A genome-wide association study for survival from a multi-centre European study identified variants associated with COVID-19 risk of death.

The clinical manifestations of SARS-CoV-2 infection vary widely among patients, from asymptomatic to life-threatening. Host genetics is one of the factors that contributes to this variability as previously reported by the COVID-19 Host Genetics Initiative (HGI), which identified sixteen loci associated with COVID-19 severity. Herein, we investigated the genetic determinants of COVID-19 mortality, by performing a case-only genome-wide survival analysis, 60 days after infection, of 3904 COVID-19 patients from the GEN-COVID and other European series (EGAS00001005304 study of the COVID-19 HGI). Using imputed genotype data, we carried out a survival analysis using the Cox model adjusted for age, age2, sex, series, time of infection, and the first ten principal components. We observed a genome-wide significant (P-value < 5.0 × 10-8) association of the rs117011822 variant, on chromosome 11, of rs7208524 on chromosome 17, approaching the genome-wide threshold (P-value = 5.19 × 10-8). A total of 113 variants were associated with survival at P-value < 1.0 × 10-5 and most of them regulated the expression of genes involved in immune response (e.g., CD300 and KLR genes), or in lung repair and function (e.g., FGF19 and CDH13). Overall, our results suggest that germline variants may modulate COVID-19 risk of death, possibly through the regulation of gene expression in immune response and lung function pathways.

Characterization of heterozygosity-rich regions in Italian and worldwide goat breeds.

Heterozygosity-rich regions (HRR) are genomic regions of high heterozygosity, which may harbor loci related to key functional traits such as immune response, survival rate, fertility, and other fitness traits. This study considered 30 Italian and 19 worldwide goat breeds genotyped with the Illumina GoatSNP50k BeadChip. The aim of the work was to study inter-breed relationships and HRR patterns using Sliding Window (SW) and Consecutive Runs (CR) detection methods. Genetic relationships highlighted a clear separation between non-European and European breeds, as well as the north-south geographic cline within the latter. The Pearson correlation coefficients between the descriptive HRR parameters obtained with the SW and CR methods were higher than 0.9. A total of 166 HRR islands were detected. CHI1, CHI11, CHI12 and CHI18 were the chromosomes harboring the highest number of HRR islands. The genes annotated in the islands were linked to various factors such as productive, reproductive, immune, and environmental adaptation mechanisms. Notably, the Montecristo feral goat showed the highest number of HRR islands despite the high level of inbreeding, underlining potential balancing selection events characterizing its evolutionary history. Identifying a species-specific HRR pattern could provide a clearer view of the mechanisms regulating the genome modelling following anthropogenic selection combined with environmental interaction.

Multiple genomic solutions for local adaptation in two closely related species (sheep and goats) facing the same climatic constraints.

The question of how local adaptation takes place remains a fundamental question in evolutionary biology. The variation of allele frequencies in genes under selection over environmental gradients remains mainly theoretical and its empirical assessment would help understanding how adaptation happens over environmental clines. To bring new insights to this issue we set up a broad framework which aimed to compare the adaptive trajectories over environmental clines in two domesticated mammal species co-distributed in diversified landscapes. We sequenced the genomes of 160 sheep and 161 goats extensively managed along environmental gradients, including temperature, rainfall, seasonality and altitude, to identify genes and biological processes shaping local adaptation. Allele frequencies at putatively adaptive loci were rarely found to vary gradually along environmental gradients, but rather displayed a discontinuous shift at the extremities of environmental clines. Of the 430 candidate adaptive genes identified, only 6 were orthologous between sheep and goats and those responded differently to environmental pressures, suggesting different putative mechanisms involved in local adaptation in these two closely related species. Interestingly, the genomes of the 2 species were impacted differently by the environment, genes related to signatures of selection were most related to altitude, slope and rainfall seasonality for sheep, and summer temperature and spring rainfall for goats. The diversity of candidate adaptive pathways may result from a high number of biological functions involved in the adaptations to multiple eco-climatic gradients, and a differential role of climatic drivers on the two species, despite their co-distribution along the same environmental gradients. This study describes empirical examples of clinal variation in putatively adaptive alleles with different patterns in allele frequency distributions over continuous environmental gradients, thus showing the diversity of genetic responses in adaptive landscapes and opening new horizons for understanding genomics of adaptation in mammalian species and beyond.

