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Feedlot diets containing different starch levels and additives change the cecal proteome involved in cattle’s energy metabolism and inflammatory response

The experiment was conducted according to the standards issued by the National Council for Animal Experimentation Control (CONCEA) and approved by the Ethics and Use of Animals Committee of the São Paulo State University (UNESP, Botucatu-SP), under protocol no 0107/2019 and in compliance with ARRIVE (animal research: reporting of in vivo experiments) guidelines30.

Animals, facilities, feeding and animal care

The animal experiment was conducted at the feedlot facilities of the Innovation and Applied Science Center of DSM Nutritional Products (I & AS Beef Center; Rio Brilhante, Mato Grosso do Sul, Brazil). Nellore bulls (n = 210) (Bos taurus indicus) from the grazing system with an average body weight of ± 380 kg were used. The animals were randomly allocated to pens (7 animals/pen) with 12 m2/animal and collective troughs (50 cm linear/animal). The program for receiving the animals consisted of weighing, deworming, and vaccinating according to the annual prophylactic calendar. The animals underwent a pre-experimental adaptation period of 10 days to standardize their rumen population and allow them to adapt to the facilities and management. The diets were formulated with the LRNS system (large ruminant nutrition system31), level 2, meeting the nutritional requirements for daily weight gain between 1.5 and 1.7 kg/animal. Animals were fed for 92 days and diets were offered ad libitum twice daily at 8 a. m. and 3 p.m.

Experimental design

A factorial 3 × 2 arrangement was used, with starch level (25%, 35%, or 45%) and additives (monensin or the essential oil blend CRINA® with the exogenous α-amylase Rumistar®) as the factor. The sodium monensin (MON; Rumensin, Elanco Animal Health, Indianapolis, IN) used was included in the diet at a dose of 26 mg/kg of dry matter. The blend of functional oils (CRINA RUMINANTS®; DSM Nutritional Products, Basel, Switzerland) containing thymol, eugenol, limonene, and vanillin32 and the exogenous enzyme α-amylase (RONOZYME RUMISTAR™; DSM Nutritional Products, Basel, Switzerland), referred to as BEOα were added to the diet at a dose of 90 mg/kg of dry matter and 560 mg/kg of dry matter, respectively. The pens were distributed in a randomized block design, totaling 6 treatments with 5 repetitions or 30 experimental units overall. The treatments were distributed within the blocks as follows: T1 (25MON), T2 (25BEOα), T3 (35MON), T4 (35BEOα), T5 (45MON), and T6 (45BEOα). According to the statistical model:

$$Y_{ijk} = mu + B_{k} + C_{i} + A_{J} + left( {C times A} right)_{ij} + varepsilon_{ijk} ,$$

where (Yijk) is the dependent variable; (mu) is the overall mean; (Bk) is the block effect; (Ci) is concentrate; (AJ) is additive; ((C times A)ij) is the interaction between concentrate and additive effects; and (varepsilon ijk) is the residual error.

Diets and their chemical composition

The experimental diets were composed of natural bagasse sugarcane, ground corn, soybean hulls, cottonseed, soybeans, core minerals and vitamins, urea, and additives. The transition to the finishing diet was managed as follows: for 14 days, two diets with 65% and 75% concentrate were provided for 7 days each. From the 15th day of the experiment until slaughter, a finishing diet containing 85% concentrate was provided (Table 4).

Table 4 Aining increasing starch levels (25, 35, and 45%) and additives (monensin, blend of essential oil + exogenous α-amylase) in diets for Nellore cattle feedlot.

