The vaginal microbiome plays a critical role in reproductive health, yet most studies remain descriptive and functional features connecting microbial communities to host physiology remain poorly understood. In endometriosis, alterations in the vaginal microbiome and host glycosylation have been reported, yet ecological properties connecting these systems remain unclear. We investigated whether vaginal resistome functional redundancy (FR) represents a functional link between microbial community structure, microbial metabolic capacity, and host glycomic variation across endometriosis severity. Shotgun metagenomic sequencing was performed on high vaginal swabs from women with healthy controls, minimal/mild, and moderate/severe endometriosis (n = 40). While total antibiotic resistance genes (ARG) abundance remained relatively stable across disease groups, resistome FR increased significantly in moderate/severe endometriosis, reflecting a transition from low-diversity, Lactobacillus-dominated communities toward more taxonomically diverse, ARG-harbouring taxa. Increased redundancy was associated with higher microbial alpha diversity and enrichment of glycan-related metabolic pathways, particularly UDP-N-acetyl-D-glucosamine biosynthesis, a precursor pathway for glycan assembly. These microbial functional features correlated with host glycomic signatures in serum and urine. Mediation and path modelling analyses supported associations among resistome FR, predicted UDP-sugar pathway potential, host glycomic variation, and endocrine-related traits. Our findings identify resistome FR as a quantifiable ecological property of the vaginal microbiome that is associated with microbial metabolic capacity and host glycomic variation in endometriosis. Rather than acting as a direct driver, FR may serve as a marker of microbiome organisation that relates to host-associated phenotypes, providing a framework for understanding microbiome–glycome interactions in reproductive tract disease.

The infant resistome, the collection of antimicrobial resistance genes (ARGs) of newborns, is critical for gut microbiota establishment. Using metagenomic sequencing data, we analyzed various 1-week and 1-month postpartum samples to study infant resistome establishment, ARG transmission, and its impact on functional redundancy of the microbiota. A total of 431 samples were analyzed; infant stools (1-week, n = 119; 1-month, n = 119), maternal stools (1-month postpartum, n = 120), and breastmilk (1-month postpartum, n = 73). Breastfeeding correlated with increased functional redundancy and altered bacterial-ARG co-occurrence networks in the infant resistome. Escherichia coli dominated early resistome dynamics with a higher abundance correlating with reduced functional redundancy. Bifidobacterium longum exhibited a consistent negative association with 21 ARGs at one-month in breastfed infants, while four negative relationships between ARGs and Bifidobacterium bifidum were observed in formula-fed infants. ARG transmission via breastmilk appears to be gene-specific, with the quinolone resistance gene sdrM likely transmitted under maternal antibiotic use. Delivery mode modulated the microbial environment in ways that interact with resistome structure and changing functional redundancy, particularly through genera like Staphylococcus and Streptococcus. These findings highlight the role of early feeding practices in resistome development and propose functional redundancy as a key ecological framework for understanding infant gut resistome dynamics.

Current first-line treatments of paediatric ulcerative colitis (UC) maintain a 6-month remission in only half of the patients. Relapse prediction at diagnosis could enable earlier introduction of immunosuppressants. We collected intestinal biopsies from 56 treatment-naïve children, combining mucosal quantitative microbial profiling with host epigenomics, transcriptomics, genotyping, and in vitro and in vivo experiments on selected bacteria. Baseline bacterial diversity is lower in relapsing children, who have fewer butyrate producers but more oral-associated bacteria, whereof Veillonella parvula induces inflammation in epithelial cell lines and IL10-/- mice. Microbiota has the strongest association with future relapse, followed by host epigenome and transcriptome. Interferon gamma signalling is also linked to relapse-associated bacteria. Relapse-prediction using separate omics data is outperformed by a robust machine learning approach combining microbiomes and epigenomes. In summary, host-microbe data have prognostic potential in paediatric UC. Our translational findings also suggest that pro-inflammatory oral-associated colonizers can exploit the reduced colonic bacterial diversity of relapsing children.

