Influence of body lesion severity on oxidative status and gut microbiota of weaned pigs.

Body lesions in pigs are a common welfare concern, particularly during the weaning period. These lesions can lead to pain, infection, and impaired mobility, resulting in reduced growth performance and increased mortality. Moreover, weaning stress can affect gut microbiota, immune response and increase the oxidative stress of piglets during this transition period. It has been hypothesised that social stress and body lesions could contribute to affect the gut microbiota, physiological and immune response of piglets. The study aims to evaluate the impact of the body lesions due to social stress on microbial profile, immune response, and oxidative status of weaned piglets. Lesion score (LS) on skin, tail, ear, neck, middle trunk, and hind quarters was measured 1 week (28 days of age, T1) and 7 weeks postweaning (T2) on 45 tail-docked pigs according to the method suggested from the Walfer Quality® (2009) on a scale from 0 to 2. Based on the LS, at T1, piglets were classified as High LS (n = 16), when LS was >1 in at least two of the areas considered, or Low LS (n = 29). At T2, based on the same scoring system and to the LS observed at T1, piglets were divided into four groups: High to Low LS (H-L, n = 11), High to High LS (H-H, n = 5), Low to Low LS (L-L, n = 21) and Low to High LS (L-H, n = 8). Blood and faecal samples were collected at T1 and T2. At T1, pigs with a high LS had a lower biological antioxidant potential compared with the L group (P < 0.02). At T2, the L-H group had a lower Reactive Oxygen Metabolites concentration compared with the H-H group (P = 0.03) while the L-L group had a lower concentration of Immunoglobulin A compared with H-H and L-H groups (P = 0.02 and P = 0.04, respectively). At T1, piglets with high LS had a different microbiota compared to piglets with low LS (R2 = 0.04, P < 0.01). Low LS pigs were characterised by a higher abundance of Firmicutes, Blautia, Eubacterium coprostanoligenes, Faecalibacterium, Megasphaera, Subdoligranulum (P.adj < 0.05), while pigs with high LS were characterised by higher abundance of Bacteroidota, Rikenellaceae RC9, Prevotellaceae UCG-003, uncultured-Lachnospiraceae and uncultured-Oscillospiraceae (P.adj < 0.05). At T2, the H-H group were characterised by Oscillospirales-UCG-010, H-L by Agatobachter and L-L by Alloprevotella (P.adj < 0.05). Overall, this study provides valuable insights into the relationship between body lesions, oxidative stress, and gut microbiota in weaned pigs.

Searching for signatures of cold adaptations in modern and archaic humans: hints from the brown adipose tissue genes.

Adaptation to low temperatures has been reasonably developed in the human species during the colonization of the Eurasian landmass subsequent to Out of Africa migrations of anatomically modern humans. In addition to morphological and cultural changes, also metabolic ones are supposed to have favored human isolation from cold and body heat production and this can be hypothesized also for most Neandertal and at least for some Denisovan populations, which lived in geographical areas that strongly experienced the last glacial period. Modulation of non-shivering thermogenesis, for which adipocytes belonging to the brown adipose tissue are the most specialized cells, might have driven these metabolic adaptations. To perform an exploratory analysis aimed at looking into this hypothesis, variation at 28 genes involved in such functional pathway was investigated in modern populations from different climate zones, as well as in Neandertal and Denisovan genomes. Patterns of variation at the LEPR gene, strongly related to increased heat dissipation by mitochondria, appeared to have been shaped by positive selection in modern East Asians, but not in Europeans. Moreover, a single potentially cold-adapted LEPR allele, different from the supposed adaptive one identified in Homo sapiens, was found also in Neandertal and Denisovan genomes. These findings suggest that independent mechanisms for cold adaptations might have been developed in different non-African human groups, as well as that the evolution of possible enhanced thermal efficiency in Neandertals and in some Denisovan populations has plausibly entailed significant changes also in other functional pathways than in the examined one.

High-throughput SNP discovery in the rabbit (Oryctolagus cuniculus) genome by next-generation semiconductor-based sequencing.

