On the holobiont 'predictome' of immunocompetence in pigs

Gut microbial composition plays an important role in numerous traits, including immune response. Integration of host genomic information with microbiome data is a natural step in the prediction of complex traits, although methods to optimize this are still largely unexplored. In this paper, we assess the impact of different modelling strategies on the predictive capacity for six porcine immunocompetence traits when both genotype and microbiota data are available. We used phenotypic data on six immunity traits and the relative abundance of gut bacterial communities on 400 Duroc pigs that were genotyped for 70 k SNPs. We compared the predictive accuracy, defined as the correlation between predicted and observed phenotypes, of a wide catalogue of models: reproducing kernel Hilbert space (RKHS), Bayes C, and an ensemble method, using a range of priors and microbial clustering strategies. Combined (holobiont) models that include both genotype and microbiome data were compared with partial models that use one source of variation only. Overall, holobiont models performed better than partial models. Host genotype was especially relevant for predicting adaptive immunity traits (i.e., concentration of immunoglobulins M and G), whereas microbial composition was important for predicting innate immunity traits (i.e., concentration of haptoglobin and C-reactive protein and lymphocyte phagocytic capacity). None of the models was uniformly best across all traits. We observed a greater variability in predictive accuracies across models when microbiability (the variance explained by the microbiome) was high. Clustering microbial abundances did not necessarily increase predictive accuracy. Gut microbiota information is useful for predicting immunocompetence traits, especially those related to innate immunity. Modelling microbiome abundances deserves special attention when microbiability is high. Clustering microbial data for prediction is not recommended by default. The online version contains supplementary material available at 10.1186/s12711-023-00803-4

On the holobiont ‘predictome’ of immunocompetence in pigs

Background Gut microbial composition plays an important role in numerous traits, including immune response. Integration of host genomic information with microbiome data is a natural step in the prediction of complex traits, although methods to optimize this are still largely unexplored. In this paper, we assess the impact of different modelling strategies on the predictive capacity for six porcine immunocompetence traits when both genotype and microbiota data are available. Methods We used phenotypic data on six immunity traits and the relative abundance of gut bacterial communities on 400 Duroc pigs that were genotyped for 70 k SNPs. We compared the predictive accuracy, defined as the correlation between predicted and observed phenotypes, of a wide catalogue of models: reproducing kernel Hilbert space (RKHS), Bayes C, and an ensemble method, using a range of priors and microbial clustering strategies. Combined (holobiont) models that include both genotype and microbiome data were compared with partial models that use one source of variation only. Results Overall, holobiont models performed better than partial models. Host genotype was especially relevant for predicting adaptive immunity traits (i.e., concentration of immunoglobulins M and G), whereas microbial composition was important for predicting innate immunity traits (i.e., concentration of haptoglobin and C-reactive protein and lymphocyte phagocytic capacity). None of the models was uniformly best across all traits. We observed a greater variability in predictive accuracies across models when microbiability (the variance explained by the microbiome) was high. Clustering microbial abundances did not necessarily increase predictive accuracy. Conclusions Gut microbiota information is useful for predicting immunocompetence traits, especially those related to innate immunity. Modelling microbiome abundances deserves special attention when microbiability is high. Clustering microbial data for prediction is not recommended by default.info:eu-repo/semantics/publishedVersio

Gut eukaryotic communities in pigs : diversity, composition and host genetics contribution

Background. The pig gut microbiome harbors thousands of species of archaea, bacteria, viruses and eukaryotes such as protists and fungi. However, since the majority of published studies have been focused on prokaryotes, little is known about the diversity, host-genetic control, and contributions to host performance of the gut eukaryotic counterparts. Here we report the first study that aims at characterizing the diversity and composition of gut commensal eukaryotes in pigs, exploring their putative control by host genetics, and analyzing their association with piglets body weight. Results. Fungi and protists from the faeces of 514 healthy Duroc pigs of two sexes and two different ages were characterized by 18S and ITS ribosomal RNA gene sequencing. The pig gut mycobiota was dominated by yeasts, with a high prevalence and abundance of Kazachstania spp. Regarding protists, representatives of four genera (Blastocystis, Neobalantidium, Tetratrichomonas and Trichomitus) were predominant in more than the 80% of the pigs. Heritabilities for the diversity and abundance of gut eukaryotic communities were estimated with the subset of 60d aged piglets (N = 390). The heritabilities of α-diversity and of the abundance of fungal and protists genera were low, ranging from 0.15 to 0.28. A genome wide association study reported genetic variants related to the fungal α-diversity and to the abundance of Blastocystis spp. Annotated candidate genes were mainly associated with immunity, gut homeostasis and metabolic processes. Additionally, we explored the association of gut commensal eukaryotes with piglet body weight. Our results pointed to a positive contribution of fungi from the Kazachstania genus, while protists displayed both positive (Blastocystis and Entamoeba) and negative (Trichomitus) associations with piglet body weight. Conclusions. Our results point towards a minor and taxa specific genetic control over the diversity and composition of the pig gut eukaryotic communities. Moreover, we provide evidences of the associations between piglets' body weight after weaning and members from the gut fungal and protist eukaryote community. Overall, this study highlights the relevance of considering, along with that of bacteria, the contribution of the gut eukaryote communities to better understand host-microbiome association and their role on pig performance, welfare and health