Dietary energy content was calculated according to the LRNS system31 and Total digestible nutrients (TDN) were determined by the equation: TDN = digestible CP + (digestible EE × 2.25) + digestible NDF + digestible non-structural carbohydrate (NSC). Crude protein was determined by assessing the nitrogen content of the samples with the Kjeldahl method33. The NDF concentration was assessed with the methodology described by Van Soest et al.34 and corrected for CP and ashes. Starch was determined by the equation: NSC = 100 − CP − EE − NDF − ash, where ash content was determined by incinerating samples at 550 °C for 2 h in a muffle furnace35. Physically effective neutral detergent fiber (peNFD) was determined according to Kononoff et al.’s methods36. Samples of diets were collected to determine particle-size distribution by sieving with the Penn State particle-size separator and reported on an as-fed basis.

Proteomics sample collection and preparation

The animals were transported to a commercial slaughterhouse where they were stunned by brain concussions with a captive dart gun. After bleeding hide removal and evisceration, cecum samples about 4 cm square were collected and washed with phosphate-buffered saline (PBS), transferred to 15 mL polypropylene bottles, and placed in liquid nitrogen (− 196 °C) for later protein extraction. Each pen was considered an experimental unit, so a pool of samples was made by homogenizing cecal tissue from animals given the same treatment; three animals per experimental unit (N = 5) were used, i.e., 15 animals/group or 90 animals total (15 animals from each of six groups).

Extraction, precipitation and quantification of proteins

To extract the protein fraction, the tissue was macerated with a mortar and pestle in the presence of liquid nitrogen. The extracting solution was added at a rate of 1 mL ultrapure water per 1 g tissue and then the samples were homogenized with an OMMI-BEAD RUPTOR4 cell disruptor (Kennesaw, Georgia, United States) over three 30-s cycles. The samples were then separated into protein extracts and the supernatant was collected after refrigerated centrifugation (− 4 °C) with a UNIVERSAL 320R HETTICH (Tuttlingen, Baden-Württemberg, Germany). The proteins were precipitated in 80% (v/v) acetone (J.T. Baker, Phillipsburg, New Jersey, United States), using 300 μL of supernatant and 600 μL of 80% acetone. The samples were stored at 2 °C for 1.5 h and then centrifuged at 14,000 rpm for 30 min; the supernatant was discarded and the protein pellet was solubilized in 1 mL of 0.50 mol/L NaOH (Merck, Darmstadt, Germany). The protein concentrations were determined by the Biuret method37, using an analytical curve with a concentration range of 0–100 g/L of standard bovine albumin solution (Acros Organics, NJ, United States) at 100 g/L.

Electrophoretic separations of protein fractions using 2D-PAGE

For isoelectric focusing, about 375 µg of proteins from each group were applied to individual strips; the sample was resolubilized with a solution containing 7 mol/L urea, 2 mol/L thiourea, 2% CHAPS (m/v) (GE Healthcare, Uppsala, Sweden), ampholytes at a pH of 3 to 10 at 0.5% (v/v) (GE Healthcare, Uppsala, Sweden), and 0.002% bromophenol blue (GE Healthcare, Uppsala, Sweden), in addition to 2.8 mg of dithiothreitol (USB, Cleveland, Ohio, United States). Approximately 900 µL of mineral oil was added at room temperature for 12 h to rehydrate the strips and prevent evaporation and urea crystals. After this period, the strips were added to the EttanTMIPGphorTM3 isoelectric focusing system (IEF) (GE Healthcare, Uppsala, Sweden). The electrical voltage used was established by the protocol described by Braga et al.38. At the end of the focusing period, the strip was balanced in two 15-min stages. First, 10 mL of a solution containing 6 mol/L urea, 2% SDS (w/v), 30% glycerol (v/v), 50 mmol/L Tris–HCl (pH 8.8), 0.002% bromophenol blue (w/v), and 2% DTT (w/v) was used to keep the proteins in their reduced forms38,37. In the second stage, a solution in which DTT was replaced with 2.5% (w/v) iodoacetamide was used to alkylate the thiol groups of the proteins and prevent possible reoxidation. After strip balancing, the second portion of the electrophoretic process (SDS-PAGE) occurred.