The European rabbit (Oryctolagus cuniculus) is a domesticated species with one of the broadest ranges of economic and scientific applications and fields of investigation. Rabbit genome information and assembly are available (oryCun2.0), but so far few studies have investigated its variability, and massive discovery of polymorphisms has not been published yet for this species. Here, we sequenced two reduced representation libraries (RRLs) to identify single nucleotide polymorphisms (SNPs) in the rabbit genome. Genomic DNA of 10 rabbits belonging to different breeds was pooled and digested with two restriction enzymes (HaeIII and RsaI) to create two RRLs which were sequenced using the Ion Torrent Personal Genome Machine. The two RRLs produced 2 917 879 and 4 046 871 reads, for a total of 280.51 Mb (248.49 Mb with quality >20) and 417.28 Mb (360.89 Mb with quality >20) respectively of sequenced DNA. About 90% and 91% respectively of the obtained reads were mapped on the rabbit genome, covering a total of 15.82% of the oryCun2.0 genome version. The mapping and ad hoc filtering procedures allowed to reliably call 62 491 SNPs. SNPs in a few genomic regions were validated by Sanger sequencing. The Variant Effect Predictor Web tool was used to map SNPs on the current version of the rabbit genome. The obtained results will be useful for many applied and basic research programs for this species and will contribute to the development of cost-effective solutions for high-throughput SNP genotyping in the rabbit.

Exploring copy number variation in the rabbit (Oryctolagus cuniculus) genome by array comparative genome hybridization.

The European rabbit (Oryctolagus cuniculus) is relevant in a large spectrum of fields: it is a livestock, a pet, a biomedical model and a biotechnology tool, a wild resource and a pest. The sequencing of the rabbit genome has opened new perspectives to study this lagomorph at the genome level. We herein investigated for the first time the O. cuniculus genome by array comparative genome hybridization (aCGH) and established a first copy number variation (CNV) genome map in this species comprising 155 copy number variation regions (CNVRs; 95 gains, 59 losses, 1 with both gain and loss) covering ~0.3% of the OryCun2.0 version. About 50% of the 155 CNVRs identified spanned 139 different protein coding genes, 110 genes of which were annotated or partially annotated (including Major Histocompatibility Complex genes) with 277 different gene ontology terms. Many rabbit CNVRs might have a functional relevance that should be further investigated.

Identification and association analysis of several hundred single nucleotide polymorphisms within candidate genes for back fat thickness in Italian Large White pigs using a selective genotyping approach.

Combining different approaches (resequencing of portions of 54 obesity candidate genes, literature mining for pig markers associated with fat deposition or related traits in 77 genes, and in silico mining of porcine expressed sequence tags and other sequences available in databases), we identified and analyzed 736 SNP within candidate genes to identify markers associated with back fat thickness (BFT) in Italian Large White sows. Animals were chosen using a selective genotyping approach according to their EBV for BFT (276 with most negative and 279 with most positive EBV) within a population of ≈ 12,000 pigs. Association analysis between the SNP and BFT has been carried out using the MAX test proposed for case-control studies. The designed assays were successful for 656 SNP: 370 were excluded (low call rate or minor allele frequency <5%), whereas the remaining 286 in 212 genes were taken for subsequent analyses, among which 64 showed a P(nominal) value <0.1. To deal with the multiple testing problem in a candidate gene approach, we applied the proportion of false positives (PFP) method. Thirty-eight SNP were significant (P(PFP) < 0.20). The most significant SNP was the IGF2 intron3-g.3072G>A polymorphism (P(nominal) < 1.0E-50). The second most significant SNP was the MC4R c.1426A>G polymorphism (P(nominal) = 8.0E-05). The third top SNP (P(nominal) = 6.2E-04) was the intronic TBC1D1 g.219G>A polymorphic site, in agreement with our previous results obtained in an independent study. The list of significant markers also included SNP in additional genes (ABHD16A, ABHD5, ACP2, ALMS1, APOA2, ATP1A2, CALR, COL14A1, CTSF, DARS, DECR1, ENPP1, ESR1, GH1, GHRL, GNMT, IKBKB, JAK3, MTTP, NFKBIA, NT5E, PLAT, PPARG, PPP2R5D, PRLR, RRAGD, RFC2, SDHD, SERPINF1, UBE2H, VCAM1, and WAT). Functional relationships between genes were obtained using the Ingenuity Pathway Analysis (IPA) Knowledge Base. The top scoring pathway included 19 genes with a P(nominal) < 0.1, 2 of which (IKBKB and NFKBIA) are involved in the hypothalamic IKKß/NFκB program that could represent a key axis to affect fat deposition traits in pigs. These results represent a starting point to plan marker-assisted selection in Italian Large White nuclei for BFT. Because of similarities between humans and pigs, this study might also provide useful clues to investigate genetic factors affecting human obesity.

