SCARPET: site-specific quantification of methylated and nonmethylated adenosines reveals m6A stoichiometry.

m6A has different stoichiometry at different positions in different mRNAs. However, the exact stoichiometry of m6A is difficult to measure. Here, we describe SCARPET (site-specific cleavage and radioactive-labeling followed by purification, exonuclease digestion, and thin-layer chromatography), a simple and streamlined biochemical assay for quantifying m6A at any specific site in any mRNA. SCARPET involves a site-specific cleavage of mRNA immediately 5' of an adenosine site in an mRNA. This site is radiolabeled with 32P, and after a series of steps to purify the RNA and to remove nonspecific signals, the nucleotide is resolved by TLC to visualize A and m6A at this site. Quantification of these spots reveals the m6A stoichiometry at the site of interest. SCARPET can be applied to poly(A)-enriched RNA, or preferably purified mRNA, which produces more accurate m6A stoichiometry measurements. We show that sample processing steps of SCARPET can be performed in a single day, and results in a specific and accurate measurement of m6A stoichiometry at specific sites in mRNA. Using SCARPET, we measure exact m6A stoichiometries in specific mRNAs and show that Zika genomic RNA lacks m6A at previously mapped sites. SCARPET will be useful for testing specific sites for their m6A stoichiometry and to assess how m6A stoichiometry changes in different conditions and cellular contexts.

ß Cell and Autophagy: What Do We Know?

Pancreatic ß cells are central to glycemic regulation through insulin production. Studies show autophagy as an essential process in ß cell function and fate. Autophagy is a catabolic cellular process that regulates cell homeostasis by recycling surplus or damaged cell components. Impaired autophagy results in ß cell loss of function and apoptosis and, as a result, diabetes initiation and progress. It has been shown that in response to endoplasmic reticulum stress, inflammation, and high metabolic demands, autophagy affects ß cell function, insulin synthesis, and secretion. This review highlights recent evidence regarding how autophagy can affect ß cells' fate in the pathogenesis of diabetes. Furthermore, we discuss the role of important intrinsic and extrinsic autophagy modulators, which can lead to ß cell failure.

Development of multiple AI pipelines that predict neoadjuvant chemotherapy response of breast cancer using H&E-stained tissues.

In recent years, the treatment of breast cancer has advanced dramatically and neoadjuvant chemotherapy (NAC) has become a common treatment method, especially for locally advanced breast cancer. However, other than the subtype of breast cancer, no clear factor indicating sensitivity to NAC has been identified. In this study, we attempted to use artificial intelligence (AI) to predict the effect of preoperative chemotherapy from hematoxylin and eosin images of pathological tissue obtained from needle biopsies prior to chemotherapy. Application of AI to pathological images typically uses a single machine-learning model such as support vector machines (SVMs) or deep convolutional neural networks (CNNs). However, cancer tissues are extremely diverse and learning with a realistic number of cases limits the prediction accuracy of a single model. In this study, we propose a novel pipeline system that uses three independent models each focusing on different characteristics of cancer atypia. Our system uses a CNN model to learn structural atypia from image patches and SVM and random forest models to learn nuclear atypia from fine-grained nuclear features extracted by image analysis methods. It was able to predict the NAC response with 95.15% accuracy on a test set of 103 unseen cases. We believe that this AI pipeline system will contribute to the adoption of personalized medicine in NAC therapy for breast cancer.

Pro-Inflammatory Cytokines Promote the Transcription of Circular RNAs in Human Pancreatic ß Cells.

Circular RNAs (circRNAs) have recently been implicated in impaired ß-cell function in diabetes. Using microarray-based profiling of circRNAs in human EndoC-ßH1 cells treated with pro-inflammatory cytokines, this study aimed to investigate the expression and possible regulatory roles of circRNAs in human ß cells. We identified ~5000 ß-cell-expressed circRNAs, of which 84 were differentially expressed (DE) after cytokine exposure. Pathway analysis of the host genes of the DE circRNAs revealed the enrichment of cytokine signaling pathways, indicative of circRNA transcription from inflammatory genes in response to cytokines. Multiple binding sites for ß-cell-enriched microRNAs and RNA-binding proteins were observed for the highly upregulated circRNAs, supporting their function as 'sponges' or 'decoys'. We also present evidence for circRNA sequence conservation in multiple species, the presence of cytokine-induced regulatory elements, and putative protein-coding potential for the DE circRNAs. This study highlights the complex regulatory potential of circRNAs, which may play a crucial role during immune-mediated ß-cell destruction in type 1 diabetes.