Effect of the Selective Dry Cow Therapy on Udder Health and Milk Microbiota.

Recently, the use of antimicrobials on dairy farms has been significantly limited from both the legislative and consumer points of view. This study aims to check the efficacy of selective dry cow therapy (SDCT) versus blanket dry cow therapy (BDCT) on bovine udder in healthy animals. SDTC is when an antibiotic is administered only to infected cows, compared with BDCT, where all cows receive an antimicrobial, regardless of their infection status. The milk samples were collected from enrolled Holstein Friesian cows 7 days before dry-off (T0) and 10 days after calving (T1) to assess somatic cell count (SCC), intramammary infections (IMIs), and milk microbiota variation. After pre-drying sampling, cows are randomly assigned to the following treatments: internal teat sealant alone (ITS; 24 cows), which is a treatment in a cow that does not receive antibiotics in SDTC, or in combination with intramammary antibiotic treatment (A+ITS; 22 cows). Non-statistically significant results are found between the two treatment groups at T1 for SCC, milk yield, and alpha diversity in milk microbiota. A statistically (p < 0.033) T1 IMI decrease is reported in the A+ITS group, and a significant beta diversity analysis is shown between the two timepoints (p = 0.009). This study confirms the possibility of selective drying without new IMI risk or increased SCC at calving, considering healthy cows without contagious infections and SCC values >200,000 cells/mL in the previous lactation.

Effects of Thymbra capitata essential oil on in vitro fermentation end-products and ruminal bacterial communities.

An in vitro trial was carried out to investigate the effects of natural Thymbra capitata essential oil (NEO) and its main compounds [including carvacrol, p-cymene, γ-terpinene given alone or in a synthetic combination (SEO)] on ruminal fermentation and the bacterial community using batch cultures inoculated with ruminal digesta and incubating two different basal diets [high-forage (F) and high-concentrate (C) diet]. After 24 h of incubation, primary fermentation end-products [gas, methane, volatile fatty acids (VFAs) and ammonia] and rumen microbial diversity were determined. NEO reduced the total VFA concentration (P < 0.05) only in the C diet. In contrast, SEO and carvacrol decreased the total VFA concentration (P < 0.05) only in the F diet. Methane production was not affected (P > 0.05) by any of the experimental treatments or diets evaluated. Microbial diversity analysis showed only a moderate effect of carvacrol and SEO on 13 genera, including, mainly, Atopobium and Blautia (involved in subacute ruminal acidosis) or Candidatus Saccharimonas (related to laminitis). In conclusion, T. capitata EO has a limited potential to attain nutritional or environmental benefits, but further research should be carried out to clarify its effects on animal health and microbial food safety.

Genome-wide mapping of signatures of selection using a high-density array identified candidate genes for growth traits and local adaptation in chickens.

BACKGROUND: Availability of single nucleotide polymorphism (SNP) genotyping arrays and progress in statistical analyses have allowed the identification of genomic regions and genes under selection in chicken. In this study, SNP data from the 600 K Affymetrix chicken array were used to detect signatures of selection in 23 local Italian chicken populations. The populations were categorized into four groups for comparative analysis based on live weight (heavy vs light) and geographical area (Northern vs Southern Italy). Putative signatures of selection were investigated by combining three extended haplotype homozygosity (EHH) statistical approaches to quantify excess of haplotype homozygosity within (iHS) and between (Rsb and XP-EHH) groups. Presence of runs of homozygosity (ROH) islands was also analysed for each group. RESULTS: After editing, 541 animals and 313,508 SNPs were available for statistical analyses. In total, 15 candidate genomic regions that are potentially under selection were detected among the four groups: eight within a group by iHS and seven by combining the results of Rsb and XP-EHH, which revealed divergent selection between the groups. The largest overlap between genomic regions identified to be under selection by the three approaches was on chicken chromosome 8. Twenty-one genomic regions were identified with the ROH approach but none of these overlapped with regions identified with the three EHH-derived statistics. Some of the identified regions under selection contained candidate genes with biological functions related to environmental stress, immune responses, and disease resistance, which indicate local adaptation of these chicken populations. CONCLUSIONS: Compared to commercial lines, local populations are predominantly reared as backyard chickens, and thus, may have developed stronger resistance to environmental challenges. Our results indicate that selection can play an important role in shaping signatures of selection in local chicken populations and can be a starting point to identify gene mutations that could have a useful role with respect to climate change.