A first comparative map of copy number variations in the sheep genome.

We carried out a cross species cattle-sheep array comparative genome hybridization experiment to identify copy number variations (CNVs) in the sheep genome analysing ewes of Italian dairy or dual-purpose breeds (Bagnolese, Comisana, Laticauda, Massese, Sarda, and Valle del Belice) using a tiling oligonucleotide array with ~385,000 probes designed on the bovine genome. We identified 135 CNV regions (CNVRs; 24 reported in more than one animal) covering ~10.5 Mb of the virtual sheep genome referred to the bovine genome (0.398%) with a mean and a median equal to 77.6 and 55.9 kb, respectively. A comparative analysis between the identified sheep CNVRs and those reported in cattle and goat genomes indicated that overlaps between sheep and both other species CNVRs are highly significant (P<0.0001), suggesting that several chromosome regions might contain recurrent interspecies CNVRs. Many sheep CNVRs include genes with important biological functions. Further studies are needed to evaluate their functional relevance.

The prediction of protein-protein interacting sites in genome-wide protein interaction networks: the test case of the human cell cycle.

In this paper we aim at investigating possible correlations between the number of putative interaction patches of a given protein, as inferred by an algorithm that we have developed, and its degree (number of edges of the protein node in a protein interaction network). We focus on the human cell cycle that, as compared with other biological processes, comprises the largest number of proteins whose structure is known at atomic resolution both as monomers and as interacting complexes. For predicting interaction patches we specifically develop a HM-SVM based method reaching 71% overall accuracy with a correlation coefficient value equal to 0.43 on a non redundant set of protein complexes. To test the biological meaning of our predictions, we also explore whether interacting patches contain energetically important residues and/or disease related mutations and find that predicted patches are endowed with both features. Based on this, we propose that mapping the protein with all the predicted interaction patches bridges the molecule to the interactome at the cell level. To test our hypothesis we downloaded interaction data from interaction data bases and find that the number of predicted interaction patches significantly correlates (Pearson correlation value >0.3) with the number of the known interactions (edges) per protein in the human interactome, as contained in MINT and IntAct. We also show that the correlation increases (Pearson correlation value >0.5) when the subcellular co-localization and the co-expression levels of the interacting partners are taken into account.

Molecular mechanism of thioredoxin regulation in photosynthetic A2B2-glyceraldehyde-3-phosphate dehydrogenase.

