Stochastic Gene Expression in a Lentiviral Positive Feedback Loop: HIV-1 Tat Fluctuations Drive Phenotypic Diversity

Stochastic gene expression has been implicated in a variety of cellular processes, including cell differentiation and disease. In this issue of Cell, Weinberger et al. (2005) take an integrated computational-experimental approach to study the Tat transactivation feedback loop in HIV-1 and show that fluctuations in a key regulator, Tat, can result in a phenotypic bifurcation. This phenomenon is observed in an isogenic population where individual cells display two distinct expression states corresponding to latent and productive infection by HIV-1. These findings demonstrate the importance of stochastic gene expression in molecular "decision-making."Comment: Supplemental data available as q-bio.MN/060800

Supplemental Data: Stochastic Gene Expression in a Lentiviral Positive Feedback Loop: HIV-1 Tat Fluctuations Drive Phenotypic Diversity

Supplemental data for "Stochastic Gene Expression in a Lentiviral Positive Feedback Loop: HIV-1 Tat Fluctuations Drive Phenotypic Diversity" [q-bio.MN/0608002, Cell. 2005 Jul 29;122(2):169-82].Comment: Supplemental data for q-bio.MN/060800

First-in-Human Study of MANP: A Novel ANP (Atrial Natriuretic Peptide) Analog in Human Hypertension

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Feeding microalgae meal (All-G Rich (TM); Schizochytrium limacinum CCAP 4087/2) to beef heifers. I: Effects on longissimus lumborum steak color and palatibility

Citation: Phelps, K. J., Drouillard, J. S., O'Quinn, T. G., Burnett, D. D., Blackmon, T. L., Axman, J. E., . . . Gonzalez, J. M. (2016). Feeding microalgae meal (All-G Rich (TM); Schizochytrium limacinum CCAP 4087/2) to beef heifers. I: Effects on longissimus lumborum steak color and palatibility. Journal of Animal Science, 94(9), 4016-4029. doi:10.2527/jas2016-0487The objective of this study was to examine effects of 4 levels of microalgae meal (All-G Rich, Schizochytrium limacinum CCAP 4087/2; Alltech Inc., Nicholasville, KY) supplementation to the diet of finishing heifers on longissimus lumborum (LL) steak PUFA content, beef palatability, and color stability. Crossbred heifers (n = 288; 452 +/- 23 kg initial BW) were allocated to pens (36 pens and 8 heifers/ pen), stratified by initial pen BW (3,612 +/- 177 kg), and randomly assigned within strata to 1 of 4 treatments: 0, 50, 100, and 150 g . heifer(-1) . d(-1) of microalgae meal. After 89 d of feeding, cattle were harvested and LL were collected for determination of fatty acid composition and Warner-Bratzler shear force (WBSF), trained sensory panel evaluation, and 7-d retail color stability and lipid oxidation analyses. Feeding microalgae meal to heifers increased (quadratic, P 0.25) but tended (P = 0.10) to increase total PUFA in a quadratic manner (P = 0.03). Total omega-6 PUFA decreased (linear, P = 0.01) and total omega-3 PUFA increased (quadratic, P 0.16); however, off-flavor intensity increased with increasing concentration of microalgae meal in the diet (quadratic, P 0.19); therefore, the negative effects of microalgae on color stability were not due to fiber metabolism differences. Feeding microalgae meal to finishing heifers improves PUFA content of beef within the LL, but there are adverse effects on flavor and color stability

Feeding microalgae meal (All-G Rich (TM); Schizochytrium limacinum CCAP 4067/2) to beef heifers. II: Effects on ground beef color and palatability