Gut Microbiome Associated With Graves Disease and Graves Orbitopathy: The INDIGO Multicenter European Study.

CONTEXT: Gut bacteria can influence host immune responses but little is known about their role in tolerance-loss mechanisms in Graves disease (GD; hyperthyroidism caused by autoantibodies, TRAb, to the thyrotropin receptor, TSHR) and its progression to Graves orbitopathy (GO). OBJECTIVE: This work aimed to compare the fecal microbiota in GD patients, with GO of varying severity, and healthy controls (HCs). METHODS: Patients were recruited from 4 European countries (105 GD patients, 41 HCs) for an observational study with cross-sectional and longitudinal components. RESULTS: At recruitment, when patients were hyperthyroid and TRAb positive, Actinobacteria were significantly increased and Bacteroidetes significantly decreased in GD/GO compared with HCs. The Firmicutes to Bacteroidetes (F:B) ratio was significantly higher in GD/GO than in HCs. Differential abundance of 15 genera was observed in patients, being most skewed in mild GO. Bacteroides displayed positive and negative correlations with TSH and free thyroxine, respectively, and was also significantly associated with smoking in GO; smoking is a risk factor for GO but not GD. Longitudinal analyses revealed that the presence of certain bacteria (Clostridiales) at diagnosis correlated with the persistence of TRAb more than 200 days after commencing antithyroid drug treatment. CONCLUSION: The increased F:B ratio observed in GD/GO mirrors our finding in a murine model comparing TSHR-immunized with control mice. We defined a microbiome signature and identified changes associated with autoimmunity as distinct from those due to hyperthyroidism. Persistence of TRAb is predictive of relapse; identification of these patients at diagnosis, via their microbiome, could improve management with potential to eradicate Clostridiales.

Stacked kinship CNN vs. GBLUP for genomic predictions of additive and complex continuous phenotypes.

Deep learning is impacting many fields of data science with often spectacular results. However, its application to whole-genome predictions in plant and animal science or in human biology has been rather limited, with mostly underwhelming results. While most works focus on exploring alternative network architectures, in this study we propose an innovative representation of marker genotype data and tested it against the GBLUP (Genomic BLUP) benchmark with linear and nonlinear phenotypes. From publicly available cattle SNP genotype data, different types of genomic kinship matrices are stacked together in a 3D pile from where 2D grayscale slices are extracted and fed to a deep convolutional neural network (DNN). We simulated nine phenotype scenarios with combinations of additivity, dominance and epistasis, and compared the DNN to GBLUP-A (computed using only the additive kinship matrix) and GBLUP-optim (additive, dominance, and epistasis kinship matrices, as needed). Results varied depending on the accuracy metric employed, with DNN performing better in terms of root mean squared error (1-12% lower than GBLUP-A; 1-9% lower than GBLUP-optim) but worse in terms of Pearson's correlation (0.505 for DNN compared to 0.672 and 0.669 of GBLUP-A and GBLUP-optim for fully additive case; 0.274 for DNN, 0.279 for GBLUP-A, and 0.477 for GBLUP-optim for fully dominant case). The proposed approach offers a basis to explore further the application of DNN to tabular data in whole-genome predictions.

Relationship between total and differential quarter somatic cell counts at dry-off and early lactation.

Mastitis is a most common disease of dairy cows and causes tremendous economic loss to the dairy industry worldwide. Somatic cell counts (SCC) reflect the inflammatory response to infections and is a metric used as key indicator in mastitis screening programs, typically within the framework of national milk recording schemes. Besides the determination of total SCC, the differentiation of cell types has been described to be beneficial for a more definite description of the actual udder health status of dairy cows. Differential somatic cell count (DSCC) represents the combined proportion of polymorphonuclear leukocytes (PMN) and lymphocytes expressed as a percentage of the total. The aim of this study was to investigate the relationship between SCC and differential somatic cell count (DSCC) in individual quarter milk samples collected at different time points: at dry-off, after calving and at the lactation peak. We used individual quarter data from farms representing the specialized production system of Parmigiano Reggiano cheese in Northern Italy. Average DSCC values ranged between 44.9% and 56.3%, with higher values (60.4%-72.1%) in milk samples with ≥ 1 million SCC/ml (where the proportion of samples with DSCC > 70% can be as high as 0.73). Moderate overall correlations between DSCC and log(SCC) were estimated (Pearson = 0.42, Spearman = 0.38), with a clear increasing trend with parity and around the lactation peak (e.g. Pearson = 0.59 at 60 DIM in parity 4). Taking SCC values as indicators of subclinical mastitis, DSCC would diagnose mastitis with 0.75 accuracy. Data editing criteria do have an impact on results, with stricter filtering leading to lower correlations between log(SCC) and DSCC. In conclusion DSCC and SCC provide different descriptions of the udder health status of dairy cows which, at least to some extent, are independent. DSCC alone doesn't provide more accurate information than SCC at quarter level but, used in combination with SCC, can be of potential interest within the framework of milk recording programs, especially in the context of selective dry-cow therapy (SDCT). However, this needs further investigation and updated threshold values need to be selected and validated.

