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Very preterm infants (VPIs) are born with an immature gut and predisposed to gut microbiota dysbiosis-related diseases, for example, necrotizing enterocolitis. Although fortification of human milk is required for these infants, the optimal fortifier remains uncertain. Bovine colostrum (BC), rich in protein and bioactive components, could serve as an alternative to conventional fortifiers (CF). The gut microbiota (GM) of 225 VPIs fed human milk fortified with either BC or CF (FortiColos study, NCT03537365) was profiled by 16S rRNA gene amplicon sequencing of fecal samples collected before, and after 1 and 2 weeks of fortification. Birth mode exhibited transient effects on the microbial community structure shortly after birth, with cesarean section-born VPIs dominated by Firmicutes, whereas vaginally born VPIs were dominated by Proteobacteria. This birth mode-derived difference diminished with age and disappeared around 1 month after birth. Fortifier type affected the microbial community structure to a modest extent, but no specific taxa significantly differed between the BC and CF groups. Fecal pH, increased by BC, was positively correlated with Staphylococcus and Corynebacterium and negatively with Bifidobacterium abundance. Change in the relative abundance of Staphylococcus was negatively correlated with body weight gain. Collectively, fortification of human milk with BC or CF does influence the GM of VPIs but only to a modest extent during early life. Birth mode appears to have a significant, but temporary influence on the GM during this period.IMPORTANCEEarly life is a key period for gut microbiota (GM) establishment, where enteral feeding plays a significant role. This is also the case for infants born preterm, who, due to their immature gut, are at a high risk of developing GM dysbiosis-related diseases. Human milk is the optimal feed for preterm infants, but it requires fortification to reach adequate levels of especially protein. Only a few studies have investigated the impact of fortifiers on GM development in preterm infants. Here, we demonstrate that two different bovine milk-based fortifiers, bovine colostrum and a conventional fortifier based on mature bovine milk, exhibit limited effects on the microbial community structure of very preterm infants. These findings suggest that although great care in terms of optimally maturing the preterm infant GM should be taken, the choice of fortifier only has limited impact. In clinical practice, the choice of fortifier can thus be fully focussed on optimizing preterm infant nutrition.CLINICAL TRIALSThis study is registered with ClinicalTrials.gov as NCT03537365.

k-mer frequency information in biological sequences is used for a wide range of applications, including taxonomy classification, sequence similarity estimation, and supervised learning. However, in spite of its widespread utility, k-mer counting has been largely neglected for diversity estimation. This work examines the application of k-mer counting for alpha and beta diversity as well as supervised classification from microbiome marker-gene sequencing data sets (16S rRNA gene and full-length fungal internal transcribed spacer [ITS] sequences). Results demonstrate a close correspondence with phylogenetically aware diversity metrics, and advantages for using k-mer-based metrics for measuring microbial biodiversity in microbiome sequencing surveys. k-mer counting appears to be a suitable and efficient strategy for feature processing prior to diversity estimation as well as supervised learning in microbiome surveys. This allows the incorporation of subsequence-level information into diversity estimation without the computational cost of pairwise sequence alignment. k-mer counting is proposed as a complementary approach for feature processing prior to diversity estimation and supervised learning analyses, enabling large-scale reference-free profiling of microbiomes in biogeography, ecology, and biomedical data. A method for k-mer counting from marker-gene sequence data is implemented in the QIIME 2 plugin q2-kmerizer (https://github.com/bokulich-lab/q2-kmerizer).

Importance: k-mers are all of the subsequences of length k that comprise a sequence. Comparing the frequency of k-mers in DNA sequences yields valuable information about the composition of these sequences and their similarity. This work demonstrates that k-mer frequencies from marker-gene sequence surveys can be used to inform diversity estimates and machine learning predictions that incorporate sequence composition information. Alpha and beta diversity estimates based on k-mer frequencies closely correspond to phylogenetically aware diversity metrics, suggesting that k-mer-based diversity estimates are useful proxy measurements especially when reliable phylogenies are not available, as is often the case for some DNA sequence targets such as for internal transcribed spacer sequences.

