Pseudomonas syringae coffee blight is associated with the horizontal transfer of plasmid-encoded type III effectors.

The emergence of new pathogens is an ongoing threat to human health and agriculture. While zoonotic spillovers received considerable attention, the emergence of crop diseases is less well studied. Here, we identify genomic factors associated with the emergence of Pseudomonas syringae bacterial blight of coffee. Fifty-three P. syringae strains from diseased Brazilian coffee plants were sequenced. Comparative and evolutionary analyses were used to identify loci associated with coffee blight. Growth and symptomology assays were performed to validate the findings. Coffee isolates clustered in three lineages, including primary phylogroups PG3 and PG4, and secondary phylogroup PG11. Genome-wide association study of the primary PG strains identified 37 loci, including five effectors, most of which were encoded on a plasmid unique to the PG3 and PG4 coffee strains. Evolutionary analyses support the emergence of coffee blight in PG4 when the coffee-associated plasmid and associated effectors derived from a divergent plasmid carried by strains associated with other hosts. This plasmid was only recently transferred into PG3. Natural diversity and CRISPR-Cas9 plasmid curing were used to show that strains with the coffee-associated plasmid grow to higher densities and cause more severe disease symptoms in coffee. This work identifies possible evolutionary mechanisms underlying the emergence of a new lineage of coffee pathogens.

Predictive modeling of antibiotic eradication therapy success for new-onset Pseudomonas aeruginosa pulmonary infections in children with cystic fibrosis.

Chronic Pseudomonas aeruginosa (Pa) lung infections are the leading cause of mortality among cystic fibrosis (CF) patients; therefore, the eradication of new-onset Pa lung infections is an important therapeutic goal that can have long-term health benefits. The use of early antibiotic eradication therapy (AET) has been shown to clear the majority of new-onset Pa infections, and it is hoped that identifying the underlying basis for AET failure will further improve treatment outcomes. Here we generated machine learning models to predict AET outcomes based on pathogen genomic data. We used a nested cross validation design, population structure control, and recursive feature selection to improve model performance and showed that incorporating population structure control was crucial for improving model interpretation and generalizability. Our best model, controlling for population structure and using only 30 recursively selected features, had an area under the curve of 0.87 for a holdout test dataset. The top-ranked features were generally associated with motility, adhesion, and biofilm formation.

Cooperative virulence via the collective action of secreted pathogen effectors.

Although virulence is typically attributed to single pathogenic strains, here we investigated whether effectors secreted by a population of non-virulent strains could function as public goods to enable the emergence of collective virulence. We disaggregated the 36 type III effectors of the phytopathogenic bacterium Pseudomonas syringae strain PtoDC3000 into a 'metaclone' of 36 coisogenic strains, each carrying a single effector in an effectorless background. Each coisogenic strain was individually unfit, but the metaclone was collectively as virulent as the wild-type strain on Arabidopsis thaliana, suggesting that effectors can drive the emergence of cooperation-based virulence through their public action. We show that independently evolved effector suits can equally drive this cooperative behaviour by transferring the effector alleles native to the strain PmaES4326 into the conspecific but divergent strain PtoDC3000. Finally, we transferred the disaggregated PtoDC3000 effector arsenal into Pseudomonas fluorescens and show that their cooperative action was sufficient to convert this rhizosphere-inhabiting beneficial bacterium into a phyllosphere pathogen. These results emphasize the importance of microbial community interactions and expand the ecological scale at which disease may be attributed.

Habitats Within the Plant Root Differ in Bacterial Network Topology and Taxonomic Assortativity.

The root microbiome is composed of distinct epiphytic (rhizosphere) and endophytic (endosphere) habitats. Differences in abiotic and biotic factors drive differences in microbial community diversity and composition between these habitats, though how they shape the interactions among community members is unknown. Here, we coupled a large-scale characterization of the rhizosphere and endosphere bacterial communities of 30 plant species across two watering treatments with co-occurrence network analysis to understand how root habitats and soil moisture shape root bacterial network properties. We used a novel bootstrapping procedure and null network modeling to overcome some of the limitations associated with microbial co-occurrence network construction and analysis. Endosphere networks had elevated node betweenness centrality versus the rhizosphere, indicating greater overall connectivity among core bacterial members of the root endosphere. Taxonomic assortativity was higher in the endosphere, whereby positive co-occurrence was more likely between bacteria within the same phylum while negative co-occurrence was more likely between bacterial taxa from different phyla. This taxonomic assortativity could be driven by positive and negative interactions among members of the same or different phylum, respectively, or by similar niche preferences associated with phylum rank among root inhabiting bacteria across plant host species. In contrast to the large differences between root habitats, drought had limited effects on network properties but did result in a higher proportion of shared co-occurrences between rhizosphere and endosphere networks. Our study points to fundamentally different ecological processes shaping bacterial co-occurrence across root habitats. [Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Detection of Covid-19 Outbreaks Using Built Environment Testing for SARS-CoV-2.