How Geography and Climate Shaped the Genomic Diversity of Italian Local Cattle and Sheep Breeds.

Understanding the relationships among geography, climate, and genetics is increasingly important for animal farming and breeding. In this study, we examine these inter-relationships in the context of local cattle and sheep breeds distributed along the Italian territory. To this aim, we used redundancy analysis on genomic data from previous projects combined with geographical coordinates and corresponding climatic data. The effect of geographic factors (latitude and longitude) was more important in sheep (26.4%) than that in cattle (13.8%). Once geography had been partialled out of analysis, 10.1% of cattle genomic diversity and 13.3% of that of sheep could be ascribed to climatic effects. Stronger geographic effects in sheep can be related to a combination of higher pre-domestication genetic variability together with biological and productive specificities. Climate alone seems to have had less impact on current genetic diversity in both species, even if climate and geography are greatly confounded. Results confirm that both species are the result of complex evolutionary histories triggered by interactions between human needs and environmental conditions.

Oral ecological environment modifications by hard-cheese: from pH to microbiome: a prospective cohort study based on 16S rRNA metabarcoding approach.

BACKGROUND: The oral ecosystem conditions dental health, and is known to be positively modified by oral hygiene which cannot always be performed between meals, especially outside home. It is therefore important to identify the practices to be adopted to influence the oral environment in an anticariogenic direction. Milk and cheese are considered functional foods and have a role on oral health. There are several mechanisms by which cheese exerts its beneficial effects on teeth. The aim of the present study was to examine whether short term consumption of hard cheese would affect the oral pH and microbial flora of healthy adults modifying ecological oral environment. The Next Generation Sequencing (NGS) approach was applied to study the effect of Italian Grana Padano (GP), as a prototype of typical hard cheese, on the oral microbiota composition. Finally, we explored Streptococcus mutans/sanguinis ratio as a marker of protective biofilm composition. METHODS: Nine oral-healthy adults were instructed to eat 25 gr of GP cheese for 5 consecutive days. Three time points were chosen for supragingival samples collection and pH measurement. 16S rRNA-gene sequences were obtained both from oral samples and GP cheese using the MiSeq platform and analyzed against the expanded Human Oral Microbiome Database (eHOMD). ProgPerm was used to perform statistical analyses to investigate strain differential representation after cheese consumption. RESULTS: Taxonomic analyses of the oral microbiota revealed that Firmicutes was the most abundant phylum, followed by Proteobacteria and Actinobacteria. GP cheese significantly modifies oral pH, causing a shift toward basic conditions which are kept for a few hours. The Streptococcus mutans/Streptococcus sanguinis ratio lowers in the last observed timepoint. CONCLUSION: Our results reveal that a portion of GP cheese eaten after dinner provides important micronutrients (i.e. calcium, vitamins and some aminoacids such as arginine) and changes oral pH toward basic conditions, resulting in a light modification of the oral microbiome towards the reduction of the overall amount of acidophilic bacteria. Furthermore, the S. mutans/S. sanguinis ratio is reduced, contributing to obtain a more protecting environment towards caries establishment and evolution.

Dietary Administration of L-Carnitine During the Fattening Period of Early Feed Restricted Lambs Modifies Ruminal Fermentation but Does Not Improve Feed Efficiency.

