Effect of maternal prebiotic supplementation on human milk immunological composition: Insights from the SYMBA study

Background: Immunomodulatory proteins in human milk (HM) can shape infant immune development. However, strategies to modulate their levels are currently unknown. This study investigated whether maternal prebiotic supplementation alters the levels of immunomodulatory proteins in HM. Methods: The study was nested within the SYMBA double-blind randomized controlled trial (ACTRN12615001075572), which investigated the effects of maternal prebiotic (short-chain galacto-oligosaccharides/long-chain fructo-oligosaccharides) supplementation from \u3c21 weeks gestation during pregnancy until 6 months postnatal during lactation on child allergic disease risk. Mother–child dyads receiving prebiotics (n = 46) or placebo (n = 54) were included in this study. We measured the levels of 24 immunomodulatory proteins in HM collected at 2, 4, and 6 months. Results: Cluster analysis showed that the overall immunomodulatory protein composition of milk samples from both groups was similar. At 2 months, HM of prebiotic-supplemented women had decreased levels of TGF-β1 and TSLP (95% CI: −17.4 [−29.68, −2.28] and −57.32 [−94.22, −4.7] respectively) and increased levels of sCD14 (95% CI: 1.81 [0.17, 3.71]), when compared to the placebo group. At 4 months, IgG1 was lower in the prebiotic group (95% CI: −1.55 [−3.55, −0.12]) compared to placebo group. Conclusion: This exploratory study shows that prebiotic consumption by lactating mothers selectively alters specific immunomodulatory proteins in HM. This finding is crucial for understanding how prebiotic dietary recommendations for pregnant and lactating women can modify the immune properties of HM and potentially influence infant health outcomes through immune support from breastfeeding

Study protocol for a stepped-wedge cluster (nested) randomized controlled trial of antenatal colostrum expression (ACE) instruction in first-time mothers: The ACE study

Background: Although many mothers initiate breastfeeding, supplementation with human-milk substitutes (formula) during the birth hospitalization is common and has been associated with early breastfeeding cessation. Colostrum hand expressed in the last few weeks before birth, known as antenatal colostrum expression (ACE), can be used instead of human-milk substitutes. However, evidence is lacking on the efficacy of ACE on breastfeeding outcomes and in non-diabetic mothers. Methods and Planned Analysis: This multicenter stepped-wedge cluster (nested) randomized controlled trial aims to recruit 945 nulliparous pregnant individuals. The trial is conducted in two phases. During Phase 1, control group participants are under standard care. During Phase 2, participants are randomized to ACE instruction via a pre-recorded online video or a one-on-one session with a midwife. Adjusted logistic regression analysis will be used to examine the relationship between ACE instruction and breastfeeding outcomes. Research Aims and Questions: Primary aim: (1) Does advising pregnant individuals to practice ACE and providing instruction improve exclusive breastfeeding rates at 4 months postpartum? Secondary research questions: (2) Do individuals who practice ACE have higher rates of exclusive breastfeeding during the initial hospital stay after birth? (3) Is teaching ACE via an online video non-inferior to one-on-one instruction from a midwife? (4) Does expressing colostrum in pregnancy influence time to secretory activation, or (5) result in any differences in the composition of postnatal colostrum? Discussion: Trial findings have important implications for maternity practice, with the online video providing an easily accessible opportunity for ACE education as part of standard antenatal care

Modulating gut microbiota in a mouse model of Graves' orbitopathy and its impact on induced disease

BACKGROUND: Graves' disease (GD) is an autoimmune condition in which autoantibodies to the thyrotropin receptor (TSHR) cause hyperthyroidism. About 50% of GD patients also have Graves' orbitopathy (GO), an intractable disease in which expansion of the orbital contents causes diplopia, proptosis and even blindness. Murine models of GD/GO, developed in different centres, demonstrated significant variation in gut microbiota composition which correlated with TSHR-induced disease heterogeneity. To investigate whether correlation indicates causation, we modified the gut microbiota to determine whether it has a role in thyroid autoimmunity. Female BALB/c mice were treated with either vancomycin, probiotic bacteria, human fecal material transfer (hFMT) from patients with severe GO or ddH2O from birth to immunization with TSHR-A subunit or beta-galactosidase (βgal; age ~ 6 weeks). Incidence and severity of GD (TSHR autoantibodies, thyroid histology, thyroxine level) and GO (orbital fat and muscle histology), lymphocyte phenotype, cytokine profile and gut microbiota were analysed at sacrifice (~ 22 weeks). RESULTS: In ddH2O-TSHR mice, 84% had pathological autoantibodies, 67% elevated thyroxine, 77% hyperplastic thyroids and 70% orbital pathology. Firmicutes were increased, and Bacteroidetes reduced relative to ddH2O-βgal; CCL5 was increased. The random forest algorithm at the genus level predicted vancomycin treatment with 100% accuracy but 74% and 70% for hFMT and probiotic, respectively. Vancomycin significantly reduced gut microbiota richness and diversity compared with all other groups; the incidence and severity of both GD and GO also decreased; reduced orbital pathology correlated positively with Akkermansia spp. whilst IL-4 levels increased. Mice receiving hFMT initially inherited their GO donors' microbiota, and the severity of induced GD increased, as did the orbital brown adipose tissue volume in TSHR mice. Furthermore, genus Bacteroides, which is reduced in GD patients, was significantly increased by vancomycin but reduced in hFMT-treated mice. Probiotic treatment significantly increased CD25+ Treg cells in orbital draining lymph nodes but exacerbated induced autoimmune hyperthyroidism and GO. CONCLUSIONS: These results strongly support a role for the gut microbiota in TSHR-induced disease. Whilst changes to the gut microbiota have a profound effect on quantifiable GD endocrine and immune factors, the impact on GO cellular changes is more nuanced. The findings have translational potential for novel, improved treatments. Video abstract

An FPT Approach for Predicting Protein Localization from Yeast Genomic Data

Accurately predicting the localization of proteins is of paramount importance in the quest to determine their respective functions within the cellular compartment. Because of the continuous and rapid progress in the fields of genomics and proteomics, more data are available now than ever before. Coincidentally, data mining methods been developed and refined in order to handle this experimental windfall, thus allowing the scientific community to quantitatively address long-standing questions such as that of protein localization. Here, we develop a frequent pattern tree (FPT) approach to generate a minimum set of rules (mFPT) for predicting protein localization. We acquire a series of rules according to the features of yeast genomic data. The mFPT prediction accuracy is benchmarked against other commonly used methods such as Bayesian networks and logistic regression under various statistical measures. Our results show that mFPT gave better performance than other approaches in predicting protein localization. Meanwhile, setting 0.65 as the minimum hit-rate, we obtained 138 proteins that mFPT predicted differently than the simple naive bayesian method (SNB). In our analysis of these 138 proteins, we present novel predictions for the location for 17 proteins, which currently do not have any defined localization. These predictions can serve as putative annotations and should provide preliminary clues for experimentalists. We also compared our predictions against the eukaryotic subcellular localization database and related predictions by others on protein localization. Our method is quite generalized and can thus be applied to discover the underlying rules for protein-protein interactions, genomic interactions, and structure-function relationships, as well as those of other fields of research