Built Environment Testing for SARS-CoV-2Wastewater testing has proven to be a valuable tool for forecasting Covid-19 outbreaks. Fralick et al. now report that swabbing of surfaces (i.e., floors) for SARS-CoV-2 may provide a similar benefit for predicting outbreaks in long-term care homes.

Human milk nutrient fortifiers alter the developing gastrointestinal microbiota of very-low-birth-weight infants.

Nutrient fortifiers are added to human milk to support the development of very-low-birth-weight infants. Currently, bovine-milk-based fortifiers (BMBFs) are predominantly administered, with increasing interest in adopting human-milk-based fortifiers (HMBFs). Although beneficial for growth, their effects on the gastrointestinal microbiota are unclear. This triple-blind, randomized clinical trial (NCT02137473) tested how nutrient-enriching human milk with HMBF versus BMBF affects the gastrointestinal microbiota of infants born < 1,250 g during hospitalization. HMBF-fed infants (n = 63, n = 269 stools) showed lower microbial diversity, altered microbial community structure, and changes in predicted microbial functions compared with BMBF-fed infants (n = 56, n = 239 stools). HMBF-fed infants had higher relative and normalized abundances of unclassified Enterobacteriaceae and lower abundances of Clostridium sensu stricto. Post hoc analyses identified dose-dependent relationships between individual feed components (volumes of mother's milk, donor milk, and fortifiers) and the microbiota. These results highlight how nutrient fortifiers impact the microbiota of very-low-birth-weight infants during a critical developmental window.

Systematic profiling of the chicken gut microbiome reveals dietary supplementation with antibiotics alters expression of multiple microbial pathways with minimal impact on community structure.

BACKGROUND: The emergence of antimicrobial resistance is a major threat to global health and has placed pressure on the livestock industry to eliminate the use of antibiotic growth promotants (AGPs) as feed additives. To mitigate their removal, efficacious alternatives are required. AGPs are thought to operate through modulating the gut microbiome to limit opportunities for colonization by pathogens, increase nutrient utilization, and reduce inflammation. However, little is known concerning the underlying mechanisms. Previous studies investigating the effects of AGPs on the poultry gut microbiome have largely focused on 16S rDNA surveys based on a single gastrointestinal (GI) site, diet, and/or timepoint, resulting in an inconsistent view of their impact on community composition. METHODS: In this study, we perform a systematic investigation of both the composition and function of the chicken gut microbiome, in response to AGPs. Birds were raised under two different diets and AGP treatments, and 16S rDNA surveys applied to six GI sites sampled at three key timepoints of the poultry life cycle. Functional investigations were performed through metatranscriptomics analyses and metabolomics. RESULTS: Our study reveals a more nuanced view of the impact of AGPs, dependent on age of bird, diet, and intestinal site sampled. Although AGPs have a limited impact on taxonomic abundances, they do appear to redefine influential taxa that may promote the exclusion of other taxa. Microbiome expression profiles further reveal a complex landscape in both the expression and taxonomic representation of multiple pathways including cell wall biogenesis, antimicrobial resistance, and several involved in energy, amino acid, and nucleotide metabolism. Many AGP-induced changes in metabolic enzyme expression likely serve to redirect metabolic flux with the potential to regulate bacterial growth or produce metabolites that impact the host. CONCLUSIONS: As alternative feed additives are developed to mimic the action of AGPs, our study highlights the need to ensure such alternatives result in functional changes that are consistent with site-, age-, and diet-associated taxa. The genes and pathways identified in this study are therefore expected to drive future studies, applying tools such as community-based metabolic modeling, focusing on the mechanistic impact of different dietary regimes on the microbiome. Consequently, the data generated in this study will be crucial for the development of next-generation feed additives targeting gut health and poultry production. Video Abstract.