Alternative splicing of METTL3 explains apparently METTL3-independent m6A modifications in mRNA.

N6-methyladenosine (m6A) is a highly prevalent mRNA modification that promotes degradation of transcripts encoding proteins that have roles in cell development, differentiation, and other pathways. METTL3 is the major methyltransferase that catalyzes the formation of m6A in mRNA. As 30% to 80% of m6A can remain in mRNA after METTL3 depletion by CRISPR/Cas9-based methods, other enzymes are thought to catalyze a sizable fraction of m6A. Here, we reexamined the source of m6A in the mRNA transcriptome. We characterized mouse embryonic stem cell lines that continue to have m6A in their mRNA after Mettl3 knockout. We show that these cells express alternatively spliced Mettl3 transcript isoforms that bypass the CRISPR/Cas9 mutations and produce functionally active methyltransferases. We similarly show that other reported METTL3 knockout cell lines express altered METTL3 proteins. We find that gene dependency datasets show that most cell lines fail to proliferate after METTL3 deletion, suggesting that reported METTL3 knockout cell lines express altered METTL3 proteins rather than have full knockout. Finally, we reassessed METTL3's role in synthesizing m6A using an exon 4 deletion of Mettl3 and found that METTL3 is responsible for >95% of m6A in mRNA. Overall, these studies suggest that METTL3 is responsible for the vast majority of m6A in the transcriptome, and that remaining m6A in putative METTL3 knockout cell lines is due to the expression of altered but functional METTL3 isoforms.

Alphaherpesvirus US3 protein-mediated inhibition of the m6A mRNA methyltransferase complex.

Chemical modifications of mRNA, the so-called epitranscriptome, represent an additional layer of post-transcriptional regulation of gene expression. The most common epitranscriptomic modification, N6-methyladenosine (m6A), is generated by a multi-subunit methyltransferase complex. We show that alphaherpesvirus kinases trigger phosphorylation of several components of the m6A methyltransferase complex, including METTL3, METTL14, and WTAP, which correlates with inhibition of the complex and a near complete loss of m6A levels in mRNA of virus-infected cells. Expression of the viral US3 protein is necessary and sufficient for phosphorylation and inhibition of the m6A methyltransferase complex. Although m6A methyltransferase complex inactivation is not essential for virus replication in cell culture, the consensus m6A methylation motif is under-represented in alphaherpesvirus genomes, suggesting evolutionary pressure against methylation of viral transcripts. Together, these findings reveal that phosphorylation can be associated with inactivation of the m6A methyltransferase complex, in this case mediated by the viral US3 protein.

N6-methyladenosine in poly(A) tails stabilize VSG transcripts.

RNA modifications are important regulators of gene expression1. In Trypanosoma brucei, transcription is polycistronic and thus most regulation happens post-transcriptionally2. N6-methyladenosine (m6A) has been detected in this parasite, but its function remains unknown3. Here we found that m6A is enriched in 342 transcripts using RNA immunoprecipitation, with an enrichment in transcripts encoding variant surface glycoproteins (VSGs). Approximately 50% of the m6A is located in the poly(A) tail of the actively expressed VSG transcripts. m6A residues are removed from the VSG poly(A) tail before deadenylation and mRNA degradation. Computational analysis revealed an association between m6A in the poly(A) tail and a 16-mer motif in the 3' untranslated region of VSG genes. Using genetic tools, we show that the 16-mer motif acts as a cis-acting motif that is required for inclusion of m6A in the poly(A) tail. Removal of this motif from the 3' untranslated region of VSG genes results in poly(A) tails lacking m6A, rapid deadenylation and mRNA degradation. To our knowledge, this is the first identification of an RNA modification in the poly(A) tail of any eukaryote, uncovering a post-transcriptional mechanism of gene regulation.

Does rapid sequence divergence preclude RNA structure conservation in vertebrates?