Early feed restriction of lambs may program animals to achieve reduced feed efficiency traits as a consequence of permanent mitochondrial dysfunction. The hypothesis at the background of the present study is that dietary administration of L-Carnitine (a compound that promotes the activation and transportation of fatty acids into the mitochondria) during the fattening period of early feed restricted lambs can: (a) improve the biochemical profile of early feed restricted lambs, (b) improve feed efficiency, (c) modulate the ruminal and intestinal microbiota, and (d) induce changes in the gastrointestinal mucosa, including the immune status. Twenty-two newborn male Merino lambs were raised under natural conditions but separated from the dams for 9 h daily to allow feed restriction during the suckling period. At weaning, lambs were assigned to a control group being fed ad libitum a complete pelleted diet during the fattening phase (CTRL, n = 11), whereas the second group (CARN, n = 11) received the same diet supplemented with 3 g of L-Carnitine/kg diet. The results revealed that even though L-Carnitine was absorbed, feed efficiency was not modified by dietary L-Carnitine during the fattening period (residual feed intake, p > 0.05), whereas ruminal fermentation was improved [total short-chain fatty acids (SCFAs), 113 vs. 154 mmol/l; p = 0.036]. Moreover, a trend toward increased concentration of butyrate in the ileal content (0.568 vs. 1.194 mmol/100 ml SCFA; p = 0.074) was observed. Other effects, such as reduced heart weight, lower levels of markers related to muscle metabolism or damage, improved renal function, and increased ureagenesis, were detected in the CARN group. Limited changes in the microbiota were also detected. These findings suggest that L-Carnitine may improve ruminal fermentation parameters and maintain both the balance of gut microbiota and the health of the animals. However, the improved ruminal fermentation and the consequent greater accumulation of intramuscular fat might have hidden the effects caused by the ability of dietary L-Carnitine to increase fatty acid oxidation at the mitochondrial level. This would explain the lack of effects of L-Carnitine supplementation on feed efficiency and points toward the need of testing lower doses, probably in the context of animals being fed in excess non-protein nitrogen.

Integrating heterogeneous across-country data for proxy-based random forest prediction of enteric methane in dairy cattle.

Direct measurements of methane (CH4) from individual animals are difficult and expensive. Predictions based on proxies for CH4 are a viable alternative. Most prediction models are based on multiple linear regressions (MLR) and predictor variables that are not routinely available in commercial farms, such as dry matter intake (DMI) and diet composition. The use of machine learning (ML) algorithms to predict CH4 emissions from across-country heterogeneous data sets has not been reported. The objectives were to compare performances of ML ensemble algorithm random forest (RF) and MLR models in predicting CH4 emissions from proxies in dairy cows, and assess effects of imputing missing data points on prediction accuracy. Data on CH4 emissions and proxies for CH4 from 20 herds were provided by 10 countries. The integrated data set contained 43,519 records from 3,483 cows, with 18.7% missing data points imputed using k-nearest neighbor imputation. Three data sets were created, 3k (no missing records), 21k (missing DMI imputed from milk, fat, protein, body weight), and 41k (missing DMI, milk fat, and protein records imputed). These data sets were used to test scenarios (with or without DMI, imputed vs. nonimputed DMI, milk fat, and protein), and prediction models (RF vs. MLR). Model predictive ability was evaluated within and between herds through 10-fold cross-validation. Prediction accuracy was measured as correlation between observed and predicted CH4, root mean squared error (RMSE) and mean normalized discounted cumulative gain (NDCG). Inclusion of DMI in the model improved within and between-herd prediction accuracy to 0.77 (RMSE = 23.3%) and 0.58 (RMSE = 31.9%) in RF and to 0.50 (RMSE = 0.327) and 0.13 (RMSE = 42.71) in MLR, respectively than when DMI was not included in the predictive model. When missing DMI records were imputed, within and between-herd accuracy increased to 0.84 (RMSE = 18.5%) and 0.63 (RMSE = 29.9%), respectively. In all scenarios, RF models out-performed MLR models. Results suggest routinely measured variables from dairy farms can be used in developing globally robust prediction models for CH4 if coupled with state-of-the-art techniques for imputation and advanced ML algorithms for predictive modeling.

Gut microbiome modifications over time when removing in-feed antibiotics from the prophylaxis of post-weaning diarrhea in piglets.