The strip was applied to a 12.5% (w/v) polyacrylamide gel previously prepared on a glass plate (180 × 160 × 1.5 mm). The gel was placed next to the strip with a piece of filter paper containing 6 µL of a molecular mass standard (GE Healthcare, Uppsala, Sweden), with proteins of different molecular masses (β-phosphorylase [97.0 kDa], albumin [66.0 kDa], ovalbumin [45.0 kDa], carbonic anhydrase [30.0 kDa], trypsin inhibitor [20.1 kDa], and α-lactalbumin [14.4 kDa]). The strip and filter paper were sealed with 0.5% agarose solution (w/v) to ensure contact with the polyacrylamide gel. The run program was then applied at 100 V for 30 min and a further 250 V for 2 h. After the run period, the gels were immersed in a fixative solution containing10% acetic acid (v/v) and 40% ethanol (v/v) for 30 min. Then, the proteins were revealed with colloidal Coomassie G-250 (USB, Cleveland, Ohio, United States) for 72 h and removed by washing with ultrapure water38,39,40,41.

The gels obtained (Supplemental Fig. S1) were scanned and their images analyzed with the image processing program ImageMaster 2D Platinum 7.0 (GeneBio, Geneva, Switzerland; www.gelifescience.com), which allows the estimation of the isoelectric points and molecular masses of the separated proteins and calculation of the number of spots obtained via gel electrophoresis. Three replicates of each gel were used to evaluate the reproducibility of each protein spot obtained in the replicates of the gels by overlaying the image from one gel over the other in the image treatment program39,40,41,42.

Protein identification by mass spectrometry (LC–MS/MS)

The differentially expressed spots were characterized via mass spectrometry after the identification was standardized according to the highest protein score, pI, and molecular mass (MM) closest to the theoretical and experimental results. Among the proteins identified, 12 were classified as functional for this study as they are related to energy metabolism and inflammatory responses.

The protein spots were characterized with LC–MS/MS after being subjected to tryptic digestion and peptide elution according to the methodology Shevchenko et al.43 described. The aliquots of the solutions containing the eluted peptides were analyzed to obtain the mass spectra with the nanoAcquity UPLC system coupled to the Xevo G2 QTof mass spectrometer (Waters, Milford, MA, United States). Proteins were identified by searching in the UniProt database (www.uniprot.org) within the Bos taurus species. Proteins were considered depending on their theoretical and experimental isoelectric points, molecular masses, and scores (> 60). After identifying FASTA sequences in the proteins, their sequences were analyzed with OMICSBOX software (BLAST2GO)44 and they were categorized by their molecular function, biological processes, and biochemical activities with gene ontology (GO).

Proteomic statistical analysis

The starch level and additive were the fixed effects analyzed in a factorial design; thus, the groups were compared through contrasts to verify differentially expressed protein spots. Only proteins with significantly altered levels were selected for identification by MS. The images were analyzed with ImageMaster Platinum software version 7.0, which establishes correlations (matching) between groups. For this correlation, three gel replicates were compared for volume, distribution, relative intensity, isoelectric point, and molecular mass in an analysis of variance (ANOVA) with a t-test to determine the significance of differentially expressed protein spots.

Following the average mode of background subtraction, individual spot intensity volume was normalized with total intensity volume (the summation of the intensity volumes obtained from all spots in the same 2-DE gel). The normalized intensity volume values of individual protein spots were then used to determine differential protein expression among experimental groups. A heatmap showed the correlation coefficient of the spot expression values and, after checking the differentially expressed spots (t-test, P < 0.05), the log2 FC values were used for hierarchical cluster analysis.

Pathways enrichment analysis

The same KEGG-IDs were used to analyze metabolic pathways using the Kyoto Encyclopedia of Genes and Genomes function (KEGG pathways)45,46,47 and Reactome pathway enrichment analysis yielded similar results about the specific pathways affected, allowing the expressions of proteins encoding enzymes found in the database to be mapped.

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