Human Microbes Research Articles

Association between sulfur microbial diet and the risk of esophageal cancer: a prospective cohort study in 101,752 American adults

BackgroundSulfur microbial diet (SMD) is a dietary pattern closely related to the intestinal load of sulfur-metabolizing microbes in humans. Diet and microbes may play an important role in the carcinogenesis of esophagus. However, epidemiological studies on SMD and esophageal cancer (EC) risk are scarce. Here, we evaluated this association based on a large American cohort.MethodsIn the cohort of the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial, a SMD score was calculated to evaluate participants’ compliance of SMD pattern, with higher scores presenting greater adherence. Cox hazards regression model was used to explore the association between the SMD score and the incidence of EC, esophageal squamous cell carcinoma (ESCC), and esophageal adenocarcinoma (EA). Subgroup analyses were conducted to figure out potential modifiers interacting with SMD on EC. Sensitivity analyses were used to testify the robustness of our main result.ResultsAmong 101,752 participants, 154 EC cases, consisted of 41 ESCC cases and 97 EA cases, were identified with mean follow-up of 8.9 years. In the fully adjusted model, the highest versus the lowest quartiles of the SMD score were found to be associated with an increased risk of EC and ESCC (EC: HRQ4 vs. Q1: 1.64; 95% CI: 1.05, 2.56; P = 0.016 for trend; ESCC: HRQ4 vs. Q1: 2.37; 95% CI: 1.02, 5.47; P = 0.031 for trend), while not significantly associated with increases risk of EA (HRQ4 vs. Q1: 1.41; P = 0.144 for trend). The main result remained through a series of sensitivity analyses. Subgroup analyses showed a stronger association between SMD and EC in participants with no regular consumption of aspirin (HRQ4 vs. Q1: 1.90; 95% CI: 1.04, 3.47) than in those using aspirin regularly (HRQ4 vs. Q1: 1.37; 95% CI: 0.71, 2.66) (P = 0.008 for interaction).ConclusionAdherence to the SMD pattern may be associated with increased risks of EC and ESCC, particularly for EC in individuals who do not regularly consume aspirin.

Gut heavy metal and antibiotic resistome of humans living in the high Arctic

Contaminants, such as heavy metals (HMs), accumulate in the Arctic environment and the food web. The diet of the Indigenous Peoples of North Greenland includes locally sourced foods that are central to their nutritional, cultural, and societal health but these foods also contain high concentrations of heavy metals. While bacteria play an essential role in the metabolism of xenobiotics, there are limited studies on the impact of heavy metals on the human gut microbiome, and it is so far unknown if and how Arctic environmental contaminants impact the gut microbes of humans living in and off the Arctic environment. Using a multiomics approach including amplicon, metagenome, and metatranscriptome sequencing, we identified and assembled a near-complete (NC) genome of a mercury-resistant bacterial strain from the human gut microbiome, which expressed genes known to reduce mercury toxicity. At the overall ecological level studied through α- and β-diversity, there was no significant effect of heavy metals on the gut microbiota. Through the assembly of a high number of NC metagenome-assembled genomes (MAGs) of human gut microbes, we observed an almost complete overlap between heavy metal-resistant strains and antibiotic-resistant strains in which resistance genes were all located on the same genetic elements.

Biosynthetic enzyme analysis identifies a protective role for TLR4-acting gut microbial sulfonolipids in inflammatory bowel disease