Accelerated evolution of any portion of the genome is of significant interest, potentially signaling positive selection of phenotypic traits and adaptation. Accelerated evolution remains understudied for structured RNAs, despite the fact that an RNA's structure is often key to its function. RNA structures are typically characterized by compensatory (structure-preserving) basepair changes that are unexpected given the underlying sequence variation, i.e., they have evolved through negative selection on structure. We address the question of how fast the primary sequence of an RNA can change through evolution while conserving its structure. Specifically, we consider predicted and known structures in vertebrate genomes. After careful control of false discovery rates, we obtain 13 de novo structures (and three known Rfam structures) that we predict to have rapidly evolving sequences-defined as structures where the primary sequences of human and mouse have diverged at least twice as fast (1.5 times for Rfam) as nearby neutrally evolving sequences. Two of the three known structures function in translation inhibition related to infection and immune response. We conclude that rapid sequence divergence does not preclude RNA structure conservation in vertebrates, although these events are relatively rare.

Prediction of non-muscle invasive bladder cancer recurrence using machine learning of quantitative nuclear features.

Non-muscle invasive bladder cancer (NMIBC) generally has a good prognosis; however, recurrence after transurethral resection (TUR), the standard primary treatment, is a major problem. Clinical management after TUR has been based on risk classification using clinicopathological factors, but these classifications are not complete. In this study, we attempted to predict early recurrence of NMIBC based on machine learning of quantitative morphological features. In general, structural, cellular, and nuclear atypia are evaluated to determine cancer atypia. However, since it is difficult to accurately quantify structural atypia from TUR specimens, in this study, we used only nuclear atypia and analyzed it using feature extraction followed by classification using Support Vector Machine and Random Forest machine learning algorithms. For the analysis, 125 patients diagnosed with NMIBC were used; data from 95 patients were randomly selected for the training set, and data from 30 patients were randomly selected for the test set. The results showed that the support vector machine-based model predicted recurrence within 2 years after TUR with a probability of 90% and the random forest-based model with probability of 86.7%. In the future, the system can be used to objectively predict NMIBC recurrence after TUR.

Cross-species high-resolution transcriptome profiling suggests biomarkers and therapeutic targets for ulcerative colitis.

Background: Ulcerative colitis (UC) is a disorder with unknown etiology, and animal models play an essential role in studying its molecular pathophysiology. Here, we aim to identify common conserved pathological UC-related gene expression signatures between humans and mice that can be used as treatment targets and/or biomarker candidates. Methods: To identify differentially regulated protein-coding genes and non-coding RNAs, we sequenced total RNA from the colon and blood of the most widely used dextran sodium sulfate Ulcerative colitis mouse. By combining this with public human Ulcerative colitis data, we investigated conserved gene expression signatures and pathways/biological processes through which these genes may contribute to disease development/progression. Results: Cross-species integration of human and mouse Ulcerative colitis data resulted in the identification of 1442 genes that were significantly differentially regulated in the same direction in the colon and 157 in blood. Of these, 51 genes showed consistent differential regulation in the colon and blood. Less known genes with importance in disease pathogenesis, including SPI1, FPR2, TYROBP, CKAP4, MCEMP1, ADGRG3, SLC11A1, and SELPLG, were identified through network centrality ranking and validated in independent human and mouse cohorts. Conclusion: The identified Ulcerative colitis conserved transcriptional signatures aid in the disease phenotyping and future treatment decisions, drug discovery, and clinical trial design.

Plasma Exosome-Enriched Extracellular Vesicles From Lactating Mothers With Type 1 Diabetes Contain Aberrant Levels of miRNAs During the Postpartum Period.