Predictive modeling of Pseudomonas syringae virulence on bean using gradient boosted decision trees.

Pseudomonas syringae is a genetically diverse bacterial species complex responsible for numerous agronomically important crop diseases. Individual P. syringae isolates are assigned pathovar designations based on their host of isolation and the associated disease symptoms, and these pathovar designations are often assumed to reflect host specificity although this assumption has rarely been rigorously tested. Here we developed a rapid seed infection assay to measure the virulence of 121 diverse P. syringae isolates on common bean (Phaseolus vulgaris). This collection includes P. syringae phylogroup 2 (PG2) bean isolates (pathovar syringae) that cause bacterial spot disease and P. syringae phylogroup 3 (PG3) bean isolates (pathovar phaseolicola) that cause the more serious halo blight disease. We found that bean isolates in general were significantly more virulent on bean than non-bean isolates and observed no significant virulence difference between the PG2 and PG3 bean isolates. However, when we compared virulence within PGs we found that PG3 bean isolates were significantly more virulent than PG3 non-bean isolates, while there was no significant difference in virulence between PG2 bean and non-bean isolates. These results indicate that PG3 strains have a higher level of host specificity than PG2 strains. We then used gradient boosting machine learning to predict each strain's virulence on bean based on whole genome k-mers, type III secreted effector k-mers, and the presence/absence of type III effectors and phytotoxins. Our model performed best using whole genome data and was able to predict virulence with high accuracy (mean absolute error = 0.05). Finally, we functionally validated the model by predicting virulence for 16 strains and found that 15 (94%) had virulence levels within the bounds of estimated predictions. This study strengthens the hypothesis that P. syringae PG2 strains have evolved a different lifestyle than other P. syringae strains as reflected in their lower level of host specificity. It also acts as a proof-of-principle to demonstrate the power of machine learning for predicting host specific adaptation.

Immunoglobulin A nephropathy is characterized by anticommensal humoral immune responses.

IgA nephropathy (IgAN) is a leading cause of kidney failure, yet little is known about the immunopathogenesis of this disease. IgAN is characterized by deposition of IgA in the kidney glomeruli, but the source and stimulus for IgA production are not known. Clinical and experimental data suggest a role for aberrant immune responses to mucosal microbiota in IgAN, and in some countries with high disease prevalence, tonsillectomy is regarded as standard-of-care therapy. To evaluate the relationship between microbiota and mucosal immune responses, we characterized the tonsil microbiota in patients with IgAN versus nonrelated household-matched control group participants and identified increased carriage of the genus Neisseria and elevated Neisseria-targeted serum IgA in IgAN patients. We reverse-translated these findings in experimental IgAN driven by BAFF overexpression in BAFF-transgenic mice rendered susceptible to Neisseria infection by introduction of a humanized CEACAM-1 transgene (B × hC-Tg). Colonization of B × hC-Tg mice with Neisseria yielded augmented levels of systemic Neisseria-specific IgA. Using a custom ELISPOT assay, we discovered anti-Neisseria-specific IgA-secreting cells within the kidneys of these mice. These findings suggest a role for cytokine-driven aberrant mucosal immune responses to oropharyngeal pathobionts, such as Neisseria, in the immunopathogenesis of IgAN. Furthermore, in the presence of excess BAFF, pathobiont-specific IgA can be produced in situ within the kidney.

Micronutrient supplements can promote disruptive protozoan and fungal communities in the developing infant gut.

Supplementation with micronutrients, including vitamins, iron and zinc, is a key strategy to alleviate child malnutrition. However, association of gastrointestinal disorders with iron has led to ongoing debate over their administration. To better understand their impact on gut microbiota, we analyse the bacterial, protozoal, fungal and helminth communities of stool samples collected from a subset of 80 children at 12 and 24 months of age, previously enrolled into a large cluster randomized controlled trial of micronutrient supplementation in Pakistan (ClinicalTrials.gov identifier NCT00705445). We show that while bacterial diversity is reduced in supplemented children, vitamins and iron (as well as residence in a rural setting) may promote colonization with distinct protozoa and mucormycetes, whereas the addition of zinc appears to ameliorate this effect. We suggest that the risks and benefits of micronutrient interventions may depend on eukaryotic communities, potentially exacerbated by exposure to a rural setting. Larger studies are needed to evaluate the clinical significance of these findings and their impact on health outcomes.