The trillions of microorganisms inhabiting the human gut are intricately linked to human health. While specific microbes have been associated with diseases, microbial abundance alone cannot reveal the molecular mechanisms involved. One such important mechanism is the biosynthesis of functional metabolites. Here, we develop a biosynthetic enzyme-guided disease correlation approach to uncover microbial functional metabolites linked to disease. Applying this approach, we negatively correlate the expression of gut microbial sulfonolipid (SoL) biosynthetic enzymes to inflammatory bowel disease (IBD). Targeted chemoinformatics and metabolomics then confirm that SoL abundance is significantly decreased in IBD patient data and samples. In a mouse model of IBD, we further validate that SoL abundance is decreased while inflammation is increased in diseased mice. We show that SoLs consistently contribute to the immunoregulatory activity of different SoL-producing human microbes. We further reveal that sulfobacins A and B, representative SoLs, act on Toll-like receptor 4 (TLR4) and block lipopolysaccharide (LPS) binding, suppressing both LPS-induced inflammation and macrophage M1 polarization. Together, these results suggest that SoLs mediate a protective effect against IBD through TLR4 signaling and showcase a widely applicable biosynthetic enzyme-guided disease correlation approach to directly link the biosynthesis of gut microbial functional metabolites to human health.

Clove (Syzygium aromaticum) Extract has Antibacterial and Antifungal Effects against Human Scalp Microbes

Clove (Syzygium aromaticum) Extract has Antibacterial and Antifungal Effects against Human Scalp Microbes

Verification of utilization ability of Bifidobacterium and Lactobacillus to difructose anhydride III in vitro by its hydrolases and their application in Jerusalem artichoke tuber to improve nutrition

The functional Difructose anhydride III (DFA-III) lacks reported utilization by special probiotics of Bifidobacterium and Lactobacillus. DFA-III hydrolase (DFA-IIIase), converting DFA-III to inulobiose, is a critical enzyme for the metabolism of DFA-III, which stands for the utilization ability of DFA-III by microorganisms. Hence, the research identified six potential DFA-IIIases from Bifidobacterium and Lactobacillus species, suggesting that DFA-III has the potential to proliferate these bacteria. Notably, the DFA-IIIase from Bifidobacterium adolescentis belonging to the human intestinal microbe exhibits a hydrolysis rate of up to 67 % for DFA-III, which is the highest among the reported DFA-IIIases to date. When DFA-IIIases were applied to Jerusalem artichokes, DFA-III, inulobiose, and fructo-oligosaccharides were significantly produced. The in vitro work indicates that Bifidobacterium and Lactobacillus have the potential ability to utilize DFA-III by DFA-IIIases. Moreover, the first application of DFA-IIIase in Jerusalem artichokes provides valuable insights into comprehensive strategies for utilizing high-inulin agricultural products.

Essential genes for Haemophilus parainfluenzae survival and biofilm growth.

Haemophilus parainfluenzae (Hp) is a Gram-negative, highly prevalent, and abundant commensal in the human oral cavity, and an infrequent extraoral opportunistic pathogen. Hp occupies multiple niches in the oral cavity, including the supragingival plaque biofilm. Little is known about how Hp interacts with its neighbors in healthy biofilms nor its mechanisms of pathogenesis as an opportunistic pathogen. To address this, we identified the essential genome and conditionally essential genes in in vitro biofilms aerobically and anaerobically. Using transposon insertion sequencing (TnSeq) with a highly saturated mariner transposon library in two strains, the ATCC33392 type-strain (Hp 392) and oral isolate EL1 (Hp EL1), we show that the essential genomes of Hp 392 and Hp EL1 are composed of 395 (20%) and 384 (19%) genes, respectively. The core essential genome, consisting of 341 (17%) essential genes conserved between both strains, was composed of genes associated with genetic information processing, carbohydrate, protein, and energy metabolism. We also identified conditionally essential genes for aerobic and anaerobic biofilm growth, which were associated with carbohydrate and energy metabolism in both strains. RNAseq analysis determined that most genes upregulated during anaerobic growth are not essential for Hp 392 anaerobic survival. The completion of this library and analysis under these conditions gives us a foundational insight into the basic biology of H. parainfluenzae in differing oxygen conditions, similar to its in vivo habitat. This library presents a valuable tool for investigation into conditionally essential genes for an organism that lives in close contact with many microbial species in the human oral habitat.IMPORTANCEHaemophilus parainfluenzae is a highly abundant human commensal microbe, present in most healthy individuals where it colonizes the mouth. H. parainfluenzae correlates with good oral health and may play a role in preservation of healthy host status. Also, H. parainfluenzae can cause opportunistic infections outside of the oral cavity. To date, little is known about how H. parainfluenzae colonizes the human host, despite being such a frequent and abundant part of our human microbiome. Here, we demonstrate the creation and use of a powerful tool, a TnSeq library, used to identify genes necessary for both the outright growth of this organism and also genes conditionally essential for growth in varying oxygen status which it can encounter in the human host. This tool and these data serve as a foundation for further study of this relatively unknown organism that may play a role in preserving human health.

