, the underpinning molecular insights are yet to be fully explored. This work reports the determination of differences at the protein level between two distinct groups of hair shape: very straight samples versus very curly hair samples. An in-depth highresolution liquid-chromatography mass spectrometry proteome analysis study was performed on hair samples from 50 individuals (pooled in 10 × 5 samples) with very curly hair and 50 subjects with very straight hair (pooled in 10 × 5 samples) to decipher differences between the two experimental groups at the protein level. Our results demonstrate that a distinction between the two experimental groups (very straight vs. very curly) can be made based on their overall protein profiles in a multivariate analysis approach. Further investigation of the protein expression levels between these two groups pinpointed 13 unique proteins which were found to be significantly different between the two groups, with an adjusted p-value < 0.05 and a fold change of more than two. Although differences between the very curly and the very straight hair sample groups could be identified, linkage between population differences and curl phenotype is currently unknown and requires further investigation.

The challenges of peptidomics in complementing proteomics in a clinical context.

Naturally occurring peptides, including growth factors, hormones, and neurotransmitters, represent an important class of biomolecules and have crucial roles in human physiology. The study of these peptides in clinical samples is therefore as relevant as ever. Compared to more routine proteomics applications in clinical research, peptidomics research questions are more challenging and have special requirements with regard to sample handling, experimental design, and bioinformatics. In this review, we describe the issues that confront peptidomics in a clinical context. After these hurdles are (partially) overcome, peptidomics will be ready for a successful translation into medical practice.

FACS-Based Proteomics Enables Profiling of Proteins in Rare Cell Populations.

Understanding disease pathology often does not require an overall proteomic analysis of clinical samples but rather the analysis of different, often rare, subpopulations of cells in a heterogeneous mixture of cell types. For the isolation of pre-specified cellular subtypes, fluorescence activated cell sorting (FACS) is commonly used for its ability to isolate the required cell populations with high purity, even of scarce cell types. The proteomic analysis of a limited number of FACS-sorted cells, however, is very challenging as both sample preparation inefficiencies and limits in terms of instrument sensitivity are present. In this study, we used CD14+CD15+ immune cells sorted out of peripheral blood mononuclear cells isolated from whole blood to improve and evaluate FACS-based proteomics. To optimize both the protein extraction protocol and the mass spectrometry (MS) data acquisition method, PBMCs as well as commercialized HeLa digest were used. To reflect the limited number of sorted cells in some clinical samples, different numbers of sorted cells (1000, 5000, 10,000, or 50,000) were used. This allowed comparing protein profiles across samples with limited protein material and provided further insights in the benefits and limitations of using a very limited numbers of cells.

Comprehensive Peptide Analysis of Mouse Brain Striatum Identifies Novel sORF-Encoded Polypeptides.

Bio-active peptides are involved in the regulation of most physiological processes in the body. Classical bio-active peptides (CBAPs) are cleaved from a larger precursor protein and stored in secretion vesicles from which they are released in the extracellular space. Recently, another non-classical type of bio-active peptides (NCBAPs) has gained interest. These typically are not secreted but instead appear to be translated from short open reading frames (sORF) and released directly into the cytoplasm. In contrast to CBAPs, these peptides are involved in the regulation of intra-cellular processes such as transcriptional control, calcium handling and DNA repair. However, bio-chemical evidence for the translation of sORFs remains elusive. Comprehensive analysis of sORF-encoded polypeptides (SEPs) is hampered by a number of methodological and biological challenges: the low molecular mass (many 4-10 kDa), the low abundance, transient expression and complications in data analysis. We developed a strategy to address a number of these issues. Our strategy is to exclude false positive identifications. In total sample, we identified 926 peptides originated from 37 known (neuro)peptide precursors in mouse striatum. In addition, four SEPs were identified including NoBody, a SEP that was previously discovered in humans and three novel SEPS from 5' untranslated transcript regions (UTRs).

CONSTANd : A Normalization Method for Isobaric Labeled Spectra by Constrained Optimization.