Citation: Phelps, K. J., Drouillard, J. S., O'Quinn, T. G., Burnett, D. D., Blackmon, T. L., Axman, J. E., . . . Gonzalez, J. M. (2016). Feeding microalgae meal (All-G Rich (TM); Schizochytrium limacinum CCAP 4067/2) to beef heifers. II: Effects on ground beef color and palatability. Journal of Animal Science, 94(9), 4030-4039. doi:10.2527/jas2016-0488The objective of this study was to examine the effects of feeding microalgae meal (All-G Rich, Schizochytrium limacinum CCAP 4087/2; Alltech Inc., Nicholasville, KY) to finishing heifers on 85% lean and 15% fat (85/15) ground beef PUFA content, palatability, and color stability. Crossbred heifers (n = 288; 452 +/- 23 kg initial BW) were allocated to pens (36 pens and 8 heifers/pen), stratified by initial pen BW (3,612 +/- 177 kg), and randomly assigned within strata to 1 of 4 treatments: 0, 50, 100, and 150 g center dot heifer(-1) center dot d(-1) of microalgae meal. After 89 d of feeding, a subset of heifers (3/pen) was harvested and the rectus femoris, vastus lateralis, vastus medialis, and vastus intermedius were collected for processing into ground beef. At 42 d postmortem, 85/15 ground beef was formulated and formed into 112-g patties and fatty acid composition, subjective palatability, and 96-h retail color stability analyses were conducted. Increasing dietary microalgae meal concentration increased ground beef 20: 5n-3 and 22: 6n-3 fatty acids (quadratic, P 0.12). Feeding microalgae meal affected (P = 0.02) b* at 24 h and decreased (linear, P = 0.08) b* at 48 h. From h 0 to 36 of display, microalgae affected redness of patties (P 0.20) but tended to affect (P = 0.10) cohesiveness scores. As the amount of microalgae meal fed to heifers increased, beef flavor intensity decreased (linear, P < 0.01) and off-flavor intensity increased (quadratic, P < 0.05). Surface oxymyoglobin and metmyoglobin were impacted by microalgae meal from 12 to 36 h of display (P < 0.01). From 48 to 84 h of display, feeding microalgae meal to heifers decreased (linear, P < 0.09) surface oxymyoglobin and increased (linear, P < 0.02) surface metmyoglobin of patties. Although feeding microalgae meal to heifers increases the PUFA content of 85/15 ground beef, there are undesirable effects on flavor and color stability

Effect of growth-promoting technologies on Longissimus lumborum muscle fiber morphometrics, collagen solubility, and cooked meat tenderness

Citation: Ebarb, S. M., Drouillard, J. S., Maddock-Carlin, K. R., Phelps, K. J., Vaughn, M. A., Burnett, D. D., . . . Gonzalez, J. M. (2016). Effect of growth-promoting technologies on Longissimus lumborum muscle fiber morphometrics, collagen solubility, and cooked meat tenderness. Journal of Animal Science, 94(2), 869-881. doi:10.2527/jas2015-9888The objective of the study was to examine the effect of growth-promoting technologies (GP) on Longissimus lumborum steak tenderness, muscle fiber cross-sectional area (CSA), and collagen solubility. Crossbred feedlot heifers (n = 33; initial BW 464 +/- 6 kg) were blocked by BW and assigned to 1 of 3 treatments: no GP (CON; n = 11); implant, no zilpaterol hydrochloride (IMP; n = 11); implant and zilpaterol hydrochloride (COMBO; n = 11). Heifers assigned to receive an implant were administered Component TE-200 on d 0 of the study, and the COMBO group received 8.3 mg/kg DM of zilpaterol hydrochloride for the final 21 d of feeding with a 3 d withdrawal period. Following harvest, strip loins were collected and fabricated into 4 roasts and aged for 3, 14, 21, or 35 d postmortem. Fiber type was determined by immunohistochemistry. After aging, objective tenderness and collagen solubility were measured. There was a treatment x day of aging (DOA) interaction for Warner-Bratzler shear force (WBSF; P 0.31). Soluble collagen amount tended to be affected (P = 0.06) by a treatment x DOA interaction which was due to COMBO muscle having more soluble collagen than the other 2 treatments on d 21 of aging (P < 0.02). Correlation analysis indicated that type I, IIA, and IIX fiber CSA are positively correlated with WBSF at d 3 and 14 of aging (P < 0.01), but only type IIX fibers are correlated at d 21 and 35 of aging (P < 0.03). At these time periods, total and insoluble collagen became positively correlated with WBSF (P < 0.01). This would indicate that relationship between muscle fiber CSA and WBSF decreases during postmortem aging, while the association between WBSF and collagen characteristics strengthens. The use of GP negatively impacted meat tenderness primarily through increased muscle fiber CSA and not through altering collagen solubility

