Obesity and type 2 diabetes (T2D) are linked both with host genetics and with environmental factors, including dysbioses of the gut microbiota. However, it is unclear whether these microbial changes precede disease onset. Twin cohorts present a unique genetically-controlled opportunity to study the relationships between lifestyle factors and the microbiome. In particular, we hypothesized that family-independent changes in microbial composition and metabolic function during the sub-clinical state of T2D could be either causal or early biomarkers of progression.

According to the hygiene hypothesis, the increasing incidence of autoimmune diseases in western countries may be explained by changes in early microbial exposure, leading to altered immune maturation. We followed gut microbiome development from birth until age three in 222 infants in Northern Europe, where early-onset autoimmune diseases are common in Finland and Estonia but are less prevalent in Russia. We found that Bacteroides species are lowly abundant in Russians but dominate in Finnish and Estonian infants. Therefore, their lipopolysaccharide (LPS) exposures arose primarily from Bacteroides rather than from Escherichia coli, which is a potent innate immune activator. We show that Bacteroides LPS is structurally distinct from E. coli LPS and inhibits innate immune signaling and endotoxin tolerance; furthermore, unlike LPS from E. coli, B. dorei LPS does not decrease incidence of autoimmune diabetes in non-obese diabetic mice. Early colonization by immunologically silencing microbiota may thus preclude aspects of immune education.

Single-cell assays have revealed the importance of heterogeneity in many biological systems. However, limited sensitivity is a major hurdle for uncovering cellular variation. To overcome it, we developed CloneSeq, combining clonal expansion inside 3D hydrogel spheres and droplet-based RNA sequencing (RNA-seq). We show that clonal cells maintain similar transcriptional profiles and cell states. CloneSeq of lung cancer cells revealed cancer-specific subpopulations, including cancer stem-like cells, that were not revealed by scRNA-seq. Clonal expansion within 3D soft microenvironments supported cellular stemness of embryonic stem cells (ESCs) even without pluripotent media, and it improved epigenetic reprogramming efficiency of mouse embryonic fibroblasts. CloneSeq of ESCs revealed that the differentiation decision is made early during Oct4 downregulation and is maintained during early clonal expansion. Together, we show CloneSeq can be adapted to different biological systems to discover rare subpopulations by leveraging the enhanced sensitivity within clones.

Massively parallel sequencing of cDNA has enabled deep and efficient probing of transcriptomes. Current approaches for transcript reconstruction from such data often rely on aligning reads to a reference genome, and are thus unsuitable for samples with a partial or missing reference genome. Here we present the Trinity method for de novo assembly of full-length transcripts and evaluate it on samples from fission yeast, mouse and whitefly, whose reference genome is not yet available. By efficiently constructing and analyzing sets of de Bruijn graphs, Trinity fully reconstructs a large fraction of transcripts, including alternatively spliced isoforms and transcripts from recently duplicated genes. Compared with other de novo transcriptome assemblers, Trinity recovers more full-length transcripts across a broad range of expression levels, with a sensitivity similar to methods that rely on genome alignments. Our approach provides a unified solution for transcriptome reconstruction in any sample, especially in the absence of a reference genome.

The use of genome-wide RNA abundance profiling by microarrays and deep sequencing has spurred a revolution in our understanding of transcriptional control. However, changes in mRNA abundance reflect the combined effect of changes in RNA production, processing, and degradation, and thus, mRNA levels provide an occluded view of transcriptional regulation.

Whether the human fetus and the prenatal intrauterine environment (amniotic fluid and placenta) are stably colonized by microbial communities in a healthy pregnancy remains a subject of debate. Here we evaluate recent studies that characterized microbial populations in human fetuses from the perspectives of reproductive biology, microbial ecology, bioinformatics, immunology, clinical microbiology and gnotobiology, and assess possible mechanisms by which the fetus might interact with microorganisms. Our analysis indicates that the detected microbial signals are likely the result of contamination during the clinical procedures to obtain fetal samples or during DNA extraction and DNA sequencing. Furthermore, the existence of live and replicating microbial populations in healthy fetal tissues is not compatible with fundamental concepts of immunology, clinical microbiology and the derivation of germ-free mammals. These conclusions are important to our understanding of human immune development and illustrate common pitfalls in the microbial analyses of many other low-biomass environments. The pursuit of a fetal microbiome serves as a cautionary example of the challenges of sequence-based microbiome studies when biomass is low or absent, and emphasizes the need for a trans-disciplinary approach that goes beyond contamination controls by also incorporating biological, ecological and mechanistic concepts.