Mass mortality of Diadematidae urchins, caused by the Diadema antillarum scuticociliatosis Philaster clade (DScPc), affected the Caribbean in spring 2022 and subsequently spread to the eastern Mediterranean, Red Sea, and western Indian Ocean. A key question around Diadematidae scuticociliatosis (DSc), the disease caused by the scuticociliate, is whether the urchin microbiome varies between scuticociliatosis-affected and grossly normal urchins. Tissue samples from both grossly normal and abnormal Diadema antillarum were collected in the field during the initial assessment of the DSc causative agent and from an experimental challenge of DScPc culture on aquacultured D. antillarum. Specimens were analyzed using 16S rRNA gene amplicon sequencing. Additional abnormal urchin samples were collected from the most recent outbreak site in the western Indian Ocean (Réunion Island). At reference (i.e., unaffected by DSc) sites, Kistimonas spp., Propionigenium spp., and Endozoicomonas spp. were highly represented in amplicon libraries. DSc-affected urchin amplicon libraries had lower taxonomic richness and a greater representation of taxa related to Fangia hongkongensis and Psychrobium spp. Amplicon libraries of urchins experimentally challenged with the DSc pathogen had some shifts in microbial composition, but F. hongkongensis was not a part of the core bacteria in DSc-challenged specimens. DSc-affected Echinothrix diadema from Réunion Island showed a similar high representation of F. hongkongensis as that seen on Caribbean D. antillarum. Our results suggest that DSc alters Diadematidae microbiomes and that F. hongkongensis may be a candidate bacterial biomarker for DSc in environmental samples. The mechanism driving microbiome variation in host-pathogen interactions remains to be explored.IMPORTANCEThe mass mortality of Diadematidae urchins due to Diadema antillarum scuticociliatosis (DSc) has had significant ecological impacts, spreading from the Caribbean to the eastern Mediterranean, Red Sea, and western Indian Ocean. This study investigates whether the microbiome of urchins varies between those affected by DSc and those that are not. Using 16S rRNA gene amplicon sequencing, researchers found that DSc-affected urchins had lower taxonomic richness and a greater representation of Fangia hongkongensis and Psychrobium spp. The findings indicate that F. hongkongensis could serve as a bacterial biomarker for DSc in environmental samples, providing a potential tool for early detection and management of the disease. Understanding these microbiome changes is crucial for developing strategies to mitigate the spread and impact of DSc on marine ecosystems.

Respiratory disease (RD) is a worldwide leading threat to the pig industry, but there is still limited understanding of the pathogens associated with swine RD. In this study, we conducted a nationwide genomic surveillance on identifying viruses, bacteria, and antimicrobial resistance genes (ARGs) from the lungs of pigs with RD in China. By performing metatranscriptomic sequencing combined with metagenomic sequencing, we identified 21 viral species belonging to 12 viral families. Among them, porcine reproductive and respiratory syndrome virus, influenza A virus, herpes virus, adenovirus, and parvovirus were commonly identified. However, emerging viruses, such as Getah virus and porcine respiratory coronaviruses, were also characterized. Apart from viruses, a total of 164 bacterial species were identified, with Streptococcus suis, Mycoplasma hyorhinis, Mycoplasma hyopneumoniae, Glaesserella parasuis, and Pasteurella multocida being frequently detected in high abundances. Notably, Escherichia coli, Enterococcus faecalis, Staphylococcus aureus, and Klebsiella pneumoniae were also highly detected. Our further analysis revealed a complex interaction between the identified pathogens in swine RD. We also conducted retrospectively analyses to demonstrate the prevalent viral genotypes or bacterial serotypes associated with swine RD in China. Finally, we identified 48 ARGs, which conferred resistance to 13 predicted antimicrobial classes, and many of these ARGs were significantly associated with a substantial number of mobile genetic elements, including transposons (e.g., tnpAIS1, tnpA1353, int3, and ISCau1) and plasmids (e.g., Col(BS512), Col(YC)]. These findings will contribute to further understanding the etiology, epidemiology, and microbial interactions in swine RD, and may also shed a light on the development of effective vaccines.IMPORTANCEIn this study, we identified viruses and bacteria from the lungs of pigs with RD in China at a nationwide farm scale by performing metatranscriptomic sequencing combined with metagenomic sequencing. We also demonstrated the complex interactions between different viral and/or bacterial species in swine RD. Our work provides a comprehensive knowledge about the etiology, epidemiology, and microbial interactions in swine RD and data reference for the research and development of effective vaccines against the disease.

Periodontitis is closely related to renal health, but the specific influence of Porphyromonas gingivalis (P. gingivalis), a key pathogen in periodontitis, on the development of acute kidney injury (AKI) in mice has not been fully elucidated. In our study, AKI was induced in mice through ischemia-reperfusion injury while administering oral infection with P. gingivalis. Comprehensive analyses were conducted, including 16S rRNA sequencing, liquid chromatography-mass spectrometry (LC-MS) metabolomics, and transcriptome sequencing. In vitro, the identified metabolite was used to stimulate mouse neutrophils. Subsequently, these modified neutrophils were co-cultured with mouse renal tubular epithelial cells. The results showed that oral infection with P. gingivalis significantly exacerbated AKI in mice. 16S rRNA sequencing revealed notable shifts in gut microbiota composition. LC-MS metabolomics analysis identified significant metabolic alterations, particularly the upregulation of 3-indoleacrylic acid in the serum. Transcriptome sequencing showed an increased expression of neutrophilic granule protein (Ngp), which was closely associated with 3-indoleacrylic acid, and the presence of Porphyromonas. Cellular experiments demonstrated that 3-indoleacrylic acid could activate neutrophils, leading to an elevation in NGP protein levels, a response that was associated with renal epithelial cell injury. Oral infection with P. gingivalis exacerbated AKI through the gut-kidney axis, involving gut microbiota dysbiosis, metabolic disturbances, and increased renal expression of Ngp.

Importance: This study provides novel insights into the relationship between periodontal health and renal function. Porphyromonas gingivalis oral infection disrupted the balance of gut microbiota and was an important modifier determining the severity of acute kidney injury. Under the "gut-kidney axis," P. gingivalis might cause an increase in the level of the gut microbial metabolite 3-indoleacrylic acid, interfering with kidney immunity and disrupting the maintenance of kidney epithelium.