The influence of a maternal vegan diet on carnitine and vitamin B2 concentrations in human milk

BackgroundThe maternal diet greatly influences the nutritional composition of human milk. With the rise of vegan diets by lactating mothers, there are concerns about the nutritional adequacy of their milk. Two important nutrients, vitamin B2 and carnitine, are mostly ingested via animal products.ObjectiveWe investigated the influence of a vegan diet on the vitamin B2 and carnitine concentrations in milk and serum of lactating women.MethodsIn this case–control study, 25 lactating mothers following an exclusive vegan diet were comparted to 25 healthy lactating mothers with an omnivorous diet without use of supplements. High-performance liquid chromatography and liquid chromatography–tandem mass spectrometry were used to measure vitamin B2 and carnitine concentrations, respectively. A linear regression model was used to determine differences in human milk and serum concentrations between study groups.ResultsVitamin B2 concentrations in human milk and serum did not differ between study groups. While the human milk free carnitine (C0) and acetyl carnitine (C2) concentrations did not differ between study groups, serum carnitine concentrations were lower in participants following a vegan diet than in omnivorous women (p < 0.0001).ConclusionA maternal vegan diet did not affect human milk concentration of vitamin B2 and carnitine. Breastfed infants of mothers following an exclusive vegan diet therefore are likely not at increased risk of developing a vitamin B2 or carnitine deficiency

Substrate Micropatterning as a New in Vitro Cell Culture System to Study Myelination

Artículo de publicación ISIMyelination is a highly regulated developmental process whereby oligodendrocytes in the central nervous system and Schwann cells in the peripheral nervous system ensheathe axons with a multilayered concentric membrane. Axonal myelination increases the velocity of nerve impulse propagation. In this work, we present a novel in vitro system for coculturing primary dorsal root ganglia neurons along with myelinating cells on a highly restrictive and micropatterned substrate. In this new coculture system, neurons survive for several weeks, extending long axons on defined Matrigel tracks. On these axons, myelinating cells can achieve robust myelination, as demonstrated by the distribution of compact myelin and nodal markers. Under these conditions, neurites and associated myelinating cells are easily accessible for studies on the mechanisms of myelin formation and on the effects of axonal damage on the myelin sheath.Regenerative Medicine and Nanomedicine Initiative of the Canadian Institutes of Health Research (CIHR) RMF-7028 FONDECYT 1080252 CIHR Ministry of Industry of Canada Rio Tinto Alcan Molson Foundatio

NetCTLpan: pan-specific MHC class I pathway epitope predictions

Reliable predictions of immunogenic peptides are essential in rational vaccine design and can minimize the experimental effort needed to identify epitopes. In this work, we describe a pan-specific major histocompatibility complex (MHC) class I epitope predictor, NetCTLpan. The method integrates predictions of proteasomal cleavage, transporter associated with antigen processing (TAP) transport efficiency, and MHC class I binding affinity into a MHC class I pathway likelihood score and is an improved and extended version of NetCTL. The NetCTLpan method performs predictions for all MHC class I molecules with known protein sequence and allows predictions for 8-, 9-, 10-, and 11-mer peptides. In order to meet the need for a low false positive rate, the method is optimized to achieve high specificity. The method was trained and validated on large datasets of experimentally identified MHC class I ligands and cytotoxic T lymphocyte (CTL) epitopes. It has been reported that MHC molecules are differentially dependent on TAP transport and proteasomal cleavage. Here, we did not find any consistent signs of such MHC dependencies, and the NetCTLpan method is implemented with fixed weights for proteasomal cleavage and TAP transport for all MHC molecules. The predictive performance of the NetCTLpan method was shown to outperform other state-of-the-art CTL epitope prediction methods. Our results further confirm the importance of using full-type human leukocyte antigen restriction information when identifying MHC class I epitopes. Using the NetCTLpan method, the experimental effort to identify 90% of new epitopes can be reduced by 15% and 40%, respectively, when compared to the NetMHCpan and NetCTL methods. The method and benchmark datasets are available at http://www.cbs.dtu.dk/services/NetCTLpan/

Proteome Sampling by the HLA Class I Antigen Processing Pathway

The peptide repertoire that is presented by the set of HLA class I molecules of an individual is formed by the different players of the antigen processing pathway and the stringent binding environment of the HLA class I molecules. Peptide elution studies have shown that only a subset of the human proteome is sampled by the antigen processing machinery and represented on the cell surface. In our study, we quantified the role of each factor relevant in shaping the HLA class I peptide repertoire by combining peptide elution data, in silico predictions of antigen processing and presentation, and data on gene expression and protein abundance. Our results indicate that gene expression level, protein abundance, and rate of potential binding peptides per protein have a clear impact on sampling probability. Furthermore, once a protein is available for the antigen processing machinery in sufficient amounts, C-terminal processing efficiency and binding affinity to the HLA class I molecule determine the identity of the presented peptides. Having studied the impact of each of these factors separately, we subsequently combined all factors in a logistic regression model in order to quantify their relative impact. This model demonstrated the superiority of protein abundance over gene expression level in predicting sampling probability. Being able to discriminate between sampled and non-sampled proteins to a significant degree, our approach can potentially be used to predict the sampling probability of self proteins and of pathogen-derived proteins, which is of importance for the identification of autoimmune antigens and vaccination targets

A case series exploring the human milk polyclonal IgA1 response to repeated SARS-CoV-2 vaccinations by LC-MS based fab profiling

