The evolutionary strategy of transferring maternal antibodies via milk profoundly impacts the survival, lifelong health, and wellbeing of all neonates, including a pronounced impact on human breastfeeding success and infant development. While there has been increased recognition that interorgan connectivity influences the quality of a mother's milk, potentially to personalize it for her offspring, the underlying bases for these processes are incompletely resolved. Here, we define an essential role of Peyer's patches (PPs) for the generation of plasma cells that secrete maternal immunoglobulin A (IgA) into milk. Our metagenomic analysis reveals that the presence of certain residential microorganisms in the gastrointestinal (GI) tract, such as Bacteroides acidifaciens and Prevotella buccalis, is indispensable for the programming of maternal IgA synthesis prior to lactational transfer. Our data provide important insights into how the microbiome of the maternal GI environment, specifically through PPs, can be communicated to the next generation via milk.

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Background Establishing fecal microbiota transplantation (FMT) to prevent multifactorial diarrhea in calves is challenging because of the differences in farm management practices, the lack of optimal donors, and recipient selection. In this study, the underlying factors of successful and unsuccessful FMT treatment cases are elucidated, and the potential markers for predicting successful FMT are identified using fecal metagenomics via 16S rRNA gene sequencing, fecal metabolomics via capillary electrophoresis time-of-flight mass spectrometry, and machine learning approaches. Results Specifically, 20 FMT treatment cases, in which feces from healthy donors were intrarectally transferred into recipient diarrheal calves, were conducted with a success rate of 70%. Selenomonas was identified as a microorganism genus that showed significant donor–recipient compatibility in successful FMT treatments. A strong positive correlation between the microbiome and metabolome data, which is a prerequisite factor for FMT success, was confirmed by Procrustes analysis in successful FMT (r = 0.7439, P = 0.0001). Additionally, weighted gene correlation network analysis confirmed the positively or negatively correlated pairs of bacterial taxa (family Veillonellaceae) and metabolomic features (i.e., amino acids and short-chain fatty acids) responsible for FMT success. Further analysis aimed at establishing criteria for donor selection identified the genus Sporobacter as a potential biomarker in successful donor selection. Low levels of metabolites, such as glycerol 3-phosphate, dihydroxyacetone phosphate, and isoamylamine, in the donor or recipients prior to FMT, are predicted to facilitate FMT. Conclusions Overall, we provide the first substantial evidence of the factors related to FMT success or failure; these findings could improve the design of future microbial therapeutics for treating diarrhea in calves.

To investigate 3′-end-processing signals in Aspergillus oryzae, we created a nucleotide sequence data set of the 3′-untranslated region (3′ UTR) plus 100 nucleotides (nt) sequence downstream of the poly(A) site using A. oryzae expressed sequence tags and genomic sequencing data. This data set comprised 1065 sequences derived from 1042 unique genes. The average 3′ UTR length in A. oryzae was 241 nt, which is greater than that in yeast but similar to that in plants. The 3′ UTR and 100 nt sequence downstream of the poly(A) site is notably U-rich, while the region located 15–30 nt upstream of the poly(A) site is markedly A-rich. The most frequently found hexanucleotide in this A-rich region is AAUGAA, although this sequence accounts for only 6% of all transcripts. These data suggested that A. oryzae has no highly conserved sequence element equivalent to AAUAAA, a mammalian polyadenylation signal. We identified that putative 3′-end-processing signals in A. oryzae, while less well conserved than those in mammals, comprised four sequence elements: the furthest upstream U-rich element, A-rich sequence, cleavage site, and downstream U-rich element flanking the cleavage site. Although these putative 3′-end-processing signals are similar to those in yeast and plants, some notable differences exist between them.