Oligosaccharides and Microbiota in Human Milk Are Interrelated at 3 Months Postpartum in a Cohort of Women with a High Prevalence of Gestational Impaired Glucose Tolerance.

BACKGROUND: Human milk is a rich source of human milk oligosaccharides (HMOs) and bacteria. It is unclear how these components interact within the breast microenvironment. OBJECTIVES: The objectives were first, to investigate the association between maternal characteristics and HMOs, and second, to assess the association between HMOs and microbial community composition and predicted function in milk from women with high rates of gestational glucose intolerance. METHODS: This was an exploratory analysis of a previously completed prospective cohort study (NCT01405547) where milk samples (n = 107) were collected at 3 mo postpartum. Milk microbiota composition was analyzed by V4-16S ribosomal RNA gene sequencing and HMOs by rapid high-throughput HPLC. Data were stratified and analyzed by maternal secretor status phenotype and associations between HMOs and microbiota were determined using linear regression models (ɑ-diversity), Adonis (B-diversity), Poisson regression models (differential abundance), and general linear models (predicted microbial function). RESULTS: Prepregnancy BMI, race, and frequency of direct breastfeeding, but not gestational glucose intolerance, were found to be significantly associated with a number of HMOs among secretors and non-secretors. Fucosyllacto-N-hexaose was negatively associated with microbial richness (Chao1) among secretors [B-estimate (SE): -9.3 × 102 (3.4 × 102); P = 0.0082] and difucosyllacto-N-hexaose was negatively associated with microbiota diversity (Shannon index) [-1.7 (0.78); P = 0.029] among secretors. Lacto-N-neotetraose (LNnT) was associated with both microbial B-diversity (weighted UniFrac R2 = 0.040, P = 0.036) and KEGG ortholog B-diversity (Bray-Curtis R2 = 0.039, P = 0.043) in secretors. Additionally, difucosyllactose in secretors and disialyllacto-N-hexaose and LNnT in non-secretors were associated with enrichment of predicted microbial genes encoding for metabolism- and infection-related pathways (P-false discovery rate < 0.1). CONCLUSIONS: HMOs are associated with the microbial composition and predicted microbial functions in human milk at 3 mo postpartum. Further research is needed to investigate the role these relations play in maternal and infant health.

Comparative genomic insights into the epidemiology and virulence of plant pathogenic pseudomonads from Turkey.

Pseudomonas is a highly diverse genus that includes species that cause disease in both plants and animals. Recently, pathogenic pseudomonads from the Pseudomonas syringae and Pseudomonas fluorescens species complexes have caused significant outbreaks in several agronomically important crops in Turkey, including tomato, citrus, artichoke and melon. We characterized 169 pathogenic Pseudomonas strains associated with recent outbreaks in Turkey via multilocus sequence analysis and whole-genome sequencing, then used comparative and evolutionary genomics to characterize putative virulence mechanisms. Most of the isolates are closely related to other plant pathogens distributed among the primary phylogroups of P. syringae, although there are significant numbers of P. fluorescens isolates, which is a species better known as a rhizosphere-inhabiting plant-growth promoter. We found that all 39 citrus blast pathogens cluster in P. syringae phylogroup 2, although strains isolated from the same host do not cluster monophyletically, with lemon, mandarin orange and sweet orange isolates all being intermixed throughout the phylogroup. In contrast, 20 tomato pith pathogens are found in two independent lineages: one in the P. syringae secondary phylogroups, and the other from the P. fluorescens species complex. These divergent pith necrosis strains lack characteristic virulence factors like the canonical tripartite type III secretion system, large effector repertoires and the ability to synthesize multiple bacterial phytotoxins, suggesting they have alternative molecular mechanisms to cause disease. These findings highlight the complex nature of host specificity among plant pathogenic pseudomonads.

The Impact of Migration on the Gut Metagenome of South Asian Canadians.