Humanising Higher Education as a tool to enrich society: challenges and opportunities’

Humanising higher education through a multi angle approach can be transformational for students and staff, can inspire learning, advance knowledge, and enrich society. During this thematic forum we will introduce our approach to embedding a culture of kindness, a positive mindset and a caring approach, all areas included as part of our university's implementation plan as a route to humanise our practice. We will begin by exploring the notion of humanising which according to Galvin and Todres (2013, p. 10/11) is to “uphold a particular view or value of what it means to be human, and furthermore to find ways to act on this concern. Such concern also needs to be practically translated into the more experiential issues of what practices can make people feel more human”. Traditionally humanising practice has been explored within health and social care, we felt that its essence and the humanising framework developed by Todres at al. (2009) could be applied within the context of higher education. Todres et al. (2009), explain that there are two main foundations to base the strategies to humanise practice. The first one is that the vocabulary used must be simple and continuously focus on humanising issues. The second one is to make sure that this humanising focus is championed at all levels of an organisation. Within the higher education environment, these encompass the language, values, attitudes, and behaviours that can be shared, and role modelled within every level of the organisation. We will relate it to our own experiences in various roles within the university and how taking on a humanising approach has shaped the way in which we practice (Devis-Rozental and Clarke 2020). Looking at humanising from a positive organisational culture point of view, we will then explore some of the challenges we have faced as culture leaders introducing this new way of being. We will then discuss the ways in which we have overcome these challenges and reflect on our experiences. We will draw on our previous work to present the research evidenced practice we are embedding and how this has already influenced some of our university wide responses. During the thematic forum we will then foster dialogue and interaction by posing to the audience the following themes which have informed our work on humanising higher education: • We are much more than a font of knowledge, our role as educators to inspire learning • Disrupting the them and us culture prevalent in some higher education institutions when referring to academics and professional members of staff • Values based practice as a tool to humanise environments, it is all about our people • Embedding socio-emotional intelligence in the curriculum to enhance the student experience (Devis-Rozental 2018) • Applying an appreciative inquiry lens to improve our practice • Working collaboratively through embedding ubuntu as a philosophy of working to strengthen the heart of our teams • Practicing with our head, hand and heart to deliver excellence in higher education • Leading with kindness to develop a sense of belonging • Spotlighting out relational energy to embed a positive organisational culture • Positive educational strategies to inspire learning in higher education • Creating working environment where individuals feel are able to bring their unique selves and find their purpose to enrich society • The place of passion in higher education as an engine for positive chang

Leveraging host-genetics and gut microbiota to determine immunocompetence in pigs

The gut microbiota influences host performance playing a relevant role in homeostasis and function of the immune system. The aim of the present work was to identify microbial signatures linked to immunity traits and to characterize the contribution of host-genome and gut microbiota to the immunocompetence in healthy pigs. To achieve this goal, we undertook a combination of network, mixed model and microbial-wide association studies (MWAS) for 21 immunity traits and the relative abundance of gut bacterial communities in 389 pigs genotyped for 70K SNPs. The heritability (h 2 ; proportion of phenotypic variance explained by the host genetics) and microbiability (m 2 ; proportion of variance explained by the microbial composition) showed similar values for most of the analyzed immunity traits, except for both IgM and IgG in plasma that was dominated by the host genetics, and the haptoglobin in serum which was the trait with larger m 2 (0.275) compared to h 2 (0.138). Results from the MWAS suggested a polymicrobial nature of the immunocompetence in pigs and revealed associations between pigs gut microbiota composition and 15 of the analyzed traits. The lymphocytes phagocytic capacity (quantified as mean fluorescence) and the total number of monocytes in blood were the traits associated with the largest number of taxa (6 taxa). Among the associations identified by MWAS, 30% were confirmed by an information theory network approach. The strongest confirmed associations were between Fibrobacter and phagocytic capacity of lymphocytes (r = 0.37), followed by correlations between Streptococcus and the percentage of phagocytic lymphocytes (r = -0.34) and between Megasphaera and serum concentration of haptoglobin (r = 0.26). In the interaction network, Streptococcus and percentage of phagocytic lymphocytes were the keystone bacterial and immune-trait, respectively. Overall, our findings reveal an important connection between gut microbiota composition and immunity traits in pigs, and highlight the need to consider both sources of information, host genome and microbial levels, to accurately characterize immunocompetence in pigs. The online version contains supplementary material available at 10.1186/s42523-021-00138-9