Post-weaning diarrhea (PWD) in pigs has mainly an infectious basis and control strategies are centred on antibiotics added to the diet. Given concerns on the spread of multi-resistant bacteria, it is necessary to develop alternative prophylactic approaches to control PWD in piglets. The most promising alternative strategies are based on substances that act indirectly on the bacteria by stimulating the immune system or by improving gut health. The aim of this study was to evaluate the effect on the gut microbiota of feed supplemented with a mixture of essential oils (garlic and oregano) in weaning piglets, compared to traditional PWD management (in-feed antibiotics) and to a control group without any diet supplementation. The study involved 197 piglets from 18 litters in a single farm. The piglets were followed from birth to day 58 of age and were weaned at day 26. During the experimental period, the animals were monitored for weight and growth, average daily gain, morbidity and mortality. For the metataxonomics analysis, rectal samples were collected from 17 piglets from the three experimental groups at 4 different time-points (days 1, 12, 26 and 58). Results revealed that the gut microbiota in pre- and post-weaning piglets was dominated by the phyla Firmicutes (51%), Bacteroidetes (25%) and Proteobacteria (16%), which together make up for over 90% of the entire piglet core gut microbiota. The core microbiota comprised 10 taxa before weaning and 43 taxa after weaning, with 7 taxa overlapping between timepoints: two of them (Prevotella 9, p-value = 0.00095; Solobacterium p-value = 0.00821) were significantly more abundant after weaning. All alpha diversity indexes were significantly different between pre- and post-weaning, while only Shannon and Simpson diversity and equitability were significantly different between treatments. Based on the matrix of Bray-Curtis dissimilarities, samples showed clear clustering per timepoint (before and after weaning, p-value < 0.001) and between treatments by timepoint (p-value = 0.0086). The oil-diet group showed a consistently higher F:B ratio at all timepoints. These results show that the pig gut microbiota changes significantly with weaning, and suggest that the use of essential oils as feed supplementation to control PWD does not seem to alter sgnificantly the microbiota nor the growth parameters of piglets, however modifications of specific taxa may occur.

Could Dietary Supplementation with Different Sources of N-3 Polyunsaturated Fatty Acids Modify the Rabbit Gut Microbiota?

The present study evaluated the effects of feed supplemented with two dietary sources of n-3 polyunsaturated fatty acids (PUFAs; fish oil and extruded flaxseed) on the gut microbiota, caecal fermentations, gastrointestinal histology, and histochemistry in rabbits. Fifteen male New Zealand White rabbits were divided into three groups (n = 5/group) and fed with different diets from weaning (35 days of age) until slaughtering (90 days of age): C group, fed with a commercial diet; F group, supplemented with 10% of extruded flaxseed; and O group, supplemented with 3.5% of fish oil. At slaughter, the content of the stomach, duodenum, jejunum, ileum, caecum, and colon was collected and analyzed by Next Generation 16S rRNA gene sequencing. Tissue samples of the same tracts were evaluated with histological and histochemical analysis. Ammonia and lactic acid in the caecum were also quantified. Twenty-nine operational taxonomic units (OTUs) were significantly different between groups. Groups receiving n-3 PUFAs supplementation showed an increase in Bacteroidetes and Lachnospiraceae in several gastrointestinal tracts, while Bacilli abundance, as well as Firmicutes/Bacteroidetes ratio, were reduced compared to the control group (for all p < 0.05). Caecal ammonia was lower in the F than C group (p < 0.032), whereas no difference was found for lactic acid. Finally, histological evaluations revealed a mild hemorrhagic infiltration and vessels ectasia in the stomach mucosa of both F and O groups, but no effect of nutritional treatment was evidenced by the histochemical analyses. In conclusion, n-3 PUFAs supplementation could modify the rabbit gut microbiota and fermentation. The increase in beneficial bacterial populations may, at least partially, explain the positive effects of n-3 PUFAs diet supplementation on human and animals' health, although the appropriate dosage should be established.

Dietary Supplementation with Goji Berries (Lycium barbarum) Modulates the Microbiota of Digestive Tract and Caecal Metabolites in Rabbits.