Limosilactobacillus reuteri promotes the expression and secretion of enteroendocrine- and enterocyte-derived hormones.

Observations that intestinal microbes can beneficially impact host physiology have prompted investigations into the therapeutic usage of such microbes in a range of diseases. For example, the human intestinal microbe Limosilactobacillus reuteri strains ATCC PTA 6475 and DSM 17938 are being considered for use for intestinal ailments including colic, infection, and inflammation as well as non-intestinal ailments including osteoporosis, wound healing, and autism spectrum disorder. While many of their beneficial properties are attributed to suppressing inflammatory responses in the gut, we postulated that L. reuteri may also regulate hormones of the gastrointestinal tract to affect physiology within and outside of the gut. To determine if L. reuteri secreted factors impact the secretion of enteric hormones, we treated an engineered jejunal organoid line, NGN3-HIO, which can be induced to be enriched in enteroendocrine cells, with L. reuteri 6475 or 17938 conditioned medium and performed transcriptomics. Our data suggest that these L. reuteri strains affect the transcription of many gut hormones, including vasopressin and luteinizing hormone subunit beta, which have not been previously recognized as being produced in the gut epithelium. Moreover, we find that these hormones appear to be produced in enterocytes, in contrast to canonical gut hormones which are produced in enteroendocrine cells. Finally, we show that L. reuteri conditioned media promotes the secretion of several enteric hormones including serotonin, GIP, PYY, vasopressin, and luteinizing hormone subunit beta. These results support L. reuteri affecting host physiology through intestinal hormone secretion, thereby expanding our understanding of the mechanistic actions of this microbe.

Revealing microbial community characteristics in healthy human, cat and canine salivas and looking for species-specific microbes.

As two kinds of increasingly popular pets, the saliva of cat or canine is most likely to be left at the crime scene compared with the common types of body fluids in forensics. Accurately identifying the species of saliva samples found at the crime scene involving pets will help the investigators find available testing materials, reduce the consumption of reagents and save the investigative time of the case. Therefore, it is necessary to explore the characteristics and differences of saliva microbiomes of cat, canine and human. In this study, 16S rRNA gene amplicon sequencing technology was used to reveal microbial communities of saliva samples of healthy human, cat, and canine. Alpha diversity analyses indicated that canine saliva demonstrated the highest microbial diversity, followed by cat saliva, whereas human saliva microbial diversity was the lowest. The saliva samples of the three species all had their own unique microbial community compositions, and the dominant phyla of canine and cat salivas were Proteobacteria and Bacteroidete, while the dominant phyla of human saliva were Firmicutes and Proteobacteria. There was no significant statistical difference in the salivary microbiota obtained by the two collection methods (cotton swab and liquid saliva). The gender of cats and canines might have no effect on the salivary microbiota, but the different breeds had an impact on their saliva microbiomes. Principal coordinates analysis, non-metric multidimensional scaling analysis and random forest analysis all indicated significant differences in microbial community structures among the three species, allowing inference on the species sources of saliva samples by microbiome method. Differential microbial biomarkers for the salivas of three species were screened out using a variety of bioinformatics analyses, and the results demonstrated that Prevotella melaninogenica, Veillonella parvula, and Haemophilus parainfluenzae could be used as species-specific microbial biomarkers of human saliva. The detections of human species-specific microbes provide a potential method for determining human saliva.