Type 1 diabetes is an immune-driven disease, where the insulin-producing beta cells from the pancreatic islets of Langerhans becomes target of immune-mediated destruction. Several studies have highlighted the implication of circulating and exosomal microRNAs (miRNAs) in type 1 diabetes, underlining its biomarker value and novel therapeutic potential. Recently, we discovered that exosome-enriched extracellular vesicles carry altered levels of both known and novel miRNAs in breast milk from lactating mothers with type 1 diabetes. In this study, we aimed to characterize exosomal miRNAs in the circulation of lactating mothers with and without type 1 diabetes, hypothesizing that differences in type 1 diabetes risk in offspring from these groups are reflected in the circulating miRNA profile. We performed small RNA sequencing on exosome-enriched extracellular vesicles extracted from plasma of 52 lactating mothers around 5 weeks postpartum (26 with type 1 diabetes and 26 age-matched controls), and found a total of 2,289 miRNAs in vesicles from type 1 diabetes and control libraries. Of these, 176 were differentially expressed in plasma from mothers with type 1 diabetes (167 upregulated; 9 downregulated, using a cut-off of abs(log2FC) >1 and FDR adjusted p-value <0.05). Extracellular vesicles were verified by nanoparticle tracking analysis, transmission electron microscopy and immunoblotting. Five candidate miRNAs were selected based on their involvement in diabetes and immune modulation/beta-cell functions: hsa-miR-127-3p, hsa-miR-146a-5p, hsa-miR-26a-5p, hsa-miR-24-3p and hsa-miR-30d-5p. Real-time qPCR validation confirmed that hsa-miR-146a-5p, hsa-miR-26a-5p, hsa-miR-24-3p, and hsa-miR-30d-5p were significantly upregulated in lactating mothers with type 1 diabetes as compared to lactating healthy mothers. To determine possible target genes and affected pathways of the 5 miRNA candidates, computational network-based analyses were carried out with TargetScan, mirTarBase, QIAGEN Ingenuity Pathway Analysis and PantherDB database. The candidates showed significant association with inflammatory response and cytokine and chemokine mediated signaling pathways. With this study, we detect aberrant levels of miRNAs within plasma extracellular vesicles from lactating mothers with type 1 diabetes during the postpartum period, including miRNAs with associations to disease pathogenesis and inflammatory responses.

Transcriptional regulation of N6-methyladenosine orchestrates sex-dimorphic metabolic traits.

Males and females exhibit striking differences in the prevalence of metabolic traits including hepatic steatosis, a key driver of cardiometabolic morbidity and mortality. RNA methylation is a widespread regulatory mechanism of transcript turnover. Here, we show that presence of the RNA modification N6-methyladenosine (m6A) triages lipogenic transcripts for degradation and guards against hepatic triglyceride accumulation. In male but not female mice, this protective checkpoint stalls under lipid-rich conditions. Loss of m6A control in male livers increases hepatic triglyceride stores, leading to a more 'feminized' hepatic lipid composition. Crucially, liver-specific deletion of the m6A complex protein Mettl14 from male and female mice significantly diminishes sex-specific differences in steatosis. We further surmise that the m6A installing machinery is subject to transcriptional control by the sex-responsive BCL6-STAT5 axis in response to dietary conditions. These data show that m6A is essential for precise and synchronized control of lipogenic enzyme activity and provide insights into the molecular basis for the existence of sex-specific differences in hepatic lipid traits.

A Dual Systems Genetics Approach Identifies Common Genes, Networks, and Pathways for Type 1 and 2 Diabetes in Human Islets.

Type 1 and 2 diabetes (T1/2D) are complex metabolic diseases caused by absolute or relative loss of functional ß-cell mass, respectively. Both diseases are influenced by multiple genetic loci that alter disease risk. For many of the disease-associated loci, the causal candidate genes remain to be identified. Remarkably, despite the partially shared phenotype of the two diabetes forms, the associated loci for T1D and T2D are almost completely separated. We hypothesized that some of the genes located in risk loci for T1D and T2D interact in common pancreatic islet networks to mutually regulate important islet functions which are disturbed by disease-associated variants leading to ß-cell dysfunction. To address this, we took a dual systems genetics approach. All genes located in 57 T1D and 243 T2D established genome-wide association studies (GWAS) loci were extracted and filtered for genes expressed in human islets using RNA sequencing data, and then integrated with; (1) human islet expression quantitative trait locus (eQTL) signals in linkage disequilibrium (LD) with T1D- and T2D-associated variants; or (2) with genes transcriptionally regulated in human islets by pro-inflammatory cytokines or palmitate as in vitro models of T1D and T2D, respectively. Our in silico systems genetics approaches created two interaction networks consisting of densely-connected T1D and T2D loci genes. The "T1D-T2D islet eQTL interaction network" identified 9 genes (GSDMB, CARD9, DNLZ, ERAP1, PPIP5K2, TMEM69, SDCCAG3, PLEKHA1, and HEMK1) in common T1D and T2D loci that harbor islet eQTLs in LD with disease-associated variants. The "cytokine and palmitate islet interaction network" identified 4 genes (ASCC2, HIBADH, RASGRP1, and SRGAP2) in common T1D and T2D loci whose expression is mutually regulated by cytokines and palmitate. Functional annotation analyses of the islet networks revealed a number of significantly enriched pathways and molecular functions including cell cycle regulation, inositol phosphate metabolism, lipid metabolism, and cell death and survival. In summary, our study has identified a number of new plausible common candidate genes and pathways for T1D and T2D.