In quantitative proteomics applications, the use of isobaric labels is a very popular concept as they allow for multiplexing, such that peptides from multiple biological samples are quantified simultaneously in one mass spectrometry experiment. Although this multiplexing allows that peptide intensities are affected by the same amount of instrument variability, systematic effects during sample preparation can also introduce a bias in the quantitation measurements. Therefore, normalization methods are required to remove this systematic error. At present, a few dedicated normalization methods for isobaric labeled data are at hand. Most of these normalization methods include a framework for statistical data analysis and rely on ANOVA or linear mixed models. However, for swift quality control of the samples or data visualization a simple normalization technique is sufficient. To this aim, we present a new and easy-to-use data-driven normalization method, named CONSTANd. The CONSTANd method employs constrained optimization and prior information about the labeling strategy to normalize the peptide intensities. Further, it allows maintaining the connection to any biological effect while reducing the systematic and technical errors. As a result, peptides can not only be compared directly within a multiplexed experiment, but are also comparable between other isobaric labeled datasets from multiple experimental designs that are normalized by the CONSTANd method, without the need to include a reference sample in every experimental setup. The latter property is especially useful when more than six, eight or ten (TMT/iTRAQ) biological samples are required to detect differential peptides with sufficient statistical power and to optimally make use of the multiplexing capacity of isobaric labels.

Protein-protein cross-linking and human health: the challenge of elucidating with mass spectrometry.

INTRODUCTION: In several biomedical research fields, the cross-linking of peptides and proteins has an important impact on health and wellbeing. It is therefore of crucial importance to study this class of post-translational modifications in detail. The huge potential of mass spectrometric technologies in the mapping of these protein-protein cross-links is however overshadowed by the challenges that the field has to overcome. Areas covered: In this review, we summarize the different pitfalls and challenges that the protein-protein cross-linking field is confronted with when using mass spectrometry approaches. We additionally focus on native disulfide bridges as an example and provide some examples of cross-links that are important in the biomedical field. Expert commentary: The current flow of methodological improvements, mainly from the chemical cross-linking field, has delivered a significant contribution to deciphering native and insult-induced cross-links. Although an automated data analysis of proteome-wide peptide cross-linking is currently only possible in chemical cross-linking experiments, the field is well on the way towards a more automated analysis of native and insult-induced cross-links in raw mass spectrometry data that will boost its potential in biomedical applications.

The use of elemental mass spectrometry in phosphoproteomic applications.

Reversible phosphorylation is one of the most important post-translational modifications in mammalian cells. Because this molecular switch is an important mechanism that diversifies and regulates proteins in cellular processes, knowledge about the extent and quantity of phosphorylation is very important to understand the complex cellular interplay. Although phosphoproteomics strategies are applied worldwide, they mainly include only molecular mass spectrometry (like MALDI or ESI)-based experiments. Although identification and relative quantification of phosphopeptides is straightforward with these techniques, absolute quantification is more complex and usually requires for specific isotopically phosphopeptide standards. However, the use of elemental mass spectrometry, and in particular inductively coupled plasma mass spectrometry (ICP-MS), in phosphoproteomics-based experiments, allow one to absolutely quantify phosphopeptides. Here, these phosphoproteomic applications with ICP-MS as elemental detector are reviewed. Pioneering work and recent developments in the field are both described. Additionally, the advantage of the parallel use of molecular and elemental mass spectrometry is stressed.

Designing biomedical proteomics experiments: state-of-the-art and future perspectives.

With the current expanded technical capabilities to perform mass spectrometry-based biomedical proteomics experiments, an improved focus on the design of experiments is crucial. As it is clear that ignoring the importance of a good design leads to an unprecedented rate of false discoveries which would poison our results, more and more tools are developed to help researchers designing proteomic experiments. In this review, we apply statistical thinking to go through the entire proteomics workflow for biomarker discovery and validation and relate the considerations that should be made at the level of hypothesis building, technology selection, experimental design and the optimization of the experimental parameters.

Translating clinical proteomics: the importance of study design.

Mass spectrometry-based clinical proteomics approaches were introduced into the biomedical field more than two decades ago. Despite recent developments both in the field of mass spectrometry and bioinformatics, the gap between proteomics results and their translation into clinical practice still needs to be closed, as implementation of proteomics results in the clinic appears to be scarce. An extra focus on the importance of the experimental design is therefore of crucial importance.

The benefits and limitations of reaction cell and sector field inductively coupled plasma mass spectrometry in the detection and quantification of phosphopeptides.

RATIONALE: The phosphorylation of proteins is one of the most important post-translational modifications in nature. Knowledge of the quantity or degree of protein phosphorylation in biological samples is extremely important. A combination of liquid chromatography (LC) and inductively coupled plasma mass spectrometry (ICP-MS) allows the absolute and relative quantification of the phosphorus signal. METHODS: A comparison between dynamic reaction cell quadrupole ICP-MS (DRC-Q-ICP-MS) and high-resolution sector field ICP-MS (SF-ICP-MS) in detecting signals of phosphorus-containing species using identical capillary LC (reversed-phase technology) and nebulizer settings was performed. RESULTS: A method to diminish the reversed-phase gradient-related signal instability in phosphorus detection with LC/ICP-MS applications was developed. Bis(4-nitrophenyl)phosphate (BNPP) was used as a standard to compare signal-to-noise ratios and limits of detection (LODs) between the two instrumental setups. The LOD reaches a value of 0.8 µg L(-1) when applying the DRC technology in Q-ICP-MS and an LOD of 0.09 µg L(-1) was found with the SF-ICP-MS setup. This BNPP standard was further used to compare the absolute quantification possibilities of phosphopeptides in these two setups. CONCLUSIONS: This one-to-one comparison of two interference-reducing ICP-MS instruments demonstrates that absolute quantification of individual LC-separated phosphopeptides is possible. However, based on the LOD values, SF-ICP-MS has a higher sensitivity in detecting phosphorus signals and thus is preferred in phosphopeptide analysis.