Quantitative and dynamic profiling of human gut core microbiota by real-time PCR

The human gut microbiota refers to a diverse community of microorganisms that symbiotically exist in the human intestinal system. Altered microbial communities have been linked to many human pathologies. However, there is a lack of rapid and efficient methods to assess gut microbiota signatures in practice. To address this, we established an appraisal system containing 45 quantitative real-time polymerase chain reaction (qPCR) assays targeting gut core microbes with high prevalence and/or abundance in the population. Through comparative genomic analysis, we selected novel species-specific genetic markers and primers for 31 of the 45 core microbes with no previously reported specific primers or whose primers needed improvement in specificity. We comprehensively evaluated the performance of the qPCR assays and demonstrated that they showed good sensitivity, selectivity, and quantitative linearity for each target. The limit of detection ranged from 0.1 to 1.0 pg/µL for the genomic DNA of these targets. We also demonstrated the high consistency (Pearson’s r = 0.8688, P < 0.0001) between the qPCR method and metagenomics next-generation sequencing (mNGS) method in analyzing the abundance of selected bacteria in 22 human fecal samples. Moreover, we quantified the dynamic changes (over 8 weeks) of these core microbes in 14 individuals using qPCR, and considerable stability was demonstrated in most participants, albeit with significant individual differences. Overall, this study enables the simple and rapid quantification of 45 core microbes in the human gut, providing a promising tool to understand the role of gut core microbiota in human health and disease.Key points• A panel of original qPCR assays was developed to quantify human gut core microbes.• The qPCR assays were evaluated and compared with mNGS using real fecal samples.• This method was used to dynamically profile the gut core microbiota in individuals.

An atlas of human vector-borne microbe interactions reveals pathogenicity mechanisms

Vector-borne diseases are a leading cause of death worldwide and pose a substantial unmet medical need. Pathogens binding to host extracellular proteins (the "exoproteome") represents a crucial interface in the etiology of vector-borne disease. Here, we used bacterial selection to elucidate host-microbe interactions in high throughput (BASEHIT)-a technique enabling interrogation of microbial interactions with 3,324 human exoproteins-to profile the interactomes of 82 human-pathogen samples, including 30 strains of arthropod-borne pathogens and 8 strains of related non-vector-borne pathogens. The resulting atlas revealed 1,303 putative interactions, including hundreds of pairings with potential roles in pathogenesis, including cell invasion, tissue colonization, immune evasion, and host sensing. Subsequent functional investigations uncovered that Lyme disease spirochetes recognize epidermal growth factor as an environmental cue of transcriptional regulation and that conserved interactions between intracellular pathogens and thioredoxins facilitate cell invasion. In summary, this interactome atlas provides molecular-level insights into microbial pathogenesis and reveals potential host-directed targets for next-generation therapeutics.

A catalog of ethanol-producing microbes in humans.

Aim: Endogenous ethanol production emerges as a mechanism of nonalcoholic steatohepatitis, obesity, diabetes and auto-brewery syndrome. Methods: To identify ethanol-producing microbes in humans, we used the NCBI taxonomy browser and the PubMed database with an automatic query and manual verification. Results: 85 ethanol-producing microbes in human were identified. Saccharomyces cerevisiae, Candida and Pichia were the most represented fungi. Enterobacteriaceae was the most represented bacterial family with mainly Escherichia coli and Klebsiellapneumoniae. Species of the Lachnospiraceae and Clostridiaceae family, of the Lactobacillales order and of the Bifidobacterium genus were also identified. Conclusion: This catalog will help the study of ethanol-producing microbes in human in the pathophysiology, diagnosis, prevention and management of human diseases associated with endogenous ethanol production.

Scenario-based assessment of fecal pathogen sources affecting bathing water quality: novel treatment options to reduce norovirus and Campylobacter infection risks.