SUMMARY Human milk oligosaccharides (HMOs) are complex, multi-functional glycans present in human breast milk. They represent an intricate mix of heterogeneous structures which reach the infant intestine in an intact form as they resist gastrointestinal digestion. Therefore, they confer a multitude of benefits, directly and/or indirectly, to the developing neonate. Certain bifidobacterial species, being among the earliest gut colonizers of breast-fed infants, have an adapted functional capacity to metabolize various HMO structures. This ability is typically observed in infant-associated bifidobacteria, as opposed to bifidobacteria associated with a mature microbiota. In recent years, information has been gleaned regarding how these infant-associated bifidobacteria as well as certain other taxa are able to assimilate HMOs, including the mechanistic strategies enabling their acquisition and consumption. Additionally, complex metabolic interactions occur between microbes facilitated by HMOs, including the utilization of breakdown products released from HMO degradation. Interest in HMO-mediated changes in microbial composition and function has been the focal point of numerous studies, in recent times fueled by the availability of individual biosynthetic HMOs, some of which are now commonly included in infant formula. In this review, we outline the main HMO assimilatory and catabolic strategies employed by infant-associated bifidobacteria, discuss other taxa that exhibit breast milk glycan degradation capacity, and cover HMO-supported cross-feeding interactions and related metabolites that have been described thus far.

AbstractThe global outbreak of human monkeypox (mpox) in 2022, declared a Public Health Emergency of International Concern by the WHO, has underscored the urgent need for effective diagnostic tools. In August 2024 WHO again declared mpox as a Public Health Emergency of International Concern. This study presents an innovative approach using artificial intelligence (AI) to design primers for the rapid and accurate detection of mpox. Leveraging evolutionary algorithms, we developed primer sets with high specificity and sensitivity, validated insilicofor mpox main lineage and the Clade 1b. These primers are crucial for distinguishing mpox from other viruses, enabling precise diagnosis and timely public health responses. Our findings highlight the potential of AI-driven methodologies to enhance surveillance, vaccination strategies, and outbreak management, particularly for emerging zoonotic diseases. The emergence of new mpox clades, such as Clade1b, with higher mortality rates, further emphasizes the necessity for continuous monitoring and preparedness for future pandemics. This study advocates for the integration of AI in molecular diagnostics to improve public health outcomes.

Endometriosis is a chronic systemic disease, which results in endometrial-type tissue growing outside the uterus, and affects approximately 10% of reproductive-aged women worldwide. Its aetiology is poorly understood, and there is currently no long-term cure. Development and persistence of the disease depend on several coexisting factors including the vaginal microbiome. However, the role played by this important entity in endometriosis and its systemic involvement is not fully understood. Here, we investigated the vaginal microbiota, the serum and urine glycome, and antibody glycosylation in endometriosis patients. We reveal an endometriosis-specific vaginal microbiota in patients, being distinct from that present in a control group. Endometriosis patients were typified by a loss of the dominant Lactobacillus species, i.e. Lactobacillus iners, increased bacterial diversity and the presence of species such as Anaerococcus senegalensis, Prevotella jejuni, Porphyromonas bennonis and Anaerococcus octavius. The presence of trigalactosylated and triantennary serum glycans and urine core fucosylated mono-antennary glycans from IgG correlated with the vaginal presence of the bacterium A. senegalensis in endometriosis patients. Urine glycans did not differ in endometriosis, but urine IgG identified four novel sulfated glycans differing from serum IgG indicating functional relevance. Our findings contribute to understanding the relationships between the vaginal microbiota and the serum and urine glycome on the one hand, and endometriosis on the other. Further functional studies are warranted.

Immunoglobulins play a vital role in host immune response and in the pathogenesis of conditions like asthma. Therapeutic agents such as monoclonal antibodies target specific elements of the asthmatic inflammatory cascade. Decisions to utilize these medications are often based on systemic inflammatory profiling without direct insight into the airway inflammatory profile. We sought to investigate the relationship between immunoglobulin and cytokine profiles in the airway and systemic immune compartments of adult asthmatics. Blood sampling and bronchoscopy with bronchoalveolar lavage (BAL) were performed in 76 well-defined adult asthmatics. Antibody and cytokine profiles were measured in both BAL and serum using ELISA and quantibody arrays. There was no relationship between BAL and serum levels of IgE. This is of significance in an asthma population. For some analytes, correlation analysis was significant (P < 0.05) indicating representativeness of our cohort and experimental setup in those cases. Nevertheless, the predictive power (r2) of the BAL-to-serum comparisons was mostly low except for TNF-α (r2 = 0.73) when assuming a simple (linear) relationship. This study highlights the importance of sample site when investigating the roles of immunoglobulins and cytokines in disease pathogenesis and suggests that both localized and systemic immune responses are at play. The prescription of asthma monoclonal therapy is generally based on systemic evaluation of cytokine and immunoglobulin levels. Our research suggests that this approach may not fully reflect the pathophysiology of the disease and may provide insight into why some patients respond to these targeted therapies while others do not.