The acquisition and development of the infant microbiome are key to establishing a healthy host-microbiome symbiosis. The maternal microbial reservoir is thought to play a crucial role in this process. However, the source and transmission routes of the infant pioneering microbes are poorly understood. To address this, we longitudinally sampled the microbiome of 25 mother-infant pairs across multiple body sites from birth up to 4 months postpartum. Strain-level metagenomic profiling showed a rapid influx of microbes at birth followed by strong selection during the first few days of life. Maternal skin and vaginal strains colonize only transiently, and the infant continues to acquire microbes from distinct maternal sources after birth. Maternal gut strains proved more persistent in the infant gut and ecologically better adapted than those acquired from other sources. Together, these data describe the mother-to-infant microbiome transmission routes that are integral in the development of the infant microbiome.

BACKGROUNDCytomegalovirus (CMV) is the most common intrauterine infection, leading to infant brain damage. Prognostic assessment of CMV-infected fetuses has remained an ongoing challenge in prenatal care, in the absence of established prenatal biomarkers of congenital CMV (cCMV) infection severity. We aimed to identify prognostic biomarkers of cCMV-related fetal brain injury.METHODSWe performed global proteome analysis of mid-gestation amniotic fluid samples, comparing amniotic fluid of fetuses with severe cCMV with that of asymptomatic CMV-infected fetuses. The levels of selected differentially excreted proteins were further determined by specific immunoassays.RESULTSUsing unbiased proteome analysis in a discovery cohort, we identified amniotic fluid proteins related to inflammation and neurological disease pathways, which demonstrated distinct abundance in fetuses with severe cCMV. Amniotic fluid levels of 2 of these proteins - the immunomodulatory proteins retinoic acid receptor responder 2 (chemerin) and galectin-3-binding protein (Gal-3BP) - were highly predictive of the severity of cCMV in an independent validation cohort, differentiating between fetuses with severe (n = 17) and asymptomatic (n = 26) cCMV, with 100%-93.8% positive predictive value, and 92.9%-92.6% negative predictive value (for chemerin and Gal-3BP, respectively). CONCLUSIONAnalysis of chemerin and Gal-3BP levels in mid-gestation amniotic fluids could be used in the clinical setting to profoundly improve the prognostic assessment of CMV-infected fetuses.FUNDINGIsrael Science Foundation (530/18 and IPMP 3432/19); Research Fund - Hadassah Medical Organization.

The infant gut microbiome is impacted by early-life feeding, as human milk oligosaccharides (HMOs) found in breastmilk cannot be digested by infants and serve as nutrients for their gut bacteria. While the vast majority of HMO-utilization research has focused on Bifidobacterium species, recent studies have suggested additional HMO-utilizers, mostly Bacteroides, yet their utilization mechanism is poorly characterized. Here, we investigate Bacteroides dorei isolates from breastfed-infants and identify that polysaccharide utilization locus (PUL) 33 enables B. dorei to utilize sialylated HMOs. We perform transcriptional profiling and identity upregulated genes when growing on sialylated HMOs. Using CRISPR-Cas12 to knock-out four PUL33 genes, combined with complementation assays, we identify GH33 as the critical gene in PUL33 for sialylated HMO-utilization. This demonstration of an HMO-utilization system by Bacteroides species isolated from infants opens the way to further characterization of additional such systems, to better understand HMO-utilization in the infant gut.