Chloroplast glyceraldehyde-3-phosphate dehydrogenase (GAPDH) is a light-regulated, NAD(P)H-dependent enzyme involved in plant photosynthetic carbon reduction. Unlike lower photosynthetic organisms, which only contain A(4)-GAPDH, the major GAPDH isoform of land plants is made up of A and B subunits, the latter containing a C-terminal extension (CTE) with fundamental regulatory functions. Light-activation of AB-GAPDH depends on the redox state of a pair of cysteines of the CTE, which can form a disulfide bond under control of thioredoxin f, leading to specific inhibition of the NADPH-dependent activity. The tridimensional structure of A(2)B(2)-GAPDH from spinach chloroplasts, crystallized in the oxidized state, shows that each disulfide-containing CTE is docked into a deep cleft between a pair of A and B subunits. The structure of the CTE was derived from crystallographic data and computational modeling and confirmed by site-specific mutagenesis. Structural analysis of oxidized A(2)B(2)-GAPDH and chimeric mutant [A+CTE](4)-GAPDH revealed that Arg-77, which is essential for coenzyme specificity and high NADPH-dependent activity, fails to interact with NADP in these kinetically inhibited GAPDH tetramers and is attracted instead by negative residues of oxidized CTE. Other subtle changes in catalytic domains and overall conformation of the tetramers were noticed in oxidized A(2)B(2)-GAPDH and [A+CTE](4)-GAPDH, compared with fully active A(4)-GAPDH. The CTE is envisioned as a redox-sensitive regulatory domain that can force AB-GAPDH into a kinetically inhibited conformation under oxidizing conditions, which also occur during dark inactivation of the enzyme in vivo.

Prediction of the transmembrane regions of beta-barrel membrane proteins with a neural network-based predictor.

A method based on neural networks is trained and tested on a nonredundant set of beta-barrel membrane proteins known at atomic resolution with a jackknife procedure. The method predicts the topography of transmembrane beta strands with residue accuracy as high as 78% when evolutionary information is used as input to the network. Of the transmembrane beta-strands included in the training set, 93% are correctly assigned. The predictor includes an algorithm of model optimization, based on dynamic programming, that correctly models eight out of the 11 proteins present in the training/testing set. In addition, protein topology is assigned on the basis of the location of the longest loops in the models. We propose this as a general method to fill the gap of the prediction of beta-barrel membrane proteins.

Tryptophanyl fluorescence lifetime distribution of hyperthermophilic beta-glycosidase from molecular dynamics simulation: a comparison with the experimental data.

A molecular dynamics simulation approach has been utilized to understand the unusual fluorescence emission decay observed for beta-glycosidase from the hyperthermophilic bacterium Solfolobus sulfotaricus (Sbeta gly), a tetrameric enzyme containing 17 tryptophanyl residues for each subunit. The tryptophanyl emission decay of Sbeta gly results from a bimodal distribution of fluorescence lifetimes with a short-lived component centered at 2.5 ns and a long-lived one at 7.4 ns (Bismuto E, Nucci R, Rossi M, Irace G, 1999, Proteins 27:71-79). From the examination of the trajectories of the side chains capable of causing intramolecular quenching for each tryptophan microenvironment and using a modified Stern-Volmer model for the emission quenching processes, we calculated the fluorescence lifetime for each tryptophanyl residue of Sbeta gly at two different temperatures, i.e., 300 and 365 K. The highest temperature was chosen because in this condition Sbeta gly evidences a maximum in its catalytic activity and is stable for a very long time. The calculated lifetime distributions overlap those experimentally determined. Moreover, the majority of trytptophanyl residues having longer lifetimes correspond to those originally identified by inspection of the crystallographic structure. The tryptophanyl lifetimes appear to be a complex function of several variables, such as microenvironment viscosity, solvent accessibility, the chemical structure of quencher side chains, and side-chain dynamics. The lifetime calculation by MD simulation can be used to validate a predicted structure by comparing the theoretical data with the experimental fluorescence decay results.

Predictions of protein segments with the same aminoacid sequence and different secondary structure: a benchmark for predictive methods.

The most stringent test for predictive methods of protein secondary structure is whether identical short sequences that are known to be present with different conformations in different proteins known at atomic resolution can be correctly discriminated. In this study, we show that the prediction efficiency of this type of segments in unrelated proteins reaches an average accuracy per residue ranging from about 72 to 75% (depending on the alignment method used to generate the input sequence profile) only when methods of the third generation are used. A comparison of different methods based on segment statistics (2nd generation methods) and/or including also evolutionary information (3rd generation methods) indicate that the discrimination of the different conformations of identical segments is dependent on the method used for the prediction. Accuracy is similar when methods similarly performing on the secondary structure prediction are tested. When evolutionary information is taken into account as compared to single sequence input, the number of correctly discriminated pairs is increased twofold. The results also highlight the predictive capability of neural networks for identical segments whose conformation differs in different proteins.