Colorectal cancer biomarker discovery and validation using LC-MS/MS-based proteomics in blood: truth or dare?

Globally, colorectal cancer (CRC) is the third most common malignant neoplasm. However, highly sensitive, specific, noninvasive tests that allow CRC diagnosis at an early stage are still needed. As circulatory blood reflects the physiological status of an individual and/or the disease status for several disorders, efforts have been undertaken to identify candidate diagnostic CRC markers in plasma and serum. In this review, the challenges, bottlenecks and promising properties of mass spectrometry (MS)-based proteomics in blood are discussed. More specifically, important aspects in clinical design, sample retrieval, sample preparation, and MS analysis are presented. The recent developments in targeted MS approaches in plasma or serum are highlighted as well.

Unravelling associations between unassigned mass spectrometry peaks with frequent itemset mining techniques.

BACKGROUND: Mass spectrometry-based proteomics experiments generate spectra that are rich in information. Often only a fraction of this information is used for peptide/protein identification, whereas a significant proportion of the peaks in a spectrum remain unexplained. In this paper we explore how a specific class of data mining techniques termed "frequent itemset mining" can be employed to discover patterns in the unassigned data, and how such patterns can help us interpret the origin of the unexpected/unexplained peaks. RESULTS: First a model is proposed that describes the origin of the observed peaks in a mass spectrum. For this purpose we use the classical correlative database search algorithm. Peaks that support a positive identification of the spectrum are termed explained peaks. Next, frequent itemset mining techniques are introduced to infer which unexplained peaks are associated in a spectrum. The method is validated on two types of experimental proteomic data. First, peptide mass fingerprint data is analyzed to explain the unassigned peaks in a full scan mass spectrum. Interestingly, a large numbers of experimental spectra reveals several highly frequent unexplained masses, and pattern mining on these frequent masses demonstrates that subsets of these peaks frequently co-occur. Further evaluation shows that several of these co-occurring peaks indeed have a known common origin, and other patterns are promising hypothesis generators for further analysis. Second, the proposed methodology is validated on tandem mass spectrometral data using a public spectral library, where associations within the mass differences of unassigned peaks and peptide modifications are explored. The investigation of the found patterns illustrates that meaningful patterns can be discovered that can be explained by features of the employed technology and found modifications. CONCLUSIONS: This simple approach offers opportunities to monitor accumulating unexplained mass spectrometry data for emerging new patterns, with possible applications for the development of mass exclusion lists, for the refinement of quality control strategies and for a further interpretation of unexplained spectral peaks in mass spectrometry and tandem mass spectrometry.

Analysis of the formalin-fixed paraffin-embedded tissue proteome: pitfalls, challenges, and future prospectives.

Formalin-fixed paraffin-embedded (FFPE) tissues are a real treasure for retrospective analysis considering the amount of samples present in hospital archives, combined with pathological, clinical, and outcome information available for every sample. Although unlocking the proteome of these tissues is still a challenge, new approaches are being developed. In this review, we summarize the different mass spectrometry platforms that are used in human clinical studies to unravel the FFPE proteome. The different ways of extracting crosslinked proteins and the analytical strategies are pointed out. Also, the pitfalls and challenges concerning the quality of FFPE proteomic approaches are depicted. We also evaluated the potential of these analytical methods for future clinical FFPE proteomics applications.

Characterizing lysinoalanine crosslinks in food systems: Discovery of a diagnostic ion in model peptides using MALDI mass spectrometry.

Formation of lysinoalanine protein-protein crosslinks during food processing adversely impacts nutritional value. However, mapping lysinoalanine directly in food is challenging. We characterized the fragmentation pattern of lysinoalanine crosslinks in synthetic peptide models over a range of pH and time treatments using mass spectrometry. A putative diagnostic ion resulting from the cleavage of the α-carbon and ß-carbon of lysinoalanine is identified in MALDI MS/MS spectra. This represents the first step in mapping lysinoalanine in real food samples with higher precision than currently identifiable through standard or customized software. We then determined a correlated trend in the reduction of disulfide bonds and formation of lysinoalanine with increasing pH and time. Mapping lysinoalanine formation is critical to enhance our understanding of molecular processes impacting the nutritional value of foods, including notably in the development of protein alternatives that use alkaline treatment to extract protein isolates.