Prediction of early recurrence of hepatocellular carcinoma after resection using digital pathology images assessed by machine learning.

Hepatocellular carcinoma (HCC) is a representative primary liver cancer caused by long-term and repetitive liver injury. Surgical resection is generally selected as the radical cure treatment. Because the early recurrence of HCC after resection is associated with low overall survival, the prediction of recurrence after resection is clinically important. However, the pathological characteristics of the early recurrence of HCC have not yet been elucidated. We attempted to predict the early recurrence of HCC after resection based on digital pathologic images of hematoxylin and eosin-stained specimens and machine learning applying a support vector machine (SVM). The 158 HCC patients meeting the Milan criteria who underwent surgical resection were included in this study. The patients were categorized into three groups: Group I, patients with HCC recurrence within 1 year after resection (16 for training and 23 for test); Group II, patients with HCC recurrence between 1 and 2 years after resection (22 and 28); and Group III, patients with no HCC recurrence within 4 years after resection (31 and 38). The SVM-based prediction method separated the three groups with 89.9% (80/89) accuracy. Prediction of Groups I was consistent for all cases, while Group II was predicted to be Group III in one case, and Group III was predicted to be Group II in 8 cases. The use of digital pathology and machine learning could be used for highly accurate prediction of HCC recurrence after surgical resection, especially that for early recurrence. Currently, in most cases after HCC resection, regular blood tests and diagnostic imaging are used for follow-up observation; however, the use of digital pathology coupled with machine learning offers potential as a method for objective postoprative follow-up observation.

Application of Multiplex Bisulfite PCR-Ligase Detection Reaction-Real-Time Quantitative PCR Assay in Interrogating Bioinformatically Identified, Blood-Based Methylation Markers for Colorectal Cancer.

The analysis of CpG methylation in circulating tumor DNA fragments has emerged as a promising approach for the noninvasive early detection of solid tumors, including colorectal cancer (CRC). The most commonly employed assay involves bisulfite conversion of circulating tumor DNA, followed by targeted PCR, then real-time quantitative PCR (alias methylation-specific PCR). This report demonstrates the ability of a multiplex bisulfite PCR-ligase detection reaction-real-time quantitative PCR assay to detect seven methylated CpG markers (CRC or colon specific), in both simulated (approximately 30 copies of fragmented CRC cell line DNA mixed with approximately 3000 copies of fragmented peripheral blood DNA) and CRC patient-derived cell-free DNAs. This scalable assay is designed for multiplexing and incorporates steps for improved sensitivity and specificity, including the enrichment of methylated CpG fragments, ligase detection reaction, the incorporation of ribose bases in primers, and use of uracil DNA glycosylase. Six of the seven CpG markers (located in promoter regions of PPP1R16B, KCNA3, CLIP4, GDF6, SEPT9, and GSG1L) were identified through integrated analyses of genome-wide methylation data sets for 31 different types of cancer. These markers were mapped to CpG sites at the promoter region of VIM; VIM and SEPT9 are established epigenetic markers of CRC. Additional bioinformatics analyses show that the methylation at these CpG sites negatively correlates with the transcription of their corresponding genes.

Prediction of blood-based biomarkers and subsequent design of bisulfite PCR-LDR-qPCR assay for breast cancer detection.