South Asian (SA) Canadian immigrants have a higher risk of developing certain immune-mediated inflammatory diseases compared to non-migrant SAs. We sought to investigate the effect of migration on the gut metagenome and to identify microbiological associations between migration and conditions that may influence the development of immune-mediated inflammatory diseases. Metagenomic analysis of 58 first-generation (GEN1) SA immigrants and 38 unrelated Canadian born children-of-immigrants (GEN2) determined that the time lived in Canada was associated with continued changes in gut microbial communities. Migration of GEN1 to Canada early in life results in a gut community with similarities to GEN2 SA Canadians and non-SA North Americans. Conversely, GEN1 immigrants who arrived recently to Canada exhibited pronounced differences from GEN2, while displaying microbial similarities to a non-migrating SA cohort. Multivariate analysis identified that community composition was primarily influenced by high abundance taxa. Prevotella copri dominated in GEN1 and non-migrant SAs. Clostridia and functionally related Bacteroidia spp. replaced P. copri dominance over generations in Canada. Mutually exclusive Dialister species occurred at differing relative abundances over time and generations in Canada. This shift in species composition is accompanied by a change in genes associated with carbohydrate utilization and short-chain fatty acid production. Total energy derived from carbohydrates compared to protein consumption was significantly higher for GEN1 recent immigrants, which may influence the functional requirements of the gut community. This study demonstrates the associations between migration and the gut microbiome, which may be further associated with the altered risk of immune-mediated inflammatory diseases observed for SA Canadians.

Evaluation of digital dispense-assisted broth microdilution antimicrobial susceptibility testing for Pseudomonas aeruginosa isolates.

Antimicrobial susceptibility testing (AST) is essential for detecting resistance in Pseudomonas aeruginosa and other bacterial pathogens. Here we evaluated the performance of broth microdilution (BMD) panels created using a semi-automated liquid handler, the D300e Digital Dispenser (Tecan Group Ltd., CH) that relies on inkjet printing technology. Microtitre panels (96-well) containing nine twofold dilutions of 12 antimicrobials from five classes (ß-lactams, ß-lactam/ß-lactamase inhibitors, aminoglycosides, fluoroquinolones, polymyxins) were prepared in parallel using the D300e Digital Dispenser and standard methods described by CLSI/ISO. To assess performance, panels were challenged with three well characterized quality control organisms and 100 clinical P. aeruginosa isolates. Traditional agreement and error measures were used for evaluation. Essential (EA) and categorical (CA) agreements were 92.7% and 98.0% respectively for P. aeruginosa isolates with evaluable on-scale results. The majority of minor errors that fell outside acceptable EA parameters (≥ ± 1 dilution, 1.9%) were seen with aztreonam (5%) and ceftazidime (4%), however all antimicrobials displayed acceptable performance in this situation. Differences in MIC were often log2 dilution lower for D300e dispensed panels. Major and very major errors were noted for aztreonam (2.6%) and cefepime (1.7%) respectively. The variable performance of D300e panels suggests that further testing is required to confirm their diagnostic utility for P. aeruginosa.

Pseudomonas aeruginosa Strain-sharing in Early Infection Among Children With Cystic Fibrosis.

BACKGROUND: We previously identified Pseudomonas aeruginosa isolates with characteristics typical of chronic infection in some early infections in children with cystic fibrosis (CF), suggesting that these isolates may have been acquired from other patients. Our objective was to define the extent of P. aeruginosa strain-sharing in early CF infections and its impact on antibiotic eradication treatment failure rates. METHODS: We performed whole genome sequencing on isolates from early pediatric CF pulmonary infections and from the following comparator groups in the same hospital: chronic CF infection, sink drains, sterile site infections, and asymptomatic carriage. Univariate logistic regression was used to assess factors associated with treatment failure. RESULTS: In this retrospective, observational study, 1029 isolates were sequenced. The CF clones strain B and clone C were present. In 70 CF patients with early infections, 14 shared strains infected 29 (41%) patients over 5 years; 16% (n = 14) of infections had mixed strains. In the 70 children, approximately one-third of shared-strain infections were likely due to patient-to-patient transmission. Mixed-strain infections were associated with strain-sharing (odds ratio, 8.50; 95% confidence interval, 2.2-33.4; P = .002). Strain-sharing was not associated with antibiotic eradication treatment failure; however, nosocomial strain transmission was associated with establishment of chronic infection in a CF sibling pair. CONCLUSIONS: Although early P. aeruginosa CF infection is thought to reflect acquisition of diverse strains from community reservoirs, we identified frequent early CF strain-sharing that was associated with the presence of mixed strains and instances of possible patient-to-patient transmission.