Neural networks predict protein folding and structure: artificial intelligence faces biomolecular complexity.

In the genomic era DNA sequencing is increasing our knowledge of the molecular structure of genetic codes from bacteria to man at a hyperbolic rate. Billions of nucleotides and millions of aminoacids are already filling the electronic files of the data bases presently available, which contain a tremendous amount of information on the most biologically relevant macromolecules, such as DNA, RNA and proteins. The most urgent problem originates from the need to single out the relevant information amidst a wealth of general features. Intelligent tools are therefore needed to optimise the search. Data mining for sequence analysis in biotechnology has been substantially aided by the development of new powerful methods borrowed from the machine learning approach. In this paper we discuss the application of artificial feedforward neural networks to deal with some fundamental problems tied with the folding process and the structure-function relationship in proteins.

The effect of tryptophanyl substitution on folding and structure of myoglobin.

Mammalian myoglobins contain two tryptophanyl residues at the invariant positions 7 (A-5) and 14 (A-12) in the N-terminal region (A helix) of the protein molecule. The crucial role of tryptophanyl residues has been investigated by site-directed mutagenesis and molecular dynamics simulation. The apomyoglobin mutants with a double W-->F substitution were found to be not correctly folded and therefore not expressed as holoprotein. The introduction of a tyrosyl residue at position 7, that is, W7YW14F, resulted in the expression of a correctly folded myoglobin. Not correctly folded apomyoglobins were found with the following mutants: W7FW14Y, W7EW14F, W7FW14E, W7KW14F, W7FW14K. Moreover, in all these cases, very low levels of expression were observed. The acid-induced denaturation curves of wild-type and folded mutant W7YW14F, obtained following the fluorescence variation of the extrinsic fluorophore 1-anilino-8-naphthalenesulfonate, revealed that the stability of the native state of mutant apoprotein is decreased, thus indicating that the replacement W-->Y in position 7 is able to restore a correct folding but not the same stability. Molecular dynamics simulation indicated that both tryptophans are involved in forming favorable, specific tertiary interactions in the native apomyoglobin structure. The lack of some of these interactions caused by tryptophanyl replacement affects the overall protein structure and may provide an explanation for the observed stability decrease. In the case of the double W-->F substitution, the simulated structure shows conclusively the domain formed by helices A, G and H to be not correctly folded. This effect is attenuated if at least one of the two residues is conserved or a tyrosyl residue replaces W7.

A data base of minimally frustrated alpha helical segments extracted from proteins according to an entropy criterion.

A data base of minimally frustrated alpha helical segments is defined by filtering a set comprising 822 non redundant proteins, which contain 4783 alpha helical structures. The data base definition is performed using a neural network-based alpha helix predictor, whose outputs are rated according to an entropy criterion. A comparison with the presently available experimental results indicates that a subset of the data base contains the initiation sites of protein folding experimentally detected and also protein fragments which fold into stable isolated alpha helices. This suggests the usage of the data base (and/or of the predictor) to highlight patterns which govern the stability of alpha helices in proteins and the helical behavior of isolated protein fragments.

An entropy criterion to detect minimally frustrated intermediates in native proteins.

The analysis of the information flow in a feed-forward neural network suggests that the output of the network can be used to compute a structural entropy for the sequence-to-secondary structure mapping. On this basis, we formulate a minimum entropy criterion for the identification of minimally frustrated traits with helical conformation that correspond to initiation sites of protein folding. The entropy of protein segments can be viewed as a nucleation propensity that is useful to characterize putative regions where folding is likely to be initiated with the formation of stretches of alpha-helices under the predominant influence of local interactions. Our procedure is successfully tested in the search for initiation sites of protein folding for which independent experimental and computational evidence exists. Our results lend support to the view that folding is a hierarchical event in which, in harmony with the minimal frustration principle, the final conformation preserves structural modules formed in the early stages of the process.