BACKGROUND: Interrogation of site-specific CpG methylation in circulating tumor DNAs (ctDNAs) has been employed in a number of studies for early detection of breast cancer (BrCa). In many of these studies, the markers were identified based on known biology of BrCa progression, and interrogated using methyl-specific PCR (MSP), a technique involving bisulfite conversion, PCR, and qPCR. METHODS: In this report, we are demonstrating the development of a novel assay (Multiplex Bisulfite PCR-LDR-qPCR) which can potentially offer improvements to MSP, by integrating additional steps such as ligase detection reaction (LDR), methylated CpG target enrichment, carryover protection (use of uracil DNA glycosylase), and minimization of primer-dimer formation (use of ribose primers and RNAseH2). The assay is designed to for breast cancer-specific CpG markers identified through integrated analyses of publicly available genome-wide methylation datasets for 31 types of primary tumors (including BrCa), as well as matching normal tissues, and peripheral blood. RESULTS: Our results indicate that the PCR-LDR-qPCR assay is capable of detecting ~ 30 methylated copies of each of 3 BrCa-specific CpG markers, when mixed with excess amount unmethylated CpG markers (~ 3000 copies each), which is a reasonable approximation of BrCa ctDNA overwhelmed with peripheral blood cell-free DNA (cfDNA) when isolated from patient plasma. The bioinformatically-identified CpG markers are located in promoter regions of NR5A2 and PRKCB, and a non-coding region of chromosome 1 (upstream of EFNA3). Additional bioinformatic analyses would reveal that these methylation markers are independent of patient race and age, and positively associated with signaling pathways associated with BrCa progression (such as those related to retinoid nuclear receptor, PTEN, p53, pRB, and p27). CONCLUSION: This report demonstrates the potential utilization of bisulfite PCR-LDR-qPCR assay, along with bioinformatically-driven biomarker discovery, in blood-based BrCa detection.

Single-molecule detection of cancer mutations using a novel PCR-LDR-qPCR assay.

Detection of low-abundance mutations in cell-free DNA is being used to identify early cancer and early cancer recurrence. Here, we report a new PCR-LDR-qPCR assay capable of detecting point mutations at a single-molecule resolution in the presence of an excess of wild-type DNA. Major features of the assay include selective amplification and detection of mutant DNA employing multiple nested primer-binding regions as well as wild-type sequence blocking oligonucleotides, prevention of carryover contamination, spatial sample dilution, and detection of multiple mutations in the same position. Our method was tested to interrogate the following common cancer somatic mutations: BRAF:c.1799T>A (p.Val600Glu), TP53:c.743G>A (p.Arg248Gln), KRAS:c.35G>C (p.Gly12Ala), KRAS:c.35G>T (p.Gly12Val), KRAS:c.35G>A (p.Gly12Asp), KRAS:c.34G>T (p.Gly12Cys), and KRAS:c.34G>A (p.Gly12Ser). The single-well version of the assay detected 2-5 copies of these mutations, when diluted with 10,000 genome equivalents (GE) of wild-type human genomic DNA (hgDNA) from buffy coat. A 12-well (pixel) version of the assay was capable of single-molecule detection of the aforementioned mutations at TP53, BRAF, and KRAS (specifically p.Gly12Val and p.Gly12Cys), mixed with 1,000-2,250 GE of wild-type hgDNA from plasma or buffy coat. The assay described herein is highly sensitive, specific, and robust, and potentially useful in liquid biopsies.

Breast Milk-Derived Extracellular Vesicles Enriched in Exosomes From Mothers With Type 1 Diabetes Contain Aberrant Levels of microRNAs.

The breast milk plays a crucial role in shaping the initial intestinal microbiota and mucosal immunity of the infant. Interestingly, breastfeeding has proven to be protective against the early onset of immune-mediated diseases including type 1 diabetes. Studies have shown that exosomes from human breast milk are enriched in immune-modulating miRNAs suggesting that exosomal miRNAs (exomiRs) transferred to the infant could play a critical role in the development of the infant's immune system. We extracted exomiRs from breast milk of 52 lactating mothers (26 mothers with type 1 diabetes and 26 healthy mothers), to identify any differences in the exomiR content between the two groups. Small RNA-sequencing was performed to identify known and novel miRNAs in both groups. A total of 631 exomiRs were detected by small RNA sequencing including immune-related miRNAs such as hsa-let-7c, hsa-miR-21, hsa-miR-34a, hsa-miR-146b, and hsa-miR-200b. In addition, ~200 novel miRNAs were identified in both type 1 diabetes and control samples. Among the known miRNAs, nine exomiR's were found differentially expressed in mothers with type 1 diabetes compared to healthy mothers. The highly up-regulated miRNAs, hsa-miR-4497, and hsa-miR-3178, increased lipopolysaccharide-induced expression and secretion of tumor necrosis factor α (TNFα) in human monocytes. The up-regulated miRNA target genes were significantly enriched for longevity-regulating pathways and FoxO signaling. Our findings suggest a role of breast milk-derived exomiRs in modulating the infant's immune system.