Maternal Diet and Infant Feeding Practices Are Associated with Variation in the Human Milk Microbiota at 3 Months Postpartum in a Cohort of Women with High Rates of Gestational Glucose Intolerance.

BACKGROUND: Human milk contains a diverse community of bacteria believed to play a role in breast health and inoculation of the infant's gastrointestinal tract. The role of maternal nutrition and infant feeding practices on the human milk microbiota remains poorly understood. OBJECTIVE: Our aim was to explore the associations between maternal diet (delivery to 3 mo postpartum), infant feeding practices, and the microbial composition and predicted function in milk from women with varied metabolic status. METHODS: This was an exploratory analysis of a previously completed prospective cohort study of women with varying degrees of gestational glucose intolerance (NCT01405547). Milk samples (n = 93 mothers) were collected at 3 mo postpartum. Maternal dietary information (validated food-frequency questionnaire) and infant feeding practices (human milk exclusivity, frequency of direct breastfeeding per day) were collected. V4-16S ribosomal RNA gene sequencing (Illumina MiSeq) was conducted to determine microbiota composition. RESULTS: Intake of polyunsaturated fat [ß estimate (SE): 0.036 (0.018), P = 0.047] and fiber from grains [0.027 (0.013), P = 0.048] were positively associated with ɑ-diversity (Shannon index) of human milk. Overall microbial composition of human milk clustered based on human milk exclusivity (weighted UniFrac R2 = 0.034, P = 0.015; Bray-Curtis R2 = 0.041, P = 0.007), frequency of direct breastfeeding per day (Bray-Curtis R2 = 0.057, P = 0.026), and maternal fiber intake from grains (Bray-Curtis R2 = 0.055, P = 0.040). Total fiber, fiber from grains, dietary fat, and infant feeding practices were also associated with a number of differentially abundant taxa. The overall composition of predicted microbial functions was associated with total fiber consumption (Bray-Curtis R2 = 0.067, P = 0.036) and human milk exclusivity (Bray-Curtis R2 = 0.041, P = 0.013). CONCLUSIONS: Maternal consumption of fiber and fat, as well as mother's infant feeding practices, are important determinants of the human milk microbiota. Understanding whether these microbial changes impact an infant's overall health and development requires future study.

Ecological Succession of Polymicrobial Communities in the Cystic Fibrosis Airways.

Antimicrobial therapies against cystic fibrosis (CF) lung infections are largely aimed at the traditional, well-studied CF pathogens such as Pseudomonas aeruginosa and Burkholderia cepacia complex, despite the fact that the CF lung harbors a complex and dynamic polymicrobial community. A clinical focus on the dominant pathogens ignores potentially important community-level interactions in disease pathology, perhaps explaining why these treatments are often less effective than predicted based on in vitro testing. A better understanding of the ecological dynamics of this ecosystem may enable clinicians to harness these interactions and thereby improve treatment outcomes. Like all ecosystems, the CF lung microbial community develops through a series of stages, each of which may present with distinct microbial communities that generate unique host-microbe and microbe-microbe interactions, metabolic profiles, and clinical phenotypes. While insightful models have been developed to explain some of these stages and interactions, there is no unifying model to describe how these infections develop and persist. Here, we review current perspectives on the ecology of the CF airway and present the CF Ecological Succession (CFES) model that aims to capture the spatial and temporal complexity of CF lung infection, address current challenges in disease management, and inform the development of ecologically driven therapeutic strategies.

Mothers of Preterm Infants Have Individualized Breast Milk Microbiota that Changes Temporally Based on Maternal Characteristics.