Goji berries show health benefits, although the possible mechanisms of action, including compositional changes in the gut microbiome, are still not fully understood. The aim of this study was to evaluate the effect of Goji berry supplementation on microbiota composition and metabolites in the digestive tracts of rabbits. Twenty-eight New Zealand White rabbits were fed with a commercial feed (control group, C; n = 14) or the same diet supplemented with 3% of Goji berries (Goji group, G; n = 14), from weaning (35 days old) until slaughter (90 days old). At slaughter, samples from the content of the gastrointestinal tracts were collected and analyzed by Next Generation 16S rRNA Gene Sequencing to evaluate the microbial composition. Ammonia and lactic acid were also quantified in caecum. Results showed differences in microbiota composition between the groups for two phyla (Cyanobacteria and Euryarchaeota), two classes (Methanobacteria and Bacilli), five orders, fourteen families, and forty-five genera. Ruminococcaceae (p < 0.05) and Lachnospiraceae (p < 0.01) were more abundant in G than in C group. Lactobacillaceae also showed differences between the two groups, with Lactobacillus as the predominant genus (p = 0.002). Finally, Goji berry supplementation stimulated lactic acid fermentation (p < 0.05). Thus, Goji berry supplementation could modulate gastrointestinal microbiota composition and caecal fermentation.

Feeding Pre-weaned Calves With Waste Milk Containing Antibiotic Residues Is Related to a Higher Incidence of Diarrhea and Alterations in the Fecal Microbiota.

The cows receiving antibiotics for intra-mammary infection (IMI) produce milk that cannot be marketed. This is considered waste milk (WM), and a convenient option for farmers is using it as calf food. However, adding to the risk of selecting resistant bacteria, residual antibiotics might interfere with the gut microbiome development and influence gastrointestinal health. We assessed the longitudinal effect of unpasteurized WM containing residual cefalexin on calf intestinal health and fecal microbiota in an 8-week trial. After 3 days of colostrum, six calves received WM and six calves received bulk tank milk (BM) for 2 weeks. For the following 6 weeks, all 12 calves received milk substitute and starter feed. Every week for the first 2 weeks and every 2 weeks for the remaining 6 weeks, we subjected all calves to clinical examination and collected rectal swabs for investigating the fecal microbiota composition. Most WM calves had diarrhea episodes in the first 2 weeks of the trial (5/6 WM and 1/6 BM), and their body weight was significantly lower than that of BM calves. Based on 16S rRNA gene analysis, WM calves had a lower fecal microbiota alpha diversity than that in BM calves, with the lowest p-value at Wk4 (p < 0.02), 2 weeks after exposure to WM. The fecal microbiota beta diversity of the two calf groups was also significantly different at Wk4 (p < 0.05). Numerous significant differences were present in the fecal microbiota taxonomy of WM and BM calves in terms of relative normalized operational taxonomic unit (OTU) levels, affecting five phyla, seven classes, eight orders, 19 families, and 47 genera. At the end of the trial, when 6 weeks had passed since exposure to WM, the phyla Bacteroidetes, Firmicutes, and Saccharibacteria were lower, while Chlamydiae were higher in WM calves. Notably, WM calves showed a decrease in beneficial taxa such as Faecalibacterium, with a concomitant increase in potential pathogens such as Campylobacter, Pseudomonas, and Chlamydophila spp. In conclusion, feeding pre-weaned calves with unpasteurized WM containing antibiotics is related to a higher incidence of neonatal diarrhea and leads to significant changes in the fecal microbiota composition, further discouraging this practice in spite of its short-term economic advantages.

Modulating gut microbiota in a mouse model of Graves' orbitopathy and its impact on induced disease.