Implementazione di uno strumento multidimensionale per la valutazione del dolore nel processo di triage globale: uno studio pilota

INTRODUZIONE: Nel triage è fondamentale la rilevazione del dolore come previsto dalle linee di indirizzo e dalla Raccomandazione Ministeriale  15 che specifica la necessità dell’utilizzo di una metodologia di valutazione che permetta la corretta attribuzione del codice di triage senza sovra/sottostime mantenendo qualità e sicurezza, anche attraverso la corretta valutazione del dolore. Nel metodo Manchester Triage System (MTS), per determinare il codice di priorità, viene utilizzata la Manchester Pain Ruler Scale (MPRS), strumento multidimensionale validato anche in italiano per pazienti adulti e pediatrici. MATERIALI E METODI: Studio di coorte prospettico di maggiorenni acceduti al PS presentando come sintomo principale il dolore con elevata stabilità delle funzioni vitali di base. RISULTATI: Sulla totalità dei casi, MPRS è più sensibile nella valutazione del dolore nel processo di triage globale, infatti nel 40% dei casi (42/104) tale score si è rivelato un punteggio congruente al trattamento. NRS è risultata classificare in maniera adeguata nel 10% dei casi (11/104). Inoltre MPRS appare più specifica per il dolore di primo e terzo livello. L’utilizzo di MPRS permette di osservare una riduzione del under/over triage rispetto ad NRS.  CONCLUSIONI: Da questo studio sono emersi nuovi quesiti riguardanti la valutazione del dolore in fase di triage, ma anche dati che ritengono MPRS più sensibile e specifica rispetto a NRS nonostante l’utilizzo di un modello di triage globale differente da MTS. Inoltre MPRS descrive in maniera più accurata il dolore in triage rispetto ad alcune fasce di età esesso, riducendo l’over/under triage.INTRODUCTION: In the triage, the detection of pain is fundamental as required by the guidelines and Ministerial Recommendation 15, which specifies the need for the use of an assessment methodology that allows the correct assignment of the triage code without over/underestimation while maintaining quality and safety, including through the correct assessment of pain. In the Manchester Triage System (MTS) method, the Manchester Pain Ruler Scale (MPRS), a multidimensional instrument also validated in Italian for adult and pediatric patients, is used to determine the priority code. MATERIALS AND METHODS: Prospective cohort study of adult adults who accessed the PS presenting pain as their main symptom with high stability of basic vital functions. RESULTS: On the totality of cases, MPRS is more sensitive in assessing pain in the overall triage process; in fact, in 40% of cases (42/104), this score was congruent with treatment. NRS was found to rank adequately in 10% of cases (11/104). In addition, MPRS appears to be more specific for first- and third-level pain. MPRS allows us to observe a reduction in under/over triage compared with NRS. CONCLUSIONS: New questions regarding the assessment of pain in triage emerged from this study. However, data found MPRS more sensitive and specific than NRS despite using a different global triage model than MTS. In addition, MPRS more accurately describes pain in triage concerning certain age groups and gender, reducing over/under triage

In vivo cisplatin-resistant neuroblastoma metastatic model reveals tumour necrosis factor receptor superfamily member 4 (TNFRSF4) as an independent prognostic factor of survival in neuroblastoma

Neuroblastoma is the most common solid extracranial tumour in children. Despite major advances in available therapies, children with drug-resistant and/or recurrent neuroblastoma have a dismal outlook with 5-year survival rates of less than 20%. Therefore, tackling relapsed tumour biology by developing and characterising clinically relevant models is a priority in finding targetable vulnerability in neuroblastoma. Using matched cisplatin-sensitive KellyLuc and resistant KellyCis83Luc cell lines, we developed a cisplatin-resistant metastatic MYCN-amplified neuroblastoma model. The average number of metastases per mouse was significantly higher in the KellyCis83Luc group than in the KellyLuc group. The vast majority of sites were confirmed as having lymph node metastasis. Their stiffness characteristics of lymph node metastasis values were within the range reported for the patient samples. Targeted transcriptomic profiling of immuno-oncology genes identified tumour necrosis factor receptor superfamily member 4 (TNFRSF4) as a significantly dysregulated MYCN-independent gene. Importantly, differential TNFRSF4 expression was identified in tumour cells rather than lymphocytes. Low TNFRSF4 expression correlated with poor prognostic indicators in neuroblastoma, such as age at diagnosis, stage, and risk stratification and significantly associated with reduced probability of both event-free and overall survival in neuroblastoma. Therefore, TNFRSF4 Low expression is an independent prognostic factor of survival in neuroblastoma

The Role of activated leukocyte cell adhesion molecule (ALCAM) in endometrial cancer progression and dissemination /

Premi Extraordinari de Doctorat concedit pels programes de doctorat de la UAB per curs acadèmic 2016-201