Breast milk contains human milk oligosaccharides (HMOs) that cannot be digested by infants, yet nourish their developing gut microbiome. While Bifidobacterium are the best-known utilizers of individual HMOs, a longitudinal study examining the evolving microbial community at high-resolution coupled with mothers' milk HMO composition is lacking. Here, we developed a high-throughput method to quantify Bifidobacterium longum subsp. infantis (BL. infantis), a proficient HMO-utilizer, and applied it to a longitudinal cohort consisting of 21 mother-infant dyads. We observed substantial changes in the infant gut microbiome over the course of several months, while the HMO composition in mothers' milk remained relatively stable. Although Bifidobacterium species significantly influenced sample variation, no specific HMOs correlated with Bifidobacterium species abundance. Surprisingly, we found that BL. infantis colonization began late in the breastfeeding period both in our cohort and in other geographic locations, highlighting the importance of focusing on BL. infantis dynamics in the infant gut.

Bacterial community acquisition in the infant gut impacts immune education and disease susceptibility. We compared bacterial strains across and within families in a prospective birth cohort of 44 infants and their mothers, sampled longitudinally in the first months of each child's life. We identified mother-to-child bacterial transmission events and describe the incidence of family-specific antibiotic resistance genes. We observed two inheritance patterns across multiple species, where often the mother's dominant strain is transmitted to the child, but occasionally her secondary strains colonize the infant gut. In families where the secondary strain of B. uniformis was inherited, a starch utilization gene cluster that was absent in the mother's dominant strain was identified in the child, suggesting the selective advantage of a mother's secondary strain in the infant gut. Our findings reveal mother-to-child bacterial transmission events at high resolution and give insights into early colonization of the infant gut.

The human gut microbiome matures towards the adult composition during the first years of life and is implicated in early immune development. Here, we investigate the effects of microbial genomic diversity on gut microbiome development using integrated early childhood data sets collected in the DIABIMMUNE study in Finland, Estonia and Russian Karelia. We show that gut microbial diversity is associated with household location and linear growth of children. Single nucleotide polymorphism- and metagenomic assembly-based strain tracking revealed large and highly dynamic microbial pangenomes, especially in the genus Bacteroides, in which we identified evidence of variability deriving from Bacteroides-targeting bacteriophages. Our analyses revealed functional consequences of strain diversity; only 10% of Finnish infants harboured Bifidobacterium longum subsp. infantis, a subspecies specialized in human milk metabolism, whereas Russian infants commonly maintained a probiotic Bifidobacterium bifidum strain in infancy. Groups of bacteria contributing to diverse, characterized metabolic pathways converged to highly subject-specific configurations over the first two years of life. This longitudinal study extends the current view of early gut microbial community assembly based on strain-level genomic variation.

Mode of delivery strongly influences the early infant gut microbiome. Children born by cesarean section (C-section) lack Bacteroides species until 6-18 months of age. One hypothesis is that these differences stem from lack of exposure to the maternal vaginal microbiome. Here, we re-evaluate this hypothesis by comparing the microbial profiles of 75 infants born vaginally or by planned versus emergent C-section. Multiple children born by C-section have a high abundance of Bacteroides in their first few days of life, but at 2 weeks, both C-section groups lack Bacteroides (primarily according to 16S sequencing), despite their difference in exposure to the birth canal. Finally, a comparison of microbial strain profiles between infants and maternal vaginal or rectal samples finds evidence for mother-to-child transmission of rectal rather than vaginal strains. These results suggest differences in colonization stability as an important factor in infant gut microbiome composition rather than birth canal exposure.