BACKGROUND: Graves' disease (GD) is an autoimmune condition in which autoantibodies to the thyrotropin receptor (TSHR) cause hyperthyroidism. About 50% of GD patients also have Graves' orbitopathy (GO), an intractable disease in which expansion of the orbital contents causes diplopia, proptosis and even blindness. Murine models of GD/GO, developed in different centres, demonstrated significant variation in gut microbiota composition which correlated with TSHR-induced disease heterogeneity. To investigate whether correlation indicates causation, we modified the gut microbiota to determine whether it has a role in thyroid autoimmunity. Female BALB/c mice were treated with either vancomycin, probiotic bacteria, human fecal material transfer (hFMT) from patients with severe GO or ddH2O from birth to immunization with TSHR-A subunit or beta-galactosidase (ßgal; age ~ 6 weeks). Incidence and severity of GD (TSHR autoantibodies, thyroid histology, thyroxine level) and GO (orbital fat and muscle histology), lymphocyte phenotype, cytokine profile and gut microbiota were analysed at sacrifice (~ 22 weeks). RESULTS: In ddH2O-TSHR mice, 84% had pathological autoantibodies, 67% elevated thyroxine, 77% hyperplastic thyroids and 70% orbital pathology. Firmicutes were increased, and Bacteroidetes reduced relative to ddH2O-ßgal; CCL5 was increased. The random forest algorithm at the genus level predicted vancomycin treatment with 100% accuracy but 74% and 70% for hFMT and probiotic, respectively. Vancomycin significantly reduced gut microbiota richness and diversity compared with all other groups; the incidence and severity of both GD and GO also decreased; reduced orbital pathology correlated positively with Akkermansia spp. whilst IL-4 levels increased. Mice receiving hFMT initially inherited their GO donors' microbiota, and the severity of induced GD increased, as did the orbital brown adipose tissue volume in TSHR mice. Furthermore, genus Bacteroides, which is reduced in GD patients, was significantly increased by vancomycin but reduced in hFMT-treated mice. Probiotic treatment significantly increased CD25+ Treg cells in orbital draining lymph nodes but exacerbated induced autoimmune hyperthyroidism and GO. CONCLUSIONS: These results strongly support a role for the gut microbiota in TSHR-induced disease. Whilst changes to the gut microbiota have a profound effect on quantifiable GD endocrine and immune factors, the impact on GO cellular changes is more nuanced. The findings have translational potential for novel, improved treatments. Video abstract.

Employing a systematic approach to biobanking and analyzing clinical and genetic data for advancing COVID-19 research.

Within the GEN-COVID Multicenter Study, biospecimens from more than 1000 SARS-CoV-2 positive individuals have thus far been collected in the GEN-COVID Biobank (GCB). Sample types include whole blood, plasma, serum, leukocytes, and DNA. The GCB links samples to detailed clinical data available in the GEN-COVID Patient Registry (GCPR). It includes hospitalized patients (74.25%), broken down into intubated, treated by CPAP-biPAP, treated with O2 supplementation, and without respiratory support (9.5%, 18.4%, 31.55% and 14.8, respectively); and non-hospitalized subjects (25.75%), either pauci- or asymptomatic. More than 150 clinical patient-level data fields have been collected and binarized for further statistics according to the organs/systems primarily affected by COVID-19: heart, liver, pancreas, kidney, chemosensors, innate or adaptive immunity, and clotting system. Hierarchical clustering analysis identified five main clinical categories: (1) severe multisystemic failure with either thromboembolic or pancreatic variant; (2) cytokine storm type, either severe with liver involvement or moderate; (3) moderate heart type, either with or without liver damage; (4) moderate multisystemic involvement, either with or without liver damage; (5) mild, either with or without hyposmia. GCB and GCPR are further linked to the GCGDR, which includes data from whole-exome sequencing and high-density SNP genotyping. The data are available for sharing through the Network for Italian Genomes, found within the COVID-19 dedicated section. The study objective is to systematize this comprehensive data collection and begin identifying multi-organ involvement in COVID-19, defining genetic parameters for infection susceptibility within the population, and mapping genetically COVID-19 severity and clinical complexity among patients.

Characterization of Bacterial Microbiota Composition along the Gastrointestinal Tract in Rabbits.

The microbiota is extremely important for the animal's health, but, to date, knowledge on the intestinal microbiota of the rabbit is very limited. This study aimed to describe bacterial populations that inhabit the different gastrointestinal compartments of the rabbit: stomach, duodenum, jejunum, ileum, caecum, and colon. Samples of the luminal content from all compartments of 14 healthy New White Zealand rabbits were collected at slaughter and analyzed using next generation 16S rRNA Gene Sequencing. The findings uncovered considerable differences in the taxonomic levels among the regions of the digestive tract. Firmicutes were the most abundant phylum in all of the sections (45.9%), followed by Bacteroidetes in the large intestine (38.9%) and Euryarchaeota in the foregut (25.9%). Four clusters of bacterial populations were observed along the digestive system: (i) stomach, (ii) duodenum and jejunum, (iii) ileum, and (iv) large intestine. Caecum and colon showed the highest richness and diversity in bacterial species, while the highest variability was found in the upper digestive tract. Knowledge of the physiological microbiota of healthy rabbits could be important for preserving the health and welfare of the host as well as for finding strategies to manipulate the gut microbiota in order to also promote productive performance.