Wastewater discharge and runoff waters are significant sources of human and animal fecal microbes in surface waters. Human-derived fecal contamination of water is generally estimated to pose a greater risk to human health than animal fecal contamination, but animals may serve as reservoirs of zoonotic pathogens. In this study, quantitative microbial risk assessment (QMRA) tools were used to evaluate the hygienic impact of sewage effluents and runoff water from municipalities and animal farms on surface and bathing waters. The human-specific microbial source tracking (MST) marker HF183 was used to evaluate the dilution of fecal pathogens originating from the sewage effluent discharge to the downstream watershed. As novel risk management options, the efficiency of UV-LED disinfection and wetland treatment as well as biochar filtration was tested on-site for the contamination sources. According to the dilution pattern of the MST marker HF183, microbes from wastewater were diluted (2.3-3.7 log10) in the receiving waters. The scenario-based QMRA revealed, that the health risks posed by exposure to human-specific norovirus GII and zoonotic Campylobacter jejuni during the bathing events were evaluated. The risk for gastroenteritis was found to be elevated during wastewater contamination events, where especially norovirus GII infection risk increased (1-15 cases per day among 50 bathers) compared with the business as usual (BAU) situation (1 case per day). The noted C. jejuni infection risk was associated with animal farm contamination (1 case per day, versus 0.2-0.6 cases during BAU). Tertiary treatment of wastewater with wetland treatment and UV-LED disinfection effectively reduced the waterborne gastroenteritis risks associated with bathing. Based on the experiences from this study, a QMRA-based approach for health risk evaluations at bathing sites can be useful and is recommended for bathing site risk assessments in the future. In case of low pathogen numbers at the exposure sites, the MST marker HF183 could be used as a pathogen dilution coefficient for the watershed under evaluation. The full-scale implementation of novel tertiary treatment options at wastewater treatment plants (WWTPs) as well as on-site runoff water treatment options should be considered for infection risk management at locations where scenario-based QMRA implies elevated infection risks.

The Interaction between Human Microbes and Advanced Glycation End Products: The Role of Klebsiella X15 on Advanced Glycation End Products' Degradation.

Previous studies have shown that advanced glycation end products (AGEs) are implicated in the occurrence and progression of numerous diseases, with dietary AGEs being particularly associated with intestinal disorders. In this study, methylglyoxal-beta-lactoglobulin AGEs (MGO-β-LG AGEs) were utilized as the exclusive nitrogen source to investigate the interaction between protein-bound AGEs and human gut microbiota. The high-resolution mass spectrometry analysis of alterations in peptides containing AGEs within metabolites before and after fermentation elucidated the capacity of intestinal microorganisms to enzymatically hydrolyze long-chain AGEs into short-chain counterparts. The 16S rRNA sequencing revealed Klebsiella, Lactobacillus, Escherichia-Shigella, and other genera as dominant microbiota at different fermentation times. A total of 187 potential strains of AGE-metabolizing bacteria were isolated from the fermentation broth at various time points. Notably, one strain of Klebsiella exhibited the most robust growth capacity when AGEs served as the sole nitrogen source. Subsequently, proteomics was employed to compare the changes in protein levels of Klebsiella X15 following cultivation in unmodified proteins and proteins modified with AGEs. This analysis unveiled a remodeled amino acid and energy metabolism pathway in Klebsiella in response to AGEs, indicating that Klebsiella may possess a metabolic pathway specifically tailored to AGEs. This study found that fermenting AGEs in healthy human intestinal microbiota altered the bacterial microbiota structure, especially by increasing Klebsiella proliferation, which could be a key factor in AGEs' role in causing diseases, particularly intestinal inflammation.

MCHAN: Prediction of Human Microbe-drug Associations Based on Multiview Contrastive Hypergraph Attention Network