The lungs have their own microbiota which seems to be altered in disease processes such as asthma.Viral infection accounts for many asthma exacerbations.Little is known about the lung virome, and the role that viruses play in non-exacerbating asthmatics.We aimed to assess if detection of virus in bronchoscopy samples of asthmatic patients in a non-exacerbating state influences their asthma control and modulates airway cytokine composition.Patients were recruited from a specialist asthma clinic and underwent bronchoscopy with standardised bronchoalveolar lavage (BAL).Viral analysis was performed; cell differential and cytokine levels were measured.Forty-six samples were obtained of which 10.8% demonstrated evidence of airway virus, and 91.3% of patients in the cohort were classed as severe asthmatics.Oral steroid use was significantly higher in severe asthmatic patients with virus detected, and the forced expiratory volume in one second tended to be lower in the virus-detected group.It was also found that BAL interleukin-13 and tumor necrosis factor-α levels were significantly higher in severe asthmatic patients with virus detected.Our results suggest that in severe asthmatics in a non-exacerbating state, the presence of virus resulted in overall poorer asthma control.The pattern of cytokine elevation seen in asthmatic patients with virus detected may provide insight to the pathophysiology involved.

"The Potential Role of Gastric Microbiology in Respiratory Disease." American Journal of Respiratory and Critical Care Medicine, 0(ja), pp.

Typically, animal models studying gastrointestinal microbiotas compromised in early life have employed either germ-free animals or mice treated with a cocktail of antibiotics. Such studies intend to mimic scenarios of infants born by caesarean section and/or subjected to antibiotic treatment. However, the antibiotics used in these studies are rarely prescribed to infants. Therefore, an early life model was developed in which the murine gastrointestinal microbiota was severely disrupted by clindamycin treatment. In this mouse model, we investigated the extent supplementation with a synbiotic mixture of prebiotics, being scGOS/lcFOS with the human milk oligosaccharide 2’-Fucosyllactose (2’-FL), in combination with or without single strain or mix of “infant type” bifidobacteria, can rescue an antibiotic-compromised microbiota. Shotgun metagenomic sequencing showed that the microbiota was severely disrupted by the clindamycin challenge. No recovery was observed 3 weeks post-challenge in the scGOS/lcFOS/2’FL group, while the group that received the synbiotic treatment of scGOS/lcFOS/2’-FL with Bifidobacterium breve NRBB01 showed partial recovery. Strikingly in the scGOS/lcFOS/2’-FL group receiving the mixture of bifidobacteria resulted in a recovery of the microbiota disruption. Histological analyses showed that the clindamycin-treated animals at the end of the experiment still suffered from mild oedema and villi/colonic crypt irregularities which was ameliorated by the synbiotic intervention. Our study demonstrates that supplementation of synbiotic mixture of scGOS/lcFOS/2’-FL in combination with a specific mix of infant-type bifidobacterial strains is able to partially revive an antibiotic-perturbed gastrointestinal microbiota.

As the COVID-19 pandemic winds down, it leaves behind the serious concern that future, even more disruptive pandemics may eventually surface. One of the crucial steps in handling the SARS-CoV-2 pandemic was being able to detect the presence of the virus in an accurate and timely manner, to then develop policies counteracting the spread. Nevertheless, as the pandemic evolved, new variants with potentially dangerous mutations appeared. Faced by these developments, it becomes clear that there is a need for fast and reliable techniques to create highly specific molecular tests, able to uniquely identify VOCs. Using an automated pipeline built around evolutionary algorithms, we designed primer sets for SARS-CoV-2 (main lineage) and for VOC, B.1.1.7 (Alpha) and B.1.1.529 (Omicron). Starting from sequences openly available in the GISAID repository, our pipeline was able to deliver the primer sets for the main lineage and each variant in a matter of hours. Preliminary in-silico validation showed that the sequences in the primer sets featured high accuracy. A pilot test in a laboratory setting confirmed the results: the developed primers were favorably compared against existing commercial versions for the main lineage, and the specific versions for the VOCs B.1.1.7 and B.1.1.529 were clinically tested successfully.