Unlocking the bioactivity of meat proteins: Comparison of meat and meat hydrolysate via simulated gastrointestinal digestion.

Understanding the functional attributes of meat proteins is crucial for determining their nutritional benefits. Depending on the form in which meat proteins are available, the digestive process can release peptides which are valuable for nutrition and may also possess bioactive properties, affecting physiology. Liquid chromatography - mass spectrometry (LC-MS) was used to quantitatively compare the molecular peptide features (representing non-redundant peptides), during the different stages of a simulated gastrointestinal digestion process of a minimally processed powdered meat and its enzymatically produced hydrolysate. Results from a principal component analysis (PCA) indicated that the hydrolysate did not undergo extensive additional digestion whereas the powdered meat was digested both at the gastric and in the intestinal phases. Bioactive peptide sequence prediction identified the meat hydrolysate but not the meat powder as the only source of exact and partial bioactive matches in the angiotensin-I converting enzyme and dipeptidyl peptidase IV inhibition categories. Also, a higher source of cryptides (encrypted bioactive peptides), indicated that meat hydrolysates are potentially a better substrate for the release of these enzyme inhibitory peptides. These observations thus suggest that pre-digestion of a complex food matrix such as meat, may enhance its bioavailability following oral consumption early in the digestion process. SIGNIFICANCE: This work highlights enzymatic hydrolysis of meat proteins prior to ingestion allows for potentially higher bioavailability of bioactive peptides that inhibit angiotensin-I converting enzyme and dipeptidyl peptidase IV, thus possibly aiding high blood pressure and type 2 diabetes management.

Effect of Heat Treatment on Protein Self-Digestion in Ruminants' Milk.

This study investigated whether heat treatments (raw, 63 °C for 30 min, and 85 °C for 5 min) affect protein hydrolysis by endogenous enzymes in the milk of ruminants (bovine, ovine, and caprine) using a self-digestion model. Self-digestion consisted of the incubation for six hours at 37 °C of the ruminants' milk. Free amino group concentration was measured by the o-phthaldialdehyde method, and peptide sequences were identified by chromatography-mass spectrometry. Results showed that heat treatments prior to self-digestion decreased the free NH2 by 59% in bovine milk heated at 85 °C/5 min, and by 44 and 53% in caprine milk heated at 63 °C/30 min and 85 °C/5 min, respectively. However, after self-digestion, only new free amino groups were observed for the raw and heated at 63 °C/30 min milk. ß-Casein was the most cleaved protein in the raw and heated at 63 °C/30 min bovine milk. A similar trend was observed in raw ovine and caprine milk. Self-digestion increased 6.8-fold the potential antithrombin peptides in the bovine milk heated at 63 °C/30 min. Enhancing bioactive peptide abundance through self-digestion has potential applications in the industry for functional products. Overall, heat treatments affected the free amino groups according to the species and heat treatment applied, which was reflected in the varying degrees of cleaved peptide bonds and peptides released during self-digestion.

Characterization of the Biosynthetic Gene Cluster for the Ribosomally Synthesized Cyclic Peptide Epichloëcyclins in Epichloë festucae.

The various grass-induced epichloëcyclins of the Epichloë spp. are ribosomally synthesized and post-translationally modified peptides (RiPPs), produced as small, secreted cyclopeptides from a single gene, gigA. Here, four clustered and coregulated genes (gigA, gigB, gigC, and kexB) with predicted roles in epichloëcyclin production in Epichloë festucae were evaluated through gene disruption. Subsequent chemical analysis indicates that GigB is a DUF3328 domain-containing protein associated with cyclization of epichloëcyclins; GigC is a methyltransferase enzyme responsible for N-methylation of desmethylepichloëcyclins; and KexB is a subtilisin-like enzyme, partly responsible for the propeptide cleavage of epichloëcyclin intermediates. Symbiotic effects on the host phenotype were not observed for gigA, gigC, or kexB mutants, although ΔgigB infection correlated with increased host tiller height and biomass, while only ΔkexB exhibited an effect on endophyte morphology. Disrupting epichloëcyclin biosynthesis showed negligible influence on the biosynthesis of E. festucae-associated alkaloids. Epichloëcyclins may perform other secondary metabolism functions in Epichloë and other fungi.