Background: Complex and diverse microbial communities play a pivotal role in human health and have become a new drug target. Exploring the connections between drugs and microbes not only provides profound insights into their mechanisms but also drives progress in drug discovery and repurposing. The use of wet lab experiments to identify associations is time-consuming and laborious. Hence, the advancement of precise and efficient computational methods can effectively improve the efficiency of association identification between microorganisms and drugs. Objective: In this experiment, we propose a new deep learning model, a new multiview comparative hypergraph attention network (MCHAN) method for human microbe–drug association prediction. Methods: First, we fuse multiple similarity matrices to obtain a fused microbial and drug similarity network. By combining graph convolutional networks with attention mechanisms, we extract key information from multiple perspectives. Then, we construct two network topologies based on the above fused data. One topology incorporates the concept of hypernodes to capture implicit relationships between microbes and drugs using virtual nodes to construct a hyperheterogeneous graph. Next, we propose a cross-contrastive learning task that facilitates the simultaneous guidance of graph embeddings from both perspectives, without the need for any labels. This approach allows us to bring nodes with similar features and network topologies closer while pushing away other nodes. Finally, we employ attention mechanisms to merge the outputs of the GCN and predict the associations between drugs and microbes. Results: To confirm the effectiveness of this method, we conduct experiments on three distinct datasets. The results demonstrate that the MCHAN model surpasses other methods in terms of performance. Furthermore, case studies provide additional evidence confirming the consistent predictive accuracy of the MCHAN model. Conclusion: MCHAN is expected to become a valuable tool for predicting potential associations between microbiota and drugs in the future.

Genomic and ecological approaches to identify the Bifidobacterium breve prototype of the healthy human gut microbiota.

Members of the genus Bifidobacterium are among the first microorganisms colonizing the human gut. Among these species, strains of Bifidobacterium breve are known to be commonly transmitted from mother to her newborn, while this species has also been linked with activities supporting human wellbeing. In the current study, an in silico approach, guided by ecology- and phylogenome-based analyses, was employed to identify a representative strain of B. breve to be exploited as a novel health-promoting candidate. The selected strain, i.e., B. breve PRL2012, was found to well represent the genetic content and functional genomic features of the B. breve taxon. We evaluated the ability of PRL2012 to survive in the gastrointestinal tract and to interact with other human gut commensal microbes. When co-cultivated with various human gut commensals, B. breve PRL2012 revealed an enhancement of its metabolic activity coupled with the activation of cellular defense mechanisms to apparently improve its survivability in a simulated ecosystem resembling the human microbiome.

Functional antagonism and insights into the biosynthetic potential of human gut-derived microbes

The specialised small molecules encoded by commensal microbes mediate distinct functional interactions. However, there is a landscape of antagonistic interactions mediated by specialised strains and their small molecules. Herein, the antagonistic landscape within a collection of 330 human gut-derived commensal microbial strains was elucidated to evaluate antimicrobial interactions as a defensive contributor, and gain new insights into structure-related functions. The potential antagonistic gut-derived strains displayed strain-specific selective inhibition. This is in contrast to common antimicrobial drugs, which typically wipe out a broad range of species and are usually found in environmental microbes. Genome sequencing of representative gut strains revealed the presence of significant biosynthetic gene clusters (BGCs) encoding compound families that contribute to antagonistic activities, and are important in host defence and maintaining gut homeostasis. Subsets of these BGCs were abundant in metagenomic sequencing data from healthy individuals. Furthermore, the cell culture secretome of these strains revealed potential biomarkers linked to hallmark pathways. These microorganisms have biosynthetic novelty and are a source of biologically significant natural products. Such natural products are essential in the development of new antimicrobial agents to reduce the usage of broad-spectrum antibiotics and combat antimicrobial resistance.

Microbial markets: socio-economic perspective in studying microbial communities.

Studying microbial communities through a socio-economic lens, this paper draws parallels with human economic transactions and microbes' race for resources. Extending the 'Market Economy' concept of social science to microbial ecosystems, the paper aims to contribute to comprehending the collaborative and competitive dynamics among microorganisms. Created by a multidisciplinary team of an economist, microbiologists, and mathematicians, the paper also highlights the risks involved in employing a socio-economic perspective to explain the complexities of natural ecosystems. Navigating through microbial markets offers insights into the implications of these interactions while emphasizing the need for cautious interpretation within the broader ecological context. We hope that this paper will be a fruitful source of inspiration for future studies on microbial communities.