Human milk oligosaccharides (HMOs) are a family of glycans found in breastmilk with over 200 identified structures. Despite being t​​he third-largest solid component in breastmilk, HMOs are indigestible by infants, and they serve as food for the infant gut bacteria. Most research thus far has focused on Bifidobacterium species that harbor many glycoside hydrolases (GHs) tailored to break the carbon bonds in HMO molecules. However, there are additional microbes in the infant gut, such as Bacteroides species, with increasing evidence that they, too, are able to break-down HMOs. To study the unbiased impact of breastfeeding on the infant gut microbiome, we need to investigate the underlying mechanisms of HMO utilization by all members of the infant gut. Here, we developed an optimized system for isolating Bacteroides strains from infant stool samples. We then examined the HMO utilization capacity of multiple Bacteroides isolates by performing growth curves on six common HMOs (2'-FL, DFL, 3'-SL, 6'-SL, LNT, LNnT). Isolates often displayed similar growth characteristics on similarly-structured HMOs, like sialylated or fucosylated sugars. We identified variation in HMO utilization across multiple strains of the same species, and chose to focus here on a Bacteroides dorei isolate that was able to utilize the test HMOs. We performed RNA sequencing on B. dorei cultures, comparing the transcriptional profile in minimal media supplemented with glucose or HMOs. We showed that B. dorei employs an extensive metabolic response to HMOs. Surprisingly, there was no clear up-regulation for most GH families previously known to break-down HMOs, possibly because they were almost exclusively described in Bifidobacterium species. Instead, B. dorei exhibits a generalized response to HMOs, markedly up-regulating several shared GH families across all conditions. Within each GH family, B. dorei displays a consistent pattern of up-regulation of some genes with down-regulation of the others. This response pattern to HMOs has yet to be described in other commensals of the infant gut. Our work highlights the importance of expanding the HMO-microbiome studies beyond Bifidobacterium species, sheds light on the differences across Bacteroides strains in terms of HMO utilization, and paves the way to understanding the mechanisms enabling Bacteroides HMO utilization.

Recent studies in budding yeast have shown that antisense transcription occurs at many loci. However, the functional role of antisense transcripts has been demonstrated only in a few cases and it has been suggested that most antisense transcripts may result from promiscuous bi-directional transcription in a dense genome.

Aim: Current microbiome profiling of type 1 diabetes mellitus (T1D) patients is mostly limited to gut microbiome. We characterized the oral microbiome associated with T1D in children after the onset of the disease and explored its relationship with oral physiological factors and dental status. Methods: This cohort study comprised 37 children aged 5-15 years with T1D and 29 healthy children matched in age and gender. Unstimulated whole saliva was collected from diabetic and non-diabetic children, in the morning after brushing their teeth and a fasting period of at least 1 h before sampling. 16S rRNA gene-based analysis was performed by Powersoil Pro kit by Qiagen and Phusion High-Fidelity PCR Master Mix. Oral physiological and dental parameters studied included decayed, missing, and filled teeth index, salivary flow rate, and salivary pH, glucose, calcium, phosphate, and urea levels. Results: Of the identified 105 different genera and 211 different species, the most abundant genera were Streptococcus, Prevotella, Veillonella, Haemophilus, and Neisseria. Streptococcus was more abundant in T1D children. The diabetes group had 22 taxa at the genus level and 33 taxa at the species level that were not present in the control group and the control group exhibited 6 taxa at the genus level and 9 taxa at the species level that did not exist in the diabetes group. In addition, Catonella, Fusobacterium, and Mogibacterium differed between healthy and T1D subjects. Eight species and eight subspecies were significantly more abundant among healthy children than in T1D children. Porphyromonas and Mogibacterium genera were significantly correlated with salivary parameters. We found similarities between taxa revealed in the present study and those found in gut microbiome in type 1 diabetes mellitus according to gutMDisorder database. Conclusions: Salivary microbiome analysis revealed unique microbial taxa that differed between T1D children and healthy subjects. Several genera found in the saliva of T1D children were associated with gut microbiome in T1D individuals.

Longitudinal, prospective studies often rely on multi-omics approaches, wherein various specimens are analyzed for genomic, metabolomic, and/or transcriptomic profiles. In practice, longitudinal studies in humans and other animals routinely suffer from subject dropout, irregular sampling, and biological variation that may not be normally distributed. As a result, testing hypotheses about observations over time can be statistically challenging without performing transformations and dramatic simplifications to the dataset, causing a loss of longitudinal power in the process. Here, we introduce splinectomeR, an R package that uses smoothing splines to summarize data for straightforward hypothesis testing in longitudinal studies. The package is open-source, and can be used interactively within R or run from the command line as a standalone tool. We present a novel in-depth analysis of a published large-scale microbiome study as an example of its utility in straightforward testing of key hypotheses. We expect that splinectomeR will be a useful tool for hypothesis testing in longitudinal microbiome studies.

The gut microbiota in patients with inflammatory bowel disease are perturbed in both composition and function. The vaginal microbiome and its role in the reproductive health of women with inflammatory bowel disease is less well described.