Generating equations using meta-analyses to predict iodine value of pork carcass back, belly, and jowl fat

Meta-analyses used data from existing literature to generate equations to predict finishing pig back, belly, and jowl fat iodine value (IV) followed by a prospective study to validate these equations. The final database included 24, 21, and 29 papers for back, belly, and jowl fat IV, respectively. For experiments that changed dietary fatty acid composition, initial diets (INT) were defined as those fed before the change in diet composition and final diets (FIN) were those fed after. The predictor variables tested were divided into 5 groups: (1) diet fat composition (dietary % C16:1, C18:1, C18:2, C18:3, essential fatty acid [EFA], UFA, and iodine value product) for both INT and FIN diets; (2) duration of feeding the INT and FIN diets; (3) ME or NE of the INT and FIN diet; (4) performance criteria (initial BW, final BW, ADG, ADFI, and G:F); and (5) carcass criteria (HCW and backfat thickness). PROC MIXED in SAS (SAS Institute, Inc., Cary, NC) was used to develop regression equations. Evaluation of models with significant terms was then conducted based on the Bayesian Information Criterion (BIC). The optimum equations to predict back, belly, and jowl fat IV were: backfat IV =84.83 + (6.87*INT EFA) - (3.90*FIN EFA) - (0.12*INT d) - (1.30*FIN d) - (0.11*INT EFA*FIN d) + (0.048*FIN EFA*INT d) + (0.12*FIN EFA*FIN d) - (0.0132*FIN NE) + (0.0011*FIN NE*FIN d) - (6.604*BF); belly fat IV = 106.16 + (6.21*INT EFA) - (1.50*FIN d) - (0.11*INT EFA*FIN d) - (0.0265*INT NE) + (0.00152*INT NE*FIN d) - (0.0816*HCW) - (6.35*BF); and jowl fat IV = 85.50 + (1.08*INT EFA) + (0.87*FIN EFA) - (0.014*INT d) - (0.050*FIN d) + (0.038*INT EFA*INT d) + (0.054*FIN EFA*FIN d) - (0.0146*INT NE) + (0.0322*INT BW) - (0.993*ADFI) - (7.366*BF), where INT EFA = initial period dietary essential fatty acids, %; FIN EFA = final period dietary essential fatty acids, %; INT d = initial period days; FIN d=final period days; INT NE = initial period dietary net energy, kcal/lb; FIN NE = final period dietary net energy, kcal/lb; BF = backfat depth, in.; ADFI = average daily feed intake, lb; INT BW = BW at the beginning of the experiment, lb. Dietary treatments from the validation experiment (see “Influence of Dietary Fat Source and Feeding Duration on Pig Growth Performance, Carcass Composition, and Fat Quality,†p. 210) consisted of a corn-soybean meal control diet with no added fat or a 3 × 3 factorial arrangement with main effects of fat source (4% tallow, 4% soybean oil, or a blend of 2% tallow and 2% soybean oil) and feeding duration (d 0 to 42, 42 to 84, or 0 to 84). The back, belly, and jowl fat IV equations tended to overestimate IV when actual IV values were less than approximately 65 g/100 g and underestimate belly fat IV when actual IV values were greater than approximately 74 g/100 g or when the blend or soybean oil diets were fed from d 42 to 84. Overall, with the exceptions noted, the regression equations were an accurate tool for predicting carcass fat quality based on dietary and pig performance factors.; Swine Day, Manhattan, KS, November 20, 201