DMGL-MDA: A dual-modal graph learning method for microbe-drug association prediction

The interaction between human microbes and drugs can significantly impact human physiological functions. It is crucial to identify potential microbe-drug associations (MDAs) before drug administration. However, conventional biological experiments to predict MDAs are plagued by drawbacks such as time-consuming, high costs, and potential risks. On the contrary, computational approaches can speed up the screening of MDAs at a low cost. Most computational models usually use a drug similarity matrix as the initial feature representation of drugs and stack the graph neural network layers to extract the features of network nodes. However, different calculation methods result in distinct similarity matrices, and message passing in graph neural networks (GNNs) induces phenomena of over-smoothing and over-squashing, thereby impacting the performance of the model. To address these issues, we proposed a novel graph representation learning model, dual-modal graph learning for microbe-drug association prediction (DMGL-MDA). It comprises a dual-modal embedding module, a bipartite graph network embedding module, and a predictor module. To assess the performance of DMGL-MDA, we compared it against state-of-the-art methods using two benchmark datasets. Through cross-validation, we illustrated the superiority of DMGL-MDA. Furthermore, we conducted ablation experiments and case studies to validate the effective performance of the model.

Shifts in the gut microbiota of sea urchin Diadema antillarum associated with the 2022 disease outbreak.

In recent decades, Caribbean coral reefs have lost many vital marine species due to diseases. The well-documented mass mortality event of the long-spined black sea urchin Diadema antillarum in the early 1980s stands out among these collapses. This die-off killed over 90% of D. antillarum changing the reefscape from coral to algal-dominated. Nearly 40 years later, D. antillarum populations have yet to recover. In early 2022, a new mortality event of D. antillarum was reported along the Caribbean, including Puerto Rico. This study identifies the gut microbiota changes associated with the D. antillarum during this mortality event. It contrasts them with the bacterial composition of gut samples from healthy individuals collected in 2019 by using 16S rRNA sequencing analyses. Notably, the die-off group's core microbiome resembled bacteria commonly found in the human skin and gut, suggesting potential anthropogenic contamination and wastewater pollution as contributing factors to the 2022 dysbiosis. The animals collected in 2022, especially those with signs of disease, lacked keystone taxa normally found in Diadema including Photobacterium and Propionigenium. The association between human microbes and disease stages in the long-spined urchin D. antillarum, especially in relation to anthropogenic contamination, highlights a complex interplay between environmental stressors and marine health. While these microbes might not be the direct cause of death in this species of sea urchins, their presence and proliferation can indicate underlying issues, such as immune depletion due to pollution, habitat destruction, or climate change, that ultimately compromise the health of these marine organisms.

Seeding and feeding milestones: the role of human milk microbes and oligosaccharides in the temporal development of infant gut microbiota

Abstract Breastfeeding represents a strong selective factor for shaping the infant gut microbiota. Besides providing nutritional requirements for the infant, human milk is a key source of oligosaccharides, human milk oligosaccharides (HMOs), and diverse microbes in early life. This study aimed to evaluate the influence of human milk microbiota and oligosaccharides on the composition of infant faecal microbiota at one, three, and nine months postpartum. We profiled milk microbiota, HMOs, and infant faecal microbiota from 23 mother–infant pairs at these time points. The predominant genera in milk samples were Streptococcus, Staphylococcus, and an unclassified Enterobacteriaceae genus-level taxon (Enterobacteriaceae uncl.), whereas the infant faecal microbiota was predominated by Bifidobacterium, Bacteroides, and Enterobacteriaceae uncl. Mother–infant dyads frequently shared bacterial amplicon sequence variants (ASVs) belonging to the genera Bifidobacterium, Streptococcus, Enterobacteriaceae uncl., Veillonella, Bacteroides, and Haemophilus. The individual HMO concentrations in the milk showed either no change or decreased over the lactation period, except for 3-fucosyllactose (3-FL), which increased. Neither maternal secretor status nor HMO concentrations were significantly associated with microbiota composition at the different ages or the bacterial ASVs of maternal milk and infant faeces. This study suggests an age-dependent role of milk microbes in shaping the gut microbiota, while variations in HMO concentrations show limited influence.