Liver proteomics unravel the metabolic pathways related to feed efficiency in beef cattle

Improving nutrient utilization efficiency is essential for livestock, given the current scenario of increasing demand for animal protein and sustainable resource use. In this context, understanding the biology of feed efficiency (FE) in beef cattle allows the development of markers for identification and selection of best animals for animal production. Thus, 98 young Nellore bulls were evaluated for FE and at the end of the experiment liver samples from six High Feed Efficient (HFE) and six Low Feed Efficient (LFE) animals were collected for protein extraction, digestion and analysis by HPLC-MS/MS. Data were analyzed for differential abundant proteins (DAPs), protein networks, and functional enrichment. Serum endotoxin was also quantified. We found 42 DAPs and 3 protein networks significantly related to FE. The main pathways associated with FE were: microbial metabolism; biosynthesis of fatty acids, amino acids and vitamins; glycolysis/gluconeogenesis; xenobiotic metabolism and; antigen processing and presentation. Serum endotoxins were significantly higher in LFE animals supporting the results. Therefore, the findings presented here confirmed the altered hepatic metabolism and pronounced hepatic inflammation in LFE animals supporting that the increased bacterial load is at least in part responsible for the hepatic lesions and inflammation in LFE animals9COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPESFUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESPsem informação[2014/12492-8; 2014/07566-2; 2014/02493-7; 2014/04937-

A gene co-association network regulating gut microbial communities in a Duroc pig population

Background: Analyses of gut microbiome composition in livestock species have shown its potential to contribute to the regulation of complex phenotypes. However, little is known about the host genetic control over the gut microbial communities. In pigs, previous studies are based on classical "single-gene-single-trait" approaches and have evaluated the role of host genome controlling gut prokaryote and eukaryote communities separately. Results: In order to determine the ability of the host genome to control the diversity and composition of microbial communities in healthy pigs, we undertook genome-wide association studies (GWAS) for 39 microbial phenotypes that included 2 diversity indexes, and the relative abundance of 31 bacterial and six commensal protist genera in 390 pigs genotyped for 70 K SNPs. The GWAS results were processed through a 3-step analytical pipeline comprised of (1) association weight matrix; (2) regulatory impact factor; and (3) partial correlation and information theory. The inferred gene regulatory network comprised 3561 genes (within a 5 kb distance from a relevant SNP-P < 0.05) and 738,913 connections (SNP-to-SNP co-associations). Our findings highlight the complexity and polygenic nature of the pig gut microbial ecosystem. Prominent within the network were 5 regulators, PRDM15, STAT1, ssc-mir-371, SOX9 and RUNX2 which gathered 942, 607, 588, 284 and 273 connections, respectively. PRDM15 modulates the transcription of upstream regulators of WNT and MAPK-ERK signaling to safeguard naive pluripotency and regulates the production of Th1- and Th2-type immune response. The signal transducer STAT1 has long been associated with immune processes and was recently identified as a potential regulator of vaccine response to porcine reproductive and respiratory syndrome. The list of regulators was enriched for immune-related pathways, and the list of predicted targets includes candidate genes previously reported as associated with microbiota profile in pigs, mice and human, such as SLIT3, SLC39A8, NOS1, IL1R2, DAB1, TOX3, SPP1, THSD7B, ELF2, PIANP, A2ML1, and IFNAR1. Moreover, we show the existence of host-genetic variants jointly associated with the relative abundance of butyrate producer bacteria and host performance

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

ANKK1, TTC12, and NCAM1 polymorphisms and heroin dependence: importance of considering drug exposure

Context: The genetic contribution to liability for opioid dependence is well established; identification of the responsible genes has proved challenging. Objective: To examine association of 1430 candidate gene single-nucleotide polymorphisms (SNPs)with heroin dependence, reporting here only the 71 SNPs in the chromosome 11 gene cluster (NCAM1, TTC12, ANKK1, DRD2) that include the strongest observed associations. Design: Case-control genetic association study that included 2 control groups (lacking an established optimal control group). Setting: Semistructured psychiatric interviews. Participants: A total of 1459 Australian cases ascertained from opioid replacement therapy clinics, 531 neighborhood controls ascertained from economically disadvantaged areas near opioid replacement therapy clinics, and 1495 unrelated Australian Twin Registry controls not dependent on alcohol or illicit drugs selected from a twin and family sample. Main Outcome Measure: Lifetime heroin dependence. Results: Comparison of cases with Australian Twin Registry controls found minimal evidence of association for all chromosome 11 cluster SNPs (P≥.01); a similar comparison with neighborhood controls revealed greater differences (P≥1.8×10-4). Comparing cases (n=1459) with the subgroup of neighborhood controls not dependent on illicit drugs (n=340), 3 SNPs were significantly associated (correcting for multiple testing): ANKK1 SNP rs877138 (most strongly associated; odds ratio=1.59; 95% CI, 1.32-1.92; P=9.7×10-7), ANKK1 SNP rs4938013, and TTC12 SNP rs7130431. A similar pattern of association was observed when comparing illicit drug-dependent (n=191) and nondependent (n=340) neighborhood controls, suggesting that liability likely extends to nonopioid illicit drug dependence. Aggregate heroin dependence risk associated with 2 SNPs, rs877138 and rs4492854 (located in NCAM1), varied more than 4-fold (P=2.7×10-9 for the risk-associated linear trend). Conclusions: Our results provide further evidence of association for chromosome 11 gene cluster SNPs with substance dependence, including extension of liability to illicit drug dependence. Our findings highlight the necessity of considering drug exposure history when selecting control groups for genetic investigations of illicit drug dependence

The variance shared across forms of childhood trauma is strongly associated with liability for psychiatric and substance use disorders

Introduction: Forms of childhood trauma tend to co-occur and are associated with increased risk for psychiatric and substance use disorders. Commonly used binary measures of trauma exposure have substantial limitations. Methods: We performed multigroup confirmatory factor analysis (CFA), separately by sex, using data from the Childhood Trauma (CT) Study's sample of twins and siblings (N = 2594) to derive three first-order factors (childhood physical abuse, childhood sexual abuse, and parental partner abuse) and, as hypothesized, one higher order, childhood trauma factor (CTF) representing a measure of their common variance. Results: CFA produced a good-fitting model in the CT Study; we replicated the model in the Comorbidity and Trauma (CAT) Study's sample (N = 1981) of opioid-dependent cases and controls. In both samples, first-order factors are moderately correlated (indicating they measure largely unique, but related constructs) and their loadings on the CTF suggest it provides a reasonable measure of their common variance. We examined the association of CTF score with risk for psychiatric and substance use disorders in these samples and the OZ-ALC GWAS sample (N = 1538) in which CT Study factor loadings were applied. We found that CTF scores are strongly associated with liability for psychiatric and substance use disorders in all three samples; estimates of risk are extremely consistent across samples. Conclusions: The CTF is a continuous, robust measure that captures the common variance across forms of childhood trauma and provides a means to estimate shared liability while avoiding multicollinearity. Confirmatory factor analysis was used to derive a higher order, childhood trauma factor representing a measure of the common variance across three forms of trauma: childhood physical abuse, childhood sexual abuse, and parental partner abuse. We replicated the model in a second sample. We then examined the association of childhood trauma score with risk for psychiatric and substance use disorders in these samples and a third sample in which the primary sample's factor loadings were applied finding factor scores to be strongly and consistently associated with liability for psychiatric and substance use disorders in all three samples