INTRODUCTION: Upon vaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) humans will start to produce antibodies targeting virus specific antigens that will end up in circulation. In lactating women such antibodies will also end up in breastmilk, primarily in the form of secretory immunoglobulin A1 (SIgA1), the most abundant immunoglobulin (Ig) in human milk. Here we set out to investigate the SIgA1 clonal repertoire response to repeated SARS-CoV-2 vaccination, using a LC-MS fragment antigen-binding (Fab) clonal profiling approach. METHODS: We analyzed the breastmilk of six donors from a larger cohort of 109 lactating mothers who received one of three commonly used SARS-CoV-2 vaccines. We quantitatively monitored the SIgA1 Fab clonal profile over 16 timepoints, from just prior to the first vaccination until 15  days after the second vaccination. RESULTS: In all donors, we detected a population of 89-191 vaccine induced clones. These populations were unique to each donor and heterogeneous with respect to individual clonal concentrations, total clonal titer, and population size. The vaccine induced clones were dominated by persistent clones (68%) which came up after the first vaccination and were retained or reoccurred after the second vaccination. However, we also observe transient SIgA1 clones (16%) which dissipated before the second vaccination, and vaccine induced clones which uniquely emerged only after the second vaccination (16%). These distinct populations were observed in all analyzed donors, regardless of the administered vaccine. DISCUSSION: Our findings suggest that while individual donors have highly unique human milk SIgA1 clonal profiles and a highly personalized SIgA1 response to SARS-CoV-2 vaccination, there are also commonalities in vaccine induced responses

In vitro analysis of the effects on wound healing of high- and low-molecular weight chains of hyaluronan and their hybrid H-HA/L-HA complexes

Abstract Background: Recent studies have reported the roles of Hyaluronic acid (HA) chains of diverse length in wound repair, especially considering the simultaneous occurrence in vivo of both high- (H-HA) and low-molecular weight (L-HA) hyaluronan at an injury site. It has been shown that HA fragments (5 ≤ MW ≤ 20 kDa) usually trigger an inflammatory response that, on one hand, is the first signal in the activation of a repair mechanism but on the other, when it’s overexpressed, it may promote unwanted side effects. The present experimental research has aimed to investigate H-HA, L-HA and of a newly developed complex of the two (H-HA/L-HA) for stability (e.g. hyaluronidases digestion), for their ability to promote wound healing of human keratinocytes in vitro and for their effect on cellular biomarker expression trends. Results: Time-lapse video microscopy studies proved that the diverse HA was capable of restoring the monolayer integrity of HaCat. The H-HA/L-HA complex (0.1 and 1%w/v) proved faster in regeneration also in co-culture scratch test where wound closure was achieved in half the time of H-HA stimulated cells and 2.5-fold faster than the control. Gene expression was evaluated for transformation growth factor beta 1 (TGF-β1) proving that L-HA alone increased its expression at 4 h followed by restoration of similar trends for all the stimuli. Depending on the diverse stimulation (H-HA, L-HA or the complex), metalloproteinases (MMP-2, -9, -13) were also modulated differently. Furthermore, type I collagen expression and production were evaluated. Compared to the others, persistence of a significant higher expression level at 24 h for the H-HA/L-HA complex was found. Conclusions: The outcomes of this research showed that, both at high and low concentrations, hybrid complexes proved to perform better than HA alone thus suggesting their potential as medical devices in aesthetic and regenerative medicine. Keywords: Wound healing, Hyaluronan, MMPs, Hybrid complexe

Protein Domain of Unknown Function 3233 is a Translocation Domain of Autotransporter Secretory Mechanism in Gamma proteobacteria

Vibrio cholerae, the enteropathogenic gram negative bacteria is one of the main causative agents of waterborne diseases like cholera. About 1/3rd of the organism's genome is uncharacterised with many protein coding genes lacking structure and functional information. These proteins form significant fraction of the genome and are crucial in understanding the organism's complete functional makeup. In this study we report the general structure and function of a family of hypothetical proteins, Domain of Unknown Function 3233 (DUF3233), which are conserved across gram negative gammaproteobacteria (especially in Vibrio sp. and similar bacteria). Profile and HMM based sequence search methods were used to screen homologues of DUF3233. The I-TASSER fold recognition method was used to build a three dimensional structural model of the domain. The structure resembles the transmembrane beta-barrel with an axial N-terminal helix and twelve antiparallel beta-strands. Using a combination of amphipathy and discrimination analysis we analysed the potential transmembrane beta-barrel forming properties of DUF3233. Sequence, structure and phylogenetic analysis of DUF3233 indicates that this gram negative bacterial hypothetical protein resembles the beta-barrel translocation unit of autotransporter Va secretory mechanism with a gene organisation that differs from the conventional Va system

A new approach to assess and predict the functional roles of proteins across all known structures

The three dimensional atomic structures of proteins provide information regarding their function; and codified relationships between structure and function enable the assessment of function from structure. In the current study, a new data mining tool was implemented that checks current gene ontology (GO) annotations and predicts new ones across all the protein structures available in the Protein Data Bank (PDB). The tool overcomes some of the challenges of utilizing large amounts of protein annotation and measurement information to form correspondences between protein structure and function. Protein attributes were extracted from the Structural Biology Knowledgebase and open source biological databases. Based on the presence or absence of a given set of attributes, a given protein’s functional annotations were inferred. The results show that attributes derived from the three dimensional structures of proteins enhanced predictions over that using attributes only derived from primary amino acid sequence. Some predictions reflected known but not completely documented GO annotations. For example, predictions for the GO term for copper ion binding reflected used information a copper ion was known to interact with the protein based on information in a ligand interaction database. Other predictions were novel and require further experimental validation. These include predictions for proteins labeled as unknown function in the PDB. Two examples are a role in the regulation of transcription for the protein AF1396 from Archaeoglobus fulgidus and a role in RNA metabolism for the protein psuG from Thermotoga maritima