Mother's milk contains complex microbial communities thought to be important for colonizing a preterm infant's gastrointestinal tract. However, little is known about the microbiota in the preterm mother's milk and factors influencing its composition. We characterized the temporal dynamics of microbial communities in 490 breast milk samples from 86 mothers of preterm infants (born <1,250g) over the first 8 weeks postpartum. Highly individualized microbial communities were identified in each mother's milk that changed temporally with notable alterations in predicted microbial functions. However, pre-pregnancy BMI, delivery mode, and antibiotics were associated with changes in these microbial dynamics. Individual classes of antibiotics and their duration of exposure during prenatal and postpartum periods showed unique relationships with microbial taxa abundance and diversity in mother's milk. These results highlight the temporal complexity of the preterm mother's milk microbiota and its relationship with maternal characteristics as well as the importance of discussing antibiotic stewardship for mothers.

Examining the relationship between maternal body size, gestational glucose tolerance status, mode of delivery and ethnicity on human milk microbiota at three months post-partum.

BACKGROUND: Few studies have examined how maternal body mass index (BMI), mode of delivery and ethnicity affect the microbial composition of human milk and none have examined associations with maternal metabolic status. Given the high prevalence of maternal adiposity and impaired glucose metabolism, we systematically investigated the associations between these maternal factors in women ≥20 years and milk microbial composition and predicted functionality by V4-16S ribosomal RNA gene sequencing (NCT01405547;  https://clinicaltrials.gov/ct2/show/NCT01405547 ). Demographic data, weight, height, and a 3-h oral glucose tolerance test were gathered at 30 (95% CI: 25-33) weeks gestation, and milk samples were collected at 3 months post-partum (n = 113). RESULTS: Multivariable linear regression analyses demonstrated no significant associations between maternal characteristics (maternal BMI [pre-pregnancy, 3 months post-partum], glucose tolerance, mode of delivery and ethnicity) and milk microbiota alpha-diversity; however, pre-pregnancy BMI was associated with human milk microbiota beta-diversity (Bray-Curtis R2 = 0.037). Women with a pre-pregnancy BMI > 30 kg/m2 (obese) had a greater incidence of Bacteroidetes (incidence rate ratio [IRR]: 3.70 [95% CI: 1.61-8.48]) and a reduced incidence of Proteobacteria (0.62 [0.43-0.90]) in their milk, compared to women with an overweight BMI (25.0-29.9 kg/m2) as assessed by multivariable Poisson regression. An increased incidence of Gemella was observed among mothers with gestational diabetes who had an overweight BMI versus healthy range BMI (5.96 [1.85-19.21]). An increased incidence of Gemella was also observed among mothers with impaired glucose tolerance with an obese BMI versus mothers with a healthy range BMI (4.04 [1.63-10.01]). An increased incidence of Brevundimonas (16.70 [5.99-46.57]) was found in the milk of women who underwent an unscheduled C-section versus vaginal delivery. Lastly, functional gene inference demonstrated that pre-pregnancy obesity was associated with an increased abundance of genes encoding for the biosynthesis of secondary metabolites pathway in milk (coefficient = 0.0024, PFDR < 0.1). CONCLUSIONS: Human milk has a diverse microbiota of which its diversity and differential abundance appear associated with maternal BMI, glucose tolerance status, mode of delivery, and ethnicity. Further research is warranted to determine whether this variability in the milk microbiota impacts colonization of the infant gut.

Accumulation of genetic variants associated with immunity in the selective breeding of broilers.

BACKGROUND: To satisfy an increasing demand for dietary protein, the poultry industry has employed genetic selection to increase the growth rate of broilers by over 400% in the past 50 years. Although modern broilers reach a marketable weight of ~ 2 kg in a short span of 35 days, a speed twice as fast as a broiler 50 years ago, the expedited growth has been associated with several negative detrimental consequences. Aside from heart and musculoskeletal problems, which are direct consequences of additional weight, the immune response is also thought to be altered in modern broilers. RESULTS: Given that identifying the underlying genetic basis responsible for a less sensitive innate immune response would be economically beneficial for poultry breeding, we decided to compare the genomes of two unselected meat control strains that are representative of broilers from 1957 and 1978, and a current commercial broiler line. Through analysis of genetic variants, we developed a custom prioritization strategy to identify genes and pathways that have accumulated genetic changes and are biologically relevant to immune response and growth performance. Our results highlight two genes, TLR3 and PLIN3, with genetic variants that are predicted to enhance growth performance at the expense of immune function. CONCLUSIONS: Placing these new genomes in the context of other chicken lines, reveal genetic changes that have specifically arisen in selective breeding programs that were implemented in the last 50 years.