Diet exerts a major influence upon host immune function and the gastrointestinal microbiota. Although components of the human diet (including carbohydrates, fats, and proteins) are essential sources of nutrition for the host, they also influence immune function directly through interaction with innate and cell-mediated immune regulatory mechanisms. Regulation of the microbiota community structure also provides a mechanism by which food components influence host immune regulatory processes. Here, we consider the complex interplay between components of the modern (Western) diet, the microbiota, and host immunity in the context of obesity and metabolic disease, inflammatory bowel disease, and infection.

This study found that patients with active UC have significantly increased colonic gene expression of cytosolic DNA sensor, inflammasome, STING, and type I IFN signaling pathways. The type I IFN, IFN-β, in combination with TNF-α induced JAK-dependent but NLRP3 and inflammasome-independent inflammatory cell death of colonic organoids. This novel inflammatory cell death phenotype is relevant to UC immunopathology and may partially explain the efficacy of the JAKinibs tofacitinib and upadacitinib in patients with UC.

ABSTRACTAs the COVID-19 pandemic continues to affect the world, a new variant of concern, B.1.1.529 (Omicron), has been recently identified by the World Health Organization. At the time of writing, there are still no available primer sets specific to the Omicron variant, and its identification is only possible by using multiple targets, checking for specific failures, amplifying the suspect samples, and sequencing the results. This procedure is considerably time-consuming, in a situation where time might be of the essence. In this paper we use an Artificial Intelligence (AI) technique to identify a candidate primer set for the Omicron variant. The technique, based on Evolutionary Algorithms (EAs), has been already exploited in the recent past to develop primers for the B.1.1.7/Alpha variant, that have later been successfully tested in the lab. Starting from available virus samples, the technique explores the space of all possible subsequences of viral RNA, evaluating them as candidate primers. The criteria used to establish the suitability of a sequence as primer includes its frequency of appearance in samples labeled as Omicron, its absence from samples labeled as other variants, a specific range of melting temperature, and its CG content. The resulting primer set has been validated in silico and proves successful in preliminary laboratory tests. Thus, these results prove further that our technique could be established as a working template for a quick response to the appearance of new SARS-CoV-2 variants.

Almost 2 years ago, the novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was discovered to be the causative agent of the disease COVID-19. Subsequently, SARS-CoV-2 has spread across the world infecting millions of people, resulting in the ongoing COVID-19 pandemic. The current ‘gold standard’ for COVID-19 diagnosis involves obtaining a nasopharyngeal swab (NPS) from the patient and testing for the presence of SARS-CoV-2 RNA in the specimen using real-time reverse transcription PCR (RT-qPCR). However, obtaining a NPS specimen is an uncomfortable and invasive procedure for the patient and is limited in its applicability to mass testing. Interest in saliva as an alternative diagnostic specimen is of increasing global research interest due to its malleability to mass testing, greater patient acceptability and overall ease of specimen collection. However, the current literature surrounding the sensitivity of saliva compared to NPS is conflicting. The aim of this review was to analyse the recent literature to assess the viability of saliva in COVID-19 diagnosis. We hypothesize that the discrepancies in the current literature are likely due to the variations in the saliva collection and processing protocols used between studies. The universal adaptation of an optimised protocol could alleviate these discrepancies and see saliva specimens be as sensitive, if not more, than NPS for COVID-19 diagnosis. Whilst saliva specimens are more complimentary to mass-testing, with the possibility of samples being collected from home, the RT-qPCR diagnostic process remains to be the rate-limiting step and therefore interest in salivary rapid antigen tests, which negate the wait-times of RT-qPCR with results available within 15–30 min, may be an answer to this.